• 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