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

Multiple Detection Probabilistic Data Association filter for multistatic target tracking

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

5 Author(s)
Habtemariam, B.K. ; ECE Dept., McMaster Univ., Hamilton, ON, Canada ; Tharmarasa, R. ; Kirubarajan, T. ; Grimmett, D.
more authors

A standard assumption in most tracking algorithms, like the Probabilistic Data Association (PDA) filter, Multiple Hypothesis Tracker (MHT) or the Multiframe Assignment Tracker (MFA), is that a target is detected at most once in a frame of data used for association. This one-to-one assumption is essential for correct measurement-to-track associations. When this assumption is violated, the above algorithms treat the extra detections as random clutter. When multiple detections from the same target fall within the association gate, the PDA filter tries to apportion the association probabilities, but with the fundamental assumption only one of them is correct. The MFA and the MHT algorithms try to spawn multiple tracks to handle the additional measurements from the same target, assuming at most one measurement came from each target. Both of these approaches have undesirable side effects since they ignore the possibility of multiple detections from the same target in a scan of data. Such multiple detection situations occur in multistatic tracking problems. In this paper, we proposed a new Multiple Detection Probabilistic Data Association (MD-PDA) filter for tracking a target when more than one target originated measurement may exist within the validation gate. In the proposed MD-PDA, combinatorial association events are formed to handle the possibility of multiple measurements from the same target. Modified association probabilities are calculated with the explicit assumption of multiple detections. Simulations are presented to demonstrate the effectiveness of the algorithm on a single target tracking problem in clutter. Extensions to handle multiple targets using the Joint PDA, MHT and MFA approaches are under development.

Published in:

Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on

Date of Conference:

5-8 July 2011

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.