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Multi-objective evolutionary optimization for geostationary orbit satellite mission planning 被引量:3

Multi-objective evolutionary optimization for geostationary orbit satellite mission planning
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摘要 In the past few decades, applications of geostationary orbit (GEO) satellites have attracted increasing attention, and with the development of optical technologies, GEO optical satellites have become popular worldwide. This paper proposes a general working pattern for a GEO optical satellite, as well as a target observation mission planning model. After analyzing the requirements of users and satellite control agencies, two objectives are simultaneously considered: maximization of total profit and minimization of satellite attitude maneuver angle. An NSGA-II based multi-objective optimization algorithm is proposed, which contains some heuristic principles in the initialization phase and mutation operator, and is embedded with a traveling salesman problem (TSP) optimization. The validity and performance of the proposed method are verified by extensive numerical simulations that include several types of point target distributions. In the past few decades, applications of geostationary orbit (GEO) satellites have attracted increasing attention, and with the development of optical technologies, GEO optical satellites have become popular worldwide. This paper proposes a general working pattern for a GEO optical satellite, as well as a target observation mission planning model. After analyzing the requirements of users and satellite control agencies, two objectives are simultaneously considered: maximization of total profit and minimization of satellite attitude maneuver angle. An NSGA-II based multi-objective optimization algorithm is proposed, which contains some heuristic principles in the initialization phase and mutation operator, and is embedded with a traveling salesman problem (TSP) optimization. The validity and performance of the proposed method are verified by extensive numerical simulations that include several types of point target distributions.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第5期934-945,共12页 系统工程与电子技术(英文版)
基金 supported by the National Natural Science Foundation of China(71501180 61473301)
关键词 geostationary orbit (GEO) satellitemission planning multi-objective optimization evolutionary genetic geostationary orbit (GEO) satellitemission planning multi-objective optimization evolutionary genetic
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