A modified adaptive Kalman filter for real-time applications

A modified adaptive Kalman filtering algorithm is derived for the standard linear problem under an irregular environment where all variances of the zero-mean Gaussian white (system and observation) noises are unknown a priori. This algorithm has certain merits over various existing adaptive schemes in that it is simple, efficient, and suitable for real-time applications. An illustrative numerical example is presented