Principles of Sonar Performance Modeling
Michael A. Ainslie
Principles of Sonar
Performance Modeling
Published in association with
PPraxisraxis PPublishingublishin...
Dr Michael A. Ainslie
TNO, Sonar Department
The Hague
The Netherlands
SPRINGER–PRAXIS BOOKS IN GEOPHYSICAL SCIENCES
SUBJEC...
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Foreword. ...
2.2 Essentials of underwater acoustics. . . . . . . . . . . . . . . . . . . . . 30
2.2.1 What is sound? . . . . . . . . . ...
4.3 Properties of the sea surface . . . . . . . . . . . . . . . . . . . . . . . . 159
4.3.1 Effect of wind . . . . . . . ....
6.2.3 Autocorrelation and cross-correlation functions and the
matched filter . . . . . . . . . . . . . . . . . . . . . . . ...
8.3 Sources of underwater sound . . . . . . . . . . . . . . . . . . . . . . . 414
8.3.1 Shipping source spectrum level mea...
11.2.7 Detection threshold (DT) . . . . . . . . . . . . . . . . . . . . . 581
11.2.8 Worked example . . . . . . . . . . . ...
A.2.3 Convolution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651
A.2.4 Discrete Fourier transform . . . . ...
To Anna
Preface
The science of sonar performance modeling is traditionally separated into a ‘‘wet end’’
comprising the disciplines...
Foreword
Underwater acoustics is largely a branch of physics, perhaps merging with geophysics
and oceanography, but as soo...
initially in terms of ratios of simple physical quantities, and converted to decibels only
at the end. Such an approach pr...
Acknowledgments
The eight years it has taken me to write this book were spent working at TNO in
The Hague. It has been a p...
include FishBase (www.fishbase.org), the Ocean Biogeographic Information System
(www.iobis.org), Mathworld (http://mathworl...
Figures
1.1 Sketch of Beudant’s experiment of ca. 1816 . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2 Sketch of the...
3.14 Spectral density level of signal and noise . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3.15 ROC curves for...
4.20 Near-surface bubble population density spectra . . . . . . . . . . . . . . . . . . . . . 170
4.21 Compressional and s...
8.2 Surface reflection loss in nepers calculated vs. angle and frequency . . . . . . . 368
8.3 Surface reflection loss vs. w...
9.16 Propagation loss vs. range for shallow water with a mud bottom for two
different sound speed profiles . . . . . . . . ....
11.15 Signal excess vs. range and rainfall rate for SWS . . . . . . . . . . . . . . . . . . . . 606
11.16 Geometry for wor...
Tables
2.1 Detection truth table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.1 So...
5.1 Compressional speed, shear speed, and density used to calculate the form
factors for the four metals shown in Figure 5...
9.5 Caustic ranges and corresponding two-way travel arrival times for a source at
depth 30 m and receiver at depth 50 m. ....
10.37 Spread of sound pressure level values resulting in the specified behavioral
responses in cetaceans and pinnipeds for ...
Part I
Foundations
1
Introduction
Wee represent Small Sounds as Great and Deepe; Likewise
Great Sounds, Extenuate and Sharpe; Wee make divers...
underwater detection and localization were developed in the 20th century, motivated
initially by the sinking of RMS Titani...
. Echo sounder: perhaps the most common of all man-made sonars, an echo
sounder is a device for measuring water depth by t...
classification, and tracking tasks, such as the estimation of position and velocity of a
sonar target, a satisfactory detec...
entirely equivalent, as in the end what matters is the ratio of signal power to noise
power.
Finally, to be of practical u...
the difficulty in finding reliable sources for them (in the case of Russian and Soviet
acoustics, corrected recently by the p...
1.4 A brief history of sonar 9]Sec. 1.4
Figure 1.2. Sketch of the Colladon–Sturm experiment of 1826 (reprinted fom Girard,...
1,435 m/s) are consistent with modern expectation for the respective measurement
conditions.
The second important developm...
facilities at Hawkcraig (in Fifeshire, Scotland), and expanded in 1917 to a team of
more than 80 scientists and technician...
signals were found to be very weak. Fortunately, a suitable valve amplifier, designed
by Le´ on Brillouin and G. A. Beauvai...
French scientists, including:
— the earliest known description of the echo-ranging concept, by Mersenne (1636);
— the meas...
19th century to notify them of the presence of nearby lightships: in 1889, the U.S.
Lighthouse Board described an inventio...
used—was overcome by the introduction of variable-length delay lines, which per-
mitted the operator to select the directi...
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Principles of sonar performance modeling 2010
Upcoming SlideShare
Loading in …5
×

Principles of sonar performance modeling 2010

4,744 views
4,588 views

Published on

Principles of sonar performance modeling.pdf

Published in: Education, Technology, Business
0 Comments
3 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
4,744
On SlideShare
0
From Embeds
0
Number of Embeds
19
Actions
Shares
0
Downloads
242
Comments
0
Likes
3
Embeds 0
No embeds

No notes for slide

Principles of sonar performance modeling 2010

  1. 1. Principles of Sonar Performance Modeling
  2. 2. Michael A. Ainslie Principles of Sonar Performance Modeling Published in association with PPraxisraxis PPublishingublishing Chichester, UK
  3. 3. Dr Michael A. Ainslie TNO, Sonar Department The Hague The Netherlands SPRINGER–PRAXIS BOOKS IN GEOPHYSICAL SCIENCES SUBJECT ADVISORY EDITOR: Philippe Blondel, C.Geol., F.G.S., Ph.D., M.Sc., F.I.O.A., Senior Scientist, Department of Physics, University of Bath, Bath, UK ISBN 978-3-540-87661-8 e-ISBN 978-3-540-87662-5 DOI 10.1007/978-3-540-87662-5 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2010921914 # Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Marı´a Pilar Ainslie and Jim Wilkie Project management: OPS Ltd, Gt Yarmouth, Norfolk, UK Printed on acid-free paper Springer is part of Springer Science þ Business Media (www.springer.com)
  4. 4. Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii List of figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix List of tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxv PART I FOUNDATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1 What is sonar? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Purpose, scope, and intended readership . . . . . . . . . . . . . . . . 4 1.3 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3.1 Part I: Foundations (Chapters 1–3) . . . . . . . . . . . . . . 6 1.3.2 Part II: The four pillars (Chapters 4–7) . . . . . . . . . . . 6 1.3.3 Part III: Towards applications (Chapters 8–11) . . . . . . 7 1.3.4 Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 A brief history of sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4.1 Conception and birth of sonar (–1918) . . . . . . . . . . . . 8 1.4.2 Sonar in its infancy (1918–1939) . . . . . . . . . . . . . . . . 15 1.4.3 Sonar comes of age (1939–) . . . . . . . . . . . . . . . . . . . 17 1.4.4 Swords to ploughshares . . . . . . . . . . . . . . . . . . . . . . 22 1.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2 Essential background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.1 Essentials of sonar oceanography . . . . . . . . . . . . . . . . . . . . . 27 2.1.1 Acoustical properties of seawater . . . . . . . . . . . . . . . 28 2.1.2 Acoustical properties of air . . . . . . . . . . . . . . . . . . . 30
  5. 5. 2.2 Essentials of underwater acoustics. . . . . . . . . . . . . . . . . . . . . 30 2.2.1 What is sound? . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.2 Radiation of sound . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.3 Scattering of sound . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.3 Essentials of sonar signal processing . . . . . . . . . . . . . . . . . . 42 2.3.1 Temporal filter . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 2.3.2 Spatial filter (beamformer) . . . . . . . . . . . . . . . . . . . . 44 2.4 Essentials of detection theory . . . . . . . . . . . . . . . . . . . . . . . 47 2.4.1 Gaussian distribution . . . . . . . . . . . . . . . . . . . . . . . 47 2.4.2 Other distributions . . . . . . . . . . . . . . . . . . . . . . . . . 51 2.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3 The sonar equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Objectives of sonar performance modeling . . . . . . . . . . 53 3.1.2 Concepts of ‘‘signal’’ and ‘‘noise’’ . . . . . . . . . . . . . . . 54 3.1.3 Generic deep-water scenario . . . . . . . . . . . . . . . . . . . 55 3.1.4 Chapter organization . . . . . . . . . . . . . . . . . . . . . . . 55 3.2 Passive sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2.2 Definition of standard terms (passive sonar). . . . . . . . . 58 3.2.3 Coherent processing: narrowband passive sonar . . . . . . 64 3.2.4 Incoherent processing: broadband passive sonar . . . . . . 80 3.3 Active sonar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 3.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 3.3.2 Definition of standard terms (active sonar) . . . . . . . . . 95 3.3.3 Coherent processing: CW pulse þ Doppler filter. . . . . . . 99 3.3.4 Incoherent processing: CW pulse þ energy detector . . . . 112 3.4 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 PART II THE FOUR PILLARS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 4 Sonar oceanography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 4.1 Properties of the ocean volume . . . . . . . . . . . . . . . . . . . . . . 126 4.1.1 Terrestrial and universal constants . . . . . . . . . . . . . . . 126 4.1.2 Bathymetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 4.1.3 Factors affecting sound speed and attenuation in pure seawater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 4.1.4 Speed of sound in pure seawater . . . . . . . . . . . . . . . . 139 4.1.5 Attenuation of sound in pure seawater . . . . . . . . . . . . 146 4.2 Properties of bubbles and marine life . . . . . . . . . . . . . . . . . . 148 4.2.1 Properties of air bubbles in water . . . . . . . . . . . . . . . 148 4.2.2 Properties of marine life . . . . . . . . . . . . . . . . . . . . . 152 vi Contents
  6. 6. 4.3 Properties of the sea surface . . . . . . . . . . . . . . . . . . . . . . . . 159 4.3.1 Effect of wind . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 4.3.2 Surface roughness . . . . . . . . . . . . . . . . . . . . . . . . . 166 4.3.3 Wind-generated bubbles . . . . . . . . . . . . . . . . . . . . . 169 4.4 Properties of the seabed . . . . . . . . . . . . . . . . . . . . . . . . . . 171 4.4.1 Unconsolidated sediments . . . . . . . . . . . . . . . . . . . . 172 4.4.2 Rocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 4.4.3 Geoacoustic models . . . . . . . . . . . . . . . . . . . . . . . . 183 4.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 5 Underwater acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 5.2 The wave equations for fluid and solid media . . . . . . . . . . . . . 192 5.2.1 Compressional waves in a fluid medium . . . . . . . . . . . 192 5.2.2 Compressional waves and shear waves in a solid medium 194 5.3 Reflection of plane waves . . . . . . . . . . . . . . . . . . . . . . . . . . 197 5.3.1 Reflection from and transmission through a simple fluid– fluid or fluid–solid boundary . . . . . . . . . . . . . . . . . . 198 5.3.2 Reflection from a layered fluid boundary . . . . . . . . . . 201 5.3.3 Reflection from a layered solid boundary . . . . . . . . . . 204 5.3.4 Reflection from a perfectly reflecting rough surface . . . . 205 5.3.5 Reflection from a partially reflecting rough surface . . . . 208 5.4 Scattering of plane waves . . . . . . . . . . . . . . . . . . . . . . . . . . 209 5.4.1 Scattering cross-sections and the far field . . . . . . . . . . 209 5.4.2 Backscattering from solid objects . . . . . . . . . . . . . . . 210 5.4.3 Backscattering from fluid objects . . . . . . . . . . . . . . . . 214 5.4.4 Scattering from rough boundaries . . . . . . . . . . . . . . . 223 5.5 Dispersion in the presence of impurities . . . . . . . . . . . . . . . . . 225 5.5.1 Wood’s model for sediments in dilute suspension . . . . . 225 5.5.2 Buckingham’s model for saturated sediments with inter- granular contact . . . . . . . . . . . . . . . . . . . . . . . . . . 226 5.5.3 Effect of bubbles or bladdered fish . . . . . . . . . . . . . . 227 5.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 6 Sonar signal processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 6.1 Processing gain for passive sonar . . . . . . . . . . . . . . . . . . . . . 252 6.1.1 Beam patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252 6.1.2 Directivity index . . . . . . . . . . . . . . . . . . . . . . . . . . 266 6.1.3 Array gain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 6.1.4 BB application . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 6.1.5 Time domain processing . . . . . . . . . . . . . . . . . . . . . 279 6.2 Processing gain for active sonar . . . . . . . . . . . . . . . . . . . . . . 279 6.2.1 Signal carrier and envelope . . . . . . . . . . . . . . . . . . . 280 6.2.2 Simple envelopes and their spectra . . . . . . . . . . . . . . 282 Contents vii
  7. 7. 6.2.3 Autocorrelation and cross-correlation functions and the matched filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296 6.2.4 Ambiguity function . . . . . . . . . . . . . . . . . . . . . . . . 300 6.2.5 Matched filter gain for perfect replica . . . . . . . . . . . . 306 6.2.6 Matched filter gain for imperfect replica (coherence loss) 307 6.2.7 Array gain and total processing gain (active sonar) . . . 308 6.3 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 7 Statistical detection theory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 7.1 Single known pulse in Gaussian noise, coherent processing . . . . 312 7.1.1 False alarm probability for Gaussian-distributed noise . 312 7.1.2 Detection probability for signal with random phase . . . 313 7.1.3 Detection threshold . . . . . . . . . . . . . . . . . . . . . . . . 326 7.1.4 Application to other waveforms . . . . . . . . . . . . . . . . 327 7.2 Multiple known pulses in Gaussian noise, incoherent processing 327 7.2.1 False alarm probability for Rayleigh-distributed noise amplitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 7.2.2 Detection probability for incoherently processed pulse train . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 7.3 Application to sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 7.3.1 Active sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 7.3.2 Passive sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 7.3.3 Decision strategies and the detection threshold . . . . . . 346 7.4 Multiple looks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 7.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 7.4.2 AND and OR operations . . . . . . . . . . . . . . . . . . . . 350 7.4.3 Multiple OR operations . . . . . . . . . . . . . . . . . . . . . 354 7.4.4 ‘‘M out of N ’’ operations . . . . . . . . . . . . . . . . . . . . 356 7.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 PART III TOWARDS APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . 359 8 Sources and scatterers of sound . . . . . . . . . . . . . . . . . . . . . . . . . . 361 8.1 Reflection and scattering from ocean boundaries . . . . . . . . . . . 361 8.1.1 Reflection from the sea surface . . . . . . . . . . . . . . . . . 362 8.1.2 Scattering from the sea surface . . . . . . . . . . . . . . . . . 369 8.1.3 Reflection from the seabed . . . . . . . . . . . . . . . . . . . 375 8.1.4 Scattering from the seabed . . . . . . . . . . . . . . . . . . . 391 8.2 Target strength, volume backscattering strength, and volume attenuation coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 8.2.1 Target strength of point-like scatterers . . . . . . . . . . . . 400 8.2.2 Volume backscattering strength and attenuation coeffi- cient of distributed scatterers . . . . . . . . . . . . . . . . . . 409 8.2.3 Column strength and wake strength of extended volume scatterers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412 viii Contents
  8. 8. 8.3 Sources of underwater sound . . . . . . . . . . . . . . . . . . . . . . . 414 8.3.1 Shipping source spectrum level measurements . . . . . . . 417 8.3.2 Distributed sources on the sea surface . . . . . . . . . . . . 424 8.3.3 Distributed sources on the seabed (crustacea) . . . . . . . 429 8.4 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 9 Propagation of underwater sound. . . . . . . . . . . . . . . . . . . . . . . . . . 439 9.1 Propagation loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 9.1.1 Effect of the seabed in isovelocity water . . . . . . . . . . . 440 9.1.2 Effect of a sound speed profile . . . . . . . . . . . . . . . . . 459 9.2 Noise level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 9.2.1 Deep water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 9.2.2 Shallow water . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489 9.2.3 Noise maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490 9.3 Signal level (active sonar) . . . . . . . . . . . . . . . . . . . . . . . . . 491 9.3.1 The reciprocity principle . . . . . . . . . . . . . . . . . . . . . 492 9.3.2 Calculation of echo level . . . . . . . . . . . . . . . . . . . . . 493 9.3.3 V-duct propagation (isovelocity case) . . . . . . . . . . . . . 494 9.3.4 U-duct propagation (linear profile) . . . . . . . . . . . . . . 494 9.4 Reverberation level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495 9.4.1 Isovelocity water . . . . . . . . . . . . . . . . . . . . . . . . . . 497 9.4.2 Effect of refraction . . . . . . . . . . . . . . . . . . . . . . . . . 500 9.5 Signal-to-reverberation ratio (active sonar) . . . . . . . . . . . . . . 508 9.5.1 V-duct (isovelocity case) . . . . . . . . . . . . . . . . . . . . . 508 9.5.2 U-duct (linear profile) . . . . . . . . . . . . . . . . . . . . . . . 509 9.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 510 10 Transmitter and receiver characteristics. . . . . . . . . . . . . . . . . . . . . . 513 10.1 Transmitter characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 514 10.1.1 Of man-made systems . . . . . . . . . . . . . . . . . . . . . . . 515 10.1.2 Of marine mammals . . . . . . . . . . . . . . . . . . . . . . . . 542 10.2 Receiver characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545 10.2.1 Of man-made sonar . . . . . . . . . . . . . . . . . . . . . . . . 545 10.2.2 Of marine mammals, amphibians, human divers, and fish 549 10.3 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565 11 The sonar equations revisited . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573 11.2 Passive sonar with coherent processing: tonal detector . . . . . . . 574 11.2.1 Sonar equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 574 11.2.2 Source level (SL) . . . . . . . . . . . . . . . . . . . . . . . . . . 575 11.2.3 Narrowband propagation loss (PL) . . . . . . . . . . . . . . 576 11.2.4 Noise spectrum level (NLf ) . . . . . . . . . . . . . . . . . . . 578 11.2.5 Bandwidth (BW) . . . . . . . . . . . . . . . . . . . . . . . . . . 579 11.2.6 Array gain (AG) and directivity index (DI) . . . . . . . . . 580 Contents ix
  9. 9. 11.2.7 Detection threshold (DT) . . . . . . . . . . . . . . . . . . . . . 581 11.2.8 Worked example . . . . . . . . . . . . . . . . . . . . . . . . . . 583 11.3 Passive sonar with incoherent processing: energy detector . . . . . 591 11.3.1 Sonar equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 11.3.2 Source level (SL) . . . . . . . . . . . . . . . . . . . . . . . . . . 592 11.3.3 Broadband propagation loss (PL) . . . . . . . . . . . . . . . 592 11.3.4 Broadband noise level (NL) . . . . . . . . . . . . . . . . . . . 593 11.3.5 Processing gain (PG) . . . . . . . . . . . . . . . . . . . . . . . 593 11.3.6 Broadband detection threshold (DT) . . . . . . . . . . . . . 597 11.3.7 Worked example . . . . . . . . . . . . . . . . . . . . . . . . . . 599 11.4 Active sonar with coherent processing: matched filter . . . . . . . 606 11.4.1 Sonar equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 606 11.4.2 Echo level (EL), target strength (TS), and equivalent target strength (TSeq). . . . . . . . . . . . . . . . . . . . . . . . 607 11.4.3 Background level (BL) . . . . . . . . . . . . . . . . . . . . . . . 610 11.4.4 Processing gain (PG) . . . . . . . . . . . . . . . . . . . . . . . 610 11.4.5 Detection threshold (DT) . . . . . . . . . . . . . . . . . . . . . 612 11.4.6 Worked example . . . . . . . . . . . . . . . . . . . . . . . . . . 613 11.5 The future of sonar performance modeling . . . . . . . . . . . . . . 630 11.5.1 Advances in signal processing and oceanographic model- ing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 630 11.5.2 Autonomous platforms . . . . . . . . . . . . . . . . . . . . . . 631 11.5.3 Environmental impact of anthropogenic sound . . . . . . . 631 11.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635 A Special functions and mathematical operations . . . . . . . . . . . . . . . . . 635 A.1 Definitions and basic properties of special functions . . . . . . . . 635 A.1.1 Heaviside step function, sign function, and rectangle function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635 A.1.2 Sine cardinal and sinh cardinal functions . . . . . . . . . . 636 A.1.3 Dirac delta function . . . . . . . . . . . . . . . . . . . . . . . . 636 A.1.4 Fresnel integrals . . . . . . . . . . . . . . . . . . . . . . . . . . 636 A.1.5 Error function, complementary error function, and right- tail probability function . . . . . . . . . . . . . . . . . . . . . 637 A.1.6 Exponential integrals and related functions . . . . . . . . . 639 A.1.7 Gamma function and incomplete gamma functions . . . . 640 A.1.8 Marcum Q functions . . . . . . . . . . . . . . . . . . . . . . . . 644 A.1.9 Elliptic integrals . . . . . . . . . . . . . . . . . . . . . . . . . . 644 A.1.10 Bessel and related functions . . . . . . . . . . . . . . . . . . . 645 A.1.11 Hypergeometric functions . . . . . . . . . . . . . . . . . . . . 648 A.2 Fourier transforms and related integrals . . . . . . . . . . . . . . . . 649 A.2.1 Forward and inverse Fourier transforms . . . . . . . . . . 649 A.2.2 Cross-correlation . . . . . . . . . . . . . . . . . . . . . . . . . . 650 x Contents
  10. 10. A.2.3 Convolution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651 A.2.4 Discrete Fourier transform . . . . . . . . . . . . . . . . . . . 651 A.2.5 Plancherel’s theorem . . . . . . . . . . . . . . . . . . . . . . . . 652 A.3 Stationary phase method for evaluation of integrals . . . . . . . . 652 A.3.1 Stationary phase approximation . . . . . . . . . . . . . . . . 652 A.3.2 Derivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653 A.4 Solution to quadratic, cubic, and quartic equations . . . . . . . . . 655 A.4.1 Quadratic equation . . . . . . . . . . . . . . . . . . . . . . . . 655 A.4.2 Cubic equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 655 A.4.3 Quartic and higher order equations . . . . . . . . . . . . . . 656 A.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656 B Units and nomenclature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 B.1 Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 B.1.1 SI units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 B.1.2 Non-SI units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 B.1.3 Logarithmic units . . . . . . . . . . . . . . . . . . . . . . . . . 659 B.2 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665 B.2.1 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665 B.2.3 Names of fish and marine mammals . . . . . . . . . . . . . 666 B.3 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 C Fish and their swimbladders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673 C.1 Tables of fish and bladder types . . . . . . . . . . . . . . . . . . . . . 673 C.2 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 Contents xi
  11. 11. To Anna
  12. 12. Preface The science of sonar performance modeling is traditionally separated into a ‘‘wet end’’ comprising the disciplines of acoustics and oceanography and a ‘‘dry end’’ of signal processing and detection theory. This book is my attempt to bring both aspects together to serve as a modern reference for today’s sonar performance modeler, whether for research, design, or analysis, as Urick’s Principles of Underwater Sound did for sonar engineers of his day. The similarity in the title is no accident. During the process I made some valuable discoveries that I now share with the reader. The radar literature provides a deep mine of resources, with applicable results from the theories of wave propagation, signal processing, and (an especially rich vein, largely unexploited in the sonar literature) statistical detection. From oceanography we learn that each of the world’s oceans has its own unique physical, chemical, and biological signature, with sometimes profound consequences for sonar. Marine mammals have evolved a sonar of their own, the remarkable properties of which we are only beginning to unravel, as reported in the increasingly sophisticated bioacoustics literature. Governments and industry around the world have begun to take seriously the environmental consequences of man’s use, whether deliberate or incidental, of sound in the sea. I have done my best to provide a representative snapshot of this rapidly developing field. Some readers will treat this book as a repository of facts, figures, and formulas, while others will seek in it explanations and clarity. It has been my intention to satisfy the needs of both types of reader by including mathematical derivations and worked examples, supplemented with measurements or estimates of relevant input param- eters. Of all readers I request the patience to overlook the flaws that undoubtedly remain, despite my best attempts to weed them out. Michael A. Ainslie TNO, The Hague, The Netherlands, March 2010
  13. 13. Foreword Underwater acoustics is largely a branch of physics, perhaps merging with geophysics and oceanography, but as soon as one attempts to assess a sonar’s performance under realistic conditions, a host of other engineering factors come into play. Is the desired target signal louder than all the other natural noise from wind, waves, ship engines, strumming cables? Is it louder than sound scattered from other distant objects? How do the standard signal-processing techniques such as beamforming, spectral analysis, and statistical analysis influence the probability of achieving a target detection and the probability of a false alarm? The author, Dr. Mike Ainslie, is a physicist with a considerable academic publication record and many years’ hands-on experience in sonar assessment for the U.K.’s MOD and for TNO in The Netherlands. Through a firm foundation in physics, always taking great care over the physical units, Principles of Sonar Per- formance Modeling introduces rigor and clarity into the traditional sonar equation while still answering the fundamental engineering questions. As well as dealing with the more pure disciplines of sound generation, propagation, and reverberation, it tackles sound sources, targets, signal processing, and detection theory for man-made and biological sonar. Underlying all this is a desire ‘‘to see the wood for the trees’’. For instance, it is often the case with propagation that, despite all the complexities of refraction, reflection, diffraction, scattering, and so on, some simple mechanism dominates, and sometimes one can express the entire transmission loss, ambient noise level, or reverberation level by a simple formula. This insight, or even revelation, is an important bonus and check if one is to have faith in numerical assessment of complicated search scenarios. It can also become a useful shortcut when a particular scenario is to be investigated under many different acoustic, or processing, conditions. Examples of such insights will be found throughout. The cornerstone is the derivation of the sonar equations—too often presented as indisputable fact—from simple physical principles. The derivation is presented
  14. 14. initially in terms of ratios of simple physical quantities, and converted to decibels only at the end. Such an approach provides both clarity and a systematic rationale for determining how to evaluate each sonar equation term, and occasionally throws up unexpected new corrections. The book will provide a useful reference for acousticians, engineers, physicists, mathematicians, sonar designers, and naval sonar operators whether working in research labs, the defense industry, or universities. Chris Harrison NATO Undersea Research Centre (NURC), Italy, March 2010 xvi Foreword
  15. 15. Acknowledgments The eight years it has taken me to write this book were spent working at TNO in The Hague. It has been a pleasure and a privilege to do so. The Sonar Department, despite two changes of name and two changes of leadership in that time, has provided constant support and understanding for the necessary extra-curricular activities. I wish to thank all at TNO—too many to mention all by name—who helped to make it possible. I thank D. A. Abraham, P. Blondel, D. M. F. Chapman, P. H. Dahl, C. A. F. de Jong, P. A. M. de Theije, D. D. Ellis, R. M. Hamson, C. H. Harrison, J. A. Harrison, R. A. Hazelwood, D. V. Holliday, T. G. Leighton, A. J. Robins, S. P. Robinson, C. A. M. van Moll, K. L. Williams, M. Zampolli, and two anonymous referees, all of whom reviewed at least one complete chapter and helped to improve the quality of the final product. Any remaining errors that find their way into print are entirely mine and not of the reviewers. Through his written publications, David Weston is an eternal inspiration—I have lost count of the number of times his name is cited. I also benefited from discussions with Chris Harrison, Chris Morfey, Christ de Jong, Dale Ellis, Frans-Peter Lam, Mario Zampolli, Peter Dahl, and Tim Leighton. Data or artwork were made available to me by Pascal de Theije (Figure 7.6), Peter Dahl (Figure 8.3), Alvin Robins (Figure 8.5), Vincent van Leijen (Figure 8.13), Peter van Holstein (Figure 8.14), Henry Dol (Figures 9.24 and 9.25), Mathieu Colin (all figures in Chapter 9 making use of either BELLHOP or SCOOTER), Robbert van Vossen (Figures 9.28 and 9.29), Wim Verboom (miscellaneous seal and porpoise audiograms), Garth Mix (thumbnail images of marine mammals), and Paul Wensveen (Figure 11.20). The computer model INSIGHT (version 1.4.2) was used, with permission of CORDA Ltd., to illustrate many of the sonar performance calculations. Also used were the acoustic propagation models SCOOTER and BELLHOP from the Ocean Acoustics Library (http://oalib.hlsresearch.com). Other valuable Internet resources
  16. 16. include FishBase (www.fishbase.org), the Ocean Biogeographic Information System (www.iobis.org), Mathworld (http://mathworld.wolfram.com) and Wikipedia (www. wikipedia.org). Phillipe Blondel and Clive Horwood were always available when needed for advice. Neil Shuttlewood is responsible for a professional end-product. Last but not least, none of this would have been possible without the unquestioning love and support from my wife Pilar and patience of my daughter Anna, whose teenage years are forever tinted with shades of sonar performance. Michael A. Ainslie TNO, The Hague, The Netherlands, March 2010 xviii Acknowledgments
  17. 17. Figures 1.1 Sketch of Beudant’s experiment of ca. 1816 . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2 Sketch of the Colladon–Sturm experiment of 1826 . . . . . . . . . . . . . . . . . . . 9 1.3 Inventor Reginald Fessenden and physicist Jean Daniel Colladon . . . . . . . . 9 1.4 Physicists Paul Langevin and Robert William Boyle . . . . . . . . . . . . . . . . . . 11 1.5 French statesman and mathematician Paul Painleve´ . . . . . . . . . . . . . . . . . . 13 1.6 Installation of early U.S. passive-ranging sonar with two towed eels . . . . . . 15 1.7 Sound absorption vs. frequency in seawater . . . . . . . . . . . . . . . . . . . . . . . . 19 2.1 Attenuation coefficient and audibility vs. frequency in seawater . . . . . . . . . . 30 2.2 Radiation from a point source of power W in free space . . . . . . . . . . . . . . 33 2.3 Radiation from a point source in the presence of a reflecting boundary . . . . 35 2.4 Radiation from a sheet source element of width r. . . . . . . . . . . . . . . . . . . 38 2.5 Beam patterns for L= ¼ 5 and steering angles 0, 45 deg. . . . . . . . . . . . . . . 46 2.6 Probability density functions of noise and signal-plus-noise observables . . . 50 3.1 Principles of passive detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2 Spectral density level of the radiated power at the source and intensity at the receiver. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.3 Spectral density level of the transmitter source factor and mean square pressure at the receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.4 Coherent propagation loss vs. range and target depth. . . . . . . . . . . . . . . . . 66 3.5 Spectral density level of background noise. . . . . . . . . . . . . . . . . . . . . . . . . 67 3.6 Spectral density level of signal and noise . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.7 ROC curves for a Rayleigh-distributed signal in Rayleigh noise. . . . . . . . . . 72 3.8 Propagation loss and figure of merit vs. target range . . . . . . . . . . . . . . . . . 76 3.9 Signal level vs. target range, and in-beam noise level . . . . . . . . . . . . . . . . . 77 3.10 Linear signal excess and twice detection probability vs. range for NB passive sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 3.11 Signal excess vs. target range and depth . . . . . . . . . . . . . . . . . . . . . . . . . . 79 3.12 Spectral density level of the transmitter source factor and mean square pressure at the receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.13 Propagation loss vs. frequency and target range . . . . . . . . . . . . . . . . . . . . . 83
  18. 18. 3.14 Spectral density level of signal and noise . . . . . . . . . . . . . . . . . . . . . . . . . . 84 3.15 ROC curves for a BB signal in Rayleigh noise . . . . . . . . . . . . . . . . . . . . . . 86 3.16 Propagation loss and figure of merit vs. range . . . . . . . . . . . . . . . . . . . . . . 91 3.17 Signal spectrum level vs. range, and in-beam noise spectrum level . . . . . . . . 92 3.18 Linear signal excess and twice detection probability vs. range for BB passive sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 3.19 Propagation loss vs. range and depth for the BB passive worked example . . 94 3.20 Principles of active detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 3.21 Propagation loss and figure of merit vs. target range at fixed array depth and vs. array depth for fixed range. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 3.22 Signal level and in-beam noise level vs. target range at fixed array depth and vs. array depth for fixed range. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 3.23 Linear signal excess and twice detection probability for coherent CW active sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 3.24 Signal excess vs. target range and array depth . . . . . . . . . . . . . . . . . . . . . . 111 3.25 Signal and (in-beam) background levels vs. target range at fixed array depth and vs. array depth for fixed range . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 3.26 Total background, background components, and in-beam background level vs. target range at fixed array depth and vs. array depth for fixed range . . . . . . 119 3.27 Propagation loss and figure of merit vs. target range at fixed array depth and vs. array depth for fixed range. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 3.28 Linear signal excess and twice detection probability for incoherent CW active sonar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 4.1 Global bathymetry map derived from satellite measurements of the gravity field 127 4.2 Annual average temperature map at depth 3 km. . . . . . . . . . . . . . . . . . . . . 129 4.3 Geographical variations in surface temperature for northern winter and northern summer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 4.4 Temperature profiles for locations in the northwest Pacific Ocean and northeast Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 4.5 Bathymetry map for the northwest Pacific Ocean . . . . . . . . . . . . . . . . . . . . 132 4.6 Bathymetry map for the north Atlantic Ocean . . . . . . . . . . . . . . . . . . . . . . 132 4.7 Annual average salinity map at depth 3 km . . . . . . . . . . . . . . . . . . . . . . . . 133 4.8 Temperature salinity diagram for the World Ocean . . . . . . . . . . . . . . . . . . 134 4.9 Seasonal variations in surface salinity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 4.10 Salinity profiles for locations in the northwest Pacific Ocean and northeast Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 4.11 Density profiles for locations in the northwest Pacific Ocean and northeast Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 4.12 Global acidity (K) contours at sea surface and at depth 1 km . . . . . . . . . . . 140 4.13 Arctic acidity (K) contours at the sea surface and at depth 1 km . . . . . . . . . 142 4.14 Acidity (K) profiles for major oceans . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 4.15 Sound speed profiles for locations in the northwest Pacific Ocean and northeast Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 4.16 Seawater attenuation coefficient vs. frequency . . . . . . . . . . . . . . . . . . . . . . 149 4.17 Fractional sensitivity of seawater attenuation to temperature, salinity, acidity, and depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 4.18 Geographical distribution of herring and Norway pout in the North Sea . . . 160 4.19 Wind speed scaling factors to convert from a 20 m reference height to the standard reference height of 10 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 xx Figures
  19. 19. 4.20 Near-surface bubble population density spectra . . . . . . . . . . . . . . . . . . . . . 170 4.21 Compressional and shear speed vs. density of rocks . . . . . . . . . . . . . . . . . . 181 4.22 Compressional and shear speeds vs. density for all rocks and for basalts . . . 183 5.1 Illustration of compressional and shear wave propagation. . . . . . . . . . . . . . 195 5.2 Fluid sediment layer between two uniform half-spaces . . . . . . . . . . . . . . . . 202 5.3 Form function j f ðkaÞj vs. ka for a rigid sphere, a tungsten carbide sphere, and spheres made of various metals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 5.4 Resonance frequency vs. bubble radius for air bubbles in water. . . . . . . . . . 238 5.5 Resonant bubble radius vs. frequency for air bubbles in water. . . . . . . . . . . 241 6.1 Sinc beam patterns for steering angles 0, 30, 60, and 90 deg . . . . . . . . . . . . 254 6.2 Beam patterns for continuous line array: cosine and Hann shading . . . . . . . 258 6.3 Beam patterns for continuous line array: raised cosine shading . . . . . . . . . . 260 6.4 Hamming family shading patterns and beam patterns. . . . . . . . . . . . . . . . . 262 6.5 Beam pattern of unshaded circular array. . . . . . . . . . . . . . . . . . . . . . . . . . 265 6.6 Directivity index for an unsteered continuous line array vs. normalized array length. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 6.7 Directivity index vs. steering angle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 6.8 Shading factor vs. steering angle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 6.9 Power spectrum for a Gaussian LFM pulse . . . . . . . . . . . . . . . . . . . . . . . . 288 6.10 Power spectrum for a rectangular LFM pulse . . . . . . . . . . . . . . . . . . . . . . 289 6.11 Generic ambiguity surface for Gaussian CW pulse . . . . . . . . . . . . . . . . . . . 302 6.12 Ambiguity surfaces for Gaussian CW pulses of duration 0.5 s and 2.0 s . . . . 303 6.13 Generic ambiguity surfaces for Gaussian LFM pulse . . . . . . . . . . . . . . . . . 305 7.1 ROC curves for non-fluctuating amplitude signal in Rayleigh noise . . . . . . . 315 7.2 Rayleigh, one-dominant-plus-Rayleigh, Dirac, and Rice probability distribu- tion functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318 7.3 ROC curves for Rayleigh-fading signal in Rayleigh noise . . . . . . . . . . . . . . 319 7.4 ROC curves for Rician fading signal in Rayleigh noise. . . . . . . . . . . . . . . . 321 7.5 Rice probability density functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 7.6 ROC curves for 1D þ R signal in Rayleigh noise . . . . . . . . . . . . . . . . . . . . 324 7.7 Graph of xðMÞ vs. M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 7.8 ROC curves (Albersheim approximation) for a non-fluctuating amplitude signal: variation of detection threshold with M for fixed pfa . . . . . . . . . . . . 332 7.9 ROC curves (Albersheim approximation) for a non-fluctuating amplitude signal: variation of detection threshold with pfa for fixed M . . . . . . . . . . . . 333 7.10 ROC curves for a non-fluctuating amplitude signal: incoherent addition with M ¼ 30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 7.11 ROC curves for a non-fluctuating amplitude signal: incoherent addition with M ¼ 1 to M ¼ 300 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 7.12 ROC curves for a broadband signal: limit of large M. . . . . . . . . . . . . . . . . 338 7.13 Supplementary ROC curves for a broadband non-fluctuating signal. . . . . . . 339 7.14 ROC curves for a Rayleigh fading signal: incoherent addition with M ¼ 30 . 341 7.15 ROC curves for a 1D þ R signal: incoherent addition with M ¼ 30 . . . . . . . 343 7.16 Fusion gain vs. pfa for OR operation (fixed pd) . . . . . . . . . . . . . . . . . . . . . 352 7.17 Fusion gain vs. F for OR operation (fixed D) . . . . . . . . . . . . . . . . . . . . . . 353 7.18 ROC curves for a non-fluctuating signal: effect of AND and OR fusion. . . . 354 7.19 ROC curves for a 1D þ R signal: effect of AND and OR fusion . . . . . . . . . 355 7.20 ROC curves for a Rayleigh-fading signal: effect of AND and OR fusion . . . 356 8.1 Variation of surface reflection loss with wind speed (1–4 kHz) . . . . . . . . . . . 366 Figures xxi
  20. 20. 8.2 Surface reflection loss in nepers calculated vs. angle and frequency . . . . . . . 368 8.3 Surface reflection loss vs. wind speed (30 kHz) . . . . . . . . . . . . . . . . . . . . . . 369 8.4 Seabed reflection loss vs. grazing angle for uniform unconsolidated sediments 376 8.5 Seabed reflection loss vs. angle and frequency–sediment thickness product for a layered unconsolidated sediment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 8.6 Seabed reflection loss vs. angle for rocks . . . . . . . . . . . . . . . . . . . . . . . . . . 385 8.7 Seabed reflection loss vs. angle and frequency–sediment thickness product for a sand sediment overlying a granite basement and clay over basalt. . . . . . . . . 387 8.8 Seabed reflection loss vs. angle and frequency–sediment thickness product for a sand sediment of thickness 10 m overlying a granite basement and a clay sediment of thickness 300 m over basalt. . . . . . . . . . . . . . . . . . . . . . . . . . . 390 8.9 Seabed backscattering strength for a medium sand sediment and frequency 1–30 kHz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 8.10 Comparison between predicted and measured seabed backscattering strength for a fine sand sediment and frequency 35 kHz. . . . . . . . . . . . . . . . . . . . . . 394 8.11 Seabed backscattering strength for a coarse clay sediment. . . . . . . . . . . . . . 395 8.12 Comparison between predicted and measured seabed backscattering strength for a medium silt sediment and frequency 20 kHz. . . . . . . . . . . . . . . . . . . . 396 8.13 Typical ambient noise spectra. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 8.14 Typical values of sound pressure level and peak pressure level. . . . . . . . . . . 418 8.15 Measured equivalent source spectral density levels: commercial and industrial shipping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 422 8.16 Estimated third-octave monopole source level: cargo ship Overseas Harriette 423 8.17 Areic dipole source spectrum: wind noise . . . . . . . . . . . . . . . . . . . . . . . . . 426 8.18 Areic dipole source spectrum: rain noise . . . . . . . . . . . . . . . . . . . . . . . . . . 428 8.19 Measured waveform and frequency spectrum of a single shrimp snap . . . . . 430 9.1 Geometry for bottom reflections in deep water . . . . . . . . . . . . . . . . . . . . . 441 9.2 Propagation loss vs. range for reflecting seabed at f ¼ 250 Hz . . . . . . . . . . . 442 9.3 Bottom-refracted ray paths travel through the sediment and form a caustic in the reflected field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 9.4 Propagation loss vs. range for a reflecting and refracting seabed at f ¼ 250 Hz 446 9.5 Propagation loss vs. range for a reflecting and refracting seabed: sensitivity to sediment properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450 9.6 Reflection loss vs. angle for sand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455 9.7 Propagation loss vs. range, and reflection loss vs. angle for sand and mud in shallow water at frequency 250 Hz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456 9.8 Sound speed profile in the northwest Pacific . . . . . . . . . . . . . . . . . . . . . . . 460 9.9 Propagation loss vs. range for northwest Pacific summer and winter at f ¼ 1500 Hz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 9.10 Propagation loss vs. range and depth for northwest Pacific winter profile: effect of upward refraction in surface duct . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465 9.11 Depth factor vs. receiver depth in surface duct. . . . . . . . . . . . . . . . . . . . . . 469 9.12 Ray trace illustrating formation of caustics and cusps in surface duct up to a range of 40 km, for a source depth of 30 m, and for the same case as Figure 9.10 470 9.13 Propagation loss vs. frequency and range for a surface duct . . . . . . . . . . . . 473 9.14 Ray trace illustrating the formation of convergence zones at the sea surface 475 9.15 Propagation loss vs. range and depth: effect of downward refraction on Lloyd mirror interference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 xxii Figures
  21. 21. 9.16 Propagation loss vs. range for shallow water with a mud bottom for two different sound speed profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 9.17 Approximation to D= for fixed min . . . . . . . . . . . . . . . . . . . . . . . . . . . . 482 9.18 Predicted deep ocean noise spectra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 9.19 Sensitivity of deep-water ambient noise spectra to rain rate. . . . . . . . . . . . . 486 9.20 Sensitivity of deep-water noise spectra to wind speed . . . . . . . . . . . . . . . . . 487 9.21 Predicted ambient noise spectral density level vs. frequency and depth . . . . . 488 9.22 Effect of the seabed on the ambient noise spectrum in isovelocity water . . . . 489 9.23 Effect of the sound speed profile on the ambient noise spectrum for a clay seabed 490 9.24 Dredger noise map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491 9.25 Bathymetry used for Figure 9.24. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 9.26 Reverberation for problem RMW11 and frequency 3.5 kHz . . . . . . . . . . . . 499 9.27 Reverberation depth factor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 9.28 Reverberation for problem RMW12 and frequency 3.5 kHz . . . . . . . . . . . . 504 9.29 Reverberation for problem RMW12 and frequency 3.5 kHz (close-up) . . . . . 505 9.30 Ray trace illustrating formation of caustics and cusps in a bottom duct, and propagation loss vs. range and depth at f ¼ 3.5 kHz. . . . . . . . . . . . . . . . . . 506 9.31 SRR depth factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509 10.1 Maximum multibeam echo sounder and sidescan sonar source levels vs. transmitter frequency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 10.2 Unweighted and Gaussian-weighted cosine pulses from Table 10.16 . . . . . . 530 10.3 Exponentially damped sine and decaying exponential pulses from Table 10.17 532 10.4 Mean square pressure vs. energy fraction. . . . . . . . . . . . . . . . . . . . . . . . . . 535 10.5 Comparison of echolocation pulses made by the harbor porpoise and killer whale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 548 10.6 Underwater audiograms for harbor porpoise . . . . . . . . . . . . . . . . . . . . . . . 551 10.7 Underwater audiograms for killer whale . . . . . . . . . . . . . . . . . . . . . . . . . . 552 10.8 Underwater audiograms for harbor seal . . . . . . . . . . . . . . . . . . . . . . . . . . 554 10.9 Underwater audiograms for human divers . . . . . . . . . . . . . . . . . . . . . . . . . 556 10.10 Underwater sound level weighting curves for three groups of cetaceans plus pinnipeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561 11.1 Directivity index DI ¼ 10 log10 GD for an unsteered continuous line array vs. normalized array length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 11.2 ROC curves for 1D þ R amplitude signal in Rayleigh noise . . . . . . . . . . . . 582 11.3 Propagation loss vs. range for NWP winter case . . . . . . . . . . . . . . . . . . . . 584 11.4 In-beam signal and noise levels vs. range for NWP winter and Chapter 3 NBp worked example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586 11.5 Input parameters for northwest Pacific (NWP) problem . . . . . . . . . . . . . . . 588 11.6 Signal excess vs. range and depth for NWP winter . . . . . . . . . . . . . . . . . . . 589 11.7 Signal excess vs. range and depth for NWP winter: close-up of first convergence zone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590 11.8 Albersheim’s approximation for the detection threshold . . . . . . . . . . . . . . . 598 11.9 Propagation loss vs. range and depth for SWS and for the Chapter 3 BBp worked example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 600 11.10 Signal and noise spectra for SWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601 11.11 In-beam signal and noise levels vs. range for SWS and BBp . . . . . . . . . . . . 602 11.12 Signal excess vs. range and depth for SWS . . . . . . . . . . . . . . . . . . . . . . . . 603 11.13 Input parameters for shallow-water sand (SWS). . . . . . . . . . . . . . . . . . . . . 604 11.14 In-beam signal and noise spectra for SWS . . . . . . . . . . . . . . . . . . . . . . . . . 605 Figures xxiii
  22. 22. 11.15 Signal excess vs. range and rainfall rate for SWS . . . . . . . . . . . . . . . . . . . . 606 11.16 Geometry for worked example involving killer whale hunting salmon . . . . . 614 11.17 Example measurements of orca pulse shapes and power spectra . . . . . . . . . 615 11.18 Variation in orca source level with distance from target . . . . . . . . . . . . . . . 617 11.19 Propagation loss vs. distance and broadband correction . . . . . . . . . . . . . . . 618 11.20 Orca audiogram and individual hearing threshold measurements . . . . . . . . . 620 11.21 Echo level and noise level vs. distance between orca and salmon: wind speed 2 m/s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 11.22 Echo level and noise level vs. distance between orca and salmon: wind speed 2 to 10 m/s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624 11.23 Background level vs. distance between orca and salmon: wind speed 10 m/s . 628 11.24 Array gain vs. distance between orca and salmon: wind speed 10 m/s . . . . . . 629 11.25 Signal and background levels vs. distance between orca and salmon: wind speed 10 m/s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 630 A.1 The complementary error function erfcðxÞ and three approximations . . . . . . 638 A.2 The gamma function and four approximations. . . . . . . . . . . . . . . . . . . . . . 643 A.3 The modified Bessel function and Levanon’s approximation . . . . . . . . . . . . 647 xxiv Figures
  23. 23. Tables 2.1 Detection truth table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1 Sonar equation calculation for NB passive example . . . . . . . . . . . . . . . . . . 76 3.2 Sonar equation calculation for BB passive example . . . . . . . . . . . . . . . . . . 90 3.3 Sonar equation calculation for CW active sonar example with Doppler filter 107 3.4 Sonar equation calculation for CW active sonar example with incoherent energy detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 4.1 Average salinity and potential temperature by major ocean basin . . . . . . . . 133 4.2 Seawater parameters used for evaluation of attenuation curves plotted in Figure 4.16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 4.3 Mass, length, and aspect ratio of selected sea mammals . . . . . . . . . . . . . . . 154 4.4 Volume and surface area of ellipsoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 4.5 Acoustical properties of fish flesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 4.6 Acoustical properties of whale tissue. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 4.7 Acoustical properties of euphausiids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 4.8 Values of zooplankton density and sound speed ratios . . . . . . . . . . . . . . . . 157 4.9 North Sea fish population estimates by species. . . . . . . . . . . . . . . . . . . . . . 158 4.10 WMO Beaufort wind force scale and estimated wind speed. . . . . . . . . . . . . 162 4.11 Comparison of wind speed estimates for Beaufort force 1–11 based on WMO code 1100 and CMM-IV with those of da Silva . . . . . . . . . . . . . . . . . . . . . 165 4.12 Definition of sea state . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 4.13 Beaufort wind force: relationship between wind speed and wave height . . . . 168 4.14 Sea state: relationship between wave height and wind speed . . . . . . . . . . . . 168 4.15 Sediment type vs. grain diameter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.16 Definition of sediment grain sizes and qualitative descriptions . . . . . . . . . . . 174 4.17 Default HF geoacoustic parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 4.18 Default MF geoacoustic parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 4.19 Names of sedimentary rocks resulting from the lithification of different sediment types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 4.20 Geoacoustic parameters for sedimentary and igneous rocks. . . . . . . . . . . . . 183
  24. 24. 5.1 Compressional speed, shear speed, and density used to calculate the form factors for the four metals shown in Figure 5.3 . . . . . . . . . . . . . . . . . . . . . 212 5.2 Backscattering cross-sections of large rigid objects . . . . . . . . . . . . . . . . . . . 213 5.3 Backscattering cross-sections of large fluid objects . . . . . . . . . . . . . . . . . . . 215 5.4 Water and solid grain sediment parameter values needed for Buckingham’s grain-shearing model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 5.5 Values of physical constants used for the evaluation of the bubble resonance characteristics in Figures 5.4 and 5.5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 6.1 Summary of properties for various taper functions. . . . . . . . . . . . . . . . . . . 264 6.2 Summary of beam properties for selected shading . . . . . . . . . . . . . . . . . . . 265 6.3 Summary of frequency domain properties of simple pulse envelopes . . . . . . 284 6.4 Summary of time domain properties of simple pulse shapes (envelope). . . . . 285 6.5 Summary of time domain properties of simple pulse shapes (phase). . . . . . . 285 6.6 Summary of amplitude envelopes required to synthesize simple power spectra 291 6.7 Autocorrelation functions for CW and LFM pulses . . . . . . . . . . . . . . . . . . 296 6.8 Derivation of matched filter gain for pulse duration and sample interval . . . 306 6.9 Effect of multipath on matched filter gain . . . . . . . . . . . . . . . . . . . . . . . . . 308 7.1 Comparison table: moments of probability distribution functions . . . . . . . . 320 7.2 DT þ 5 log10 M vs. M and pfa for three different pd values . . . . . . . . . . . . . 334 7.3 Application of the detection theory results of Section 7.1 to active sonar CW and FM pulses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 7.4 Equations for the detection probability for different signal amplitude distribu- tions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 7.5 Application of detection theory results to NB and BB passive sonar . . . . . . 346 7.6 Detection threshold for various statistics . . . . . . . . . . . . . . . . . . . . . . . . . . 347 7.7 Detection threshold for a 1D þ R amplitude distribution . . . . . . . . . . . . . . 348 7.8 ROC relationships and fusion gain for AND and OR operations for fixed SNR 353 8.1 Sediment properties at top and bottom of the transition layer . . . . . . . . . . . 381 8.2 p and s critical angles for representative rock parameters . . . . . . . . . . . . . . 385 8.3 Parameters for uniform fluid sediment and rock half-space . . . . . . . . . . . . . 388 8.4 Defining parameters for a layered solid medium. . . . . . . . . . . . . . . . . . . . . 389 8.5 Measurements of the Lambert parameter . . . . . . . . . . . . . . . . . . . . . . . . . 397 8.6 Target strength measurements for bladdered fish . . . . . . . . . . . . . . . . . . . . 401 8.7 Target strength measurements for whales . . . . . . . . . . . . . . . . . . . . . . . . . 403 8.8 Target strength measurements for euphausiids and bladder-less fish . . . . . . . 404 8.9 Target strength measurements for jellyfish . . . . . . . . . . . . . . . . . . . . . . . . . 407 8.10 Target strength measurements for siphonophores . . . . . . . . . . . . . . . . . . . . 407 8.11 Second World War measurements of the target strength of man-made objects 408 8.12 Predicted average night-time contribution to VBS, CS, and attenuation due to pelagic fish in the North Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 8.13 Default advice for VBS for sparse, intermediate, and dense marine life . . . . 411 8.14 Wake strength measurements for various WW2 surface ships . . . . . . . . . . . 414 8.15 Wake strength for various WW2 submarines . . . . . . . . . . . . . . . . . . . . . . . 414 8.16 Third-octave source levels of various commercial and industrial vessels . . . . 421 9.1 Characteristic properties from Chapter 4 of medium sand and mud. . . . . . . 454 9.2 Sound speed profiles for the northwest Pacific location. . . . . . . . . . . . . . . . 461 9.3 Nomenclature used for shipping densities . . . . . . . . . . . . . . . . . . . . . . . . . 484 9.4 Seabed parameters for problems RMW11 and RMW12 . . . . . . . . . . . . . . . 500 xxvi Tables
  25. 25. 9.5 Caustic ranges and corresponding two-way travel arrival times for a source at depth 30 m and receiver at depth 50 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 10.1 Source level of single-beam echo sounders . . . . . . . . . . . . . . . . . . . . . . . . . 516 10.2 Source level of sidescan sonar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 10.3 Source level of multibeam echo sounders. . . . . . . . . . . . . . . . . . . . . . . . . . 518 10.4 Source level of depth profilers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 520 10.5 Source level of fisheries search sonar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 520 10.6 Source level of hull-mounted search sonar . . . . . . . . . . . . . . . . . . . . . . . . . 521 10.7 Source level of helicopter dipping sonar . . . . . . . . . . . . . . . . . . . . . . . . . . 521 10.8 Source level of active towed array sonar . . . . . . . . . . . . . . . . . . . . . . . . . . 522 10.9 Source level of miscellaneous search sonar (including coastguard and risk mitigation sonar). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522 10.10 Source level of low-amplitude acoustic deterrents . . . . . . . . . . . . . . . . . . . . 524 10.11 Source level of high-amplitude acoustic deterrents . . . . . . . . . . . . . . . . . . . 525 10.12 Source level of acoustic communications systems . . . . . . . . . . . . . . . . . . . . 526 10.13 Source level of selected acoustic transponders and alerts . . . . . . . . . . . . . . . 527 10.14 Source level of acoustic cameras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 10.15 Source level of miscellaneous oceanographic sonar . . . . . . . . . . . . . . . . . . . 528 10.16 Relationships between different source level definitions for two symmetrical wave forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529 10.17 Relationships between different source level definitions for two asymmetrical wave forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 10.18 Relative MSP, averaged over time window during which local average exceeds specified threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533 10.19 Relative MSP, averaged over time window during which pulse energy accumulates to specified proportion of total. . . . . . . . . . . . . . . . . . . . . . . . 534 10.20 Dipole source level of air guns and air gun arrays . . . . . . . . . . . . . . . . . . . 536 10.21 Zero-to-peak source level of generator–injector air guns . . . . . . . . . . . . . . . 537 10.22 Zero-to-peak source level of seismic survey sources other than air guns . . . . 538 10.23 Summary of peak pressure and pulse energy for three types of explosive . . . 540 10.24 Specific pulse energy and apparent specific SLE for pentolite. . . . . . . . . . . . 541 10.25 Echolocation pulse parameters for selected animals . . . . . . . . . . . . . . . . . . 543 10.26 Maximum peak-to-peak source levels of high-frequency marine mammal clicks 546 10.27 Peak equivalent RMS and peak-to-peak source levels of low-frequency marine mammal pulses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 548 10.28 Hearing thresholds and sensitive frequency bands of selected cetaceans . . . . 553 10.29 MSP and EPWI hearing thresholds in air and water for four pinnipeds plus human subjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555 10.30 Hearing thresholds in water for 10 species of fish. . . . . . . . . . . . . . . . . . . . 557 10.31 Parameters of bandpass filter used in M-weighting . . . . . . . . . . . . . . . . . . . 560 10.32 Genera represented by the functional hearing groups . . . . . . . . . . . . . . . . . 561 10.33 Proposed thresholds of M-weighted sound exposure level for permanent and temporary auditory threshold shift in cetaceans and pinnipeds . . . . . . . . . . 562 10.34 Proposed thresholds of peak pressure for permanent and temporary auditory threshold shift in cetaceans and pinnipeds . . . . . . . . . . . . . . . . . . . . . . . . . 563 10.35 Outline of the severity scale from Southall et al. (2007). . . . . . . . . . . . . . . . 564 10.36 Spread of sound pressure level values resulting in the specified behavioral responses in cetaceans and pinnipeds for nonpulses. . . . . . . . . . . . . . . . . . . 564 Tables xxvii
  26. 26. 10.37 Spread of sound pressure level values resulting in the specified behavioral responses in cetaceans and pinnipeds for multiple pulses . . . . . . . . . . . . . . . 565 11.1 List of applications of man-made active and passive underwater acoustic sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 575 11.2 Error in DT incurred by assuming 1D þ R statistics . . . . . . . . . . . . . . . . . . 582 11.3 Sonar equation calculation for NWP winter . . . . . . . . . . . . . . . . . . . . . . . 587 11.4 Filter gain vs. bandwidth in octaves for a white signal and colored noise . . . 596 11.5 Sonar equation calculation for shallow-water sand . . . . . . . . . . . . . . . . . . . 604 11.6 Active sonar example, limited by hearing threshold . . . . . . . . . . . . . . . . . . 620 11.7 Active sonar example, limited by wind noise . . . . . . . . . . . . . . . . . . . . . . . 624 A.1 Integrals of integer powers of the sine cardinal function . . . . . . . . . . . . . . . 636 A.2 Selected values of the gamma function GðxÞ for 0 x 1 . . . . . . . . . . . . . 640 A.3 Examples of Fourier transform pairs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 650 B.1 SI prefixes for indices equal to an integer multiple of 3. . . . . . . . . . . . . . . . 660 B.2 SI prefixes for indices equal to an integer between þ3 and À3. . . . . . . . . . . 661 B.3 Frequently encountered non-SI units. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 662 B.4 List of abbreviations and acronyms, and their meanings . . . . . . . . . . . . . . . 667 C.1 Bladder presence and type key used in Tables C.3, C.4, and C.7 . . . . . . . . . 674 C.2 Reference key . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 674 C.3 Bladder type by order for ray-finned fishes (Actinopterygii) . . . . . . . . . . . . 675 C.4 Bladder type by family. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676 C.5 ‘‘Catchability’’ key (Yang groups) used in Table C.7 . . . . . . . . . . . . . . . . . 677 C.6 Length key used in Table C.7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 677 C.7 Fish and their bladders, sorted by scientific name. . . . . . . . . . . . . . . . . . . . 678 xxviii Tables
  27. 27. Part I Foundations
  28. 28. 1 Introduction Wee represent Small Sounds as Great and Deepe; Likewise Great Sounds, Extenuate and Sharpe; Wee make diverse Tremblings and Warblings of Sounds, which in their Originall are Entire. Wee represent and imitate all Articulate Sounds and Letters, and the Voices and Notes of Beasts and Birds. Wee have certaine Helps, which sett to the Eare doe further the Hearing greatly. Wee have also diverse Strange and Artificiall Eccho’s, Reflecting the Voice many times, and as it were Tossing it; And some that give back the Voice Lowder then it came, some Shriller, and Some Deeper; Yea some rendring the Voice, Differing in the Letters or Articulate Sound, from that they receyve. Wee have also meanes to convey Sounds in Trunks and Pipes in strange Lines, and Distances. Francis Bacon (1624) 1.1 WHAT IS SONAR? Sonar can be thought of as a kind of underwater radar, using sound instead of radio waves to interrogate its surroundings. But what is special about sound in the sea? Radio waves travel unhindered in air, whereas sound energy is absorbed relatively quickly. In water, the opposite is the case: low absorption and the presence of natural oceanic waveguides combine to permit propagation of sound over thousands of kilometers, whereas the sea is opaque to most of the electromagnetic spectrum. The word sonar is an acronym for sound navigation and ranging. The primary purpose of sonar is the detection or characterization (estimation of position, velocity, and identity) of submerged, floating, or buried objects. Electronic systems capable of
  29. 29. underwater detection and localization were developed in the 20th century, motivated initially by the sinking of RMS Titanic in 1912 and the First World War (WW1), and spurred on later by the Second World War (WW2) and the Cold War. Nevertheless, by comparison with marine fauna, man remains a novice user of underwater sound. Deprived of light in their natural habitat, dolphins have evolved a sophisticated form of sonar over millions of years, without which they would be almost blind. They transmit bursts of ultrasound, and sense the world around them by interpreting the echoes. Many fish and other aquatic animals are also capable of both producing and hearing sounds. 1.2 PURPOSE, SCOPE, AND INTENDED READERSHIP This book is aimed at anyone, novice and experienced practitioner alike, with an interest in estimating the performance of sonar, or understanding the conditions for which a particular existing or hypothetical system is likely to make a successful detection. This includes sonar analysts and designers, whether for oceanographic research, navigation, or search sonar. It also includes those studying the use of sound by marine mammals and the impact of exposure of these animals to sound. Regard- less of application, the objective of sonar performance modeling is usually to support a decision-making process. In the case of man-made sonar, the decision is likely to involve the optimization of some aspect of the design, procurement, or use of sonar. (What frequency or bandwidth is appropriate? How many sonars are needed to complete the task in the time available?) For bio-sonar there is increasing interest in the assessment (and mitigation) of the risk of damage to marine life due to anthropogenic sources of underwater sound. (What level of sound might disrupt a dolphin’s ability to locate and capture its prey? How can the risk of hearing damage be prevented or minimized?) The nature of the sought object, known as the sonar target, depends on the application. Examples include man-made objects of military interest (a mine or submarine), shipwrecks (as a navigation hazard or archeological artifact), and fish (the target of interest to a whale or fisherman). In general, sonar can be grouped into two main categories. These are active sonar and passive sonar, which are distinguished by the presence and absence, respectively, of a sound transmitter as a component of the sonar system. . An active sonar system comprises a transmitter and a receiver and works on the principle of echolocation. If a signal (in this case an echo from the target) is detected, the position of the target can be estimated from the time delay and direction of the echo. The echolocation principle is also used by radar, and by the biological sonar of bats and dolphins. . A passive sonar includes a receiver but no transmitter. The signal to be detected is then the sound emitted by the target. Examples of man-made sonar include 4 Introduction [Ch. 1
  30. 30. . Echo sounder: perhaps the most common of all man-made sonars, an echo sounder is a device for measuring water depth by timing the delay of an echo from the seabed. The strength and character of the echo can also provide an indication of bottom type. . Fisheries sonar: sonar equipment used by the fisheries industry exploits the same principle as the echo sounder, except that the purpose is to detect fish instead of the sea floor. . Military sonar: modern navies deploy a wide variety of sonar systems, designed to detect and track potential military threats such as surface ships, submarines, mines, or torpedoes. The diverse nature of these threats and of the platforms on which the sonar systems are mounted means that military sonars are them- selves diverse, with each specialized system dedicated to a particular task. . Oceanographic sensor: scientific work aimed at understanding and surveying the sea (acoustical oceanography) makes extensive use of a variety of different kinds of sonar, many of which are variants of the echo sounder. . Shadow sensor: in exceptional cases, the sonar ‘‘signal’’, instead of being the sound emitted or scattered by the target, might actually be some perturbation to the expected background. For example, the shadow of an object lying on the seabed might be detectable when the object itself is not. Many readers will be familiar with Urick’s classic Principles of Underwater Sound for Engineers,1 which provided its readers with the tools they needed to carry out sonar design and assessment studies. These tools come in the form of a set of equations relating the predicted signal-to-noise ratio to known parameters such as the radiated power of the sonar transmitter, or the size and shape of the target. This set of equations is known as the ‘‘sonar equations’’. The same basic requirement remains today, but the modeling methods have increased in sophistication during the 25 years that have elapsed since Urick’s third and final edition, with a bewildering array of computer models to choose from (Etter, 2003). The present objective is to meet the needs of the modern user or developer of such models by documenting established methods and relevant research results, using internally consistent definitions and notation throughout. The discipline of sonar performance modeling is perceived sometimes as a black art. The purpose of this book is, above all, to demystify this art by explaining the jargon and deriving the sonar equations from physical princi- ples. The book’s scope includes underwater sound, the properties of the sea relevant to the generation and propagation of sound, and the processing that occurs after an acoustic signal has been converted to an electrical one2 and then digitized. The estimation of sonar performance is taken as far as the detection (and false alarm) probability, but no further than that. While the scope excludes localization, 1.2 Purpose, scope, and intended readership 5]Sec. 1.2 1 See Urick (1967) and two later editions (Urick, 1975, 1983). 2 Conversion between electrical and acoustical energy (known as transduction), whether on transmission or reception, is excluded from the scope. The interested reader is referred to Hunt (1954) and Stansfield (1991).
  31. 31. classification, and tracking tasks, such as the estimation of position and velocity of a sonar target, a satisfactory detection capability is a prerequisite for any of these. 1.3 STRUCTURE Sonar performance modeling is a multidisciplinary science, requiring knowledge of subjects as diverse as mathematics, physics, electrical engineering, chemistry, geology, and biology.3 It is convenient to group the material into four foundation categories (or ‘‘pillars’’), on which the science of sonar performance modeling is built: sonar oceanography, underwater acoustics, sonar signal processing and statistical detection theory. The book has three main parts, described below. 1.3.1 Part I: Foundations (Chapters 1–3) Part I comprises this Introduction and two further chapters, also of an introductory nature. The purpose of Chapter 2 is to describe the essential concepts required for a basic understanding of the sonar equations, which are derived in Chapter 3. Four generic types of sonar are introduced, with a simple worked example provided for each. The material in Chapters 2 and 3 is intended as a primer, to illustrate the principles, and generally preferring simplicity to realism. Advanced readers might prefer to skip the introductory part and start reading from Chapter 4, consulting Chapter 3 only for definitions. 1.3.2 Part II: The four pillars (Chapters 4–7) Each of the four chapters in Part II is devoted to one of the four pillars. The one on oceanography (Chapter 4) describes the sea as a medium for sound propagation. Relevant properties of the oceans’ contents and boundaries are considered, such as the geoacoustical properties of sediments and rocks, sea surface waveheight spectra, near-surface bubble density, and the acoustical properties of marine life. The chapter on acoustics (Chapter 5) provides a theoretical foundation for understanding the behavior of sound in the sea, including reflection and scattering from its contents and boundaries. Cumulative propagation effects associated with multiple boundary reflections are the subject of Chapter 9. An acoustic signal arriving at a sonar receiver is converted to an electrical signal by a device known as a ‘‘transducer’’. This electrical signal is subjected to a series of operations designed to determine the presence or otherwise of a sonar target. These operations are known collectively as signal processing, which is the subject of Chapter 6. The purpose of signal processing can be thought of as either to enhance the signal from the target or to reduce the background noise. These two points of view are 6 Introduction [Ch. 1 3 The reader is assumed to have completed a degree-level course in a numerate discipline such as physics, applied mathematics, or engineering.
  32. 32. entirely equivalent, as in the end what matters is the ratio of signal power to noise power. Finally, to be of practical use, the output of the signal processing must be interpreted by a decision-maker. The chance that a sonar operator correctly (or incorrectly) deduces that a target is present is known as the probability of detection (or false alarm). The quantitative study of detection and false alarm probabilities is known as statistical detection theory, and this is the subject of Chapter 7. 1.3.3 Part III: Towards applications (Chapters 8–11) The purpose of the final chapters is to show how to apply the principles from Parts I and II to more realistic situations. Chapter 8 provides quantitative information about the sources, reflectors, and scatterers of underwater sounds, while Chapter 9 describes sound propagation in the sea and its impact on both the signal and background. Chapter 10 describes the characteristics of both man-made and biological sonar, including the sensitivity of marine animals to underwater sound. Chapter 11 brings together information from all the preceding chapters and applies it to a set of problems partly based on the worked examples of Chapter 3, introducing more advanced concepts and definitions where necessary. It closes with a speculative account of possible future development of sonar performance modeling in the 21st century. 1.3.4 Appendices In addition to the 11 chapters, there are three appendices. Two of these provide information needed for the correct interpretation of the main text, describing special functions and mathematical operations (Appendix A), and units and nomenclature (Appendix B). Finally, Appendix C can be thought of as an extension to Chapter 4. It contains information about fish and their swim bladders that will be of use to a reader interested in the interaction of sound with fish or fish shoals. 1.4 A BRIEF HISTORY OF SONAR The remainder of this Introduction is devoted to a historical account of the devel- opment of sonar. It is the author’s tribute to the work of Constantin Chilowski,4 Daniel Colladon, Pierre and Jacques Curie, Maurice Ewing, Reginald Fessenden, Harvey Hayes, Paul Langevin, H. Lichte, Leonard Liebermann, J. Marcum, Stephen Rice, and Albert Beaumont Wood. It owes its existence in no small part to the detailed accounts of Hunt (1954), Wood (1965), and Hackmann (1984). The history focuses on developments in France, Britain, and the U.S.A., as these are the places where the main early advances took place, especially during WW1. Developments in Germany and the U.S.S.R. are mentioned only briefly, partly due to 1.4 A brief history of sonar 7]Sec. 1.4 4 Zhurkovich (2008) transcribes this name as ‘‘K.V. Shilovsky’’.
  33. 33. the difficulty in finding reliable sources for them (in the case of Russian and Soviet acoustics, corrected recently by the publication of the History of Russian Underwater Acoustics, edited by Godin and Palmer, 2008). 1.4.1 Conception and birth of sonar (–1918) 1.4.1.1 Discovery and ingenuity The concept of echo ranging, by which the distance to an object is determined by measuring the time delay to an echo from that object, originates from at least as far back as the 17th century. More recent origins of sonar can be traced to two seemingly unrelated scientific developments in the 19th century, the first being the measurement of the speed of sound in seawater, ca. 1816, by Franc¸ ois Beudant, in the French Mediterranean. Beudant used a crude but effective method (illustrated in Figure 1.1), involving an underwater bell and a swimmer waving a flag. A more precise determina- tion, with improved light–sound synchronization (Figure 1.2), was made in 1826 by Colladon (Figure 1.3) and Sturm, in Lake Geneva.5 Both measurements are described by Colladon and Sturm (1827), and in both cases the values obtained (1,500 m/s and 8 Introduction [Ch. 1 Figure 1.1. Sketch of Beudant’s experiment of ca. 1816 (reprinted fom Girard, 1877). 5 Their purpose was not to measure the speed of sound for its own sake, but to determine the bulk modulus of water, which can be calculated from the sound speed if its density is known.
  34. 34. 1.4 A brief history of sonar 9]Sec. 1.4 Figure 1.2. Sketch of the Colladon–Sturm experiment of 1826 (reprinted fom Girard, 1877). Figure 1.3. Inventor Reginald Fessenden (left) and physicist Jean Daniel Colladon (right). The image of Fessenden is reprinted from http://www.ieee.ca/millennium/radio/radio_unsung.html, last accessed October 22, 2009, RadioScientist.#
  35. 35. 1,435 m/s) are consistent with modern expectation for the respective measurement conditions. The second important development is the discovery of piezoelectricity by Pierre and Jacques Curie in 1880. Experiments with certain special dielectric crystals (especially quartz and Rochelle salt) revealed that these materials respond to an applied pressure by developing a small potential difference. The converse effect, whereby an applied electric field distorts the shape of the crystal, was predicted shortly afterwards by Gabriel Lippmann and confirmed by the Curie brothers in 1881. In the late 1890s and early 1900s, some lightships were fitted with underwater bells, which were rung to alert approaching vessels of danger in conditions of poor visibility. In good visibility these sounds provided an indication of distance as well, by estimating the time delay between light and sound signals, as when estimating the distance from an electrical storm by counting seconds to the thunder following a bolt of lightning. These early underwater signaling systems would eventually mature into what we now call sonar. 1.4.1.2 The Titanic and the Fessenden oscillator The tragic collision and subsequent sinking of RMS Titanic on the night of April 14/ 15, 1912 resulted in a flurry of activity and ideas directed at providing advance warning of nearby icebergs. Lewis Richardson filed patents first for an airborne echolocation system in April 1912 and a month later for an underwater one. Reginald Fessenden (Figure 1.3) patented an electromagnetic transducer in 1913 and demon- strated its use by detecting the presence of an iceberg on April 27, 1914 at a distance of ‘‘nearly two miles’’ (i.e., approximately 3–4 km). This device became known as the Fessenden oscillator (Waller, 1989). 1.4.1.3 WW1: a sense of urgency It took an even greater tragedy, the loss of life inflicted by U-boats during WW1, to provide the focus of intellect and resources that would lead to the development of a working underwater detection system. French and British efforts began in 1915, with Paul Langevin (Figure 1.4) working in Paris with Russian engineer Constantin Chilowski, while A. B. Wood worked with Harold Gerrard in Manchester. The focus of the French research was on echolocation (‘‘active sonar’’ in modern terminology), while the British team concentrated initially on listening devices known as hydro- phones (‘‘passive sonar’’). At the outset of WW1, Lord Rutherford had assembled an extraordinary group of physicists at his laboratory at the University of Manchester, including the house- hold names Bohr, Geiger, and Chadwick. In his autobiographical account, A. B. Wood recalls (Wood, 1965): ‘‘It would be difficult to find anywhere such a galaxy of scientific talent, either before or since, working together in the same physics labora- tory at the same time.’’ Of particular relevance here are the arrivals of Wood himself in 1915 and of the Canadian physicist Robert Boyle (Figure 1.4) the following year. The Board of Invention and Research (BIR) was established in 1915, with 10 Introduction [Ch. 1
  36. 36. facilities at Hawkcraig (in Fifeshire, Scotland), and expanded in 1917 to a team of more than 80 scientists and technicians working at Parkeston Quay (Harwich, England) under the leadership of Professor W. H. Bragg. Amongst them were Boyle and Wood from Rutherford’s group, responsible, respectively, for research investi- gating echolocation and passive listening. Boyle made promising initial progress with the Fessenden oscillator, such that by late 1917 a submarine detection had been reported at a distance of 1,000 yd (910 m) (Hackmann, 1984, p. 75).6 Nevertheless, this line of work was abandoned because the frequency of Fessenden’s transmitter (1 kHz) was too low to obtain the necessary resolution in bearing for its intended purpose of locating submarines. A high- frequency transducer was needed to achieve this. In France, Langevin had begun to experiment with quartz early in 1917 after obtaining a small supply from a Paris optician. Quartz is a piezoelectric material suitable for the radiation of high-frequency sound,7 but the unamplified received 1.4 A brief history of sonar 11]Sec. 1.4 Figure 1.4. Physicists Paul Langevin (left) and Robert William Boyle (right). The image of Langevin is reprinted from Anon. (wp, a) and that of Boyle from http://www.100years.ualberta. ca, last accessed October 26, 2009. 6 The yard (symbol yd) is a unit of length defined as 0.9144 meters (see Appendix B). 7 Use here of the term ‘‘sound’’ is not restricted to the audible frequency range, but refers also to ‘‘ultrasound’’, which means that the frequency is above the upper limit of normal human hearing (i.e., 20 kHz). In general, it can also refer to sounds below 20 Hz, known as ‘‘infrasound’’. Langevin’s early experiments with quartz (April 1917) were at a frequency of 150 kHz. The frequency was later lowered to 40 kHz in order to reduce absorption.
  37. 37. signals were found to be very weak. Fortunately, a suitable valve amplifier, designed by Le´ on Brillouin and G. A. Beauvais,8 was made available to Langevin soon after, enabling him to build a system by November 1917 that ‘‘gave a signalling distance of up to six kilometres’’ (Hackmann, 1984, p. 81). The real breakthrough came when the French and British teams started sharing their findings after a series of high-level meetings held in Washington, D.C. between May and July 1917. Boyle visited Langevin shortly afterwards, when he would have learnt of the French advances. On his return to England, Boyle started working on quartz transducers, and the French amplifier was made available to the British team at Parkeston Quay. The reliance on quartz was such that, until a suitable supply was identified from Bordeaux, Boyle threatened to ‘‘raid the crystal exhibits in several geological museums’’. Meanwhile, Langevin continued with his own work in Toulon, and by February 1918 had obtained echoes from a submarine using the high-frequency (40 kHz) quartz transducers. Boyle followed suit a month later with a submarine echo from a distance of 500 yd (about 460 m). The Armistice of November 1918 led to the cancellation of plans to fit both British and French navy ships in early 1919, but asdics (as the technology of high-frequency echolocation was then called) was born.9 The term sonar was coined during WW2. The origin of the term asdics as an acronym for Anti-Submarine Division -ics, where the ‘‘ics’’ meant ‘‘activities pertaining to’’ in the same way as in ‘‘physics’’, is recounted by Wood (1965). The alternative explanation (for the term asdic, without the second ‘‘s’’) as an acronym for ‘‘Allied Submarine Detection Investigation Committee’’ appears to be a myth created by the British Admiralty in 1939 in response to a question by Oxford University Press (Hackmann, 1984, p. xxv). During the initial development of the sensor at Parkeston Quay, secrecy was such that even the material quartz was referred to by its codename ‘‘asdivite’’. On the subject of semantics, it is worth mentioning the change in meaning of the word ‘‘supersonic’’ after the end of WW2. Between the two world wars, this term was used in the U.S.A. to mean ‘‘pertaining to sound whose frequency is too high to be heard by the human ear’’, synonymous with the European term ‘‘ultrasonic’’ (Klein, 1968). Today the European term has been adopted worldwide, presumably as a consequence of the modern use of ‘‘supersonic’’ to describe ‘‘faster than sound’’ flight. The first working active sonar was built in November 1918 by Boyle, a Canadian scientist working in England. Reading an account of the early history of echo rang- ing, however, one cannot help being struck by a series of key contributions made by 12 Introduction [Ch. 1 8 This work was assisted by a wireless expert, Paul Pichon. Having deserted from the French army he found himself importing some American valve amplifiers to his adoptive Germany early in WW1. Realizing the military value of these, he took them instead to France where he— though immediately arrested—handed over his equipment to the French authorities. These early valves provided the basis for the Beauvais–Brillouin design (Hackmann, 1984, pp. 80–81). 9 Boyle’s quartz system was fitted to a trawler on November 16, 1918, five days after the end of WW1.
  38. 38. French scientists, including: — the earliest known description of the echo-ranging concept, by Mersenne (1636); — the measurement of the speed of sound in seawater, by Beudant (ca. 1816); — the discovery of piezoelectricity, by the Curie brothers and Lippmann (1880– 1881); — the development of the valve amplifier, by Beauvais and Brillouin (ca. 1916); — pioneering research on the use of quartz transducers, including the first ever detection of an echo from a submarine, by Langevin10 (1917–1918). To this impressive list one can add the work of a remarkable statesman named Paul Painleve´ (Figure 1.5). In January 1915, Chilowski had written a letter urging the French government to develop an underwater echolocation device as a defense against U-boats. Recognizing its importance and urgency, Painleve´ forwarded this letter to Langevin without delay, thus facilitating the early Langevin–Chilowski collaboration. Painleve´ also saw the value in Anglo-French co-operation, requesting a scientific exchange agreement between France and Britain in December 1915. Despite delays caused by opposition from the Admiralty, the agreement, without which the co-operation between Langevin and Boyle might not have flourished, was eventually approved by the British Government in October 1916 (Hack- mann, 1984, p. 39). 1.4.1.4 Origins of passive sonar By comparison with active sonar, invented in a race against time between Chilowski’s 1915 letter and the first successful French and Brit- ish tests in 1917, the arrival of passive sonar was a gradual affair that lasted centuries. Its 15th-century conception in Leonardo da Vin- ci’s device able to detect ships ‘‘at a great distance’’ was followed by a 400-year gesta- tion, including the 18th-century observations of Benjamin Franklin (see Section 1.4.3.3), and culminating in the listening equipment fitted to shipping vessels at the end of the 1.4 A brief history of sonar 13]Sec. 1.4 Figure 1.5. French statesman and mathematician Paul Painleve´ —rep- rinted from Anon. (wp, b). Painleve´ was Minister for Public Instruction and Inventions during the period 1915–1917, and later served two brief periods as Prime Minister in 1917 and 1925. 10 Langevin is one of five sonar scientists after whom the Pioneers of Underwater Acoustics Medal, awarded to this day by the Acoustical Society of America, is named. The others are H. J. W. Fay, R. A. Fessenden, H. C. Hayes, and G. W. Pierce. In 1959, Hayes became the first ever recipient of this medal, which was also awarded to Wood (in 1961) and to Urick (1988).
  39. 39. 19th century to notify them of the presence of nearby lightships: in 1889, the U.S. Lighthouse Board described an invention of L. I. Blake comprising an underwater bell and microphone receiver, and a similar system—patented in 1899 (Hersey, 1977)—was developed a few years later by Elisha Gray and A. J. Mundy (Lasky, 1977).11 In common with the echolocation devices of Langevin and Boyle, it was WW1 that provided the final impetus for the birth of passive sonar. An important difference, though, is that underwater listening equipment was put to practical use well before the end of the war. Portable omnidirectional hydrophones were available as early as 1915, and directional ones followed in 1917. Towed hydrophones were operational before the end of WW1, and in 1918 a prototype passive-ranging system was fitted to an American destroyer. British listening devices used during WW1, based on early American work, were developed at BIR by Wood and Gerrard (occasionally assisted by Rutherford) at Parkeston Quay and by Captain C. P. Ryan at Hawkcraig. To reduce noise, direc- tional hydrophones could be towed behind the ship in a streamlined capsule known as a ‘‘fish’’, developed by G. H. Nash. Ryan constructed a network of up to 18 underwater listening stations positioned strategically in British coastal waters. These listening stations, each comprising a field of hydrophones, were manned with shore-based operators, who listened for distinc- tive U-boat sounds and reported their position to the nearest anti-submarine flotilla. Some minefields were also equipped with special listening devices (magneto- phones), with which it was possible to determine the precise moment at which a U-boat was passing overhead. The mines could then be detonated remotely from a shore-based monitoring facility. According to Hackmann (2000), such minefields were responsible for the destruction of four U-boats towards the end of WW1, the first taking place on August 29, 1918. Early in WW1, Rutherford had proposed the use of an array of multiple hydro- phones, in theory able to both amplify the signal and provide bearing information. The Royal Navy considered the proposed device too unwieldy and the idea was dropped in Britain, but American scientists pursued it and by the end of the war had developed the most sophisticated listening devices of that time (Hayes, 1920). This American research took place at the Naval Experimental Station in New London, under the direction of Harvey Hayes. The property of sound waves that Rutherford wished to exploit is that they retain their phase coherence over distances of at least several wavelengths. The first Amer- ican device to use this property was the ‘‘M-B tube’’, comprising two groups of eight hydrophones each. The (acoustic) signals from each group were combined coherently by a sequence of equal-length delay lines before being presented (binaurally, one coherently summed group in each ear) to a human listener. The construction was such that coherent reinforcement took place from only one direction at a time, so in order to scan over different bearings it was necessary to rotate this device in the water. The inconvenience of the M-B tube—it needed to be lowered into the sea each time it was 14 Introduction [Ch. 1 11 Gray coined the term ‘‘hydrophone’’ to describe their underwater microphone, while Mundy went on to co-found the Submarine Signal Company (now part of Raytheon) in 1901.
  40. 40. used—was overcome by the introduction of variable-length delay lines, which per- mitted the operator to select the direction of listening without any form of mechanical rotation. This meant that the entire device, known as the ‘‘M-V tube’’, could be fixed to a ship’s hull, and used with the ship in motion. The M-V tube had two groups of six hydrophones (later, two groups of ten), the signals from which were presented binaurally in the same way as for the M-B tube. The capability to use the M-V tube in motion was a huge advantage, but it came at a price—the din from a ship underway. To counter the noise problem the ‘‘U-3 tube’’ (nicknamed the ‘‘eel’’), was invented. The eel comprised two groups of six hydrophones towed behind the ship, thus benefiting from lower noise levels. The U-3’s streamlined housing gave it the appearance of a snake or eel—hence its nickname. The key advance that made this possible was the use of electrical instead of acoustical delay lines, making the equipment less bulky. An experimental device comprising two towed eels and two ship-mounted M-V tubes was fitted to an American destroyer in April 1918 (Figure 1.6). The combined system was capable of passive ranging by triangulation of the two different bearings (Hayes, 1920). The first working sonar capable of localization in range and bearing was neither a French nor a British invention, but an American one. 1.4.2 Sonar in its infancy (1918–1939) 1.4.2.1 Fathometers and fish finders In peacetime, the thoughts of sonar engineers turned away from U-boats and back initially to maritime safety, and later to fishing. The principle of acoustic echo ranging was applied to measuring water depth, and Fessenden’s oscillator turned out to be 1.4 A brief history of sonar 15]Sec. 1.4 Figure 1.6. Installation of early U.S. passive-ranging sonar with two towed eels of length 40 ft (12 m), and 12 ft (4 m) apart, and two hull-mounted M-V tubes of the same length. The eel was towed about 300–500 ft (100–150 m) behind the ship (reprinted with permission from Lasky, 1977, copyright 1977 American Institute of Physics).

×