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Federated Information Mode-Matched Filters in ACC Environment

Kim Yong-Shik    (Graduate School of Systems and Information Engineering, University of Tsukuba   ); Hong Keum-Shik    (School of Mechanical Engineering, Pusan National University  );
  • 초록

    In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.


  • 주제어

    Information filter .   interacting multiple model .   extended Kalman filter .   federated filter .   sensor fusion.  

  • 참고문헌 (18)

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