International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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An Intelligent Tracking Method for a Maneuvering Target

  • Lee, Bum-Jik (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Joo, Young-Hoon (School of Electronic and Information Engineering, Kunsan University) ;
  • Park, Jin-Bae (Department of Electrical and Electronic Engineering, Yonsei University)
  • Published : 2003.03.01
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Abstract

Accuracy in maneuvering target tracking using multiple models relies upon the suit-ability of each target motion model to be used. To construct multiple models, the interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require predefined sub-models and predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers. To solve these problems, this paper proposes the GA-based IMM method as an intelligent tracking method for a maneuvering target. In the proposed method, the acceleration input is regarded as an additive process noise, a sub-model is represented as a fuzzy system to compute the time-varying variance of the overall process noise, and, to optimize the employed fuzzy system, the genetic algorithm (GA) is utilized. The simulation results show that the proposed method has a better tracking performance than the AIMM algorithm.

Keywords

References

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