DocumentCode :
1482660
Title :
A Variational Measurement Update for Extended Target Tracking With Random Matrices
Author :
Orguner, Umut
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
Volume :
60
Issue :
7
fYear :
2012
fDate :
7/1/2012 12:00:00 AM
Firstpage :
3827
Lastpage :
3834
Abstract :
This correspondence proposes a new measurement update for extended target tracking under measurement noise when the target extent is modeled by random matrices. Compared to the previous measurement update developed by Feldmann , this work follows a more rigorous path to derive an approximate measurement update using the analytical techniques of variational Bayesian inference. The resulting measurement update, though computationally more expensive, is shown via simulations to be better than the earlier method in terms of both the state estimates and the predictive likelihood for moderate amounts of prediction errors.
Keywords :
approximation theory; belief networks; matrix algebra; measurement systems; prediction theory; target tracking; analytical techniques; approximate measurement update; extended target tracking; measurement noise; prediction errors; predictive likelihood methhod; random matrices; state estimation; variational Bayesian inference; variational measurement update; Approximation methods; Density measurement; Kinematics; Noise; Noise measurement; Prediction algorithms; Target tracking; Extended target tracking; measurement update; random matrices; variational Bayes;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2012.2192927
Filename :
6177687
Link To Document :
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