ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

An Ensemble Kushner-Stratonovich-Poisson Filter for Recursive Estimation in Nonlinear Dynamical Systems

Venugopal, Mamatha and Vasu, Ram Mohan and Roy, Debasish (2016) An Ensemble Kushner-Stratonovich-Poisson Filter for Recursive Estimation in Nonlinear Dynamical Systems. In: IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 61 (3). pp. 823-828.

[img] PDF
IEEE_Tra_Aut_Con_61-3_823_2016.pdf - Published Version
Restricted to Registered users only

Download (715kB) | Request a copy
Official URL: http://dx.doi.org/10.1109/TAC.2015.2450113

Abstract

We propose a Monte Carlo filter for recursive estimation of diffusive processes that modulate the instantaneous rates of Poisson measurements. A key aspect is the additive update, through a gain-like correction term, empirically approximated from the innovation integral in the time-discretized Kushner-Stratonovich equation. The additive filter-update scheme eliminates the problem of particle collapse encountered in many conventional particle filters. Through a few numerical demonstrations, the versatility of the proposed filter is brought forth.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Keywords: Automatic control; Bayes method; filtering; Monte Carlo methods; Poisson processes; recursive estimation
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Depositing User: Id for Latest eprints
Date Deposited: 29 Apr 2016 05:20
Last Modified: 29 Apr 2016 05:20
URI: http://eprints.iisc.ac.in/id/eprint/53728

Actions (login required)

View Item View Item