| 一种成像卫星区域覆盖的自适应规划方法 |
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| 引用本文： | 刘华俊,蔡波,朱庆.一种成像卫星区域覆盖的自适应规划方法[J].武汉大学学报(信息科学版),2017,42(12):1719-1724. |
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| 作者姓名： | 刘华俊 蔡波 朱庆 |
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| 作者单位： | 1.武汉大学计算机学院, 湖北 武汉, 430072 |
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| 基金项目： | 国家自然科学基金41471320国家自然科学基金41301409高等学校博士学科点专项科研基金20130141120021 |
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| 摘 要： | 卫星对侦查区域的覆盖语义是影响侦查覆盖效率的关键因素之一。针对现有覆盖算法低效耗时的技术瓶颈，提出了一种针对成像卫星区域覆盖的自适应规划方法，包括自适应的网格划分、平衡成像精度和覆盖效率的最大可视覆盖计算以及窗口优化的卫星区域覆盖策略。通过与常用经典算法对比，验证了本文方法的有效性和鲁棒性。本文方法已成功应用于某些在轨卫星的区域覆盖任务。
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| 关 键 词： | 区域覆盖 成像卫星 自适应 滑动窗口 |
| 收稿时间： | 2015-12-15 |
Self-adaptive Planning Method of Imaging Reconnaissance Satellites Area Coverage |
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| Affiliation: | 1.School of Computer, Wuhan University, Wuhan 430072, China2.Collaborative Innovation Center for Geospatial Technology, Wuhan 430079, China3.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China |
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| Abstract: | Area coverage using imaging reconnaissance satellites belongs to mission planning problems constrained by spatio-temporal information. The current area coverage algorithms can be divided into two categories:based on single-satellite and multi-satellite. The former cannot fully utilize satellite resources, and is replaced by the latter gradually. However, the latter usually applies the existing intelligent optimization approaches simply. In addition, the drawback of both is heavily depending on user's intervene. Therefore, in this paper, a self-adaptive approach is proposed for the low-effective and time-consuming issue of current covering algorithms. Firstly, a self-adaptive way for grid division is presented to automatically generate grid; secondly, in order to balance imaging accuracy and efficiency, the largest visual coverage computing is proposed to determine the angle of each satellite; thirdly, a semantic-based sliding window optimizing strategy is designed to calculate planning sequence for area coverage. Compared with the classic algorithms, this method reduces human-computer interaction, and is more effective and robust. It has already been applied in area coverage of real conditions. |
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