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Bounds for a mixture of low-rank compound-Gaussian and white Gaussian noises

Besson, Olivier Bounds for a mixture of low-rank compound-Gaussian and white Gaussian noises. (2016) IEEE Transactions on Signal Processing, 64 (21). 5723-5732. ISSN 1053-587X

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Official URL: http://dx.doi.org/10.1109/TSP.2016.2603965

Abstract

We consider the problem of estimating the parameters of a low-rank compound-Gaussian process in white Gaussian noise. This situation typically arises in radar applications where clutter is relevantly modeled as compound-Gaussian with a rank-deficient covariance matrix of the speckle. Using a minimal and unconstrained parametrization of the problem, we derive lower bounds for estimation of the parameters describing the covariance matrix. First, assuming the textures are deterministic, the Cram\'{e}r-Rao bound is derived, which enables one to assess the impact of the time-varying textures on the estimation performance. Then, considering the textures as random, hybrid bounds are derived. In addition, we derive a lower bound for estimating the projector on the clutter subspace. Numerical simulations enable one to evaluate the impact of random, time-varying textures compared to the conventional case of constant texture, i.e., of Gaussian subspace signals in Gaussian noise.

Item Type:Article
Additional Information:("(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Audience (journal):International peer-reviewed journal
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Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
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Deposited By: Olivier Besson
Deposited On:19 Sep 2016 14:29

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