One Practical Data Fusion Algorithm Applied in Auxiliary Particle Filtering

The filtering for target tracking is discussed in the paper, in order to find a method with better accuracy and reliability than extended Kalman (EKF) filtering and unscented Kalman filtering(UKF), this paper built a non-linear system model - turn model, then a method of auxiliary particle filters combination with data fusion is proposed. Auxiliary particle filtering for character of the turn model modified every particle before resampling according to likelihood function, which can get the certain accuracy of filtering with fewest particles. In order to improve the filtering result further, it used multi-auxiliary particle filters with a practical data fusion algorithm that is efficient in turn model and can get good result through computer simulation.