A Robust DOA Estimation Method Based on Sparse Representation for Impulsive Noise Environments

doi:10.3969/j.issn.0372-2112.2018.07.001

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ACTA ELECTRONICA SINICA ›› 2018, Vol. 46 ›› Issue (7) : 1537-1544. DOI: 10.3969/j.issn.0372-2112.2018.07.001

A Robust DOA Estimation Method Based on Sparse Representation for Impulsive Noise Environments

WANG Peng^1,2, QIU Tian-shuang¹, JIN Fang-xiao¹, XIA Nan³, LI Jing-chun³

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Abstract

Inspired by the correntropy,a robust DOA (direction-of-arrival) method based on sparse representation for impulsive noise was proposed.To recover the joint-sparse signal from multiple measurement vectors,a normalized iterative hard thresholding based optimization algorithm was designed.The optimal step size of the algorithm was discussed and the convergence was proved.The simulation results demonstrate that the proposed method could realize the DOA estimation for multiple sources,and it is superior to existing methods in terms of success rate and estimation accuracy.

Key words

DOA estimation / impulsive noise / sparse representation / correntropy

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WANG Peng, QIU Tian-shuang, JIN Fang-xiao, XIA Nan, LI Jing-chun. A Robust DOA Estimation Method Based on Sparse Representation for Impulsive Noise Environments[J]. Acta Electronica Sinica, 2018, 46(7): 1537-1544. https://doi.org/10.3969/j.issn.0372-2112.2018.07.001

References

[1] KRIM H,VIVERG M.Two decades of array signal processing research:the parametric approach[J].IEEE Signal Processing Magazine,1996,13(4):67-94.
[2] 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.
[3] COTTER S F,RAO B D,ENGAN K,et al.Sparse solutions to linear inverse problems with multiple measurement vectors[J].IEEE Transactions on Signal Processing,2005,53(7):2477-2488.
[4] COTTER S F.Multiple snapshot matching pursuit for direction of arrival (DOA) estimation[A].Proceedings of the 15th European Signal Processing Conference[C].USA:IEEE,2007.247-251.
[5] HYDER M M,MAHATA K.Direction-of-arrival estimation using a mixed norm approximation[J].IEEE Transactions on Signal Processing,2010,58(9):4646-4655.
[6] YIN J H,CHEN T Q.Direction-of-arrival estimation using a sparse representation of array covariance vectors[J].IEEE Transactions on Signal Processing,2011,59(9):4489-4493.
[7] BLANCHARD J D,CERMAK M,HANLE D,et al.Greedy algorithms for joint sparse recovery[J].IEEE Transactions on Signal Processing,2014,62(7):1694-1704.
[8] 吴小川,邓维波,杨强.基于CS-MUSIC算法的DOA估计[J].系统工程与电子技术,2013,35(9):1821-1824. WU Xiao-chuan,DENG Wei-bo,YANG Qiang.DOA estimation method based on CS-MUSIC algorithm[J].Systems Engineering and Electronics,2013,35(9):1821-1824.(in Chinese)
[9] 林波,张增辉,朱炬波.基于压缩感知的DOA估计稀疏化模型与性能分析[J].电子与信息学报,2014,36(3):589-594. LIN Bo,ZHANG Zeng-hui,ZHU Ju-bo.Sparsity model and performance analysis of DOA estimation with compressive sensing[J].Journal of Electronics & Information Technology,2014,36(3):589-594.(in Chinese)
[10] 田野,练秋生,徐鹤.基于稀疏信号重构的DOA和极化角度估计算法[J].电子学报,2016,44(7):1548-1554. TIAN Ye,LIAN Qiu-sheng,XU He.DOA and polarization angle estimation algorithm based on sparse signal reconstructio n[J].Acta Electronica Sinica,2016,44(7):1548-1554.(in Chinese)
[11] 王彪,朱志慧,戴跃伟.基于具有时序结构的稀疏贝叶斯学习的水声目标DOA估计研究[J].电子学报,2016,44(3),693-698. WANG Biao,ZHU Zhi-hui,DAI Yue-wei.Direction of arrival estimation research for underwater acoustic target based on sparse Bayesian learning with temporally correlated source vectors[J].Acta Electronica Sinica,2016,44(3):693-698.(in Chinese)
[12] SONG A M,QIU T S.The equivalency of minimum error entropy criterion and minimum dispersion criterion for symmetric stable signal processing[J].IEEE Signal Processing Letters,2010,17(1):32-35.
[13] 张金凤,邱天爽,李森.冲激噪声环境下基于最大相关熵准则的韧性子空间跟踪新算法[J].电子学报,2015,43(3):483-488. ZHANG Jin-feng,Qiu Tian-shuang,LI Sen.A robust PAST algorithm based on maximum correntropy criterion for impulsive noise environments[J].Acta Electronica Sinica,2015,43(3):483-488.(in Chinese)
[14] YU L,QIU T S,LUAN S Y.Fractional time delay estimation algorithm based on the maximum correntropy criterion and the Lagrange FDF[J].Signal Processing,2015,111:222-229.
[15] Zhang J F,QIU T S,SONG A M,et al.A novel correntropy based DOA estimation algorithm in impulsive noise environments[J].Signal Processing,2014,104:346-357.
[16] CHEN B D,LEI X,LIANG J L,et al.Steady-state mean-square error analysis for adaptive filtering under the maximum correntropy criterion[J].IEEE Signal Processing Letters,2014,21(7):880-884.
[17] LIU W F,POKHAREL P P,PRINCIPE J C.Correntropy:properties and applications in non-Gaussian signal processing[J].IEEE Transactions on Signal Processing,2007,55(11):5286-5298.
[18] SHAO M,NIKIAS C L.Signal processing with fractional lower order moments:stable processes and their applications[J].Proceedings of the IEEE,1993,81(7):986-1010.
[19] BLUMENSATH T,DAVIES M E.Normalized iterative hard thresholding:guaranteed stability and performance[J].IEEE Journal of Selected Topics in Signal Processing,2010,4(2):298-309.
[20] CARRILLO R E,BARNER K E.Lorentzian iterative hard thresholding:robust compressed sensing with prior information[J].IEEE Transactions on Signal Processing,2013,61(19):4822-4833.
[21] LIU T H,MENDEL J M.A subspace-based direction finding algorithm using fractional lower order statistics[J].IEEE Transactions on Signal Processing,2001,49(8):1605-1613.