Vol. 102
Latest Volume
All Volumes
PIERC 129 [2023] PIERC 128 [2023] PIERC 127 [2022] PIERC 126 [2022] PIERC 125 [2022] PIERC 124 [2022] PIERC 123 [2022] PIERC 122 [2022] PIERC 121 [2022] PIERC 120 [2022] PIERC 119 [2022] PIERC 118 [2022] PIERC 117 [2021] PIERC 116 [2021] PIERC 115 [2021] PIERC 114 [2021] PIERC 113 [2021] PIERC 112 [2021] PIERC 111 [2021] PIERC 110 [2021] PIERC 109 [2021] PIERC 108 [2021] PIERC 107 [2021] PIERC 106 [2020] PIERC 105 [2020] PIERC 104 [2020] PIERC 103 [2020] PIERC 102 [2020] PIERC 101 [2020] PIERC 100 [2020] PIERC 99 [2020] PIERC 98 [2020] PIERC 97 [2019] PIERC 96 [2019] PIERC 95 [2019] PIERC 94 [2019] PIERC 93 [2019] PIERC 92 [2019] PIERC 91 [2019] PIERC 90 [2019] PIERC 89 [2019] PIERC 88 [2018] PIERC 87 [2018] PIERC 86 [2018] PIERC 85 [2018] PIERC 84 [2018] PIERC 83 [2018] PIERC 82 [2018] PIERC 81 [2018] PIERC 80 [2018] PIERC 79 [2017] PIERC 78 [2017] PIERC 77 [2017] PIERC 76 [2017] PIERC 75 [2017] PIERC 74 [2017] PIERC 73 [2017] PIERC 72 [2017] PIERC 71 [2017] PIERC 70 [2016] PIERC 69 [2016] PIERC 68 [2016] PIERC 67 [2016] PIERC 66 [2016] PIERC 65 [2016] PIERC 64 [2016] PIERC 63 [2016] PIERC 62 [2016] PIERC 61 [2016] PIERC 60 [2015] PIERC 59 [2015] PIERC 58 [2015] PIERC 57 [2015] PIERC 56 [2015] PIERC 55 [2014] PIERC 54 [2014] PIERC 53 [2014] PIERC 52 [2014] PIERC 51 [2014] PIERC 50 [2014] PIERC 49 [2014] PIERC 48 [2014] PIERC 47 [2014] PIERC 46 [2014] PIERC 45 [2013] PIERC 44 [2013] PIERC 43 [2013] PIERC 42 [2013] PIERC 41 [2013] PIERC 40 [2013] PIERC 39 [2013] PIERC 38 [2013] PIERC 37 [2013] PIERC 36 [2013] PIERC 35 [2013] PIERC 34 [2013] PIERC 33 [2012] PIERC 32 [2012] PIERC 31 [2012] PIERC 30 [2012] PIERC 29 [2012] PIERC 28 [2012] PIERC 27 [2012] PIERC 26 [2012] PIERC 25 [2012] PIERC 24 [2011] PIERC 23 [2011] PIERC 22 [2011] PIERC 21 [2011] PIERC 20 [2011] PIERC 19 [2011] PIERC 18 [2011] PIERC 17 [2010] PIERC 16 [2010] PIERC 15 [2010] PIERC 14 [2010] PIERC 13 [2010] PIERC 12 [2010] PIERC 11 [2009] PIERC 10 [2009] PIERC 9 [2009] PIERC 8 [2009] PIERC 7 [2009] PIERC 6 [2009] PIERC 5 [2008] PIERC 4 [2008] PIERC 3 [2008] PIERC 2 [2008] PIERC 1 [2008]
2020-05-15
Compressed Sensing DOA Estimation in the Presence of Unknown Noise
By
Progress In Electromagnetics Research C, Vol. 102, 47-62, 2020
Abstract
A new compressive sensing-based direction of arrival (DOA) estimation technique for source signal detection in the presence of unknown noise, based on the generalized correlation decomposition (GCD) algorithm, is presented. The proposed algorithm does not depend on the singular value decomposition nor on the orthogonality of the signal and the noise subspaces. Hence, the DOA estimation can be done without an a priori knowledge of the number of sources. The proposed algorithm can estimate more sources than the number of physical sensors used without any constraints or assumptions about the nature of the signal sources. It can estimate coherent source signals as well as closely-spaced sources using a small number of snapshots.
Citation
Amgad A. Salama M. Omair Ahmad M. N. S. Swamy , "Compressed Sensing DOA Estimation in the Presence of Unknown Noise," Progress In Electromagnetics Research C, Vol. 102, 47-62, 2020.
doi:10.2528/PIERC20031204
http://www.jpier.org/PIERC/pier.php?paper=20031204
References

1. Shen, Q., W. Liu, W. Cui, and S. Wu, "Underdetermined doa estimation under the compressive sensing framework: A review," IEEE Access, Vol. 4, 8865-8878, 2016.

2. Babur, G., G. O. Manokhin, A. A. Geltser, and A. A. Shibelgut, "Low-cost digital beamforming on receive in phased array radar," IEEE Transactions on Aerospace and Electronic Systems, Vol. 53, No. 3, 1355-1364, 2017.

3. Wang, V. T. and M. P. Hayes, "Synthetic aperture sonar track registration using SIFT image correspondences," IEEE Journal of Oceanic Engineering, Vol. 42, No. 4, 901-913, 2017.

4. Grzegorowski, M., "Massively parallel feature extraction framework application in predicting dangerous seismic events," 2016 Federated Conference on Computer Science and Information Systems (FedCSIS), 225-229, IEEE, 2016.

5. Moore, A. H., C. Evers, P. A. Naylor, A. H. Moore, C. Evers, and P. A. Naylor, "Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors," IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), Vol. 25, No. 1, 178-192, 2017.

6. Chen, X., X., D. W. K. Ng, W. Gerstacker, and H.-H. Chen, "A survey on multiple-antenna techniques for physical layer security," IEEE Communications Surveys & Tutorials, Vol. 19, No. 2, 1027-1053, 2017.

7. Van Trees, H. L., Detection, Estimation, and Modulation Theory, Optimum Array Processing, John Wiley & Sons, 2004.

8. Schmidt, R., "Multiple emitter location and signal parameter estimation," IEEE Transactions on Antennas and Propagation, Vol. 34, No. 3, 276-280, 1986.

9. Roy, R. and T. Kailath, "ESPRIT-estimation of signal parameters via rotational invariance techniques," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 37, No. 7, 984-995, 1989.

10. Fan, X., L. Pang, P. Shi, G. Li, and X. Zhang, "Application of bee evolutionary genetic algorithm to maximum likelihood direction-of-arrival estimation," Mathematical Problems in Engineering, Vol. 2019, No. 12, 1-11, 2019.

11. Baktash, E., M. Karimi, and X.Wang, "Maximum-likelihood direction finding under elliptical noise using the em algorithm," IEEE Communications Letters, Vol. 23, No. 6, 1041-1044, 2019.

12. Pillai, S. U., Y. Bar-Ness, and F. Haber, "A new approach to array geometry for improved spatial spectrum estimation," Proceedings of the IEEE, Vol. 73, No. 10, 1522-1524, 1985.

13. Pillai, S. and F. Haber, "Statistical analysis of a high resolution spatial spectrum estimator utilizing an augmented covariance matrix," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 35, No. 11, 1517-1523, 1987.

14. Moffet, A., "Minimum-redundancy linear arrays," IEEE Transactions on Antennas and Propagation, Vol. 16, No. 2, 172-175, 1968.

15. Ma, W.-K., T.-H. Hsieh, and C.-Y. Chi, "DOA estimation of quasi-stationary signals via Khatri-Rao subspace," 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2165-2168, IEEE, 2009.

16. Ma, W.-K., T.-H. Hsieh, and C.-Y. Chi, "DOA estimation of quasi-stationary signals with less sensors than sources and unknown spatial noise covariance: A Khatri-Rao subspace approach," IEEE Transactions on Signal Processing, Vol. 58, No. 4, 2168-2180, 2010.

17. Zhang, Y. D., M. G. Amin, and B. Himed, "Sparsity-based DOA estimation using co-prime arrays," 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3967-3971, IEEE, 2013.

18. Adhikari, K., J. R. Buck, and K. E. Wage, "Beamforming with extended co-prime sensor arrays," 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4183-4186, IEEE, 2013.

19. Shen, Q., W. Liu, W. Cui, S. Wu, Y. D. Zhang, and M. G. Amin, "Low-complexity direction-of-arrival estimation based on wideband co-prime arrays," IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 23, No. 9, 1445-1456, 2015.

20. Pal, P. and P. Vaidyanathan, "Nested arrays: A novel approach to array processing with enhanced degrees of freedom," IEEE Transactions on Signal Processing, Vol. 58, No. 8, 4167-4181, 2010.

21. Stoica, P. and A. Nehorai, "MUSIC, maximum likelihood, and Cramer-Rao bound," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 5, 720-741, 1989.

22. Stoica, P. and A. Nehorai, "Performance study of conditional and unconditional direction-of-arrival estimation," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 38, No. 10, 1783-1795, 1990.

23. Jaffer, A. G., "Maximum likelihood direction finding of stochastic sources: A separable solution," 1988 International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2893-2896, IEEE, 1988.

24. Zheng, Y., L. Liu, and X. Yang, "Spice-ml algorithm for direction-of-arrival estimation," Sensors, Vol. 20, No. 1, 119, 2020.

25. Yang, B., C. Wang, and D. Wang, "Direction-of-arrival estimation of strictly noncircular signal by maximum likelihood based on moving array," IEEE Communications Letters, Vol. 23, No. 6, 1045-1049, 2019.

26. Filippini, F., F. Colone, and A. De Maio, "Threshold region performance of multicarrier maximum likelihood direction of arrival estimator," IEEE Transactions on Aerospace and Electronic Systems, Vol. 55, No. 6, 3517-3530, 2019.

27. Viberg, M., P. Stoica, and B. Ottersten, "Array processing in correlated noise fields based on instrumental variables and subspace fitting," IEEE Transactions on Signal Processing, Vol. 43, No. 5, 1187-1199, 1995.

28. Wu, Q. and K. M. Wong, "UN-MUSIC and UN-CLE: An application of generalized correlation analysis to the estimation of the direction of arrival of signals in unknown correlated noise," IEEETransactions on Signal Processing, Vol. 42, No. 9, 2331-2343, 1994.

29. Li, T. and A. Nehorai, "Maximum likelihood direction finding in spatially colored noise fields using sparse sensor arrays," IEEE Transactions on Signal Processing, Vol. 59, No. 3, 1048-1062, 2011.

30. Bhandary, M., "Estimation of covariance matrix in signal processing when the noise covariance matrix is arbitrary ," Journal of Modern Applied Statistical Methods, Vol. 7, No. 1, 16, 2008.

31. Pan, M., G. Zhang, and Z. Hu, "Covariance difference matrix-based sparse bayesian learning for off-grid DOA estimation with colored noise," 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC), Vol. 1, 1-4, IEEE, 2019.

32. Wen, F., J. Shi, and Z. Zhang, "Direction finding for bistatic mimo radar with unknown spatially colored noise," Circuits, Systems, and Signal Processing, 1-13, 2019.

33. Yao, Y., T. N. Guo, Z. Chen, and C. Fu, "A fast multi-source sound doa estimator considering colored noise in circular array," IEEE Sensors Journal, Vol. 19, No. 16, 6914-6926, 2019.

34. Zhang, Y., G. Zhang, and H. Leung, "Atomic norm minimization methods for continuous doa estimation in colored noise ," 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 1-5, IEEE, 2019.

35. Sui, J., F. Ye, X. Wang, and F. Wen, "Fast parafac algorithm for target localization in bistatic mimo radar in the co-existence of unknown mutual coupling and spatially colored noise," IEEE Access, Vol. 7, 185720-185729, 2019.

36. Nagesha, V. and S. Kay, "Maximum likelihood estimation for array processing in colored noise," IEEE Transactions on Signal Processing, Vol. 44, No. 2, 169-180, 1996.

37. Liao, B., S.-C. Chan, L. Huang, and C. Guo, "Iterative methods for subspace and DOA estimation in nonuniform noise," IEEE Transactions on Signal Processing, Vol. 64, No. 12, 3008-3020, 2016.

38. Vorobyov, S., et al., "Maximum likelihood direction-of-arrival estimation in unknown noise fields using sparse sensor arrays," IEEE Transactions on Signal Processing, Vol. 53, No. 1, 34-43, 2005.

39. Chen, Z., G. Gokeda, and Y. Yu, Introduction to Direction-of-arrival Estimation, Artech House, 2010.

40. Godara, L. C., "Limitations and capabilities of directions-of-arrival estimation techniques using an array of antennas: A mobile communications perspective," IEEE International Symposium on Phased Array Systems and Technology, 327-333, IEEE, 1996.

41. Gorodnitsky, I. F. and B. D. Rao, "Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm ," IEEE Transactions on Signal Processing, Vol. 45, No. 3, 600-616, 1997.

42. Fuchs, J.-J., "Linear programming in spectral estimation: Application to array processing," 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vol. 6, 3161-3164, IEEE, 1996.

43. Fuchs, J.-J., "On the application of the global matched filter to DOA estimation with uniform circular arrays," IEEE Transactions on Signal Processing, Vol. 49, No. 4, 702-709, 2001.

44. Malioutov, D., M. Cetin, and A. S. Willsky, "A sparse signal reconstruction perspective for source localization with sensor arrays," IEEE Transactions on Signal Processing, Vol. 53, No. 8, 3010-3022, 2005.

45. Salama, A. A., M. O. Ahmad, and M. Swamy, "Underdetermined DOA estimation using MVDR-weighted LASSO," Sensors, Vol. 16, No. 9, 1549, 2016.

46. Liu, S. and G. Trenkler, "Hadamard, Khatri-Rao, Kronecker and other matrix products," Int. J. Inform. Syst. Sci., Vol. 4, No. 1, 160-177, 2008.

47. Hyder, M. and K. Mahata, "An approximate 0 norm minimization algorithm for compressed sensing," 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3365-3368, IEEE, 2009.

48. Berger, C. R., J. Areta, K. Pattipati, and P. Willett, "Compressed sensing --- A look beyond linear programming," 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3857-3860, IEEE, 2008.

49. Mancera, L. and J. Portilla, "l0-norm-based sparse representation through alternate projections," ICIP, Vol. 2092, Citeseer, 2006.

50. Mohimani, G. H., M. Babaie-Zadeh, and C. Jutten, "Fast sparse representation based on smoothed l0 norm," Independent Component Analysis and Signal Separation, 389-396, Springer, 2007.

51. Candes, E. J., "The restricted isometry property and its implications for compressed sensing," Comptes Rendus Mathematique, Vol. 346, No. 9, 589-592, 2008.

52. Baraniuk, R., M. Davenport, R. DeVore, and M. Wakin, "A simple proof of the restricted isometry property for random matrices," Constructive Approximation, Vol. 28, No. 3, 253-263, 2008.

53. Candes, E. J., J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Transactions on Information Theory, Vol. 52, No. 2, 489-509, 2006.

54. Donoho, D. L., "Compressed sensing," IEEE Transactions on Information Theory, Vol. 52, No. 4, 1289-1306, 2006.

55. Candes, E. J. and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies," IEEE Transactions on Information Theory, Vol. 52, No. 12, 5406-5425, 2006.

56. Xenaki, A., P. Gerstoft, and K. Mosegaard, "Compressive beamforming," The Journal of the Acoustical Society of America, Vol. 136, No. 1, 260-271, 2014.

57. Morozov, V. A., "On the solution of functional equations by the method of regularization," Soviet Math. Dokl., Vol. 7, 414-417, 1966.

58. Karl, W. C., "Regularization in image restoration and reconstruction," Handbook of Image and Video Processing, 141-160, 2000.

59. Tibshirani, R., "Regression shrinkage and selection via the lass," Journal of the Royal Statistical Society. Series B (Methodological), 267-288, 1996.

60. Chen, S. S., D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM Journal on Scientific Computing, Vol. 20, No. 1, 33-61, 1998.

61. Yin, J. and T. Chen, "Direction-of-arrival estimation using a sparse representation of array covariance vectors," IEEE Transactions on Signal Processing, Vol. 59, No. 9, 4489-4493, 2011.

62. Hansen, P. C. and D. P. O’Leary, "The use of the L-curve in the regularization of discrete ill-posed problems," SIAM Journal on Scientific Computing, Vol. 14, No. 6, 1487-150, 1993.

63. Hansen, P. C., T. K. Jensen, and G. Rodriguez, "An adaptive pruning algorithm for the discrete L-curve criterion," Journal of Computational and Applied Mathematics, Vol. 198, No. 2, 483-492, 2007.

64. Grant, M. and S. Boyd, "CVX: Matlab software for disciplined convex programming, version 2.1,", http://cvxr.com/cvx, Mar. 2014.

65. Grant, M. and S. Boyd, "Graph implementations for nonsmooth convex programs," Recent Advances in Learning and Control (V. Blondel, S. Boyd, and H. Kimura, eds.), Lecture Notes in Control and Information Sciences, 95-110, Springer-Verlag Limited, 2008.