By Topic

Exploration of adaptive filters for target tracking in the presence of model uncertainty

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

1 Author(s)
Truong, T.Q.S. ; Maritime Oper. Div., Defence Sci. & Technol. Organ., Rockingham, WA, Australia

This paper presents an investigation of Target Motion Analysis (TMA) algorithms that are designed to cope with some model uncertainty. In particular, adaptive algorithms are designed to deal with unknown noise variance. These adaptive algorithms are multiple model based techniques that are capable of tuning into the true parameter while estimating the target state. The algorithms considered are a) Static Multiple Model (SMM) Estimator, b) Generalised Pseudo Bayes (GPB) methods, and c) Interacting Multiple Model (IMM) based tracker. Simulation results verify the potential use of such algorithms.

Published in:

Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2010 Sixth International Conference on

Date of Conference:

7-10 Dec. 2010