DocumentCode :
110966
Title :
Source Enumeration in Array Processing Using a Two-Step Test
Author :
Zhihua Lu ; Zoubir, Abdelhak M.
Author_Institution :
Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany
Volume :
63
Issue :
10
fYear :
2015
fDate :
15-May-15
Firstpage :
2718
Lastpage :
2727
Abstract :
We investigate the problem of enumerating source signals impinging on an array of sensors given noisy, limited observations. The assumption of a large sample size is indispensable for most of the existing approaches so that they suffer significant performance degradation when only a small number of samples is available. Random matrix theory can capture the asymptotic distributions of the eigenvalues accurately and provide good approximations even for a finite sample size. In this paper, we take into account the relationship and distributions of the noise and signal eigenvalues based on random matrix theory and derive a simple two-step test. Numerical simulations demonstrate that it is capable of correctly determining the number of sources in the case of small sample sizes.
Keywords :
approximation theory; array signal processing; eigenvalues and eigenfunctions; matrix algebra; random processes; approximation theory; array signal processing; eigenvalues; finite sample size; numerical simulation; random matrix theory; sensor array; source signal enumeration; two-step testing; Arrays; Covariance matrices; Eigenvalues and eigenfunctions; Noise; Sensors; Sociology; Vectors; Array processing; Bayesian information criterion (BIC); hypothesis test; maximum a posteriori probability (MAP) test; model order selection; sample eigenvalue; small sample size; source enumeration;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2015.2414894
Filename :
7064763
Link To Document :
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