Analysis of single Gaussian approximation of Gaussian mixtures in Bayesian filtering applied to mixed multiple-model estimation

Date

2007-01-01

Author

Orguner, Umut

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This paper examines the effect of the moment-matched single Gaussian approximation, which is made in various multiple-model filtering applications to approximate a Gaussian mixture, on the Bayesian filter performance. The estimation error caused by the approximation is analysed for both the prediction and the measurement updates of a Bayesian filter. An approximate formula is found for the covariance of the error caused by the approximation for a general Gaussian mixture with arbitrary components. The calculated error covariance is used for obtaining a mixed multiple-model estimation algorithm which has a performance near that of GPB2 with less computations.

Subject Keywords

Control and Systems Engineering, Computer Science Applications

URI

https://hdl.handle.net/11511/45788

Journal

INTERNATIONAL JOURNAL OF CONTROL

DOI

https://doi.org/10.1080/00207170701261952

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

U. Orguner, “Analysis of single Gaussian approximation of Gaussian mixtures in Bayesian filtering applied to mixed multiple-model estimation,” INTERNATIONAL JOURNAL OF CONTROL, pp. 952–967, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/45788.