New recursive parameter estimation algorithms with varying but bounded gain matrix

The main disadvantage of the standard recursive weighted least-squares algorithm is the unbounded increase in its gain matrix when the covariance vector is not sufficiently rich. We propose a general method for updating the gain matrix. This allows us to derive many new specific algorithms in which the boundedness of the gain matrix is ensured automatically.