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An acoustic system for autonomous navigation and
tracking of marine fauna.
Pedro R. De La Torre∗, Khaled N. Salama∗, Micha...
Tag
Source level (SL)
Sea water
Transmission
loss (TL)
Hydrophone
Sensitivity (RVS)
Signal
Conditioning
gain (G)
Tone dete...
of its internal voltage controlled oscillator, it locks onto it.
The PLL was tuned to detect 51kHz signals and the DC
outp...
A
Fig. 5. Acoustic range of the hydrophone is represented as a percentage of
accurate detections performed on each of the ...
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An acoustic system for autonomous navigation and tracking of marine fauna.

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IEEE ARTICULE TEMAS ITI SQL SERVER REDES ANALISIS DISEÑO IMPLEMENTACION ITI ARTICULOS PDF ALGORITMOS GENETICOS IA B.D DOCUMENTACION REPORTE REDES NEURONALES IA INTELIGENCIA ARTIFICIAL ANGEL WHA MIGUEL ANGEL GARCIA WHA UPV UNIVERSIDAD POLITECNICA DE VICTORIA GRAFOS NODOS PROGRAMACION LATEX WORD REPORTE PLANTILLA PRACTICA PROYECTO ITI COMPUTACION SISTEMAS WEB ESCRITORIO

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An acoustic system for autonomous navigation and tracking of marine fauna.

  1. 1. An acoustic system for autonomous navigation and tracking of marine fauna. Pedro R. De La Torre∗, Khaled N. Salama∗, Michael L. Berumen∗† ∗ King Abdullah University of Science and Technology, Thuwal, Saudi Arabia † Woods Hole Oceanographic Institution, Woods Hole, USA email: pedro.torre@kaust.edu.sa Abstract—A marine acoustic system for underwater target tracking is described. This system is part of the Integrated Satel- lite and Acoustic Telemetry (iSAT) project to study marine fauna. It is a microcontroller-based underwater projector and receiver. A narrow-band, passive sonar detection architecture is described from signal generation, through transduction, reception, signal processing and up to tone extraction. Its circuit and operation principles are described. Finally, a comparison between the current energy detection method versus an alternative matched filter approach is included. I. INTRODUCTION In the field of marine ecology there are several species that, due to their nature, are particularly difficult to study. They are restless swimmers, deep divers and careless about international boundaries. All of them are ecologically important and some are a source of food, income or both. The Integrated Satellite and Acoustic Telemetry (iSAT) system is an innovative idea to study the movements of these animals in an effort to improve the spatial resolution provided by modern technology. Scientists that want to describe the life characteristics of these species, such as where they live, mate, nurse, feed, or what path do they take to get there, have to be creative. Some have investigated these behaviors by attaching to these animals electronic tags that communicate via a satellite when the animal reaches the surface. Some of the animals do not surface frequently enough to get a high resolution description of its journey, nevertheless, substantial information has been extracted from the coarse resolution that this technology has provided [1]. Marine acoustic bio-telemetry has evolved to the point where the three dimensional description of a tagged animal can be described. Despite the fact that there needs to be a network of acoustic antennas close to the tagged animal, this technology has provided valuable information of marine species [2]. Whale sharks (Rhincodon typus) are being studied in the Red Sea with both technologies [3]. The iSAT project [4], [5], shown in figure 1, aims to overcome the gap of information left by the coarse description of satellite tags and the limited coverage of acoustic receiver networks. iSAT is a vessel with an acoustic antenna under its hull and wireless communication systems on board. It follows autonomously an acoustically tagged marine animal by detecting its position underwater. Because it is at the surface, it is exposed to different com- munication networks, e.g. satellite and mobile, and therefore Fig. 1. Tracking marine fauna with the Integrated Satellite and Acoustic Telemetry (iSAT) system. Under the hull there is an array of hydrophones that detect the direction to the tag attached to the animal. The are wireless communication systems on board to provide near real time coverage. not only provides an accurate GPS reference, but also adds the potential to control remotely its operation and transfer information regularly to a research center. This paper presents the microcontroller based, acoustic communication architecture that links the tag with the vessel at the surface. It is the first system that would not require the animal to reach the surface to communicate its position. A narrow-band communications system with a phase-locked- loop detection scheme was implemented for the purpose. The reader will find the description of an analog signal processing circuit implemented on operational amplifiers. The acoustic link is described as a passive acoustic sonar and a model for its operation is presented. The last part of the document compares the current energy-based detection algorithm with an alternative correlation-based and illustrates how both are a suitable alternative to detect the source location underwater for tracking purposes. II. A NARROW BAND UNDERWATER ACOUSTIC LINK. The acoustic system is described in two parts: the projector, i.e. the tag that will be attached to an animal for iSAT to be able to track it, and the hydrophone that receives the 978-1-4799-4132-2/14/$31.00 ©2014 IEEE 197
  2. 2. Tag Source level (SL) Sea water Transmission loss (TL) Hydrophone Sensitivity (RVS) Signal Conditioning gain (G) Tone detection a) PLL or b) Correlation A B C Fig. 2. (A)A tag with the exposed circuit. On the left, two transducers are available for communication and on the right side the circuit with the battery is shown. (B) The sensors and housing are shown as an assembled hydrophone. The circuit on (C) is the part of the hydrophone that filters, detects and extracts the tone from the noise. The microcontroller is the i.c. on the lower right corner of the board. signal at the surface. The block diagram in figure 2 describes the undergoing communication process from transmission to reception for tag detection. Lead zirconate titanate (PZT) electroacoustic transducers (Noliac, Denmark) were used. Their frequency response can be measured by their impedance and is shown in figure 3. Two different geometries were used for comparison. Both are ring shaped transducers with outer diameter of 12.5mm and wall thickness of 1mm; one is 9mm long and the other one is 3mm. Noticeable is the marked resonance (fr) and anti- resonance (fa) frequencies of the transducers when measured in air. These values are fr = 78105 Hz and fa = 79860 Hz for the 9mm long and for the 3mm long they are fr = 78300 and fa = 80445. However, when the ceramics are encapsulated in urethane, the water-isolation process sends resonance to higher frequencies in the spectrum. Encapsulated transducers show a frequency response with a continuous slope of 180 and 300 Ω/octave respectively and lower impedance in comparison to when they operate without any loading. Figure 3 also shows how a lower impedance can be achieved by connecting hydrophones in parallel. This has the advantage of increasing the directionality of the sensor at the expense of higher driving power. The passive sonar equation will be used as a model to describe the acoustic system. Refer to figure 2 that represents the energy path from transmission to reception, processing and extraction of information from it. The first event in the communication process is the transmission of an acoustic signal underwater by a projector. The tag transmits a 12ms long sinusoidal signal centered at 51kHz. The user can select among four transmission rates: 0.5, 1, 2 and 5 Hz. The acoustic signal attenuates in water for two reasons: geometrical spreading of the wave which is assumed to be spherical and chemical energy absorption by the components of the sea. The latter is specific to the conditions of the sea. The absorption 40 f0 60 fr fa 100 10 2 10 3 10 4 frequency (kHz) Impedance(Ω) Fig. 3. Transducers electrical response. (-×-) and (-.-) are 3mm and 9mm long ring transducers respectively measured in air. (-*-) and (-◦-) represent the same transducers after being water isolated in urethane. (-+-) Three 9mm transducers connected in parallel show a lower impedance. coefficient (α) and therefore the transmission loss (TL) are mostly affected by frequency [6]. The acoustic wavefront reaches the PZT sensor on the receiving end at the surface. In addition to loss from atten- uation, noise will add to the signal. The receiving voltage sensitivity (RVS) of the transducer dictates how much voltage can be measured from the transducer nodes in relation to the pressure that is applied to it. A band pass filter with a gain (G) of 60dB at 51kHz and a bandwidth of 2.5kHz was implemented to increase the signal-to-noise ratio of the tag. The filter was designed in three stages and implemented with operational amplifiers OPA211 (Texas instruments). Tones are detected by a LMC567 (National Semiconductor) integrated circuit based on a phase-locked-loop (PLL). When the PLL detects the presence of a signal in phase with the frequency 198
  3. 3. of its internal voltage controlled oscillator, it locks onto it. The PLL was tuned to detect 51kHz signals and the DC output that it generates is timed by a microcontroller. In order to conclude the effective transmission of the signal, tone validation was implemented on the microcontroller: a detection with a minimum duration of 10ms is valid; everything else is discarded. The detection scheme described above depends on the amount energy within a frequency band that reaches the hy- drophone. This bandwidth is determined by the quality factor of the filters, the frequency response of the transducers and the tone detector. These factors compose the sonar equation. The minimum detection threshold (MDT) for the PLL circuit is calculated as follows: MDT = SL - TL + RVS + G. The tag’s source level (SL) was calculated to be 171 dB at 1m when referenced to 1µPa. It was modeled as a thin walled ring small in relation to the signal’s transmitted wavelength. Similarly, the receiving voltage sensitivity (RVS) for the sensor in the hydrophone was calculated as -212dB//1V/µ Pa. It is possible to derive a relation between the MDT and acoustic detection range by means of the TL = αR + 20log(R) and determine the maximum distance at which a signal will reach the receiver with enough energy to be detected. III. RESULTS The detection delay of the tone decoder depends on the input SNR. If the order of arrival of an acoustic signal to two or more hydrophones was to be determined, they would have to be placed apart a distance equivalent to, at least, the detection time times the sound speed in the water. In an experiment, tones from a function generator were sent to the analog processing circuit (figure 2.1) and detection delays were measured. The mean detection delay was 78µs (n = 101), which spatially means 12cm at a sound speed of 1546m/s. In figure 4A the upper line represents the generated signal and the lower line shows the digital decoder output. The input SNR to the PLL is 21.7dB with respect to the 1.25Vp maximum that the filters can achieve. The same measurements were made in sheltered waters in the sea. The tag was installed 5m away from the receiver, both at a depth of 1.5m with no obstacles in between. The mean detection delay increased to 623µs (n = 101, SNR = 16dB) , i.e. a 96cm equivalent. (see figure 4B). A minimum separation of 1m between hydrophones is required to correctly detect the signal’s order of arrival. The microcontroller timed the PLL’s active low digital output from the falling to the raising edge. In-band noise would interfere with the PLL and detections fail. This rendered a high proportion of missed detections. The decoder was configured to allow the largest bandwidth possible, i.e. the less restricted detecting performance. The combination of both, detection delay and detection unreliability reduced severely the detection range of the hydrophone and tag previously described. In another experiment, a hydrophone was installed 1m under the surface, and the tag was towed away from it in 30m deep water. Measurements were performed every 10m horizontally and in each of these stations, the tag was lowered vertically A B Fig. 4. A comparison between the PLL detection delay in lab conditions (A) with SNR=21dB and in the sea (B) where SNR=16dB of maximum scale. Enmarked are the results of a 100 trials experiment. every 5m. The pinging rate of the tag was 2Hz and recordings went on for a minute (120pings). The ping count of the hydrophone was compared to 120 pings and a percentage of detection calculated for each point (see figure 5). Interestingly, there is a blind spot located under the sensor with an aperture of about 45◦ . We have attributed this characteristic to the beam pattern of the cylindrical transducer. Furthermore, detection percentage drops considerably at a distance of 50m, which differs considerably from the model. To reduce this difference, several considerations need to be taken into account. For example, in-situ measurements of sea water characteristics could improve transmission loss estimates. We expect a considerable adjustment of the model output after calibrated measurements of the transducers sen- sitivity and source level are performed. The reason behind this lies in the fact that manufacturers characteristics differ considerably from the operational characteristics and current estimates are likely over estimating system’s performance. In terms of detection, a matched filter is being studied as an alternative to the process above described. For this the signal received by a hydrophone is correlated against a signal with known characteristics. Because the frequency of the transmission is known, the correlator can be modeled as a sinusoidal 51kHz 12ms signal. The correlation function maximizes in the points where both, the received signal and the correlator are more alike. The alternative is advantageous because it provides an increased SNR output that depends on 199
  4. 4. A Fig. 5. Acoustic range of the hydrophone is represented as a percentage of accurate detections performed on each of the recording points (marked with a dot). Blue regions indicate zones were the hydrophone has trouble detecting a source whereas warmer colors indicate a higher detection rate. the amount of samples processed by the correlator [7]. An additional benefit is the fact that the correlated output for a broad band signal, as opposed to that for a narrow band, has a narrower detection peak. The relevance of this characteristic is that the receivers can be located closer to each other while still be able to determine correctly the order of arrival of a signal. Figure 6 shows a comparison of both detection methods. In this model a tag is put into two different scenarios: 10mVrms and a quieter 1mVrms white noise environment. The output of the hydrophone’s signal processing circuit is indicated with continuous lines in figure 6. This is the input SNR for the decoder or, alternatively, for the correlation function. The dotted lines in the same figure indicate the output of a cross correlation between the hydrophone’s output and the correlator described above. If a threshold of detection of 6dB is used, like that indicated in the decoder datasheet, the detection distance that can be achieved with this tag and hydrophone is about 300m. However, the correlated output outperforms energy-detection over the 150m distance. These are preliminar results and research is ongoing to improve it. IV. CONCLUSIONS A microcontroller based underwater acoustic system was described. A tag transmits 51kHz, 12ms sinusoidal tone into the water. A filter with a band width of 2.5kHz and gain 30 processes the signal from a sensor in the hydrophone for a 7kHz phase-locked-loop tone detection circuit to detect it. The passive sonar model indicates that on a -40dB//V white noise environment, the circuit should be able to detect the signal at approximately 1km. A mismatch in the signal, filtering an tone extraction frequency bands reduces the signal to noise ratio and renders a high missed detection rate. Although the system is capable of detecting the target signal by its frequency, its range is sacrificed with the current architecture. A correlation model indicates that the SNR can be increased over 30dB by 0 200 400 600 800 1000 −20 0 20 40 60 80 TonedetectionSNR(dB) distance from source (m) NL = −40dB, input NL = −40dB, output NL = −60dB, input NL = −60dB, output Fig. 6. The input SNR for a detection system is plotted in continuous lines. The dotted lines show the output of the matched filter. The PLL minimum SNR of 6dB is indicated for a reference. using a matched frequency correlator, in addition to increasing the system’s capability to detect broad band signals. V. ACKNOWLEDGMENTS Special thanks to E. Lloyd Smith for his support in the development of the project. REFERENCES [1] B. a. Block, I. D. Jonsen, S. J. Jorgensen, a. J. Winship, S. a. Shaffer, S. J. Bograd, E. L. Hazen, D. G. Foley, G. a. Breed, a L Harrison, J. E. Ganong, a. Swithenbank, M. Castleton, H. Dewar, B. R. Mate, G. L. Shillinger, K. M. Schaefer, S. R. Benson, M. J. Weise, R. W. Henry, and D. P. Costa, “Tracking apex marine predator movements in a dynamic ocean.” Nature, vol. 475, no. 7354, pp. 86–90, Jul. 2011. [Online]. Available: http://www.ncbi.nlm.nih.gov/pubmed/21697831 [2] C. H. Greene, B. A. Block, D. Welch, G. Jackson, G. L. Lawson, and E. L. Rechisky, “Advances in conservation oceanography: new tagging and tracking technologies and their potential for transforming the science underlying fisheries management,” Oceanography, vol. 22, no. 1, pp. 210–223, 2009. [Online]. Available: http://ecite.utas.edu.au/56227 [3] E. F. Cagua, M. L. Berumen, and E. H. M. Tyler, “Topography and biological noise determine acoustic detectability on coral reefs,” Coral Reefs, vol. 32, no. 4, pp. 1123–1134, Aug. 2013. [Online]. Available: http://link.springer.com/10.1007/s00338-013-1069-2 [4] P. R. De La Torre, K. N. Salama, M. L. Berumen, and E. L. Smith, “The integrated satellite-acoustic telemetry ( iSAT ) system for tracking marine megafauna,” 2012 MTS/IEEE OCEANS - Yeosu, pp. 1–5, 2012. [5] P. R. De La Torre, E. L. Smith, A. Sancheti, K. N. Salama, and M. L. Berumen, “iSAT: The mega-fauna acoustic tracking system,” 2013 MTS/IEEE OCEANS - Bergen, pp. 1–6, Jun. 2013. [Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6608085 [6] M. A. Ainslie and J. G. Mccolm, “A simplified formula for viscous and chemical absorption in sea water,” Journal of the Acoustical Society of America, vol. 103, no. 3, pp. 1–2, 1998. [7] Y. W. Lee, T. P. Cheatham, and J. B. Wiesner, “The application of corre- lation functions in the detection of small signals in noise,” Massachusetts Institute of Technology, Tech. Rep. 141, 1949. 200

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