非圆信号的贝叶斯稀疏重构阵列测向方法

doi:10.7527/S1000-6893.2013.0461

Abstract

Abstract:

The performance of the subspace-based direction of arrival (DOA) estimation methods can be improved significantly via effective exploitation of the non-circularity of the incident signals, but the shortcomings of these methods in adaptation to demanding scenarios, such as low signal-to-noise ratio (SNR) and limited snapshots, can hardly be made up. The sparse Bayesian learning (SBL) technique is introduced in this paper to deal with the DOA estimation problem of non-circular signals. The spatial sparsity of the incident signals is exploited together with their non-circularity property, and the covariance and conjugate covariance matrices of the array outputs of non-circular signals are decomposed jointly under a sparsity constraint to reconstruct the spatial spectrum of the incident signals, and the DOA estimates are finally obtained according to the spectrum peak locations. This method is robust against inter-signal correlation, and its superiorities in adaptation to demanding scenarios as well as in DOA estimation precision are demonstrated by the simulation results.

Key words: array processing, direction of arrival estimation, non-circular signal, sparse Bayesian learning, joint sparse reconstruction, coherent signal

CLC Number:

LIU Zhangmeng, ZHOU Yiyu, WU Haibin. Direction of Arrival Estimation Method of Non-circular Signals via Sparse Bayesian Reconstruction[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(3): 821-827.

References

[1] Krim H, Viberg M. Two decades of array signal processing research: the parametric approach[J]. IEEE Signal Processing Magazine, 1996, 13(4): 67-94.

[2] Schmidt R. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276-280.

[3] Edelblute D J. Noncircularity[J]. IEEE Signal Processing Letters, 1996, 3(5): 156-157.

[4] Gounon P, Adnet C, Galy J. Localization angulaire de signaux non circulaires[J]. Traitement du Signal, 1998, 15(1): 17-23.

[5] Charge P, Wang Y, Saillard J. A non-circular sources direction finding method using polynomial rooting[J]. Signal Processing, 2001, 81(8): 1765-1770.

[6] Abeida H, Delmas J P. MUSIC-like estimation of direction of arrival for noncircular sources[J]. IEEE Transactions on Signal Processing, 2006, 54(7): 2678-2690.

[7] Liu J, Huang Z T, Zhou Y. Extended 2q-MUSIC algorithm for noncircular signals[J]. Signal Processing, 2008, 88(6): 1327-1339.

[8] Gao F, Nallanathan A, Wang Y. Improved MUSIC under the coexistence of both circular and noncircular sources[J]. IEEE Transactions on Signal Processing, 2008, 56(7): 3033-3038.

[9] Gorodnitsky I F, Rao B D. Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm[J]. IEEE Transactions on Signal Processing, 1997, 45(3): 600-616.

[10] Fuchs J J. On the application of the global matched filter to DOA estimation with uniform circular arrays[J]. IEEE Transactions on Signal Processing, 2001, 49(4): 702-709.

[11] Malioutov D, Cetin M, Willsky A S. A sparse signal reconstruction perspective for source localization with sensor arrays[J]. IEEE Transactions on Signal Processing, 2005, 53(8): 3010-3022.

[12] Liu Z M, Huang Z T, Zhou Y Y. Direction-of-arrival estimation of wideband signals via covariance matrix sparse representation[J]. IEEE Transactions on Signal Processing, 2011, 59(9): 4256-4270.

[13] Yin J, Chen T. Direction-of-arrival estimation using a sparse representation of array covariance vectors[J]. IEEE Transactions on Signal Processing, 2011, 59(9): 4489-4493.

[14] Liu Z M, Huang Z T, Zhou Y Y. An efficient maximum likelihood method for direction-of-arrival estimation via sparse Bayesian learning[J]. IEEE Transactions on Wireless Communications, 2012, 11(10): 3607-3617.

[15] Liu Z M, Huang Z T, Zhou Y Y. Sparsity-inducing direction finding for narrowband and wideband signals based on array covariance vectors[J]. IEEE Transactions on Wireless Communications, 2013, 12(8): 3896-3907.

[16] Liu Z M, Zhou Y Y. A unified framework and sparse Bayesian perspective for direction-of-arrival estimation in the presence of array imperfections[J]. IEEE Transactions on Signal Processing, 2013, 61(15): 3786-3798.

[17] Tipping M E. Sparse Bayesian learning and the relevance vector machine[J]. Journal of Machine Learning Research, 2001, 1(1): 211-244.

[18] Wipf D P. Bayesian methods for finding sparse representations[D]. San Diego: University of California, 2006.

[19] Dempster A P, Laird N M, Rubin D B. Maximum likelihood from incomplete data via the EM algorithm[J]. Journal of the Royal Statistical Society Series B-Statistical Methodology, 1977, 39(1): 1-38.

[20] Stoica P, Selen Y. Model-order selection: A review of information criterion rules[J]. IEEE Signal Processing Magazine, 2004, 21(4): 36-47.

[21] Fuchs J J. Multipath time-delay detection and estimation[J]. IEEE Transactions on Signal Processing, 1999, 47(1): 237-243.

Direction of Arrival Estimation Method of Non-circular Signals via Sparse Bayesian Reconstruction

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 13

Recommended Articles

Metrics

Comments

[1]	ZHANG Tao, ZHONG Lunlong, LAI Ran, GUO Juncheng. Sparse Bayesian learning method for eliminating dictionary mismatch in clutter space-time spectrum estimation [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 324592-324592.
[2]	CHEN Lu, BI Daping, PAN Jifei. A direction finding algorithm based on smooth reconstruction sparse Bayesian learning [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(6): 322087-322087.
[3]	LIU Xionghou, SUN Chao, ZHUO Jie, MA Qian, PAN Hao. An MIMO Array for High-resolution Sector-scan Imaging [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(9): 2540-2550.
[4]	HU Tong, ZHANG Gong, LI Jianfeng, ZHANG Xiaofei, BEN De. Angle Estimation in MIMO Radar with Non-circular Signals Based on Real-valued ESPRIT [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013, 34(8): 1953-1959.
[5]	LI Jing, ZENG Cao, LIAO Guisheng, TAO Haihong, ZHAO Yuannan. Interferometric DOA Estimation Based on Shift Invariance Subarrays for Suppressing Mainlobe Jamming [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013, 34(12): 2804-2814.
[6]	WANG Kerang, HE Jin, HE Yapeng, ZHU Xiaohua, ZHANG Yanhong. RTR-ESPRIT for Joint DOD and DOA Estimation for MIMO Radars [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, (5): 893-901.
[7]	LUO Zheng, ZHANG Min, LI Pengfei. A Novel 2D DOA Estimation Algorithm Based on High-order Power of Covariance Matrix [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, (4): 696-704.
[8]	PAN Jie, ZHOU Jianjiang, WANG Fei. 2-D DOA Estimation for Sparse Uniform Circular Array in Presence of Unknown Nonuniform Noise [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011, 32(3): 448-456.
[9]	JI Jianchao;BAI Long;HUANG Xun. A State Observer Based Algorithm for Aeroacoustic Beamforming [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011, 32(1): 35-40.
[10]	Wang Jianpeng;Liu Zheng;Jiang Wenli. DOA Estimation for Passive Synthetic Arrays of Moving Single Sensor [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2010, 31(7): 1445-1453.
[11]	Jiang Shengli;Wang Juting;He Jin;Liu Zhong. DOA Estimation in Impulsive Clutter for MIMO Radars [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2009, 30(8): 1454-1459.
[12]	Xia Tieqi;Wan Qun;Wang Xuegang. 2D DOA Estimation in Impulsive Noise Environments with Arbitrary Array Configuration [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2008, 29(5): 1233-1238.
[13]	Zhang Ming;Zhu Zhaoda. PROJECTION METHOD WITH APPLICATIONTO ARRAY PROCESSINGOFSINGLESNAPSHOTIN REALREGION [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 1994, 15(11): 1334-1340.