基于改进遗传算法的SAR多星协同复杂区域观测规划
SAR multi-satellite collaborative complex area observation planning based on improved genetic algorithm
- 2024年28卷第7期 页码：1822-1834
收稿：2023-07-11，
纸质出版：2024-07-07
DOI： 10.11834/jrs.20243258
移动端阅览
摘要
遥感卫星大范围区域观测在地图绘制、灾害救援等领域均具有重要作用。SAR遥感卫星具有不受云雾夜间环境影响的特点，研究SAR多星协同区域观测技术具有重要意义。针对当前缺乏SAR多星协同对复杂区域快速观测规划方法的问题，本文首先对大范围复杂区域覆盖率计算进行分析，提出了结合高斯投影、网格划分与几何运算的复杂区域覆盖率计算方法；然后对SAR条带成像模式进行覆盖分析，提出了结合角度限制和两维分解的候选区域分解方法；最后提出了结合贪婪算法初始化、精英保留策略和3次适应度函数的改进遗传算法用于区域覆盖率优化。本文选取4颗在轨SAR卫星和3个区域目标进行仿真实验，实验结果证明本文方法在北京市、天津市、上海市3个区域都能够实现优异的区域覆盖率优化，相比贪婪算法，本文方法在上述3个区域的覆盖率分别提升3.17%、2.94%、9.02%。该算法可为SAR多星协同区域观测系统的建立提供技术基础。
Abstract
Large-scale regional observations by remote-sensing satellites play an important role in mapping
disaster relief
and other fields. The efficiency of single-satellite observation is low
and multisatellite collaborative observation is the main means for rapidly observing large areas. To date
multisatellite collaborative observation is mostly studied on optical remote-sensing satellites
but research on the collaborative observation of SAR satellites is limited. Moreover
SAR satellites have imaging mechanisms and modes distinct from those of optical satellites
and thus the optical satellite collaborative planning method cannot be fully applied to SAR satellites. For the optimization of the performance of SAR multisatellite collaborative observation
research into SAR multisatellite collaborative regional observation technologies is crucial.
First
the coverage calculation of large-scale complex areas was analyzed
and a complex area coverage calculation method that combines Gaussian projection
grid division
and geometric operations and can realize the coverage calculation of any complex area
was proposed. Then
an accurate coverage analysis was performed on the SAR strip imaging mode
and a candidate area decomposition method combining angle restriction and two-dimensional decomposition was established. Optimization efficiency was improved by reducing the optimization space through angle restriction
and complex continuous optimization problems were discretized through two-dimensional decomposition. These approaches allowed the use of genetic algorithms for optimization. Finally
an improved genetic algorithm combining greedy algorithm initialization
elite retention strategy
and cubic fitness function was formulated for regional coverage optimization. Chromosome encoding
crossover
and mutation operations were designed for optimization
an optimal retention strategy was used to improve optimization speed and stability
and the cubic fitness function was used to improve the optimization effect.
This study selected four on-orbit SAR satellites
namely
GF-3 01
GF-3 02
GF-3 03
and HISEA-1
and three regional targets
namely
Beijing
Tianjin
and Shanghai
for simulation experiments. The simulation time was 5 days
and the orbit data included real TLE data. The SGP4 orbit propagation model was used
and the beam parameters of the SAR satellite were reasonably simulated. Experimental results show that the coverage rates of the proposed method on three regional targets in Beijing
Tianjin
and Shanghai increased by 3.17%
2.94%
and 9.02% compared with the coverage rates obtained with the greedy algorithm. In fine grids
the coverage result of the proposed method in the Shanghai area was 7.3% higher than that of the greedy algorithm.
This study analyzes the SAR multisatellite collaborative complex area coverage planning technology
constructs a feasible SAR multisatellite collaborative complex area observation planning process
and proposes a complex area coverage planning method suitable for the SAR multisatellite strip imaging mode. This algorithm can provide a technical basis for the establishment of a SAR multisatellite collaborative regional planning system. However
the proposed method simplifies constraints at the imaging signal processing level of SAR satellites
and subsequent research will conduct in-depth research on the characteristics of SAR satellite imaging signal processing.
关键词
Keywords
references
Bai B C . 2008 . Modeling and optimization algorithms for imaging satellites scheduling problem with task merging . Changsha : National University of Defense Technology
白保存 . 2008 . 考虑任务合成的成像卫星调度模型与优化算法研究 . 长沙 : 国防科学技术大学
Deng Y K , Yu W D , Zhang H , Wang W , Liu D C and Wang R . 2020 . Forthcoming spaceborne SAR development . Journal of Radars , 9 ( 1 ): 1 - 33
邓云凯 , 禹卫东 , 张衡 , 王伟 , 刘大成 , 王宇 . 2020 . 未来星载SAR技术发展趋势 . 雷达学报 , 9 ( 1 ): 1 - 33 [ DOI: 10.12000/JR20008 http://dx.doi.org/10.12000/JR20008 ]
Du Y H , Wang T , Xin B , Wang L , Chen Y G and Xing L N . 2020 . A data-driven parallel scheduling approach for multiple agile earth observation satellites . IEEE Transactions on Evolutionary Computation , 24 ( 4 ): 679 - 693 [ DOI: 10.1109/TEVC.2019.2934148 http://dx.doi.org/10.1109/TEVC.2019.2934148 ]
He R J . 2004 . Research on Imaging Reconnaissance Satellite Scheduling Problem . Changsha : National University of Defense Technology
贺仁杰 . 2004 . 成像侦察卫星调度问题研究 . 长沙 : 国防科学技术大学
Hu X X , Zhu W M , Ma H W , An B , Zhi Y L and Wu Y . 2021 . Orientational variable-length strip covering problem: a branch-and-price-based algorithm . European Journal of Operational Research , 289 ( 1 ): 254 - 269 [ DOI: 10.1016/j.ejor.2020.07.003 http://dx.doi.org/10.1016/j.ejor.2020.07.003 ]
Kim H and Chang Y K . 2015 . Mission scheduling optimization of SAR satellite constellation for minimizing system response time . Aerospace Science and Technology , 40 : 17 - 32 [ DOI: 10.1016/j.ast.2014.10.006 http://dx.doi.org/10.1016/j.ast.2014.10.006 ]
Kim H and Chang Y K . 2020 . Optimal mission scheduling for hybrid synthetic aperture radar satellite constellation based on weighting factors . Aerospace Science and Technology , 107 : 106287 [ DOI: 10.1016/j.ast.2020.106287 http://dx.doi.org/10.1016/j.ast.2020.106287 ]
Lemaı̂tre M , Verfaillie G , Jouhaud F , Lachiver J M and Bataille N . 2002 . Selecting and scheduling observations of agile satellites . Aerospace Science and Technology , 6 ( 5 ): 367 - 381 [ DOI: 10.1016/S1270-9638(02)01173-2 http://dx.doi.org/10.1016/S1270-9638(02)01173-2 ]
Li C S , Wang W J , Wang P B , Chen J , Xu H P , Yang W , Yu Z , Sun B and Li J W . 2016 . Current situation and development trends of spaceborne SAR technology . Journal of Electronics and Information Technology , 38 ( 1 ): 229 - 240
李春升 , 王伟杰 , 王鹏波 , 陈杰 , 徐华平 , 杨威 , 于泽 , 孙兵 , 李景文 . 2016 . 星载SAR技术的现状与发展趋势 . 电子与信息学报 , 38 ( 1 ): 229 - 240 [ DOI: 10.11999/JEIT151116 http://dx.doi.org/10.11999/JEIT151116 ]
Niu X N , Tang H and Wu L X . 2018 . Satellite scheduling of large areal tasks for rapid response to natural disaster using a multi-objective genetic algorithm . International Journal of Disaster Risk Reduction , 28 : 813 - 825 [ DOI: 10.1016/j.ijdrr.2018.02.013 http://dx.doi.org/10.1016/j.ijdrr.2018.02.013 ]
Ruan Q M . 2006 . Research on photo-reconnaissance satellites scheduling problem for area targets observation . Changsha : National University of Defense Technology .
阮启明 . 2006 . 面向区域目标的成像侦察卫星调度问题研究 . 长沙 : 国防科学技术大学
Ruan Q M , Tan Y J , Li J F and Chen Y W . 2006 . Research on segmenting and selecting of area targets . Science of Surveying and Mapping , 31 ( 1 ): 98 - 100
阮启明 , 谭跃进 , 李菊芳 , 陈英武 . 2006 . 对地观测卫星的区域目标分割与优选问题研究 . 测绘科学 , 31 ( 1 ): 98 - 100
Song Y J , Wei L N , Yang Q , Wu J , Xing L N and Chen Y W . 2023 . RL-GA: a reinforcement learning-based genetic algorithm for electromagnetic detection satellite scheduling problem . Swarm and Evolutionary Computation , 77 : 101236 [ DOI: 10.1016/j.swevo.2023.101236 http://dx.doi.org/10.1016/j.swevo.2023.101236 ]
Sun G C , Liu Y B , Xiang J X , Liu W K , Xing M D and Chen J L . 2022 . Spaceborne synthetic aperture radar imaging algorithms: an overview . IEEE Geoscience and Remote Sensing Magazine , 10 ( 1 ): 161 - 184 [ DOI: 10.1109/MGRS.2021.3097894 http://dx.doi.org/10.1109/MGRS.2021.3097894 ]
Wang C . 2014 . Research on the scheduling method of the formation flying InSAR mapping mission . Harbin : Harbin Institute of Technology
王聪 . 2014 . 编队干涉SAR对地测绘任务规划方法研究 . 哈尔滨 : 哈尔滨工业大学
Wei J . 2013 . The mission planning model and improved Ant Colony solving algorithm for networking SAR satellites // Proceedings of the 2013 International Conference on Management Science and Engineering 20th Annual Conference Proceedings . Harbin : IEEE: 14 - 19 [ DOI: 10.1109/ICMSE.2013.6586256 http://dx.doi.org/10.1109/ICMSE.2013.6586256 ]
Xu Y J , Liu X L , He R J and Chen Y G . 2020 . Multi-satellite scheduling framework and algorithm for very large area observation . Acta Astronautica , 167 : 93 - 107 [ DOI: 10.1016/j.actaastro.2019.10.041 http://dx.doi.org/10.1016/j.actaastro.2019.10.041 ]
Yu J , Xi J J , Yu L J and Jiang F H . 2015 . Study of one-orbit multi-stripes splicing imaging for agile satellite . Spacecraft Engineering , 24 ( 2 ): 27 - 34
余婧 , 喜进军 , 于龙江 , 蒋方华 . 2015 . 敏捷卫星同轨多条带拼幅成像模式研究 . 航天器工程 , 24 ( 2 ): 27 - 34 [ DOI: 10.3969/j.issn.1673-8748.2015.02.005 http://dx.doi.org/10.3969/j.issn.1673-8748.2015.02.005 ]
Zhan Z H , Shi L , Tan K C and Zhang J . 2022 . A survey on evolutionary computation for complex continuous optimization . Artificial Intelligence Review , 55 ( 1 ): 59 - 110 [ DOI: 10.1007/s10462-021-10042-y http://dx.doi.org/10.1007/s10462-021-10042-y ]
Zhang Y H , Zhang X , Wang S B , Wei C Q and Wu Q S . 2022 . Development status and analyses of micro SAR satellite . Spacecraft Engineering , 31 ( 5 ): 119 - 125
张永贺 , 张旭 , 王韶波 , 魏楚奇 , 吴秋诗 . 2022 . 微小型SAR卫星发展现状及分析 . 航天器工程 , 31 ( 5 ): 119 - 125 [ DOI: 10.3969/j.issn.1673-8748.2022.05.016 http://dx.doi.org/10.3969/j.issn.1673-8748.2022.05.016 ]
Zhou X Q , Peng M Y and Hu F . 2022 . Current status and prospects of land remote sensing satellite development in China . Satellite Application , ( 9 ): 14 - 19
周晓青 , 彭明媛 , 胡芬 . 2022 . 我国陆地遥感卫星发展现状与展望 . 卫星应用 , ( 9 ): 14 - 19 [ DOI: 10.3969/j.issn.1674-9030.2022.09.004 http://dx.doi.org/10.3969/j.issn.1674-9030.2022.09.004 ]
Zhu W M , Hu X X , Xia W and Sun H Q . 2019 . A three-phase solution method for the scheduling problem of using earth observation satellites to observe polygon requests . Computers and Industrial Engineering , 130 : 97 - 107 [ DOI: 10.1016/j.cie.2019.02.014 http://dx.doi.org/10.1016/j.cie.2019.02.014 ]
文章被引用时，请邮件提醒。
提交
相关作者
张金松 西安电子科技大学前沿交叉研究院
刘会涛 西安电子科技大学前沿交叉研究院
王虹现 西安电子科技大学雷达信号处理全国重点实验室
王士俊 山东科技大学 测绘与空间信息学院
刘苗 山东科技大学 测绘与空间信息学院
赵钰 北京市农林科学院信息技术研究中心 农业农村部农业遥感机理与定量遥感重点实验室
柳昭宇 中南大学 智能信息处理及系统研究所
刘修宇 山东科技大学 测绘与空间信息学院
相关机构
山东科技大学 测绘与空间信息学院
北京市农林科学院信息技术研究中心 农业农村部农业遥感机理与定量遥感重点实验室
中南大学 智能信息处理及系统研究所
山东省农业科学院 农业信息与经济研究所
西南交通大学 地球科学与工程学院
选择翻译语言
- 地址：北京市海淀区北四环西路19号 《遥感学报》编辑部 邮编：100190
- 联系电话：010-58887052 Email：nrsb@aircas.ac.cn
- 技术支持由北京北大方正电子有限公司提供 京ICP备20021838号-9
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies
0
批量引用
导出至
BibTeXEndnoteRefManNoteExpressNoteFirst
回到顶部