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Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially observable...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026490/ https://www.ncbi.nlm.nih.gov/pubmed/35458985 http://dx.doi.org/10.3390/s22083001 |
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author | Zhang, Zhen Wu, Jianfeng Zhao, Yan Luo, Ruining |
author_facet | Zhang, Zhen Wu, Jianfeng Zhao, Yan Luo, Ruining |
author_sort | Zhang, Zhen |
collection | PubMed |
description | In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially observable Markov decision process is proposed. By studying the partially observable Markov decision process and the posterior Cramer–Rao lower bound, a multi-sensor cooperative scheduling model and optimization objective function were established. The improvement of the particle filter algorithm by the beetle swarm optimization algorithm was studied to improve the tracking accuracy of the particle filter. Finally, the improved elephant herding optimization algorithm was used as the solution algorithm of the scheduling scheme, which further improved the algorithm performance of the solution model. The simulation results showed that the model could solve the distributed multi-sensor cooperative scheduling problem well, had higher solution performance than other algorithms, and met the real-time requirements. |
format | Online Article Text |
id | pubmed-9026490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90264902022-04-23 Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process Zhang, Zhen Wu, Jianfeng Zhao, Yan Luo, Ruining Sensors (Basel) Article In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially observable Markov decision process is proposed. By studying the partially observable Markov decision process and the posterior Cramer–Rao lower bound, a multi-sensor cooperative scheduling model and optimization objective function were established. The improvement of the particle filter algorithm by the beetle swarm optimization algorithm was studied to improve the tracking accuracy of the particle filter. Finally, the improved elephant herding optimization algorithm was used as the solution algorithm of the scheduling scheme, which further improved the algorithm performance of the solution model. The simulation results showed that the model could solve the distributed multi-sensor cooperative scheduling problem well, had higher solution performance than other algorithms, and met the real-time requirements. MDPI 2022-04-14 /pmc/articles/PMC9026490/ /pubmed/35458985 http://dx.doi.org/10.3390/s22083001 Text en © 2022 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 Zhang, Zhen Wu, Jianfeng Zhao, Yan Luo, Ruining Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title | Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title_full | Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title_fullStr | Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title_full_unstemmed | Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title_short | Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process |
title_sort | research on distributed multi-sensor cooperative scheduling model based on partially observable markov decision process |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026490/ https://www.ncbi.nlm.nih.gov/pubmed/35458985 http://dx.doi.org/10.3390/s22083001 |
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