Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster

Satellite remote sensing is developing towards the micro-satellite cluster, which brings new challenges to mission assignment and planning for the cluster. A multi-agent system (MAS) is used, but the time delay caused by communication and computation is rarely considered. To solve the problem, a neu...

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Main Authors: Xuelei Deng, Yunfeng Dong, Shucong Xie
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/21/3595
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author Xuelei Deng
Yunfeng Dong
Shucong Xie
author_facet Xuelei Deng
Yunfeng Dong
Shucong Xie
author_sort Xuelei Deng
collection DOAJ
description Satellite remote sensing is developing towards the micro-satellite cluster, which brings new challenges to mission assignment and planning for the cluster. A multi-agent system (MAS) is used, but the time delay caused by communication and computation is rarely considered. To solve the problem, a neural-network-based multi-granularity negotiation method under decentralized architecture is proposed. Firstly, we divided negotiation into three levels of granularity, and they work in different modes. Secondly, a neural network was trained to help the satellite select the best level in real-time. Through experiments, we compared the satellites working in three different levels of granularity, in which a multi-granularity decision was used. As a result of our experiments, a lower cost-effectiveness ratio was obtained, which proved that the multi-granularity negotiation method proposed in this paper is practical.
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spelling doaj.art-7189cae8b0044a9fa37b36ec866629212023-11-20T19:30:49ZengMDPI AGRemote Sensing2072-42922020-11-011221359510.3390/rs12213595Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite ClusterXuelei Deng0Yunfeng Dong1Shucong Xie2School of Astronautics, Beihang University, Beijing 100191, ChinaSchool of Astronautics, Beihang University, Beijing 100191, ChinaSchool of Astronautics, Beihang University, Beijing 100191, ChinaSatellite remote sensing is developing towards the micro-satellite cluster, which brings new challenges to mission assignment and planning for the cluster. A multi-agent system (MAS) is used, but the time delay caused by communication and computation is rarely considered. To solve the problem, a neural-network-based multi-granularity negotiation method under decentralized architecture is proposed. Firstly, we divided negotiation into three levels of granularity, and they work in different modes. Secondly, a neural network was trained to help the satellite select the best level in real-time. Through experiments, we compared the satellites working in three different levels of granularity, in which a multi-granularity decision was used. As a result of our experiments, a lower cost-effectiveness ratio was obtained, which proved that the multi-granularity negotiation method proposed in this paper is practical.https://www.mdpi.com/2072-4292/12/21/3595satellite clustermission assignment and planningdecentralizedmulti-granularity negotiation
spellingShingle Xuelei Deng
Yunfeng Dong
Shucong Xie
Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
Remote Sensing
satellite cluster
mission assignment and planning
decentralized
multi-granularity negotiation
title Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
title_full Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
title_fullStr Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
title_full_unstemmed Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
title_short Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster
title_sort multi granularity mission negotiation for a decentralized remote sensing satellite cluster
topic satellite cluster
mission assignment and planning
decentralized
multi-granularity negotiation
url https://www.mdpi.com/2072-4292/12/21/3595
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