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

Abstract

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.

Real-Time Optimal Negotiation Mode Selection Based on Three-Way Decision for Decentralized Remote Sensing Satellite Cluster

“…where X is the mission selection matrix, and x k,i,j is one element in the X. P i,j is the mission profit defined in [21]. The optical visibility constraint C o i ðtÞ and the geometric visibility constraint C g i ðtÞ are calculated the same as [21]. The time constraint C T i ðtÞ is described as…”

A Multiple Agile Satellite Staring Observation Mission Planning Method for Dense Regions

“…Liu [27] introduced a Q-network-based network scheme to address the single-satellite scheduling problem, using a profit-based competition strategy to enhance the multi-satellite mission planning system efficiency. Deng [28] suggested a neural network-based multi-grain negotiation method under a decentralized structure with a low cost-benefit ratio for mission assignment and planning of microsatellite clusters. Song [29,30] combined reinforcement learning-assisted genetic algorithms to efficiently solve the satellite scheduling problem.…”

A New Method for Remote Sensing Satellite Observation Effectiveness Evaluation

“…Remote sensing satellites distributed in different orbital positions usually use attitude maneuvers to provide high-frequency and high-resolution observation services, including point target, area target, and moving target observation tasks. However, owing to the complexity of satellites' composition and structure, as well as the varying task environments, the full utilization of valuable satellite resources is challenging [6]. Hence, it is necessary to comprehensively evaluate the observation effectiveness of remote sensing satellites, so as to ensure the optimality of the decision-making process such as tasks allocation and attitude maneuver [7,8].…”