基于指针网络架构的多星协同成像任务规划方法

doi:10.12305/j.issn.1001-506X.2025.07.18

Abstract

Abstract:

With the increase in the number of satellite resources, user imaging demands are also rapidly expanding. There is an urgent need to strengthen research on multi-satellite coordinated imaging task planning to enhance satellite service capabilities. This paper conducts research on multi-satellite coordinated imaging task planning based on deep reinforcement learning. Firstly, a mathematical model for multi-satellite cooperative imaging task planning is established, taking into account task requirements, satellite capabilities, and spatiotemporal constraints. Then, a satellite task planning algorithm based on pointer network is designed. This algorithm employs the pointer network mechanism to optimize the selection of input sequences and utilizes a Mask vector to represent various constraint conditions. Finally, simulation results show that the algorithm achieves an average task benefit improvement of at least 1.71% compared to traditional heuristic algorithms and pointer network model. The average task benefit difference for algorithms trained on instances of different task scales is no more than 0.28%, demonstrating the effectiveness and applicability of the algorithm.

Key words: multi-satellite cooperative imaging, task planning, deep reinforcement learning, pointer network

CLC Number:

Yundou ZHU, Haiquan SUN, Xiaoxuan HU. Multi-satellite cooperative imaging task planning method based on pointer network architecture[J]. Systems Engineering and Electronics, 2025, 47(7): 2246-2255.

Figures/Tables 11

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Table 1

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References 31

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实例	经度范围/(°)	纬度范围/(°)	任务收益范围	卫星数量	卫星转换时间/s	观测时长范围/s	存储占用率/%	地面站数量	下传时长范围/s
G1~G6	[-50, 130]	[-20, 60]	[1, 100]	4	15	[15, 25]	1	4	[100, 130]

实例	CPLEX		SM_G3			GA			SA算法			TS算法			PN
实例	平均任务收益	平均计算时间/s	平均任务收益	GAP/%	平均计算时间/s	平均任务收益	GAP/%	平均计算时间/s	平均任务收益	GAP/%	平均计算时间/s	平均任务收益	GAP/%	平均计算时间/s	平均任务收益	GAP/%	平均计算时间/s
G1	5 602	81	5 506	1.72	4	5 493	1.95	42	5 492	1.97	45	5 488	2.04	39	5 497	1.87	4
G2	6 408	128	6 282	1.96	6	6 216	2.99	61	6 201	3.22	56	6 166	3.77	46	6 244	2.56	5
G3	7 054	207	6 896	2.24	6	6 804	3.55	78	6 801	3.58	79	6 757	4.21	54	6 826	3.23	5
G4	-	-	7 409	-	8	7 237	-	89	7 259	-	84	7 191	-	71	7 259	-	7
G5	-	-	7 901	-	10	7 661	-	108	7 696	-	97	7 613	-	83	7 636	-	7
G6	-	-	8 151	-	11	7 905	-	137	7 920	-	112	7 851	-	104	7 897	-	8

实例	SM_G1	SM_G2	SM_G3	SM_G4	SM_G5	SM_G6	平均任务收益差/%
G1	5 502	5 497	5 503	5 500	5 502	5 500	0.10
G2	6 292	6 300	6 303	6 293	6 296	6 295	0.17
G3	6 904	6 916	6 910	6 906	6 904	6 907	0.17
G4	7 388	7 389	7 398	7 384	7 380	7 390	0.24
G5	7 882	7 891	7 893	7 886	7 889	7 891	0.14
G6	8 124	8 139	8 147	8 136	8 135	8 144	0.28

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Multi-satellite cooperative imaging task planning method based on pointer network architecture

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