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Optimum differentiation using Kalman filter theory

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1 Author(s)

Consideration is given to the construction of an optimum differentiator to give the minimum-variance unbiased estimate of the first derivatives of random signals corrupted by white noise. It is assumed that the signals are differentiable and are the outputs of a known linear finite-dimensional (possibly time-varying) system excited by white noise. Extension of the results to consider higher-order differentiation is straightforward.

Published in:

Proceedings of the IEEE  (Volume:56 ,  Issue: 5 )