By Topic

Data association and tracking from distributed sensors using hidden Markov models and evidential reasoning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Martinerie, F. ; Thomson Sintra Activites-Sous-Marines, Arcueil, France ; Forster, P.

The problem of target tracking from distributed sensors in a cluttered environment is addressed. In `Data Association and Tracking Using HMMs and Dynamic Programming', Proc. Conf. IEEE-ICASS 92, the authors introduced an approach which achieves target tracking and target motion analysis by using the hidden Markov models formalism and the Bayesian probabilities theory. This approach is theoretically valid in the single target case. A variant of this technique is introduced. It is valid in the multiple target case, with some restrictions in the case of close targets

Published in:

Decision and Control, 1992., Proceedings of the 31st IEEE Conference on

Date of Conference:

1992