DocumentCode :
190849
Title :
A fast DOA estimation algorithm based on subspace projection
Author :
Jingjing Cai ; Peng Li ; Yinping Zhang ; Guoqing Zhao
Author_Institution :
Key Lab. of Electron. Inf. Countermeasure & Simulation Technol. Minist. of Educ., Xidian Univ., Xian, China
fYear :
2014
fDate :
5-8 Aug. 2014
Firstpage :
199
Lastpage :
203
Abstract :
The Multiple Signal Classification (MUSIC) algorithm is a representative method for the Direction of Arrival (DOA) estimation. However, it has to compute Eigenvalue Decomposition (EVD) and cumulate certain snapshots for once DOA estimation, which is costly in the computation and limits its applications. This paper proposes a Subspace Projection based MUSIC (SP-MUSIC) algorithm. The algorithm avoids computing EVD in the subspace estimation. It reduces the computational complexity and need not cumulate snapshots. Moreover, a Simplified SP-MUSIC (SSP-MUSIC) is devised, which accelerates the DOA estimation further. The computation and memory usage for the both algorithms are analyzed theoretically. The computational complexities are reduced greatly, especially for the SSP-MUSIC. And the SSP-MUSIC also takes a smaller memory capacity. Through the simulations, it is illustrated that the performance of the SP-MUSIC and the SSP-MUSIC is quit close to the traditional MUSIC.
Keywords :
computational complexity; direction-of-arrival estimation; eigenvalues and eigenfunctions; signal classification; DOA estimation algorithm; EVD; MUSIC algorithm; SP-MUSIC algorithm; computational complexity reduction; direction of arrival estimation; eigenvalue decomposition; multiple signal classification algorithm; subspace estimation; subspace projection; Arrays; Computational complexity; Covariance matrices; Direction-of-arrival estimation; Eigenvalues and eigenfunctions; Estimation; Multiple signal classification; Direction of arrival (DOA); MUSIC; computational complexity; subspace projection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2014 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4799-5272-4
Type :
conf
DOI :
10.1109/ICSPCC.2014.6986182
Filename :
6986182
Link To Document :
بازگشت