Application of Regularization Particle Filtering in Underwater Target Tracking
Shouyi Yang · Video Engineering · 2012
In this paper,an underwater target tracking algorithm based on the regularization particle filtering is proposed to solve the problem that the tracking precision of the traditional kalman filter(KF) and the extended kalman filtering(EKF)is poor in nonlinear target tracking model.And an experiment is done to compare the EKF and the standard particle filtering(PF) on their tracking performance in a nonlinear dynamic model which simulates the underwater target tracking environment.The simulation results show that the filtering performance of PF is more accurate than EKF algorithm,but they are both poorer than RPF on tracking performance.With increasing of the number of particles,the tracking performance of PF and RPF become better.