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Comments on "Identification of optimum filter steady-state gain for systems with unknown noise covariances"

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2 Author(s)
Neethling, C. ; University of Cambridge, Cambridge, England ; Young, P.

The approach to the estimation of the optimum Kalman filter steady-state gain proposed by Mehra and modified by Carew and Belanger can be improved by noting the true statistical nature of the problem. A new approach based on both simple or weighted least squares is outlined and tested by Monte Carlo simulation.

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Automatic Control, IEEE Transactions on  (Volume:19 ,  Issue: 5 )