一种成像卫星区域覆盖的自适应规划方法

刘华俊; 蔡波; 朱庆

doi:10.13203/j.whugis20150120

一种成像卫星区域覆盖的自适应规划方法

刘华俊^{1, 2,},
蔡波^1, ,,
朱庆^{2, 3}

1.
武汉大学计算机学院, 湖北武汉, 430072
2.
地球空间信息技术协同创新中心, 湖北武汉, 430079
3.
西南交通大学地球科学与环境工程学院, 四川成都, 611756

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

详细信息

作者简介:
刘华俊, 博士, 副教授, 主要从事虚拟地理环境的理论与方法研究。huajunliu@whu.edu.cn

通讯作者:
蔡波, 博士, 副教授。bo_cai@yeah.net

中图分类号: P236
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出版历程
- 收稿日期: 2015-12-14
- 发布日期: 2017-12-04

Self-adaptive Planning Method of Imaging Reconnaissance Satellites Area Coverage

LIU Huajun^{1, 2,},
CAI Bo^1, ,,
ZHU Qing^{2, 3}

1.
School of Computer, Wuhan University, Wuhan 430072, China
2.
Collaborative Innovation Center for Geospatial Technology, Wuhan 430079, China
3.
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China

Funds:

The National Natural Science Foundation of China 41471320

The National Natural Science Foundation of China 41301409

the Research Fund for the Doctoral Program of Higher Education of China 20130141120021

More Information

Author Bio:
LIU Huajun, PhD, associate professor, specializes in virtual geographic environments. E-mail: huajunliu@whu.edu.cn

Corresponding author:
CAI Bo, PhD, associate professor. E-mail: bo_cai@yeah.net

摘要

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。
- 区域覆盖 /
- 成像卫星 /
- 自适应 /
- 滑动窗口
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.
- area coverage /
- imaging reconnaissance satellite /
- self-adaptive /
- sliding window

HTML全文

图 1 成像卫星区域覆盖规划算法流程图

Figure 1. Flowchart of Planning Algorithm of Imaging Reconnaissance Satellites Area Coverage

下载: 全尺寸图片幻灯片

图 2 区域覆盖实例

Figure 2. An Example of Area Coverage

下载: 全尺寸图片幻灯片

图 3 滑动窗口

Figure 3. Sliding Window

下载: 全尺寸图片幻灯片

图 4 算法结果对比

Figure 4. Comparison Result of Different Algorithms

下载: 全尺寸图片幻灯片

表 1 网格划分方法的平均覆盖率和完成时间

Table 1 Average Coverage and Complete Time for Different Mesh Division Approaches

区域	等经纬度网格划分		边界网格划分		自适应网格网格划分
区域	AC /%	完成时间	AC /%	完成时间	AC /%	完成时间
方形	95.8	1.0	97.9	5.2	97.5	1.4
圆形	95.3	1.7	98.1	7.8	97.4	2.2
任意	94.5	2.3	97.6	10.6	97.0	2.6

下载: 导出CSV

表 2 滑动窗口大小对完成时间的影响

Table 2 The Complete Time for Different Sizes of Sliding Window

区域	1	2	3	4	5	6	7
A	4.01	3.27	1.92	1.28	1.07	1.23	1.31
B	5.20	3.79	2.43	1.79	1.72	1.63	1.80
C	7.87	5.23	3.66	2.45	2.41	2.48	2.53

下载: 导出CSV

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