By Topic

New efficient target tracking based upon hidden Markov model and probabilistic data association

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)
Sitbon, S. ; Thomson Sintra ASM, Sophia-Antipolis, France ; Passerieux, J.M.

This paper deals with automatic detection and tracking using hidden Markov model and probabilistic data association in order to operate in a densely cluttered environment. After a theoretical description of the algorithm, Monte-Carlo performance comparisons with known methods like NNAF and PDAF are provided, in the case of sonar processing. Improvements are clearly shown in terms of detection and track splitting, for an increase of computation requirement less than 5. At sea signals analysis confirms this result.

Published in:

Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference on  (Volume:2 )

Date of Conference:

Oct. 30 1995-Nov. 1 1995