Weighted subspace methods and spatial smoothing: analysis and comparison

Rao, BD and Hari, KVS (1993) Weighted subspace methods and spatial smoothing: analysis and comparison. In: IEEE Transactions on Signal Processing, 41 (2). pp. 788-803.

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Abstract

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.

Item Type:	Journal Article
Publication:	IEEE Transactions on Signal Processing
Publisher:	IEEE
Additional Information:	Copyright 1993 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:	26 Apr 2011 10:01
Last Modified:	26 Apr 2011 10:01
URI:	http://eprints.iisc.ac.in/id/eprint/36462

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