DocumentCode :
1088258
Title :
Low-Complexity MDL Method for Accurate Source Enumeration
Author :
Huang, Lei ; Wu, Shunjun
Author_Institution :
Shenzhen Univ., Guangdong
Volume :
14
Issue :
9
fYear :
2007
Firstpage :
581
Lastpage :
584
Abstract :
A low-complexity method for source enumeration is proposed in this letter. Given the training data of a desired signal, an array data matrix is partitioned into orthogonal signal and noise components. The noise components are then used to calculate the total description length required to encode the array data. The model with the minimum description length (MDL) is chosen as the best model. Unlike the traditional MDL methods, the proposed method linearly partitions the array data into the cleaner signal and noise components and thereby is more accurate and computationally efficient. Its performance is demonstrated via numerical results.
Keywords :
array signal processing; interference (signal); accurate source enumeration; array data matrix; low-complexity method; minimum description length; noise components; orthogonal signal; training data; Additive noise; Array signal processing; Covariance matrix; Eigenvalues and eigenfunctions; Multidimensional signal processing; Radar signal processing; Sensor arrays; Signal to noise ratio; Training data; Wiener filter; Array signal processing; Wiener filter; direction of arrival (DOA); eigenvalue decomposition (EVD); minimum description length (MDL); multistage Wiener filter (MSWF);
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2006.885286
Filename :
4286946
Link To Document :
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