Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Federated Variable Dimension Kalman Filters with Input Estimation for Maneuvering Target Tracking

기동하는 표적의 추적을 위한 연합형 가변차원 입력추정필터

  • 황보승욱 (부산대 대학원, 현재 한국생산기술연구원) ;
  • 홍금식 (부산대학교 기계공학부 및 기계기술연구소) ;
  • 최성린 (국방과학연구소) ;
  • 최재원 (부산대학교 기계공학부 및 기계기술연구소)
  • Published : 1999.08.01
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Abstract

In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.

Keywords

References

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