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A Student s t filter for heavy tailed process and measurement noise
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Date
2013-05-26
Author
Roth, Michael
Özkan, Emre
Gustafsson, Fredrik
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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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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BibTeX
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.