Abstract
An algorithm (which does not involve the usual Riccati-type equation) for computing the gain matrices of the Kalman filter is presented. If the dimension k of the state space is much larger than that of the observation process, the number of nonlinear equations to be solved in each step is of order k rather than $k^2$ as by the usual procedure.

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