Localization and bearing estimation via structured sparsity models

2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Volumn , Issue , 2012, Pages 333-336

  Duarte, Marco F ^a  

^a University of Massachusetts Amherst   (United States)

Author keywords

bearing estimation; coherence; compressive sensing; localization; structured sparsity

Indexed keywords

BEARING ESTIMATION; COEFFICIENT VECTOR; COMPRESSIVE SENSING; LOCALIZATION; OBSERVED DATA; PARAMETER ESTIMATE; PARAMETER SPACES; RECEIVED SIGNALS; SHOW THROUGH; SPARSE APPROXIMATIONS; SPARSE SIGNAL MODELS; STRUCTURED SPARSITY;

COHERENT LIGHT; PARAMETER ESTIMATION; SIGNAL RECONSTRUCTION; SIGNAL SAMPLING;

ESTIMATION;

EID: 84868216745     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SSP.2012.6319696     Document Type: Conference Paper

References (22)

1. R. A. DeVore, "Nonlinear approximation," Acta Numerica, Vol. 7, pp. 51-150, 1998. (Pubitemid 128109432)
2. D. L. Donoho, "Denoising by soft thresholding," IEEE Trans. on Inform. Theory, Vol. 41, no. 3, 1995.
3. D. L. Donoho, "Compressed sensing," IEEE Trans. Info. Theory, Vol. 52, no. 4, pp. 1289-1306, Sept. 2006.
4. E. J. Candès, "Compressive sampling," in Int. Congress of Mathematicians, Madrid, Spain, 2006, vol. 3, pp. 1433-1452.
5. I. F. Gorodnitsky and B. D. Rao, "Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm," IEEE Trans. Signal Proc., Vol. 45, no. 3, pp. 600-616, 1997. (Pubitemid 127765947)
6. L. C. Potter, E. Ertin, J. T. Parker, and M. Cetin, "Sparsity and compressed sensing in radar imaging," Proc. IEEE, Vol. 98, no. 6, pp. 1006-1020, June 2010.
7. M. F. Duarte and R. G. Baraniuk, "Spectral compressive sensing," 2011, preprint.
8. A. M. Bruckstein, D. L. Donoho, and M. Elad, "From sparse solutions of systems of equations to sparse modeling of signals and images," SIAM Review, Vol. 51, no. 1, pp. 34-81, 2009.
9. V. Cevher, M. F. Duarte, and R. G. Baraniuk, "Localization via spatial sparsity," in European Signal Proc. Conf. (EUSIPCO), Lausanne, Switzerland, 2008.
10. V. Cevher, A. C. Gurbuz, J. H. McClellan, and R. Chellappa, "Compressive wireless arrays for bearing estimation," in IEEE Int. Conf. Acoustics, Speech, and Signal Proc. (ICASSP), Las Vegas, NV, Apr. 2008, pp. 2497-2500.
11. T. J. Shaw and G. C. Valley, "Angle of arrival detection using compressive sensing," in European Signal Proc. Conf. (EU-SIPCO), Aalborg, Denmark, Aug. 2010, pp. 1424-1428.
12. Y. Chi, L. Scharf, A. Pezeshki, and R. Calderbank, "The sensitivity to basis mismatch of compressed sensing in spectrum analysis and beamforming," IEEE Trans. Signal Proc., Vol. 59, no. 5, pp. 2182-2195, May 2011.
13. M. A. Herman and T. Strohmer, "General deviants: An analysis of perturbations in compressed sensing," IEEE J. Selected Topics in Signal Proc., Vol. 4, no. 2, pp. 342-349, Apr. 2010.
14. C. D. Austin, J. N. Ash, and R. L. Moses, "Parameter estimation using sparse reconstruction with dynamic dictionaries," in IEEE Int. Conf. Acoustics, Speech, and Signal Proc. (ICASSP), Prague, Czech Republic, May 2011, pp. 2852-2855.
15. R. G. Baraniuk, V. Cevher, M. F. Duarte, and C. Hegde, "Model-based compressive sensing," IEEE Trans. Info. Theory, Vol. 56, no. 4, pp. 1982-2001, Apr. 2010.
16. T. Blumensath and M. E. Davies, "Iterative hard thresholding for compressed sensing," Appl. Comput. Harmon. Anal., Vol. 27, no. 3, pp. 265-274, Nov. 2009.
17. J. A. Tropp and S. J. Wright, "Computational methods for sparse solution of linear inverse problems," Proc. IEEE, Vol. 98, no. 6, pp. 948-958, June 2010.
18. H. Rauhut, K. Schnass, and P. Vandergheynst, "Compressed sensing and redundant dictionaries," IEEE Trans. Info. Theory, Vol. 54, no. 5, pp. 2210-2219, May 2008. (Pubitemid 351689557)
19. E. J. Candès, Y. C. Eldar, D. Needell, and P. Randall, "Compressed sensing with coherent and redundant dictionaries," Appl. Comput. Harmon. Anal., Oct. 2010, To appear.
20. C. Hegde, M. F. Duarte, and V. Cevher, "Compressive sensing recovery of spike trains using a structured sparsity model," in Workshop on Signal Proc. with Adaptive Sparse Structured Representations (SPARS), Saint Malo, France, Apr. 2009.
21. M. A. Davenport, J. N. Laska, J. R. Treichler, and R. G. Baraniuk, "The pros and cons of compressive sensing for wideband signal acquisition: Noise folding vs. dynamic range," 2011, Preprint.
22. E. Arias-Castro and Y. C. Eldar, "Noise folding in compressed sensing," 2011, Preprint.