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FEATURE AIDED SWITCHING MODEL SET APPROACH FOR MANEUVERING TARGET TRACKING

By J. Fan, Y. Zhu, S. Fan, H. Fan, and Q. Fu

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Abstract:
Feature aided maneuver detector is popular for its low detection delay and high detection probability in decision-based single-model maneuvering target tracking (MTT) algorithms. We propose a switching model-set approach based on the feature aided maneuver detector for MTT. The filtering error dynamics in terms of detection delay are presented and a upper bound for detection delay with given standard Kalman filtering errors is accessed. Subsequently, a feature aided maneuver detector is introduced to enhance detection performance, and the filtering algorithm is proposed, including detailed filtering steps and computational formulae. Simulation results show that the proposed algorithm outperforms the popular autonomous multiple model (AMM) and interacting MM (IMM) algorithms.

Citation:
J. Fan, Y. Zhu, S. Fan, H. Fan, and Q. Fu, "Feature Aided Switching Model Set Approach for Maneuvering Target Tracking," Progress In Electromagnetics Research B, Vol. 45, 251-268, 2012.
doi:10.2528/PIERB12082803

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