Maneuvering Target Tracking Algorithm Based on Multiple Model Rao-Blackwellised Particle Filter

摘要

Target tracking is highly nonlinear problem that has been successfully addressed in recent years using particle filtering method. However, the realization of particle filter has a large amount of calculation. In order to improve the computational complexity caused by the augment of model in maneuvering tracking system, Rao-Blackwellised particle filter with better real-time and filtering precision relative to the standard particle filter, is introduced into multiple model particle filter framework. And a novel multiple model Rao-Blackwellised particle filter is proposed in this paper. Due to the dynamic combination of above two algorithms, the real-time and reliability is effective improved. The theoretical analysis and experimental results show the efficiency of the proposed algorithm.