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A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area

This paper presents a scheduling problem of using multiple synthetic aperture radar (SAR) satellites to observe a large irregular area (SMA). SMA is usually considered as a kind of nonlinear combinatorial optimized problem and its solution space strongly coupled with geometry grows exponentially wit...

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Autores principales: Zheng, Qicun, Yue, Haixia, Liu, Dacheng, Jia, Xiaoxue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055946/
https://www.ncbi.nlm.nih.gov/pubmed/36992063
http://dx.doi.org/10.3390/s23063353
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author Zheng, Qicun
Yue, Haixia
Liu, Dacheng
Jia, Xiaoxue
author_facet Zheng, Qicun
Yue, Haixia
Liu, Dacheng
Jia, Xiaoxue
author_sort Zheng, Qicun
collection PubMed
description This paper presents a scheduling problem of using multiple synthetic aperture radar (SAR) satellites to observe a large irregular area (SMA). SMA is usually considered as a kind of nonlinear combinatorial optimized problem and its solution space strongly coupled with geometry grows exponentially with the increasing magnitude of SMA. It is assumed that each solution of SMA yields a profit associated with the acquired portion of the target area, and the objective of this paper is to find the optimal solution yielding the maximal profit. The SMA is solved by means of a new method composed of three successive phases, namely, grid space construction, candidate strip generation and strip selection. First, the grid space construction is proposed to discretize the irregular area into a set of points in a specific plane rectangular coordinate system and calculate the total profit of a solution of SMA. Then, the candidate strip generation is designed to produce numerous candidate strips based on the grid space of the first phase. At last, in the strip selection, the optimal schedule for all the SAR satellites is developed based on the result of the candidate strip generation. In addition, this paper proposes a normalized grid space construction algorithm, a candidate strip generation algorithm and a tabu search algorithm with variable neighborhoods for the three successive phases, respectively. To verify the effectiveness of the proposed method in this paper, we perform simulation experiments on several scenarios and compare our method with the other seven methods. Compared to the best of the other seven methods, our proposed method can improve profit by 6.38% using the same resources.
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spelling pubmed-100559462023-03-30 A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area Zheng, Qicun Yue, Haixia Liu, Dacheng Jia, Xiaoxue Sensors (Basel) Article This paper presents a scheduling problem of using multiple synthetic aperture radar (SAR) satellites to observe a large irregular area (SMA). SMA is usually considered as a kind of nonlinear combinatorial optimized problem and its solution space strongly coupled with geometry grows exponentially with the increasing magnitude of SMA. It is assumed that each solution of SMA yields a profit associated with the acquired portion of the target area, and the objective of this paper is to find the optimal solution yielding the maximal profit. The SMA is solved by means of a new method composed of three successive phases, namely, grid space construction, candidate strip generation and strip selection. First, the grid space construction is proposed to discretize the irregular area into a set of points in a specific plane rectangular coordinate system and calculate the total profit of a solution of SMA. Then, the candidate strip generation is designed to produce numerous candidate strips based on the grid space of the first phase. At last, in the strip selection, the optimal schedule for all the SAR satellites is developed based on the result of the candidate strip generation. In addition, this paper proposes a normalized grid space construction algorithm, a candidate strip generation algorithm and a tabu search algorithm with variable neighborhoods for the three successive phases, respectively. To verify the effectiveness of the proposed method in this paper, we perform simulation experiments on several scenarios and compare our method with the other seven methods. Compared to the best of the other seven methods, our proposed method can improve profit by 6.38% using the same resources. MDPI 2023-03-22 /pmc/articles/PMC10055946/ /pubmed/36992063 http://dx.doi.org/10.3390/s23063353 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zheng, Qicun
Yue, Haixia
Liu, Dacheng
Jia, Xiaoxue
A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title_full A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title_fullStr A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title_full_unstemmed A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title_short A Scheduling Method of Using Multiple SAR Satellites to Observe a Large Area
title_sort scheduling method of using multiple sar satellites to observe a large area
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055946/
https://www.ncbi.nlm.nih.gov/pubmed/36992063
http://dx.doi.org/10.3390/s23063353
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