Title :
Efficient particle filters for tracking manoeuvring targets in clutter
Author :
Doucet, Arnaud ; Gordon, Neil
Author_Institution :
Signal Process. Group, Cambridge Univ., UK
fDate :
6/21/1905 12:00:00 AM
Abstract :
In this paper, we propose an on-line Monte Carlo (MC) filtering algorithm to perform optimal state estimation for Jump Markov Linear Systems (JMLS). The approach taken is loosely based on the bootstrap filter which, whilst being a powerful general algorithm in its original form, does not make the most of the structure of JMLS. The proposed algorithm exploits this structure and is demonstrated to provide a performance improvement over the IMM-PDA for tracking manoeuvring targets in clutter
Keywords :
tracking filters; Kalman filters; bootstrap filter; clutter; efficient particle filters; false measurements; jump Markov linear systems; manoeuvring target tracking; on-line Monte Carlo filtering algorithm; optimal state estimation; simulation-based filter; statistical model; true measurements;
Conference_Titel :
Target Tracking: Algorithms and Applications (Ref. No. 1999/090, 1999/215), IEE Colloquium on
Conference_Location :
London
DOI :
10.1049/ic:19990505
