Compressive matched-field processing

Journal of the Acoustical Society of America

Volumn 132, Issue 1, 2012, Pages 90-102

  Mantzel, William ^a   Romberg, Justin ^a   Sabra, Karim ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC DATA; COMPRESSIVE SENSING; COMPUTATIONAL WORKLOAD; NUMERICAL EXPERIMENTS; OCEAN WAVEGUIDE; OFFLINE; RECEIVED SIGNALS; SHORT-CORRELATION; SOURCE LOCALIZATION;

PARTIAL DIFFERENTIAL EQUATIONS;

BACKPROPAGATION;

EID: 84863659928     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.4728224     Document Type: Article

References (25)

1. A. B. Baggeroer, W. A. Kuperman, and P. N. Mikhalevsky, An overview of matched field methods in ocean acoustics., IEEE J. Ocean. Eng. 18 (4), 401-424 (1993). 10.1109/48.262292
2. A. B. Baggeroer, W. A. Kuperman, and H. Schmidt, Matched field processing: Source localization in correlated noise as an optimum parameter estimation problem., J. Acoust. Soc. Am. 83, 571 (1988). 10.1121/1.396151
3. A. Tolstoy, Applications of matched-field processing to inverse problems in underwater acoustics., Inverse Probl. 16, 1655 (2000). 10.1088/0266-5611/16/ 6/304
4. F. K. Gruber, E. A. Marengo, and A. J. Devaney, Time-reversal imaging with multiple signal classification considering multiple scattering between the targets., J. Acoust. Soc. Am. 115, 3042 (2004). 10.1121/1.1738451
5. E. Candès, J. Romberg, and T. Tao, Stable signal recovery from incomplete and inaccurate measurements., Commun Pure Appl. Math. 59 (8), 1207-1223 (2006). 10.1002/cpa.20124
6. E. Candès and T. Tao, Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans. Inform. Theory 52 (12), 5406-5245 (2006). 10.1109/TIT.2006.885507
7. D. L. Donoho, Compressed sensing., IEEE Trans. Inform. Theory 52 (4), 1289-1306 (2006). 10.1109/TIT.2006.871582
8. E. Candès and M. Wakin, An introduction to compressive sampling., IEEE Signal Process. Mag. 25 (2), 21-30 (2008). 10.1109/MSP.2007.914731
9. D. Healy and D. J. Brady, Compression at the physical interface., IEEE Signal Proces. Mag. 25 (2), 67-71 (2008). 10.1109/MSP.2007.914996
10. J. Romberg, Imaging via compressive sampling., IEEE Signal Process. Mag. 25 (2), 14-20 (2008). 10.1109/MSP.2007.914729
11. M. A. Davenport, P. T. Boufounos, M.B. Wakin, and R. G. Baraniuk, Signal processing with compressive measurements., IEEE J. Sel. Top. Signal Process. 4 (2), 445-460 (2010). 10.1109/JSTSP.2009.2039178
12. Lawrence Carin, Dehong Liu, and Bin Guo, In situ compressive sensing., Inverse Probl. 24 (1), 15-23 (2008). 10.1088/0266-5611/24/1/015023
13. E. A. Marengo, R. D. Hernandez, Y. R. Citron, F. K. Gruber, M. Zambrano, and H. Lev-Ari, Compressive sensing for inverse scattering., XXIX URSI General Assembly, Chicago, IL (2008).
14. G. H. Golub and C. F. Van Loan, in Matrix Computations (Johns Hopkins University Press, Baltimore, MD, 1996), pp. 69-75.
15. N. Halko, P. G. Martinsson, and J. A. Tropp, Finding structure with randomness: Stochastic algorithms for constructing approximate matrix decompositions., SIAM Rev., Surv. Rev. 53 (2), 217-288 (2011).
16. A. Fannjiang, P. Yan, and T. Strohmer, Compressed remote sensing of sparse objects., SIAM J. Imag. Sci. 3 (3), 595-618 (2009). 10.1137/090757034
17. A. C. Gurbuz, J. H. McClellan, and V. Cevher, A compressive beamforming method., in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2008).
18. V. Cevher, M. F. Duarte, and R. G. Baraniuk, Distributed target localization via spatial sparsity., in European Signal Processing Conference (EUSIPCO) (2008).
19. F. B. Jensen, W. A. Kuperman, M. B. Porter, and H. Schmidt, in Computational Ocean Acoustics (AIP Press, New York, 2000), pp. 540-552.
20. W. B. Johnson and J. Lindenstrauss, Extensions of Lipschitz mappings into a Hilbert space., in Conference in Modern Analysis and Probability (1984), pp. 189-206.
21. D. Achlioptas, Database-friendly random projections: Johnson- lindenstrauss with binary coins., J. Comput. Syst. Sci. 66, 671-687 (2003). 10.1016/S0022-0000(03)00025-4
22. S. Dasgupta and A. Gupta, An elementary proof of a theorem of johnson and lindenstrauss., Random Struct. Algorithms 22 (1), 60-65 (2003). 10.1002/rsa.10073
23. R. G. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, A simple proof of the restricted isometry property for random matrices., Constructive Approx. 28 (3), 253-263 (2008). 10.1007/s00365-007-9003-x
24. R. G. Baraniuk and M. B. Wakin, Random projections of smooth manifolds., Found. Comput. Math. 9 (1), 51-77 (2009). 10.1007/s10208-007-9011-z
25. Download the code at http://users.ece.gatech.edu/∼wmantzel3/cmfp/ code.zip (Last viewed August 21, 2011).