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The Near Constant Acceleration Gaussian Process Kernel for Tracking

Abstract:

Time series prediction is traditionally the domain of the state-based Kalman filter and very general Kalman filter process models, such as the near constant acceleration model (NCAM), have been developed to successfully track moving targets. However, the standard Kalman filter uses Markov process models and, consequently, it is difficult to track processes which include a complex periodic component. Gaussian processes are a generalisation of the Kalman filter and are able to model periodic be...

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Publication status:
Published

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Publisher copy:
10.1109/LSP.2010.2051620

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
Roberts, S More by this author
Journal:
IEEE SIGNAL PROCESSING LETTERS
Volume:
17
Issue:
8
Pages:
707-710
Publication date:
2010-08-05
DOI:
EISSN:
1558-2361
ISSN:
1070-9908
URN:
uuid:f22e4ffb-0f2e-44f8-8458-114ce598ad15
Source identifiers:
299645
Local pid:
pubs:299645

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