DOA ESTIMATION OF CLOSELY-SPACED AND SPECTRALLY-OVERLAPPED SOURCES BASED ON TIME-FREQUENCY SPARSE REPRESENTATION

被引：0

作者：

Zheng, Ling ^{[1
]}

Zhang, Haijian ^{[1
]}

Sun, Hong ^{[1
]}

机构：

[1] Wuhan Univ, Sch Elect Informat, Signal Proc Lab, Wuhan 430072, Peoples R China

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS | 2016年

关键词：

Closely-spaced and spectrally-overlapped sources; TF sparse representation; single-source TF points; DOA estimation; SOURCE SEPARATION; LOCALIZATION; SIGNALS; MATRIX;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

For the purpose of dealing with closely-spaced and spectrally-overlapped sources, a direction-of-arrival (DOA) estimation algorithm based on time-frequency (TF) sparse representation is proposed. Firstly a short-time Fourier transform (STFT) based single-source TF points selection method is briefly introduced. On this basis, we extract the STFT values corresponding to the single-source TF points of each source from the STFT values of array outputs to construct received data matrix. We then enforce sparsity by imposing the l(1) norm based penalties on TF sparse signal representation and solve the optimization problem. Finally, the DOA of each source can be estimated from over-complete basis according to the peak of TF sparse signal vector. Simulation results demonstrate the advantages of the proposed algorithm in terms of dealing with closely-spaced and spectrally-overlapped sources and the flexibility in underdetermined cases.(1)

引用

页码：3266 / 3270

页数：5

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