Infrared Fast-Maneuvering Target Tracking Based on Robust Exact Differentiator with Improved Particle Filter

Abstract

This paper deals with the problem of nonlinear uncertainties when tracking an infrared dim small target with fast maneuvers. The particle filter (PF)-based methods are mostly considered. The existing improvement methods for the PF can handle the infrared dim small target with the conventional maneuver, the motion state of which changes slowly and in most cases is assumed to be linear. However, when fast maneuvers appear on the target, the PF-based method will soon suffer from particle degeneracy, or even loss of the target. In this paper, a robust exact differentiator (RED)-based particle generating method is proposed to improve the PF. New birth particles are produced by the proposed method, which can keep up with the fast maneuvers, and ensure the particle diversity of the PF, so as to avoid the particle degeneracy and depletion, meanwhile the number of particles required can be decreased. Numerical simulations are conducted, showing that the proposed algorithm has more advantages than the state-of-the-art method.