DocumentCode
2670
Title
An MDL Algorithm for Detecting More Sources Than Sensors Using Outer-Products of Array Output
Author
Qi Cheng ; Pal, Parama ; Tsuji, Mineo ; Yingbo Hua
Author_Institution
Sch. of Eng., Univ. of Western Sydney, Sydney, NSW, Australia
Volume
62
Issue
24
fYear
2014
fDate
Dec.15, 2014
Firstpage
6438
Lastpage
6453
Abstract
In this paper, we propose an algorithm for detecting the number M of Gaussian sources received by an array of a number N (N <; M) of sensors. This algorithm is based on the minimum description length (MDL) principle using the outer-products of the array output. We show that as long as the covariance matrix of the array output has the full rank N, the covariance matrix of a vectorized outer-product of the array output has the full rank N-squared, which meets a validity condition of the MDL algorithm. We show by simulation that the MDL algorithm can perform substantially better than some relevant algorithms. A necessary identifiability condition is also obtained, for uncorrelated sources.
Keywords
covariance matrices; sensors; signal detection; Gaussian sources; MDL algorithm; covariance matrix; identifiability condition; minimum description length principle; vectorized outer-product; Arrays; Covariance matrices; Educational institutions; Noise; Sensors; Signal processing algorithms; Vectors; Array output; MDL; detection; outer-product; redundancy array;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2014.2364019
Filename
6928492
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