Estimation of noise covariance matrices for a linear time-varying stochastic process

Authors:
Pierre R. Bélanger
Affiliations:
Department of Electrical Engineering, McGill University, Montreal, Canada
Venue:
Automatica (Journal of IFAC)
Year:
1974

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Abstract

An algorithm is given to estimate the noise covariance matrices for a linear, discrete, time-varying stochastic system. If these matrices are linear with respect to a set of aparameters, it is found that the correlation products of the innovations sequence is also linear in these parameters. The fact is used to derive a least-squares algorithm, which takes a particularly simple form in the stationary case. Two examples are given.