DocumentCode :
2218358
Title :
Multi-objective evolutionary optimization of evasive maneuvers including observability performance
Author :
Dateng, Yu ; Yazhong, Luo ; Zicheng, Jiang ; Guojin, Tang
Author_Institution :
College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China
fYear :
2015
fDate :
25-28 May 2015
Firstpage :
603
Lastpage :
610
Abstract :
This paper investigates optimal orbital evasion problem with considering observability performance by using a multi-objective optimization approach. The degree of observability is defined as a new performance index, which has a negative correlation with the accuracy degree of relative state estimation. A two-objective optimization model is then formulated and the NSGA-II algorithm is employed to obtain the Pareto-optimal solution set. The numerical results show that the proposed approach can effectively and efficiently demonstrate the relations among the evasive mission characteristic parameters. The proposed approach offers a novel view in solving orbital evasion problem.
Keywords :
Covariance matrices; Extraterrestrial measurements; Observability; Optical variables measurement; Optimization; Space vehicles; State estimation; Angles-Only; Evasion Problem; NSGA-II; Observability; Optimal Evasive maneuver;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
Type :
conf
DOI :
10.1109/CEC.2015.7256946
Filename :
7256946
Link To Document :
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