Title :
Wavelet denoising for plane wave DOA estimation by MUSIC
Author :
Sathish, R. ; Anand, G.V.
Author_Institution :
Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India
Abstract :
MUSIC is a widely used technique for plane wave direction-of-arrival (DOA) estimation, which is a problem of great interest in several applications. The performance of MUSIC degrades under low signal-to-noise ratio (SNR) conditions due to errors in estimating the data covariance matrix from finite data. The paper explores the possibility of employing the wavelet denoising technique to arrest the degradation in the finite data performance of MUSIC under low SNR. We propose the application of wavelet denoising to the noisy signal at each sensor to boost the SNR before performing DOA estimation by MUSIC. A comparative study of the finite data performance of MUSIC is presented for the undenoised and denoised data, and it is shown that denoising leads to a significant reduction in the bias and mean square errors (MSE) of the DOA estimates.
Keywords :
array signal processing; covariance matrices; direction-of-arrival estimation; mean square error methods; signal classification; signal denoising; wavelet transforms; MUSIC; SNR; bias; data covariance matrix; direction-of-arrival estimation; estimation errors; finite-data performance; mean square errors; multiple signal classification; plane wave DOA estimation; sensor array; signal-to-noise ratio; wavelet denoising; Covariance matrix; Degradation; Direction of arrival estimation; Estimation error; Mean square error methods; Multiple signal classification; Noise reduction; Sensor arrays; Signal to noise ratio; Working environment noise;
Conference_Titel :
TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region
Print_ISBN :
0-7803-8162-9
DOI :
10.1109/TENCON.2003.1273244
