Compressed synthetic aperture radar

IEEE Journal on Selected Topics in Signal Processing

Volumn 4, Issue 2, 2010, Pages 244-254

  Patel, Vishal M ^a   Easley, Glenn R ^b   Healy Jr , Dennis M ^b   Chellappa, Rama ^a  

^a UNIVERSITY OF MARYLAND   (United States)

^b University of Maryland   (United States)

Author keywords

Compressed sensing (CS); Compressive sensing; Synthetic aperture radar (SAR)

Indexed keywords

COMPRESSED SENSING; COMPRESSED SENSING (CS); ELECTROMAGNETIC WAVEFORMS; HARDWARE COMPONENTS; HIGH RESOLUTION; IMAGING MODALITY; IMAGING SCHEMES; NEW APPLICATIONS; SPATIAL DISTRIBUTION; STORAGE REQUIREMENTS;

IMAGE CLASSIFICATION; IMAGING SYSTEMS; RADAR; RADAR IMAGING; SIGNAL RECONSTRUCTION; SIZE DISTRIBUTION; SYNTHETIC APERTURES;

SYNTHETIC APERTURE RADAR;

EID: 77949707850     PISSN: 19324553     EISSN: None     Source Type: Journal    
DOI: 10.1109/JSTSP.2009.2039181     Document Type: Article

References (59)

1. M. Soumekh, Synthetic Aperture Radar Signal ProcessingWith Matlab Algorithms. New York: Wiley, 1999.
2. I. G. Cumming and F. H. Wong, Digital Processing of Synthetic Aperture Radar Data. Norwood, MA: Artech House, 2005.
3. D. C. Munson, Jr., J. D. O'Brien, and W. K. Jenkins, "A tomographic formulation of spotlight-mode synthetic aperture radar," Proc. IEEE, vol.71, no.8, pp. 917-925, Aug. 1983.
4. W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic Aperture Radar: Signal Processing Algorithms. Norwood, MA: Artech House, 1995.
5. V. C. Chen and H. Ling, Time-Frequency Transforms for Radar Imaging and Signal Analysis. Norwood, MA: Artech House, 2002.
6. M. D. Desai and W. K. Jenkins, "Convolution backprojection image reconstruction for spotlight mode synthetic aperture radar," IEEE Trans. Image Process., vol.1, no.4, pp. 505-517, Oct. 1992.
7. D. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol.52, no.4, pp. 1289-1306, Apr. 2006.
8. E. Candès, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, vol.52, no.2, pp. 489-509, Feb. 2006.
9. S. G. Mobley and M. W. Maier, "Synthetic aperture radar with a nonuniform pulse repetition interval," in Proc. SSST 27th Southeastern Symp. Syst. Theory (SSST'95), 1995, pp. 498-502.
10. J. N. Laska, S. Kirolos, M. F. Duarte, T. S. Ragheb, R. G. Baraniuk, and Y. Massoud, "Theory and implementation of an analog-to-information converter using random demodulation," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), May 27-30, 2007, pp. 1959-1962.
11. J. Laska, S. Kirolos, Y. Massoud, R. Baraniuk, A. Gilbert, M. Iwen, and M. Strauss, "Random sampling for analog-to-information conversion of wideband signals," in Proc. IEEE CAS Workshop, Oct. 2006, pp. 119-122.
12. J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, "Beyond Nyquist: Efficient sampling of sparse bandlimited signals," IEEE Trans. Inf. Theory, vol.56, no.1, pp. 520-544, Jan. 2010.
13. R. Baraniuk and P. Steeghs, "Compressive radar imaging," in Proc. 2007 IEEE Radar Conf., Apr. 2007, pp. 128-133.
14. A. C. Gurbuz, J. H. McClellan, and W. R. Scott, "Compressive sensing for GPR imaging," in Proc. 41st Asilomar Conf. Signals, Syst. Comput. (ACSSC), Nov. 4-7, 2007, pp. 2223-2227.
15. A. C. Gurbuz, J. H. McClellan, and W. R. Scott, "Compressive sensing for subsurface imaging using ground penetrating radar," Signal Process., vol.89, no.10, pp. 1959-1972, Oct. 2009.
16. M. Herman and T. Strohmer, "High resolution radar via compressed sensing," IEEE Trans. Signal Process., vol.57, no.6, pp. 2275-2284, Jun. 2009.
17. J. Romberg, "Compressive sampling by random convolution," J. Imag. Sci., "," SIAM July 2008.
18. S. Bhattacharya, T. Blumensath, B. Mulgrew, and M. Davis, "Fast encoding of synthetic aperture radar raw data using compressed sensing," in Proc. IEEE Workshop on SSP, Aug. 26-29, 2007, pp. 448-452.
19. A. C. Fannjiang, P. Yan, and T. Strohmer, Compressed remote sensing of sparse objects Apr. 2009, submitted for publication.
20. M. Çetin and W. C. Karl, "Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization," IEEE Trans. Image Process., vol.10, no.4, pp. 623-631, Apr. 2001.
21. M. Çetin, "Feature-enhanced synthetic aperture radar imaging," Ph.D. dissertation, College of Eng., Boston Univ., Boston, MA, 2001.
22. C. L. Logan, "An estimation-theoretic technique for motion-compensated synthetic-aperture array imaging," Ph.D. dissertation, Dept. of Elect. Eng. and Comput. Sci., Mass. Inst. of Technol., Cambridge, MA, Feb. 2000.
23. S. Chen, D. Donoho, and M. Saunders, "Atomic decomposition by basis pursuit," SIAM J. Sci. Comp., vol.20, no.1, pp. 33-61, 1998.
24. D. L. Donoho and X. Huo, "Uncertainty principle and ideal atomic decomposition," IEEE Trans. Inf. Theory, vol.47, no.7, pp. 2845-2862, Nov. 2001.
25. E. Candès, J. Romberg, and T. Tao, "Satble signal recovery from incomplete and inaccurate measurements," Commun. Pure Appl. Math., vol.59, pp. 1207-1223, 2006.
26. R. Baraniuk, "Compressive sensing," IEEE Signal Process. Mag., vol.24, no.4, pp. 118-121, Jul. 2007.
27. E. Candès, "Compressive sampling," in Proc. Int. Congr. Math., 2006, vol.3, pp. 1433-1452.
28. E. J. Candès and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?," IEEE Trans. Inf. Theory, vol.52, no.12, pp. 5406-5425, Dec. 2006.
29. M. Rudelson and R. Vershynin, "On sparse reconstruction from Fourier and Gaussian measurements," Commun. Pure Appl. Math., vol.61, pp. 1025-1045, 2008.
30. 1 minimization," Proc. Nat. Acad. Sci., vol.100, no.5, pp. 2197-2202, Mar. 2003.
31. D. L. Donoho, M. Elad, and V. N. Temlyakov, "Stable recovery of sparse overcomplete representations in the presence of noise," IEEE Trans. Inf. Theory, vol.52, no.1, pp. 6-18, Jan. 2006.
32. H. Rauhut, K. Schnass, and P. Vandergheynst, "Compressed sensing and redundant dictionaries," IEEE Trans. Inf. Theory, vol.54, no.5, pp. 2210-2219, May 2008.
33. J. A. Tropp and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Trans. Inf. Theory, vol.53, no.12, pp. 4655-4666, Dec. 2007.
34. D. Needell and J. A. Tropp, "CoSaMP: Iterative signal recovery from incomplete and inaccurate samples," Appl. Comp. Harmonic Anal., vol.26, pp. 301-321, 2008.
35. R. L. Cook, "Stochastic sampling in computer graphics," ACM Trans. Graphics, vol.5, no.1, pp. 51-72, Apr. 1986.
36. M. Dippe and E. Wold, "Antialiasing through stochastic sampling," SIGGRAPH, vol.19, no.3, pp. 69-78, Nov. 1985.
37. A. V. Balakrishnan, "On the problem of time jitter in sampling," IRE Trans. Inf. Theory, vol.8, no.3, pp. 226-236, Apr. 1962.
38. G. Hennenfent and F. J. Herrmann, "Simply denoise:Wavefield reconstruction via jittered undersampling," Geophysics, vol.73, no.3, pp. v19-v28, June 2008.
39. M. Lustig, D. Donoho, and J. M. Pauly, "Sparse MRI: The application of compressed sensing for rapidMRimaging," Magn. Resonance Med., vol.58, no.6, pp. 1182-1195, Dec. 2007.
40. J. Provost and F. Lesage, "The application of compressed sensing for photo-acoustic tomography," IEEE Trans. Med. Imag., vol.28, no.4, pp. 585-594, Apr. 2009.
41. J. Goodman, "Some fundamental properties of speckle," J. Opt. Soc. Amer., vol.66, pp. 1145-1150, Nov. 1976.
42. C. V. Jakowatz, Jr., D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and P. A. Thompson, Spotlight-Mode Synthetic Aperture Radar: A Signal Processing Approach. New York: Springer, 1996.
43. M. Çetin, W. C. Karl, and A. S. Willsky, "Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging," Opt. Eng., vol.54, no.1, Jan. 2006, 017003.
44. R. Lavarello, F. Kamalabadi, and W. D. O'Brien, Jr., "A regularized inverse approach to ultrasonic pulse-echo imaging," IEEE Trans. Med. Imag., vol.25, no.6, pp. 712-722, Jun. 2006.
45. J. Shi and S. Osher, "A nonlinear inverse scale space method for a convex multiplicative noise model," Comput. and Appl. Math., Univ. of California, Los Angeles, Tech. Rep. 07-10, 2007.
46. E. Candes and J. Romberg, "Signal recovery from random projections," in Proc. SPIE Comput. Imag. III, San Jose, CA, 2005, vol.5674.
47. W. W. Goj, Synthetic Aperture Radar and Electronic Warfare. Norwell, MA: Artech House, 1992.
48. G. E. Stimson, Introduction to Airborne Radar, 2nd ed. Mendham, NJ: SciTech, 1998.
49. R. J. Anderson, Security Engineering: A Guide to Building Dependable Distributed Systems. Indianapolis, IN: Wiley, 2008.
50. P. N. Stoyle, "Synthetic aperture radar assembly and a method of creating a radar image of a planet surface using such an assembly," U.S. patent 5,051,749, Sep. 24, 1991.
51. D. L. Donoho, "High-dimensional centrally symmetric polytopes with neighborliness proportional to dimension," Discrete and Comput. Geom., vol.35, no.4, pp. 617-652, 2006.
52. q -regularization: Phase transition for sparse approximation," submitted for publication.
53. E. van den Berg and M. P. Friedlander, "Probing the Pareto frontier for basis pursuit solutions," SIAM J. Sci. Comp, vol.31, no.2, pp. 890-912, 2008.
54. E. van den Berg and M. P. Friedlander, "SPGL1: A solver for large-scale sparse reconstruction." [Online]. Available: http://www.cs. ubc.ca/labs/scl/spgl1
55. Center for Imaging Science Image Database [Online]. Available: http:// cis.jhu.edu/data.sets/MSTAR
56. Y. Tsaig and D. L. Donoho, "Extensions of compressed sensing," Signal Process., vol.86, no.3, pp. 533-548, Mar. 2006.
57. J. A. Fessler and B. P. Sutton, "Nonuniform fast Fourier transforms using min-max interpolation," IEEE Trans. Signal Process., vol.51, no.2, pp. 560-574, Feb. 2003.
58. M. M. Bronstein, A. M. Bronstein, M. Zibulevsky, and H. Azhari, "Reconstruction in diffraction ultrasound tomography using nonuniform FFT," IEEE Trans. Med. Imag., vol.21, no.11, pp. 1395-1401, Nov. 2002.
59. J. Walker, "Range-Doppler imaging of rotating objects," IEEE Trans. Aerosp. Electron. Syst., vol.AES-16, no.1, pp. 23-52, Jan. 1980.