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A Variational Measurement Update for Extended Target Tracking With Random Matrices
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2012 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, no 7, 3827-3834 p.Article in journal (Refereed) Published
Abstract [en]

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 et al., 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.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2012. Vol. 60, no 7, 3827-3834 p.
Keyword [en]
Extended target tracking, Measurement update, Random matrices, Variational Bayes
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-79686DOI: 10.1109/TSP.2012.2192927ISI: 000305578800039OAI: diva2:544137
Available from: 2012-08-13 Created: 2012-08-13 Last updated: 2013-07-23

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