By Topic

Robust MT Tracking Based on M-Estimation and Interacting Multiple Model Algorithm

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)
Hammes, U. ; Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany ; Zoubir, A.M.

An algorithm for mobile terminal (MT) tracking based on time-of-arrival measurements in non-line-of-sight (NLOS) environments where NLOS measurements are modeled as positive outliers is proposed. Standard filters such as the extended Kalman filter (EKF) fail because they are sensitive to outliers. In contrast, a robust EKF (REKF) always trades off efficiency in line-of-sight (LOS) versus robustness in NLOS environments and it is not possible to achieve both with the same filter. Instead, we propose to use two filters in parallel in a multiple model framework. An EKF yields high precision in LOS environments whereas an REKF provides robust state estimates when NLOS propagation comes into play. The state estimates of either filters are combined automatically based on the confidence we have for the underlying situation. It is shown via numerical studies that the proposed algorithm yields positioning accuracy similar to the EKF in LOS environments and even significantly outperforms the REKF in NLOS environments.

Published in:

Signal Processing, IEEE Transactions on  (Volume:59 ,  Issue: 7 )