Recursive fading memory filtering

A recursive, fading memory filter for time-continuous and time-discrete systems is presented as a means for overcoming the destructive influence of model errors in Kalman filter applications that lead to the occurrence of divergence. This fading memory filter is shown to be uniformly asymptotically stable under basically the same conditions as the Kalman filter and bounds on the error covariance matrix of the filter are given. An adaptive procedure for implementing the procedure is discussed in terms of a scalar example. The ease of implementation of this filter and the highly satisfactory nature of numerical results indicate the efficacy of the procedure as a desirable recursive data processing method.