An improved particle filter for non-linear problems

by: J Carpenter, P Clifford, P Fernhead

(1997)

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Abstract

The Kalman filter provides an effective solution to the linear-Gaussian filtering problem. However, where there is nonlinearity, either in the model specification or the observation process, other methods are required. We consider methods known generically as particle filters, which include the condensation algorithm and the Bayesian bootstrap or sampling importance resampling (SIR) filter.

@misc{citeulike:347156, abstract = {The Kalman filter provides an effective solution to the linear-Gaussian filtering problem. However, where there is nonlinearity, either in the model specification or the observation process, other methods are required. We consider methods known generically as particle filters, which include the condensation algorithm and the Bayesian bootstrap or sampling importance resampling (SIR) filter.}, author = {Carpenter, J. and Clifford, P. and Fernhead, P. }, citeulike-article-id = {347156}, keywords = {bayesian, carlo, filter, localization, particle, probabilistic}, posted-at = {2007-10-16 15:48:51}, priority = {3}, title = {An improved particle filter for non-linear problems}, url = {http://citeseer.ist.psu.edu/carpenter04improved.html}, year = {1997} }

RIS record

TY - GEN ID - citeulike:347156 L3 - citeulike-article-id:347156 TI - An improved particle filter for non-linear problems N2 - The Kalman filter provides an effective solution to the linear-Gaussian filtering problem. However, where there is nonlinearity, either in the model specification or the observation process, other methods are required. We consider methods known generically as particle filters, which include the condensation algorithm and the Bayesian bootstrap or sampling importance resampling (SIR) filter. KW - bayesian KW - carlo KW - filter KW - localization KW - particle KW - probabilistic AU - Carpenter, J AU - Clifford, P AU - Fernhead, P PY - 1997/// UR - http://citeseer.ist.psu.edu/carpenter04improved.html ER -

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