Adaptive state estimation for systems with unknown noise covariances

An adaptive scheme is proposed for obtaining the steady-state Kalman gain matrix for o discrete-time system without a priori knowledge of the noise covariance matrices. It is based on combining an algorithm proposed recently by Carew and Bélanger with an algorithm based on stochastic approximation. Results of simulation are given comparing the proposed method with earlier algorithms.