Time-reversal is addressed for imaging elastic targets situated in an acoustic waveguide. It is assumed that the target-sensor range is large relative to the channel depth. We investigate the theory of wideband time-reversal imaging of an extended elastic target, for which the target dimensions are large relative to the principal wavelengths. When performing time-reversal imaging one requires a forward model for propagation through the channel, and the quality of the resulting image may be used as a measure of the match between the modeled and actual (measured) channel parameters. It is demonstrated that the channel parameters associated with a given measurement may be determined via a genetic-algorithm (GA) search in parameter space, employing a cost function based on the time-reversal image quality. Example GA channel-parameter-inversion results and imagery are presented for measured at-sea data.

1.
R. P.
Gorman
and
T. J.
Sejnowski
, “
Learned classification of sonar targets using a massively parallel network
,”
IEEE Trans. Acoust., Speech, Signal Process.
36
,
1135
1140
(
1988
).
2.
B. A. Telfter, H. H. Szu, and G. Dobeck, “Adaptive time-frequency classification of acoustic backscatter,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, April 1995.
3.
G. Goo and W. L. Au, “Detection and identification of buried objects in shallow water,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, pp. 201–214, April 1996.
4.
P. H. Carter and G. Dobeck, “Classification of acoustic backscatter using the generalized target description,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, pp. 190–200, April 1996.
5.
N. Intrator, Q. Q. Huynh, and G. Dobeck, “Feature extraction from backscattered signals using wavelet dictionaries,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, pp. 183–190, April 1997.
6.
L. L. Burton and G. Dobeck, “Active sonar target imaging and classification system,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, pp. 19–33, April 1997.
7.
M. R. Azimi-Sadjadi, Q. Huang, and G. Dobeck, “Underwater target classification using multiaspect fusion and neural network,” Proc. SPIE Int. Symp. Aerospace/Defense Sensing Contr, Orlando, FL, pp. 334–341, April 1998.
8.
M. R.
Azimi-Sadjadi
,
D.
Yao
,
Q.
Huang
, and
G.
Dobeck
, “
Underwater target classification using wavelet packets and neural networks
,”
IEEE Trans. Neural Netw.
11
,
784
794
(
2000
).
9.
H. W. Liu and L. Carin, “Class-based target classification in shallow water channel based on Hidden Markov Model,” Proc. IEEE International conference on acoustics, speech and signal processing, pp. 2889–2892, Orlando, FL, May 2002.
10.
H. Liu, P. Runkle, L. Carin, T. Yoder, T. Giddings, L. Couchman, and J. Bucaro, “Classification of distant targets situated near channel bottoms,” to appear in JASA, 2004.
11.
P. R.
Runkle
,
P. K.
Bharadwaj
,
L.
Couchman
, and
L.
Carin
, “
Hidden Markov models for multi-aspect targets classification
,”
IEEE Trans. Signal Process.
47
,
2035
2040
(
1999
).
12.
P. K.
Bharadwj
,
P. R.
Runkle
, and
L.
Carin
, “
Target identification with wave-based matched pursuits and Hidden Markov Models
,”
IEEE Trans. Antennas Propag.
47
,
1543
1554
(
1999
).
13.
N.
Dasgupta
,
P. K.
Bharadwaj
,
L.
Couchman
, and
L.
Carin
, “
Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data
,”
Signal Process.
81
,
1303
1316
(
2001
).
14.
M. K.
Broadhead
, “
Broadband source signature extraction from underwater acoustics data with sparse environment information
,”
J. Acoust. Soc. Am.
97
,
1322
1325
(
1995
).
15.
M. K.
Broadhead
,
L. A.
Pflug
, and
R. L.
Field
, “
Use of high order statistics in source signature estimation
,”
J. Acoust. Soc. Am.
107
,
2576
2585
(
2000
).
16.
A.
Sarkissian
, “
Extraction of a target scattering response from measurements made over long ranges in shallow water
,”
J. Acoust. Soc. Am.
102
,
825
832
(
1997
).
17.
W. A.
Kuperman
,
W. S.
Hodgkiss
,
H. C.
Song
,
T.
Akal
,
C.
Ferla
, and
D. R.
Jackson
, “
Phase conjugation in the ocean: Experimental demonstration of an acoustic time reversal mirror
,”
J. Acoust. Soc. Am.
103
,
25
40
(
1998
).
18.
J. S.
Kim
,
H. C.
Song
, and
W. A.
Kuperman
, “
Adaptive time-reversal mirror
,”
J. Acoust. Soc. Am.
109
,
1817
1825
(
2001
).
19.
M.
Fink
, “
Time-reversal acoustics
,”
Phys. Today
50
,
34
40
(
1997
).
20.
J.-L.
Thomas
,
F.
Wu
, and
M.
Fink
, “
Time-reversal focusing applied to lithotrpsy
,”
Ultrason. Imaging
18
,
106
121
(
1996
).
21.
L.
Borcea
,
G.
Papanicolaou
,
C.
Tsogka
, and
J.
Berryman
, “
Imaging and time reversal in random media
,”
Inverse Probl.
18
,
1247
1279
(
2002
).
22.
P.
Blomberg
,
G.
Papanicolaou
, and
H. K.
Zhao
, “
Super-resolution in time-reversal acoustics
,”
J. Acoust. Soc. Am.
111
,
230
248
(
2002
).
23.
J. F.
Lingevitch
,
H. C.
Song
, and
W. A.
Kuperman
, “
Time reversed reverberation focusing in a waveguide
,”
J. Acoust. Soc. Am.
111
,
2609
2614
(
2002
).
24.
F. B. Jensen, W. A. Kuperman, M. B. Porter, and H. Schmidt, Computational Ocean Acoustics (AIP Press, New York, 1994).
25.
P.
Gerstoft
, “
Inversion of seismoacoustic data using genetic algorithms and a posteriori probability distributions
,”
J. Acoust. Soc. Am.
95
,
770
782
(
1994
).
26.
P.
Gerstoft
, “
Ocean acoustic inversion with estimation of a posteriori probability distributions
,”
J. Acoust. Soc. Am.
104
,
808
819
(
1998
).
27.
S. E.
Dosso
,
M. L.
Yeremy
,
J. M.
Ozard
, and
N. R.
Chapman
, “
Estimation of ocean bottom properties by matched-field inversion of acoustic field data
,”
IEEE J. Ocean. Eng.
18
,
232
239
(
1993
).
28.
A. M.
Thode
,
G. L.
D’Spain
, and
W. A.
Kuperman
, “
Matched-field processing, geoacoustic inversion, and source signature recovery of blue whale vocalization
,”
J. Acoust. Soc. Am.
107
,
1286
1300
(
2000
).
29.
D. E. Goldberg, Genetic Algorithms (Addision-Wesley, Reading, MA, 1989).
30.
L. B. Felsen and N. Marcuvitz, Radiation and Scattering of Waves (IEEE Press, New York, 1996).
31.
B. Steinberg, Microwave Imaging with Large Antenna Arrays (Wiley, New York, 1983).
32.
T. M. Cover and J. A. Thomas, Elements of Information Theory (Wiley, New York, 1991).
33.
J. P.
Hermand
, “
Broad-band geoacoustic inversion in shallow water from waveguide impulse response measurements on a single hydrophone: Theory and experimental results
,”
IEEE J. Ocean. Eng.
24
,
41
66
(
1999
).
34.
J. P.
Hermand
and
P.
Gerstoft
, “
Inversion of broad-band multitone data from the YELLOW SHARK summer experiments
,”
IEEE J. Ocean. Eng.
21
,
324
346
(
1996
).
35.
M.
Siderius
and
J. P.
Hermand
, “
Yellow Shark Spring 1995: Inversion results from sparse broadband acoustic measurements over a highly range-dependent soft clay layer
,”
J. Acoust. Soc. Am.
106
,
637
651
(
1999
).
36.
R. K.
Brienzo
and
W. S.
Hodgkiss
, “
Broad-band matched-field processing
,”
J. Acoust. Soc. Am.
94
,
2821
2831
(
1993
).
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