Sarkar, S and Chowdhury, SR and Venugopal, M and Vasu, RM and Roy, D (2014) A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification. In: PHYSICA D-NONLINEAR PHENOMENA, 270 . pp. 46-59.
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Abstract
A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.
Item Type: | Journal Article |
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Publication: | PHYSICA D-NONLINEAR PHENOMENA |
Publisher: | ELSEVIER SCIENCE BV |
Additional Information: | copyright for this article belongs to ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS |
Keywords: | Kushner-Stratonovich equation; Euler approximation; Inner iterations; Monte Carlo filters; Error estimates; Nonlinear system identification |
Department/Centre: | Division of Mechanical Sciences > Civil Engineering Division of Mechanical Sciences > Mechanical Engineering |
Date Deposited: | 26 Mar 2014 07:53 |
Last Modified: | 26 Mar 2014 07:53 |
URI: | http://eprints.iisc.ac.in/id/eprint/48717 |
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