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. / MC Impulse
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-93704 |
Date | January 2013 |
Creators | Roth, Michael, Ozkan, Emre, Gustafsson, Fredrik |
Publisher | Linköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Linköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Linköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Conference paper, info:eu-repo/semantics/conferenceObject, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), p. 5770-5774, info:eu-repo/grantAgreement/EC/FP7/238710 |
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