A new approach based on particle filter for target tracking with glint noise

Author

Zhang, Jungen ; Ji, Hongbing ; Xue, Qikun

Author_Institution

Sch. of Electron. Eng., Xidian Univ., Xi´´an, China

fYear

2009

fDate

11-14 Oct. 2009

Firstpage

4791

Lastpage

4795

Abstract

In radar target tracking application, the observation noise is usually non-Gaussian, which is also referred to as glint noise. The performances of conventional trackers degrade severely in the presence of glint noise. An improved particle filter, Markov chain Monte Carlo iterated extended Kalman particle filter (MCMC-IEKPF), is applied to this problem. The tracking performance of the filter is evaluated and compared to the particle filter (PF) and the Markov chain Monte Carlo particle filter (MCMC-PF) via simulations. It is shown that the MCMC-IEKPF has better tracking performance.

Keywords

Kalman filters; Markov processes; Monte Carlo methods; iterative methods; particle filtering (numerical methods); radar tracking; target tracking; Markov chain Monte Carlo method; glint noise; iterated extended Kalman particle filter; nonGaussian noise; radar target tracking; Degradation; Kalman filters; Monte Carlo methods; Noise measurement; Particle filters; Particle tracking; Performance evaluation; Proposals; Radar tracking; Target tracking; glint noise; iterated extended Kalman filter; particle filter; radar target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on

Conference_Location

San Antonio, TX

ISSN

1062-922X

Print_ISBN

978-1-4244-2793-2

Electronic_ISBN

1062-922X

Type

conf

DOI

10.1109/ICSMC.2009.5346071

Filename

5346071