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Bayesian Sparse Estimation of a Radar Scene with Weak and Strong Targets

Lasserre, Marie and Bidon, Stéphanie and Besson, Olivier and Le Chevalier, François Bayesian Sparse Estimation of a Radar Scene with Weak and Strong Targets. (2015) In: 2015 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), 16 June 2015 - 19 June 2015 (Pisa, Italy).

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Official URL: http://dx.doi.org/10.1109/CoSeRa.2015.7330262

Abstract

We consider the problem of estimating a finite number of atoms of a dictionary embedded in white noise, using a sparse signal representation (SSR) approach, a problem which is relevant in many radar applications. In particular, the estimation of a radar scene consisting of targets with wide amplitude range can be challenging since the sidelobes of a strong target can disrupt the estimation of a weak one. In this paper, we present a Bayesian algorithm able to estimate weak targets possibly hidden by strong ones. The main strength of this algorithm lies in a novel sparse-promoting prior distribution which decorrelates sparsity level and target power and makes the estimation process span the whole target power range. This algorithm is implemented through a Monte-Carlo Markov chain. It is successfully evaluated on synthetic and semiexperimental radar data.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to the IEEE (Institute of Electrical and Electronics Engineers). This paper is available at : http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7312392 “© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
HAL Id:hal-01446139
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Other partners > Delft University of Technology - TU Delft (NETHERLANDS)
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Deposited By: Marie Lasserre
Deposited On:25 Jan 2017 15:15

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