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