Electrostatic Maneuvering Target Tracking Based on Fuzzy Interacting Multiple Model Particle Filter

doi:10.3969/j.issn.1000-1093.2014.01.006

Abstract

Abstract: Interacting multiple model particle filter (IMMPF) has the defects of low precision and long updated time, which is not able to meet the requirement of the electrostatic maneuvering target tracking. To solve the problem, a new fuzzy interacting multiple model particle filter (FIMMPF) is proposed. This algorithm can adjust the transition probability matrix of IMM by fuzzy control in real-time and make the motion model that is closet to the current actual motion model occupy larger proportion in the initial state vector. In order to improve the precision of PF algorithm and reduce the updated time of algorithm, central difference expand Kalman filter algorithm is used to generate a proposed distribution and update the target state. The theory analysis and simulation results show that FIMMPF can track the electrostatic maneuvering target with higher positioning precision and smaller updated time.

Key words: information processing, electrostatic detection, fuzzy interacting multiple model particle filter, maneuvering target tracking

CLC Number:

TN911.23

FU Wei， ZHENG Bin. Electrostatic Maneuvering Target Tracking Based on Fuzzy Interacting Multiple Model Particle Filter[J]. Acta Armamentarii, 2014, 35(1): 42-48.

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