DocumentCode :
643821
Title :
DOA estimation for closely spaced signals
Author :
Jian Liu ; Ai-min Song ; Feng Yang ; Xing-yang Guo ; Jiao Guan
Author_Institution :
Sch. of Inf. & Navig., Air Force Eng. Univ., Xi´an, China
fYear :
2013
fDate :
5-8 Aug. 2013
Firstpage :
1
Lastpage :
4
Abstract :
High resolution direction of arrival (DOA) estimation algorithms based on the subspace decomposition received considerable attention while rarely used in the practical applications. One of the reasons is its difficulty to resolve closely spaced signals in low signal-to-noise ratio (SNR). For applications of closely spaced signals within a priori known angle range, we filter the spectrum in direction domain to improve the SNRs of signals on array sensors and reconstruct the covariance matrix with which MUSIC algorithm is applied. The improvement in the aspects of resolution and accuracy in low SNR is shown by Monte-Carlo simulations.
Keywords :
Monte Carlo methods; covariance matrices; direction-of-arrival estimation; signal classification; signal reconstruction; signal resolution; MUSIC algorithm; Monte-Carlo simulation; SNR; array sensor signal; closely-spaced signals; covariance matrix reconstruction; direction domain; direction-of-arrival estimation algorithm; high-resolution DOA estimation algorithm; priori known angle range; signal-to-noise ratio; subspace decomposition; Arrays; Direction-of-arrival estimation; Multiple signal classification; Sensors; Signal processing algorithms; Signal resolution; Signal to noise ratio; Array signal processing; MUSIC; direction-domain filtering; direction-of-arrival (DOA) estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
Type :
conf
DOI :
10.1109/ICSPCC.2013.6664142
Filename :
6664142
Link To Document :
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