Open Access

Joint Tracking of Manoeuvring Targets and Classification of Their Manoeuvrability

EURASIP Journal on Advances in Signal Processing20042004:613289

https://doi.org/10.1155/S1110865704404223

Received: 30 May 2003

Published: 7 November 2004

Abstract

Semi-Markov models are a generalisation of Markov models that explicitly model the state-dependent sojourn time distribution, the time for which the system remains in a given state. Markov models result in an exponentially distributed sojourn time, while semi-Markov models make it possible to define the distribution explicitly. Such models can be used to describe the behaviour of manoeuvring targets, and particle filtering can then facilitate tracking. An architecture is proposed that enables particle filters to be both robust and efficient when conducting joint tracking and classification. It is demonstrated that this approach can be used to classify targets on the basis of their manoeuvrability.

Keywords and phrases

trackingclassificationmanoeuvring targetsparticle filtering

Authors’ Affiliations

(1)
QinetiQ Ltd
(2)
Department of Engineering, University of Cambridge

Copyright

© Maskell 2004