基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

doi:10.11959/j.issn.1000-436x.2021219

Abstract

Abstract:

To solve the problem that most of the existing direction of arrival(DOA) estimation methods for coherent signals could not be used in the case of under determination, where the number of incident signals exceeds the number of sensors, a DOA estimation method combining complex fast independent component analysis (FastICA) and sparse reconstruction algorithm was proposed.When the number of uniform circular array(UCA) sensors was M, the DOA of M(M-1) incident signals could be estimatedat most.To solve the problem of poor separation effect of complex FastICA in the case of low signal-to-noise ratio(SNR), two general denoising complex FastICA algorithm were proposed, which could be used in the case of circular signal and non-circular signal.The results of simulation and measured data show that the proposed algorithm can estimate both coherent and incoherent signals in underdetermined cases.Compared with several existing algorithm, the proposed DOA estimation algorithm has good performance.

Key words: underdetermined, complex fast independent component analysis, sparse reconstruction, DOA estimation, denoising, coherent signal

CLC Number:

TN98

Jin HOU, Yunzhe LI, Tianyu LI. Underdetermined DOA estimation of coherent signals based on denoising complex FastICA and sparse reconstruction[J]. Journal on Communications, 2021, 42(11): 172-181.

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References 19

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算法	平均收敛次数/次
非线性FastICA算法	68
除噪复数FastICA算法	12
去噪复数FastICA算法	14

算法	DOA估计结果
目标DOA	[103°,[256°,320°]]
L1-SVD	[103°,[256°,319°]]
MUSIC	[103°,320°]
DML	[103°,256°]
本文所提算法	[103°,[256°,320°]]

算法	DOA结果	错误个数
目标DOA	[37°,96°,171°,290°,322°,358°]	—
L1-SVD	[95°,138°,169°,198°,288°,358°]	1
MUSIC	[37°,100°,171°,224°,288°,321°]	2
DML	[95°,169°,195°,260°,333°,358°]	3
本文所提算法	[37°,96°,171°,290°,322°,358°]	0

Underdetermined DOA estimation of coherent signals based on denoising complex FastICA and sparse reconstruction

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