Iterated gain-based stochastic filters for dynamic system identification |
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| Authors: | Tara Raveendran Debasish Roy Ram Mohan Vasu |
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| Institution: | 1. Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, India;2. Computational Mechanics Lab, Department of Civil Engineering, Indian Institute of Science, Bangalore, India |
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| Abstract: | We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner–Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-à-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. |
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