A Variational Measurement Update for Extended Target Tracking With Random Matrices

2012-07-01
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.
IEEE TRANSACTIONS ON SIGNAL PROCESSING

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Citation Formats
U. Orguner, “A Variational Measurement Update for Extended Target Tracking With Random Matrices,” IEEE TRANSACTIONS ON SIGNAL PROCESSING, pp. 3827–3834, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38321.