A new approach, recursive incremental estimation, is presented for identification of time-varying systems. The basic idea is to assume implicitly a changing system model, instead of a constant one as with most variants of the standard least squares algorithm, and then to identify the characteristics of this model. The derived algorithm can enlarge the memory length of the estimator while maintaining tracking ability, so that some of the major problems experienced with the existing algorithms can be reduced.