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A Variational Bayes Sparse Recovery of Migrating Targets in AR Noise

Branco, Rodolfo Augusto Serra Sammarco and Bidon, Stéphanie A Variational Bayes Sparse Recovery of Migrating Targets in AR Noise. (2018) In: 2018 IEEE Radar Conference (RadarConf18), 23 April 2018 - 27 April 2018 (Oklahoma City, United States).

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Official URL: https://doi.org/10.1109/RADAR.2018.8378564

Abstract

In this paper, we consider the problem of unambiguously estimating migrating targets even that located in blind speeds. We especially focus our attention on developing an algorithm with a low complexity for intensive use on experimental data in presence of diffuse clutter. Accordingly, we describe a variational Bayes sparse recovery based on a previously described hierarchical model (assuming migrating targets amid AR noise). The technique does alleviate ambiguities on real data collected by a wideband radar in a very reasonable amount of time.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to the IEEE (Institute of Electrical and Electronics Engineers). This paper is available at : https://ieeexplore.ieee.org/document/8378564 “© 2018 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.
Audience (conference):International conference proceedings
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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: Stéphanie Bidon
Deposited On:09 Apr 2019 10:55

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