MCMC particle filter for tracking in a partially known multipath environment

Author

Karunaratne, B. Sachintha ; Morelande, Mark R. ; Moran, Bill

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Melbourne, VIC, Australia

fYear

2013

Firstpage

6332

Lastpage

6336

Abstract

The principal difficultly in tracking in an urban terrain is the presence of multipaths. However by using proper modelling and signal processing techniques these multipaths can be used favourably. In this paper we consider a more robust model of the urban terrain by not assuming exact wall locations but rather allowing for small deviations. This is achieved by introducing a random phase shift to the radar equation. A MCMC based particle filter which uses an adaptive kernel to improve the mobility of the Markov Chain is proposed with supporting simulation results.

Keywords

Markov processes; Monte Carlo methods; adaptive filters; particle filtering (numerical methods); radar signal processing; radar tracking; random processes; MCMC particle filter; Markov chain; adaptive kernel; multipath environment; radar equation; random phase shift; small deviations; urban terrain tracking; wall locations; Approximation methods; Bandwidth; Kernel; Markov processes; Radar tracking; Robustness; MCMC; kernel; multipath; particle filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on

Conference_Location

Vancouver, BC

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2013.6638884

Filename

6638884