空间碎片多次观测的多卫星调度方法

doi:10.12305/j.issn.1001-506X.2025.11.17

摘要/Abstract

摘要：

针对多个卫星对多个空间目标在一定时间区间内的多次观测规划问题，提出一种多种群遗传邻域搜索算法（multi-population genetic neighborhood search algorithm，MPGNSA）。首先，考虑卫星观测能力与空间目标观测需求，以目标的观测频次与观测时间在观测周期内收益最大化为设计方向。其次，分析卫星任务规划的约束条件，建立卫星对于空间目标观测任务规划模型。此外，在整体上采用多种群并行进化的方式，在各种群的进化过程中，建立编码方式与启发式规则，保证基因的高适应度，并引入邻域搜索的思想，提升算法收敛速度。最后，仿真结果表明，MPGNSA在任务规划中能够获得较其他对比算法更高的最终适应度；在相同的计算时间限制下，MPGNSA的适应度高于其他对比算法。MPGNSA在提高任务收益和优化调度效率方面具有明显优势，在有限的计算时间内能够提供更高效的解决方案。

关键词: 卫星任务规划, 多星协同, 多种群进化, 遗传算法, 邻域搜索

Abstract:

Aiming at the problem of scheduling repeated observations of multiple space targets by multiple satellites within a given time period, a multi-population genetic neighborhood search algorithm (MPGNSA) is proposed. Firstly, taking into account the observation capabilities of satellites and the observation requirements of targets, the design direction is to maximize the benefits of the observation frequency and time of the target in the observation cycle. Then, the constraints of satellite task scheduling and develop a planning model for satellite-based observation of space targets are analyzed. In addition, a parallel evolutionary approach across multi-population is adopted, an encoding scheme and heuristic rules are employed during the evolution process to ensure high-fitness individuals, while a neighborhood search mechanism is introduced to enhance convergence speed. Finally, simulation results show that MPGNSA achieves higher final fitness compared to other algorithms. Under the same computational time constraints, MPGNSA also yields higher task benefits than other algorithms. It can be concluded that MPGNSA has significant advantages in improving task fitness and optimizing scheduling efficiency, offering more efficient solutions within limited computational time.

Key words: satellite mission planning, multi-satellite collaboration, multi-population evolution, genetic algorithm, neighborhood search

中图分类号:

V 11

王大力, 董磊, 李华旺, 郑珍珍, 胡海鹰. 空间碎片多次观测的多卫星调度方法[J]. 系统工程与电子技术, 2025, 47(11): 3685-3698.

Dali WANG, Lei DONG, Huawang LI, Zhenzhen ZHENG, Haiying HU. Multi-satellite task scheduling method for repeated observation of space debris[J]. Systems Engineering and Electronics, 2025, 47(11): 3685-3698.

图/表 28

表1

符号定义"

符号	定义
$ S $	卫星集合, $ S=\mathrm{ }\{{S}_{1},{S}_{2},{S}_{3}, \cdots , {S}_{{\mathrm{ns}}}\} $，$ {S}_{i} $ 表示第$ i $颗卫星
$ T $	目标集合, $ T=\left\{{T}_{1},{T}_{2},{T}_{3} ,\cdots , {T}_{{\mathrm{nt}}}\right\} $, $ {T}_{j} $代表第$ j $个目标
$ {S}_{{\mathrm{prop}}},{T}_{{\mathrm{prop}}} $	卫星、目标的轨道数据
$ {\mathrm{ns }}$, $ {\mathrm{nt}} $	卫星、目标的数量
$ r $	$ r=\left\{{r}_{1},{r}_{2} ,\cdots, {r}_{{\mathrm{nt}}}\right\} $，$ {r}_{i} $ 为第$ i $个目标所需求的观测次数
$ {\mathrm{tr }}$	$ {\mathrm{tr}}=\left\{{{\mathrm{tr}}}_{1},{{\mathrm{tr}}}_{2} ,\cdots, {{\mathrm{tr}}}_{{\mathrm{nt}}}\right\} $，$ {\mathrm{t}}{{\mathrm{r}}}_{j} $为第$ j $个目标所需每次观测时长
$ {T}_{\mathrm{s}\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{c}\mathrm{h}} $	卫星进行任务切换所需要的时间
${\mathrm{ DT }}$	整体规划区间，$ {{\mathrm{DT}}}_{{\mathrm{s}}},{{\mathrm{DT}}}_{{\mathrm{e}}} $为开始与结束时刻
${\mathrm{ TCWST}} $	$ {{\mathrm{TCWS}}}{{\mathrm{T}}}_{ij} $表示卫星$ {S}_{i} $对卫星$ {T}_{j} $的所有可观测时间窗口
${\mathrm{ TAW }}$	每个目标的实际观测时间，$ {{\mathrm{TAW}}}_{jk} $为目标$ {T}_{j} $在区间$ {\mathrm{DT}} $内的第$ k $次实际观测时间； $ {{\mathrm{TAWST}}}_{jk} $为其观测开始时间，$ {{\mathrm{TAWET}}}_{jk} $为其观测结束时间
$ {\mathrm{SAW}} $	$ \mathrm{每}\mathrm{颗}\mathrm{卫}\mathrm{星}\mathrm{实}\mathrm{际}\mathrm{观}\mathrm{测}\mathrm{时}\mathrm{间}\mathrm{序}\mathrm{列}，{{\mathrm{SAW}}}_{ij} $为卫星$ {S}_{i} $在区间${\mathrm{ DT }}$内的第$ j $次任务的观测窗口； $ {{\mathrm{SAWST}}}_{ij} $为其观测开始时间，$ {{\mathrm{SAWET}}}_{ij} $为其观测结束时间
$ {\mathrm{Satload }}$	卫星负载，$ {{\mathrm{Satload}}}_{i} $为卫星$ i $最终工作总时长，含任务执行时长与任务切换时长
$ {X}_{ijk} $	$ {X}_{ijk}为 $布尔变量，记录卫星$ i $在对目标$ j $的第$ k $个观测窗口是否进行了观测（1代表观测，0代表未观测）

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卫星编号	a/km	e	i/（°）	ω/（°）	Ω/（°）	M/（°）
Sat1	7378.14	0	99.5	0	10.9	0
Sat2	7378.14	0	99.5	0	10.9	60
Sat3	7378.14	0	99.5	0	10.9	120
Sat4	7378.14	0	99.5	0	10.9	180
Sat5	7378.14	0	99.5	0	10.9	240
Sat6	7378.14	0	99.5	0	10.9	300

编号	a/km	e	i/（°）	ω/（°）	Ω/（°）	M/（°）
Tar1	6899.7	0	143.4	57.09	62.9	6.4
Tar2	7059.02	0	98.13	100.47	90	311.22
Tar3	7484.39	0.04	63.42	358.84	98.61	34.45
Tar4	7097.69	0.01	57.01	130.38	57.49	340.77
Tar5	6736.88	0.01	96.88	191.12	14.87	14.34
						

目标编号	观测次数/次	每次观测时间/s
1	10	240
2	8	300
3	6	480
4	8	480
5	7	300
6	7	300
7	6	420
8	10	420
9	6	420
10	8	420
		

卫星编号	任务数量/个	任务总时长/h	负载率/%
Sat1	82	7.825	65.21
Sat2	89	7.875	65.63
Sat3	89	7.85	65.42
Sat4	87	7.85	65.42
Sat5	83	7.808	65.07
Sat6	88	7.867	65.56
合计	516	—	—

目标编号	观测次数/次	观测时长/s	观测方案
目标编号	观测次数/次	观测时长/s	卫星	开始时刻	结束时刻
目标1	10	240	1	0:39:09	0:43:09
			3	2:06:29	2:10:29
			2	3:06:42	3:10:42
			2	4:41:54	4:45:54
			3	5:21:45	5:25:45
			4	6:51:45	6:55:45
			4	7:51:33	7:55:33
			5	9:26:08	9:30:08
			5	10:02:45	10:06:45
			5	11:43:35	11:47:35
目标2	8	300	1	0:33:39	0:38:39
			2	2:10:28	2:15:28
			1	3:49:47	3:54:47
			2	5:27:28	5:32:28
			2	7:05:46	7:10:46
			3	8:36:12	8:41:12
			4	10:18:57	10:23:57
			4	11:20:02	11:25:02
目标3	6	480	3	0:00:01	0:08:01
			4	1:39:11	1:47:11
			3	3:24:31	3:32:31
			1	5:28:44	5:36:44
			6	8:17:12	8:25:12
			5	10:10:59	10:18:59
目标4	8	480	2	0:03:31	0:11:31
			1	1:56:10	2:04:10
			2	3:35:47	3:43:47
			4	5:06:20	5:14:20
			5	6:38:32	6:46:32
			1	7:15:13	7:23:13
			1	9:01:22	9:09:22
			2	1038:44	10:46:44
目标5	7	300	2	1:34:43	1:39:43
			3	3:18:34	3:23:34
			2	5:01:35	5:06:35
			3	6:32:45	6:37:45
			3	8:14:56	8:19:56
			4	9:51:12	9:56:12
			4	11:38:08	11:43:08