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