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http://dx.doi.org/10.5302/J.ICROS.2003.9.10.747

A Variable Dimensional Structure with Probabilistic Data Association Filter for Tracking a Maneuvering Target in Clutter Environment  

안병완 (GM DAEWOO Auto & Technology, 기술연구소)
최재원 (부산대학교 기계공학부 및 기계기술연구소)
송택렬 (한양대학교 전자전기제어계측공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.9, no.10, 2003 , pp. 747-754 More about this Journal
Abstract
An enhancement of the probabilistic data association filter is presented for tracking a single maneuvering target in clutter environment. The use of the variable dimensional structure leads the probabilistic data association filter to adjust to real motion of a target. The detection of the maneuver for the model switching is performed by the acceleration estimates taken from a bias estimator of the two stage Kalman filter. The proposed algorithm needs low computational power since it is implemented with a single filtering procedure. A simple Monte Carlo simulation was performed to compare the performance of the proposed algorithm and the IMMPDA filter.
Keywords
probabilistic data association filter; maneuver detection; variable dimensional structure;
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