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Field experiment
Channel 1
Channel 3
Channel 4
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Time series and power spectrum, boat at 3000 rpm
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Boat running at a speed of 18 knots, channel 1,3
and 4
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Boat running at a speed of 18 knots, channel 1,3
and 4
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Multipath Characterization of Hydroacoustic
Signals by Autocoherence EstimationLeif
Persson, John W.C. Robinson and Melvin J.
HinichNational Defence Research
Establishment FOA, S172 90 Stockholm, Sweden.
Also at Dep. of Seismology, Uppsala University,
S-75002 Uppsala, Sweden. National Defence
Research Establishment FOA, S172 90 Stockholm,
Sweden. Applied Research Laboratories, The
University of Texas at Austin. P.O. 8029, Austin,
TX, 78713-8029.
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Definitions 1 Bicoherence Estimation
Identification of Source Frequencies
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Time-frequency channel 3
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Time-frequency channel 4
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Time-frequency channel 1
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Bicoherence 3000 rpm
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Objectives and Contents

• We use bicoherence analysis for identification of
  source frequencies.
• Bearing and range estimation of C-W narrow-band
  sonar-signals are difficult in shallow water .
• Spatial filtering and smoothing in sonar array
  processing reduce the temporal and spatial
  resolution.
• We use autocoherence as a measure for multipath
  analysis on real data generated by a small boat
  in the Baltic sea.

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Definitions 2 Autocoherence Estimation
Degree of randomness in the signal expressed in
a SNR type of measure
x(t) s(t) u(t)
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Autocoherence at frequencies 228, 230 and 232 Hz
channel 3
Autocoherence
Time sec
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Autocoherence at frequencies 230, 552 and 716 Hz,
channel 3
Autocoherence
Time sec
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Autocoherence at frequencies 230, 552 and 716 Hz,
channel 1
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Conclusions

• We use bicoherence for identification of source
  frequencies prior multipath analysis.
• We use autocoherence as a measure for quantify
  the level of multipath.
• At longer distances (i.e. gt300m) the
  autocoherence is relatively large.
• At shorter distances (i.e. lt300m) the
  autocoherence decreases as the boat approach the
  sonar.