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Space–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning / Qisong Wu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 2 (February 2016) . - pp 944 - 957 Titre : Space–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning Type de document : Article/Communication Auteurs : Qisong Wu, Auteur ; Yimin D. Zhang, Auteur ; Moeness G. Amin, Auteur ; Brahim Himed, Auteur Année de publication : 2016 Article en page(s) : pp 944 - 957 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage dirigé [Termes IGN] capteur passif [Termes IGN] estimation bayesienne [Termes IGN] estimation des paramètres [Termes IGN] filtre adaptatif [Termes IGN] image radar [Termes IGN] matrice de covariance Mots-clés libres : sparse Bayesian learning Résumé : (Auteur) Conventional space-time adaptive processing suffers from the requirement of a large number of secondary samples. In this paper, a novel method is proposed to accurately estimate the clutter covariance matrix based on a small number of secondary samples, by exploiting the common clutter support across nearby range cells in the angle-Doppler domain. By taking advantage of the intrinsic sparsity of the clutter in the angle-Doppler domain, the recently developed sparse Bayesian learning technique is employed for high-resolution clutter profile estimation. The proposed method does not require the independent and identically distributed secondary sample assumption, and the required number of secondary data samples can be significantly reduced. In addition, we propose a sparse reconstruction-based approach to acquire the 2-D motion parameters of moving targets, by exploiting their group sparsity in the velocity domain in the multistatic passive radar systems. Simulation results verify the effectiveness of the proposed algorithm. Numéro de notice : A2016-118 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2470518 En ligne : https://doi.org/10.1109/TGRS.2015.2470518 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79998 [article]

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