多星协同观测遗传-演进双层任务规划算法

doi:10.12305/j.issn.1001-506X.2024.06.22

Abstract

Abstract:

Multi-satellite cooperative mission planning method is a key node in the space-based satellite system architecture. Firstly, the multi-satellite cooperative for Earth observation mission is analyzed and a multi-satellite cooperative mission planning model is established, including satellite orbit parameters, constraint conditions, and target points to be observed. Then, a genetic-evolutionary bi-level solution architecture is designed, which decomposes the multi-satellite mission planning problem into a top multi-satellite mission assignment problem and a bottom single-satellite mission scheduling problem. The upper level uses the guided multi-population genetic algorithm (MPGA) to integrate the heuristic results into the task allocation algorithm, and the lower level uses the improved genetic algorithm to solve the single-satellite task scheduling problem. Finally, aiming at the applicability problem, two groups of objectives are set randomly and uniformly distributed, and experiments are designed with different numbers of satellites to prove the effectiveness of the genetic-evolutionary bi-level solution framework.

Key words: satellite task planning, genetic-evolutionary architecture, multi-population genetic algorithm (MPGA), parallel algorithm

CLC Number:

Yangyang LI, Junren LUO, Wanpeng ZHANG, Fengtao XIANG. Genetic-evolutionary bi-level mission planning algorithm for multi-satellite cooperative observation[J]. Systems Engineering and Electronics, 2024, 46(6): 2044-2053.

Figures/Tables 19

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任务内存消耗/MB	下传电量消耗/(J/s)	传输速率/(MB/s)	充电速率/W	卫星存储容量/GB	卫星电池容量/J
[32, 64]	5	1	5	16	20 000

卫星编号	半长轴/m	离心率	轨道倾角/(°)	近地点辐角/(°)	升交点赤经/(°)	真近点角/(°)
Sat1	7 171.393	0	96.576	0	175.72	0.075
Sat2	7 171.393	0	96.576	0	145.72	30.075
Sat3	7 171.393	0	96.576	0	115.72	60.075
Sat4	7 171.393	0	96.576	0	85.72	90.075
Sat5	7 171.393	0	96.576	0	55.72	120.075
Sat6	7 171.393	0	96.576	0	25.72	150.075
Sat7	7 193.589	0	98.726	77.105	107.085	184.637
Sat8	6 891.852	0	97.325	237.611	333.934	112.26
Sat9	6 836.068	0	97.326	81.466	76.8	136.42
Sat10	7 046.723	0	98.138	80.162	178.688	244.539

参数设置	任务类型
参数设置	多星任务分配	单星任务调度
种群个体数量	10个种群, 100个体	10
交叉概率	0.7	0.4
变异概率	0.3	0.4
遗传代数	最优值持续10代时终止循环	最优值迭代5代终止循环或指定代数
选择方法	轮盘赌	轮盘赌

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Genetic-evolutionary bi-level mission planning algorithm for multi-satellite cooperative observation

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