Novel Roughening Method for Reentry Vehicle Tracking Using Particle Filter

Abstract

An improvement for the generic particle filter (PF) is to add a roughening step in resampling. This paper studied the reentry vehicle tracking problem using PF with roughening. A novel algorithm to calculate the reasonable standard deviation of the roughening jitter is proposed. For comparison, the Unscented Kalman filter, the generic PF and the PF with the typical roughening are used to gauge the estimation performance, and the results favor the PF with the proposed roughening method. The generic PF and the PF with the typical roughening have low probabilities of success under conditions of comparatively large initialization bias and accurate radar measurement. The proposed PF can handle these cases efficiently and give better performance.