Suboptimal Adaptive Filter for Dynamic Systems with Uncertainties

V. Shin (Korea)


Estimate, Kalman filter, adaptive filter, and parallel structure


This paper considers the problem of recursive estimation in linear discrete-time systems with uncertain observations. In [1], [2] we have proposed an optimal mean square combination of arbitrary number correlated and uncorrelated estimates. In this paper this result is applied to the adaptive filtering. The reduced-order robust filter with parallel structure is herein presented. In consequence of parallel structure of the filter the parallel computers can be used for their design. A lower computational complexity and lower memory demand are achieved with the proposed suboptimal filter than in optimal adaptive Lainiotis-Kalman filter. Example demonstrates the accuracy and efficiency of application of the new filter.

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