DocumentCode :
1787731
Title :
Continuous sparse recovery for direction of arrival estimation with co-prime arrays
Author :
Zhao Tan ; Nehorai, Arye ; Eldar, Yonina C.
Author_Institution :
Dept. of Electr. & Syst. Eng., Washington Univ. in St. Louis, St. Louis, MO, USA
fYear :
2014
fDate :
22-25 June 2014
Firstpage :
393
Lastpage :
396
Abstract :
We consider the problem of direction of arrival (DOA) estimation using a newly proposed structure of co-prime arrays. A continuous sparse recovery method is implemented in order to increase resolution. We show that in the noiseless case one can theoretically detect up to MN/2 sources with only 2M+N sensors via continuous sparse recovery. The noise statistics of co-prime arrays are also analyzed to demonstrate the robustness of the proposed optimization scheme. Using numerical examples, we show the superiority of the proposed method.
Keywords :
array signal processing; direction-of-arrival estimation; signal resolution; statistical analysis; 2M+N sensors; DOA estimation; co-prime array structure; continuous sparse recovery method; direction of arrival estimation; noise statistics; optimization scheme; Arrays; Conferences; Direction-of-arrival estimation; Estimation; Multiple signal classification; Optimization; Signal resolution; Direction of arrival estimation; co-prime arrays; continuous sparse recovery method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th
Conference_Location :
A Coruna
Type :
conf
DOI :
10.1109/SAM.2014.6882425
Filename :
6882425
Link To Document :
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