Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging

This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achiev...

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Detalles Bibliográficos
Autores principales: Zhang, Shuanghui, Liu, Yongxiang, Li, Xiang, Bi, Guoan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883302/
https://www.ncbi.nlm.nih.gov/pubmed/27136551
http://dx.doi.org/10.3390/s16050611
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author Zhang, Shuanghui
Liu, Yongxiang
Li, Xiang
Bi, Guoan
author_facet Zhang, Shuanghui
Liu, Yongxiang
Li, Xiang
Bi, Guoan
author_sort Zhang, Shuanghui
collection PubMed
description This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.
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spelling pubmed-48833022016-05-27 Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging Zhang, Shuanghui Liu, Yongxiang Li, Xiang Bi, Guoan Sensors (Basel) Article This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression. MDPI 2016-04-28 /pmc/articles/PMC4883302/ /pubmed/27136551 http://dx.doi.org/10.3390/s16050611 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Shuanghui
Liu, Yongxiang
Li, Xiang
Bi, Guoan
Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title_full Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title_fullStr Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title_full_unstemmed Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title_short Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging
title_sort logarithmic laplacian prior based bayesian inverse synthetic aperture radar imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883302/
https://www.ncbi.nlm.nih.gov/pubmed/27136551
http://dx.doi.org/10.3390/s16050611
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