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Spatial Wavelet Packet Denoising for Improved DOA Estimation

Sathish, R and Anand, GV (2004) Spatial Wavelet Packet Denoising for Improved DOA Estimation. In: 14th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, 29 September - 1 October, 2004, Sao Luis, Brazil, pp. 745-754.


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The performance of direction-of-arrival (DOA) estimation techniques such as MUSIC degrades progressively with decreasing signal-to-noise ratio (SNR). The DOA estimation performance may be improved by employing a pre-processor that enhances the SNR, before performing the DOA estimation. In this paper, a denoising technique based on the use of wavelet packet transform in the spatial domain is proposed for enhancing the output SNR of a uniform linear array of sensors receiving narrowband signals in the form of plane waves from different directions. The technique involves the use of a spatial wavelet packet transform (SWPT) followed by a block thresholding scheme based on the norm of SWPT subvectors in different spatial frequency subbands. This method has the advantage of not requiring the high sampling rates demanded by the temporal wavelet denoising techniques. It is shown through simulations that SWPT denoising (SWD) requires a sampling rate that is just 2-4 times the signal frequency, whereas temporal wavelet denoising (TWD) requires a much higher sampling rate for achieving a comparable SNR gain. Consequently, at lower sampling rates, the DOA estimation performance indices, such as bias, mean square error and resolution, achieved by SWD are much superior to those achieved by TWD or by undenoised data.

Item Type: Conference Paper
Publisher: IEEE
Additional Information: copyright 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 27 Apr 2007
Last Modified: 19 Sep 2010 04:35
URI: http://eprints.iisc.ac.in/id/eprint/9869

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