Cart (Loading....) | Create Account
Close category search window
 

IMMJPDA versus MHT and Kalman filter with NN correlation: performance comparison

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 $31
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

4 Author(s)

In a tracking problem a radar periodically scans the volume under surveillance and provides detections (plots) that indicate a target presence. Multitarget tracking systems in operational use today generally adopt Kalman filter (KF) techniques (coupled with a manoeuvre detector to introduce some kind of adaptivity), and nearest neighbour (NN) correlation. Today there are two new approaches to the tracking problem, namely: interacting multiple model joint probabilistic data association (IMMJPDA) and multiple hypothesis tracking (MHT) which promise improved tracking performance. The paper provides a performance comparison between these three tracking algorithms in terms of track maintenance probability and tracking errors. The NN + KF algorithm is used as reference because of its widespread use. Results show that MHT is superior to IMMJPDA and, as expected, both perform better than NN + KF; the cost of additional performance is increased, yet feasible, computing power

Published in:

Radar, Sonar and Navigation, IEE Proceedings -  (Volume:144 ,  Issue: 2 )

Date of Publication:

Apr 1997

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.