• DocumentCode
    711284
  • Title

    Space object tracking and maneuver detection via interacting multiple model cubature Kalman filters

  • Author

    Bin Jia ; Blasch, Erik ; Pham, Khanh D. ; Dan Shen ; Zhonghai Wang ; Xin Tian ; Genshe Chen

  • Author_Institution
    Intell. Fusion Technol., Inc., Germantown, MD, USA
  • fYear
    2015
  • fDate
    7-14 March 2015
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Space object tracking and maneuver detection play an essential role in space situation awareness (SSA). The ordinary Kalman filter and its variants may give large error due to the maneuver of the space object. In this paper, to consistently track a maneuvering space object, the interacting multiple model (IMM) filter is utilized. Multiple Models with different process noise levels are used to distinguish the maneuvering effects. The IMM cubature Kalman filter (IMM-CKF) is used to track the maneuvering space object which considers of the geometric relations between the space object, space based optical (SBO) sensor, and the sun. The geometric relation highly affects the quality of the observation. A scenario which contains a target spacecraft and four SBO sensors is used to test performance of the IMM-CKF. We also compare the IMM-CKF and the ordinary cubature Kalman filter (CKF). The results indicate that IMM-CKF is more robust than the CKF when the space object undergoes a maneuver. In addition, the detection of a maneuver can be obtained by using the IMM-CKF. Hence, IMM-CKF could facilitate future SBO based SSA mission awareness.
  • Keywords
    Kalman filters; aerospace instrumentation; object detection; object tracking; optical sensors; IMM-CKF; SBO based SSA mission awareness; SBO sensor; geometric relation; interacting multiple model cubature Kalman filters; maneuver detection; maneuvering space object tracking; ordinary cubature Kalman filter; process noise levels; space based optical sensor; space situation awareness; target spacecraft; Earth; Kalman filters; Mathematical model; Noise; Object tracking; Radar tracking; Space vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2015 IEEE
  • Conference_Location
    Big Sky, MT
  • Print_ISBN
    978-1-4799-5379-0
  • Type

    conf

  • DOI
    10.1109/AERO.2015.7119076
  • Filename
    7119076