Autonomous Mission Planning Method for Optical Imaging Satellites Based on Real-Time Cloud Cover Information

Zhiliang Li; Limin Zhao; Yun Liu; Xingfeng Chen; Hang Chen; Fengjie Zheng; Yunli Zhang; Donghong Wang; Jiaguo Li; Jun Liu; Shumin Liu

doi:10.3390/rs14112635

Remote Sensing (May 2022)

Autonomous Mission Planning Method for Optical Imaging Satellites Based on Real-Time Cloud Cover Information

Zhiliang Li,
Limin Zhao,
Yun Liu,
Xingfeng Chen,
Hang Chen,
Fengjie Zheng,
Yunli Zhang,
Donghong Wang,
Jiaguo Li,
Jun Liu,
Shumin Liu

Affiliations

Zhiliang Li: School of Space Information, Space Engineering University, Beijing 101416, China
Limin Zhao: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Yun Liu: The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050000, China
Xingfeng Chen: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Hang Chen: School of Space Information, Space Engineering University, Beijing 101416, China
Fengjie Zheng: School of Space Information, Space Engineering University, Beijing 101416, China
Yunli Zhang: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Donghong Wang: Beijing Institute of Tracking and Telecommunications Technology, Beijing 100094, China
Jiaguo Li: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Jun Liu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Shumin Liu: School of Software Engineering, Jiangxi University of Science and Technology, Nanchang 330013, China

DOI: https://doi.org/10.3390/rs14112635
Journal volume & issue: Vol. 14, no. 11
p. 2635

Abstract

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Cloud cover is an important factor limiting the earth observation efficiency of optical imaging satellites. Existing solutions include avoiding cloudy observation time windows by onboard cloud detectors and ground monitors, which are difficult to improve satellite observation efficiency in time. In order to solve the problem, firstly, a Geostationary Earth Orbit (GEO) and Low Earth Orbit (LEO) satellites cooperation scheme by using cloud cover information provided by GEO meteorological satellite to guide the imaging of LEO optical satellites is proposed, and the operation flow and key elements in this scheme are analyzed. Secondly, Fengyun-4 GEO meteorological satellite and its cloud mask (CLM) products are analyzed. Thirdly, an autonomous mission planning algorithm based on real-time cloud cover information is proposed. Computational results have demonstrated the effectiveness of the proposed GEO–LEO satellites cooperation scheme by taking the actual orbit and payload data of Fengyun-4 and Gaofen-1/2 satellites as examples.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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