Analysis of MUSIC algorithm with sensor gain and phase perturbations
Signal Processing
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
A denoising approach to multisensor signal estimation
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
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In this paper, we explore the use of wavelet based denoising techniques to improve the Direction-of-Arrival (DOA) estimation performance of array processors at low SNR. Traditional single sensor wavelet denoising techniques are not suitable for this application since they fail to preserve the intersensor signal correlation. We propose two correlation preserving techniques for denoising multi-sensor signals: (1) the Temporal Wavelet Array Denoising (TWAD) technique developed by Rao and Jones [IEEE Trans. Signal Processing, vol. 48, pp. 1225---1234, 2000], and (2) a new Spatial Wavelet Array Denoising (SWAD) technique. It is shown that SWAD offers the advantage of a significant reduction in computational complexity at the cost of a slight reduction in SNR gain. The denoised array data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented for MUSIC (without denoising), TWAD-MUSIC, and SWAD-MUSIC, to illustrate the improvement in DOA estimation performance brought about by denoising.