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基于区域目标网格化的多星协同观测方法*

郑起存1,2, 岳海霞1†, 刘大成1,2, 李华1,2, 任明山1,2, 贾小雪1   

  1. 1 中国科学院空天信息创新研究院, 北京 100190;
    2 中国科学院大学电子电气与通信工程学院, 北京 100049
  • 收稿日期:2022-11-07 修回日期:2023-03-06 发布日期:2023-03-21
  • 通讯作者: E-mail: hnyhx@mail.ie.ac.cn
  • 基金资助:
    *青年科学基金(61901446)资助

Multi-satellite cooperative observation method based on area target gridding

ZHENG Qicun1,2, YUE Haixia1, LIU Dacheng1,2, LI Hua1,2, REN Mingshan1,2, JIA Xiaoxue1   

  1. 1 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China;
    2 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-11-07 Revised:2023-03-06 Published:2023-03-21

摘要: 通过分析多颗SAR卫星对某一大面积区域目标进行协同观测的约束条件,以给定任务周期内观测收益最大为目标函数建立约束满足模型。为改善传统的禁忌搜索算法应用于多星协同观测问题时,易收敛于局部最优解的缺点,提出了一种改进的变邻域禁忌搜索算法求解此问题。在算法实现的过程中,将区域目标网格化从而动态生成观测模式,并以此计算观测模式对应的观测率。相对于传统的禁忌搜索算法,本文提出的变邻域禁忌搜索算法可以在同等资源下将观测收益提高8%以上。

关键词: SAR, 多星协同, 区域目标, 变邻域禁忌搜索算法

Abstract: By analyzing the constraints of using multiple SAR satellites to observe a specific large area target, the constraint satisfaction model is established with the objective function of maximizing the observation profit within a given mission time horizon. To improve the global search ability of the traditional tabu search algorithm, an improved tabu search algorithm with variable neighbourhood is proposed. In the implementation of the tabu search algorithm with variable neighbourhood, the area target is gridded to dynamically generate observation patterns, and the observation rates corresponding to the observation patterns are calculated. Compared to the traditional tabu search algorithm, the variable neighbourhood tabu search algorithm proposed in this paper could increase the observation profit by more than 8% with the same computational burden.

Key words: SAR, multi-satellite cooperation, area target, variable neighbourhood tabu search algorithm

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