DocumentCode :
3421127
Title :
Doa estimation by covariance matrix sparse reconstruction of coprime array
Author :
Chengwei Zhou ; Zhiguo Shi ; Yujie Gu ; Goodman, Nathan A.
Author_Institution :
Dept. of ISEE, Zhejiang Univ., Hangzhou, China
fYear :
2015
fDate :
19-24 April 2015
Firstpage :
2369
Lastpage :
2373
Abstract :
In this paper, we propose a direction-of-arrival estimation method by covariance matrix sparse reconstruction of coprime array. Specifically, source locations are estimated by solving a newly formulated convex optimization problem, where the difference between the spatially smoothed covariance matrix and the sparsely reconstructed one is minimized. Then, a sliding window scheme is designed for source enumeration. Finally, the power of each source is re-estimated as a least squares problem. Compared with existing methods, the proposed method achieves more accurate source localization and power estimation performance with full utilization of increased degrees of freedom provided by coprime array.
Keywords :
covariance matrices; direction-of-arrival estimation; least squares approximations; optimisation; signal reconstruction; DOA estimation; convex optimization problem; coprime array; direction-of-arrival estimation; least squares problem; power estimation performance; source enumeration; source localization; source locations; sparse reconstruction; spatially smoothed covariance matrix; Arrays; Conferences; Covariance matrices; Direction-of-arrival estimation; Estimation; Sparse matrices; Compressive sensing; coprime array; direction-of-arrival estimation; power estimation; source localization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
Type :
conf
DOI :
10.1109/ICASSP.2015.7178395
Filename :
7178395
Link To Document :
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