A new off-line identification algorithm capable of estimating system parameters varying in a discontinuous way is described. The proposed method, based on the concept referred to as competitive smoothing, combines in a nonlinear fashion the estimates yielded by two Kalman filters running forward and backward in time, respectively. Extensions to banks of several Kalman filters (each filter designed for different hypothetical rate of parameter variation) are also discussed and results of computer simulations are presented.