Research on Adaptive Filtering Algorithm for Maneuvering Target Tracking

Abstract

For the maneuvering target tracking problem, based on the truncation of the normal probability density model, the self-adaptive adjustment of the noise variance is achieved by the functional relationship between the target maneuvering condition and the change of the position estimator at the adjacent sampling time, and a new adaptive filtering algorithm which is based on truncated normal probability density model modified is proposed. The computer simulation results show that the algorithm has good tracking performance when tracking maneuvering targets, and greatly improves the ability to track non-maneuvering targets.