A Student s t filter for heavy tailed process and measurement noise

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2013-05-26

Author

Roth, Michael
Özkan, Emre
Gustafsson, Fredrik

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We consider the filtering problem in linear state space models with heavy tailed process and measurement noise. Our work is based on Student's t distribution, for which we give a number of useful results. The derived filtering algorithm is a generalization of the ubiquitous Kalman filter, and reduces to it as special case. Both Kalman filter and the new algorithm are compared on a challenging tracking example where a maneuvering target is observed in clutter.

Subject Keywords

Student's t distribution, Kalman filter, Robustness, Outliers

URI

https://hdl.handle.net/11511/39196

DOI

https://doi.org/10.1109/icassp.2013.6638770

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Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

M. Roth, E. Özkan, and F. Gustafsson, “A Student s t filter for heavy tailed process and measurement noise,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39196.