By Topic

Off-Line and Real-Time ML-PDA Track Validation

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
$33 $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

3 Author(s)
Wayne Blanding ; Dept. of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269. Email: ; Peter Willett ; Yaakov Bar-Shalom

We present two procedures for validating track estimates obtained using the Maximum Likelihood Probabilistic Data Association (ML-PDA) algorithm. The ML-PDA, developed for Very Low Observable (VLO) target tracking, always provides a track estimate that must then be tested for target existence by comparing the value of the Log Likelihood Ratio (LLR) at the track estimate to a threshold. Using extreme value theory, we show that in the absence of a target the LLR at the track estimate obeys approximately a Gumbel distribution rather than the Gaussian distribution previously ascribed to it in the literature. The off-line track validation procedure relies on extensive offline simulations to obtain a set of track validation thresholds. The real-time procedure uses the data set that produced the track estimate to also determine the track validation threshold. The performance of these two procedures is investigated through simulation of an active sonar tracking scenario by comparing the false and true track acceptance probabilities

Published in:


Date of Conference:

18-21 Sept. 2006