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Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method
A new CS-based inverse synthetic aperture radar (ISAR) imaging framework is proposed to enhance both the image performance and the robustness at a low SNR. An ISAR echo preprocessing method for enhancing the ISAR imaging quality of compressed sensing (CS) based algorithms is developed by implementin...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308767/ https://www.ncbi.nlm.nih.gov/pubmed/30551621 http://dx.doi.org/10.3390/s18124409 |
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author | Yin, Zhiping Lu, Xinfei Chen, Weidong |
author_facet | Yin, Zhiping Lu, Xinfei Chen, Weidong |
author_sort | Yin, Zhiping |
collection | PubMed |
description | A new CS-based inverse synthetic aperture radar (ISAR) imaging framework is proposed to enhance both the image performance and the robustness at a low SNR. An ISAR echo preprocessing method for enhancing the ISAR imaging quality of compressed sensing (CS) based algorithms is developed by implementing matched filtering, echo denoising and matrix optimization sequentially. After the preprocessing, the two-dimensional (2D) SL0 algorithm is applied to reconstruct an ISAR image in the range and cross-range plane through a series of 2D matrices using the 2D CS theory, rather than converting the 2D convex optimization problem to the one-dimensional (1D) problem in the image reconstruction process. The proposed preprocessing framework is verified by simulations and experiment. Simulations and experimental results show that the ISAR image obtained by the 2D sparse recovery algorithm with our proposed method has a better performance. |
format | Online Article Text |
id | pubmed-6308767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63087672019-01-04 Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method Yin, Zhiping Lu, Xinfei Chen, Weidong Sensors (Basel) Article A new CS-based inverse synthetic aperture radar (ISAR) imaging framework is proposed to enhance both the image performance and the robustness at a low SNR. An ISAR echo preprocessing method for enhancing the ISAR imaging quality of compressed sensing (CS) based algorithms is developed by implementing matched filtering, echo denoising and matrix optimization sequentially. After the preprocessing, the two-dimensional (2D) SL0 algorithm is applied to reconstruct an ISAR image in the range and cross-range plane through a series of 2D matrices using the 2D CS theory, rather than converting the 2D convex optimization problem to the one-dimensional (1D) problem in the image reconstruction process. The proposed preprocessing framework is verified by simulations and experiment. Simulations and experimental results show that the ISAR image obtained by the 2D sparse recovery algorithm with our proposed method has a better performance. MDPI 2018-12-13 /pmc/articles/PMC6308767/ /pubmed/30551621 http://dx.doi.org/10.3390/s18124409 Text en © 2018 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 Yin, Zhiping Lu, Xinfei Chen, Weidong Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title | Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title_full | Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title_fullStr | Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title_full_unstemmed | Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title_short | Echo Preprocessing to Enhance SNR for 2D CS-Based ISAR Imaging Method |
title_sort | echo preprocessing to enhance snr for 2d cs-based isar imaging method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308767/ https://www.ncbi.nlm.nih.gov/pubmed/30551621 http://dx.doi.org/10.3390/s18124409 |
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