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Multi-satellite mission allocation and scheduling method for large-scale problem
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AI
DOI：10.1016/j.asr.2025.05.067.png)
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Abstract
En 中文
The application of multiple agile earth observation satellites (multi-AEOSs) in handling large-scale observation missions has garnered widespread attention. This paper presents the potential game-based allocation method (PGAM) for the large-scale problem of multi-AEOSs constellation. First, the mission planning process is divided into two phases, including mission allocation for the whole constellation and mission scheduling for individual EOSs. A heuristic collaborative mechanism is designed to balance the maximization of observation targets and minimization of waiting time, based on AEOS entry sequence into the area of interest (AoI). The multi-AEOS mission allocation problem is then transformed into a generalized ordinal potential game (GOPG). Consequently, the Nash equilibrium (NE) is rigorously proved to be obtainable. Finally, the local strategy search algorithm (LSSA) is introduced for scheduling individual AEOSs in order to rapidly converging to the NE, in which two strategies combining global and local search are developed. The simulation results demonstrate that the PGAM-LSSA outperforms the competing algorithms in various instances.
Keywords:
multi-AEOSs
mission allocation
potential game
Nash equilibrium
local strategy search algorithm
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