Title :
Direction of arrival estimation via sparse representation of fourth order statistics
Author :
Shuang Li ; Xiaoxiao Jiang ; Wei He ; Yingguan Wang
Author_Institution :
Key Lab. of Wireless Sensor Networks & Commun., Shanghai Inst. of Microsyst. & Inf. Technol., Shanghai, China
Abstract :
In this paper, a new direction of arrival (DOA) estimation method is proposed based on the sparse presentation of array covariance matrix of a difference co-array, which is obtained by exploiting fourth order cumulants. The DOAs are estimated by finding the sparsest solution in a redundant basis. We also give a theoretical guidance to select the regularization parameter. Since fourth order cumulants are used, our method can not only detect more sources than sensors but also can suppress spatially colored noise. Besides, our method achieves higher resolution compared with existing methods. Simulation results are given to demonstrate the effectiveness and excellent performance of the proposed method.
Keywords :
array signal processing; covariance matrices; direction-of-arrival estimation; higher order statistics; signal denoising; signal representation; signal resolution; DOA estimation method; array covariance matrix; difference coarray; direction of arrival estimation method; fourth order cumulant; fourth order statistics; regularization parameter; sensor; signal resolution; sparse representation; spatially colored noise suppression; Arrays; Covariance matrices; Direction-of-arrival estimation; Estimation; Sensors; Signal to noise ratio; Vectors; Array signal processing; direction of arrival estimation; fourth order cumulants; sparse representation;
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
DOI :
10.1109/ICSPCC.2013.6663951