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Radar Signals
Tutorial 3
LFM, Coherent Train and Frequency Coding
Outline
 More on LFM
 Range sidelobe reduction
 Coherent train of identical pulses
 Large improvement in Doppler resolution
 Frequency-modulated pulse (besides LFM)
 Costas code
 Nonlinear FM
LFM review
LFM range sidelobe reduction
 Amplitude weighting Square-root of Hamming window
 To maintain matched filtering, the weight should be
split between the transmitter and receiver
 Yet a linear power amplifier is required
LFM Hamming-weighted LFM
Sidelobe suppression and mainlobe broadening
A train of pulses
 A coherent train of identical unmodulated pulses
 Signal
 Complex envelop
 Unmodulated pulse
6 pulses and duty cycle = 0.2
Large improvement in Doppler resolution
Resolutions and Ambiguities
Frequency-modulated pulses
 Previously discussed LFM
 The volume of AF concentrates in a slowly decaying
diagonal ridge
 An advantage when Doppler resolution is not
expected from a single pulse
 Relatively high autocorrelation sidelobe
 Other frequency-modulation schemes
 Better Doppler resolution
 Lower autocorrelation sidelobes
Matrix representation of quantized LFM
M contiguous time slices tb
M
frequency
slices
Δf
There is only one dot in each
column and each row.
The AF can be predicted
roughly by overlaying a copy of
this binary matrix and shifting it
to some (delay, Doppler).
A coincidence of N points
indicates a peak of N/M
Costas coding (1984)
The number of coinciding dots
cannot be larger than one for
all but the zero-shift case.
A narrow peak at the origin and
low sidelobes elsewhere
 A Costas signal
 Hopping frequency
 Complex envelope
Check whether Costas
If all elements in a row of the difference matrix are
different from each other, the signal is Costas.
Peak sidelobe is
-13.7 dB
Exhaustive search of Costas codes
Construction of Costas code
 Welch 1 (Golomb & Taylor, 1984)
 Applicable for M = p – 1 where p can be any prime
number larger than 2.
 Let α be a primitive element in GF(p)
 Numbering the columns of the array j = 0,1,...,p-2
and the rows i = 1,2,...,p-1. Then we put a dot in
position (i, j) if and only if i = αj
 M = 4
 p = M + 1 = 5
 GF(5) = {0 1 2 3 4}
 Use α = 2:
 Use α = 3:
{1 2 4 3}
{1 3 4 2}
Nonlinear Frequency Modulation
 Stationary-phase concept
 The energy spectral density at a certain frequency is
relatively large if the rate of the change of this
frequency is relatively small
 Design the phase (frequency) to fit a good spectrum
Low auto-cor
sidelobes
High sidelobes at
high Doppler cuts
Future talks
 Phase-coded pulse
 Barker codes
 Chirplike phase codes
 Our codes
Thank you
Sep. 2009

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RadarSignal theory by New gen of 2023.ppt

  • 1. Radar Signals Tutorial 3 LFM, Coherent Train and Frequency Coding
  • 2. Outline  More on LFM  Range sidelobe reduction  Coherent train of identical pulses  Large improvement in Doppler resolution  Frequency-modulated pulse (besides LFM)  Costas code  Nonlinear FM
  • 4. LFM range sidelobe reduction  Amplitude weighting Square-root of Hamming window
  • 5.  To maintain matched filtering, the weight should be split between the transmitter and receiver  Yet a linear power amplifier is required
  • 6. LFM Hamming-weighted LFM Sidelobe suppression and mainlobe broadening
  • 7. A train of pulses  A coherent train of identical unmodulated pulses  Signal  Complex envelop  Unmodulated pulse
  • 8. 6 pulses and duty cycle = 0.2
  • 9. Large improvement in Doppler resolution
  • 11. Frequency-modulated pulses  Previously discussed LFM  The volume of AF concentrates in a slowly decaying diagonal ridge  An advantage when Doppler resolution is not expected from a single pulse  Relatively high autocorrelation sidelobe  Other frequency-modulation schemes  Better Doppler resolution  Lower autocorrelation sidelobes
  • 12. Matrix representation of quantized LFM M contiguous time slices tb M frequency slices Δf There is only one dot in each column and each row. The AF can be predicted roughly by overlaying a copy of this binary matrix and shifting it to some (delay, Doppler). A coincidence of N points indicates a peak of N/M
  • 13. Costas coding (1984) The number of coinciding dots cannot be larger than one for all but the zero-shift case. A narrow peak at the origin and low sidelobes elsewhere
  • 14.
  • 15.  A Costas signal  Hopping frequency  Complex envelope
  • 16. Check whether Costas If all elements in a row of the difference matrix are different from each other, the signal is Costas.
  • 18. Exhaustive search of Costas codes
  • 19. Construction of Costas code  Welch 1 (Golomb & Taylor, 1984)  Applicable for M = p – 1 where p can be any prime number larger than 2.  Let α be a primitive element in GF(p)  Numbering the columns of the array j = 0,1,...,p-2 and the rows i = 1,2,...,p-1. Then we put a dot in position (i, j) if and only if i = αj
  • 20.  M = 4  p = M + 1 = 5  GF(5) = {0 1 2 3 4}  Use α = 2:  Use α = 3: {1 2 4 3} {1 3 4 2}
  • 21. Nonlinear Frequency Modulation  Stationary-phase concept  The energy spectral density at a certain frequency is relatively large if the rate of the change of this frequency is relatively small  Design the phase (frequency) to fit a good spectrum
  • 22.
  • 24. Future talks  Phase-coded pulse  Barker codes  Chirplike phase codes  Our codes Thank you Sep. 2009