B-spline based Extended target tracking technology in cluttered environments

Abstract

In order to solve the problem of tracking single extended targets in a cluttered environment, this thesis proposes a B-spline based probabilistic data association extended target tracking method (ET-BS-PDA). Firstly, the state of the extended target is modelled using B-sample strips, secondly, all events associated with the extended target will be counted based on valid measurements, and the probability of the associated events will be computed using the full probability principle. Finally, we use probabilistic data association algorithms to update state and covariance of extended targets and verify effectiveness of extended target tracking algorithms in cluttered environments through simulations.