This paper prolposes a VFM (Variable Fading Memory)Kalman filtering and applies it to the parameter estimation for time-varying signals. By adaptively calculating the fading memory, the proposed algorithm does not require any predetermined fading memory when estimating the time-varying signal parameter. Moreover, the proposed algorithm has faster convergence speed than fixed fading memory one in case the signal contains an impulsive outlier. The performance of parameter estimation for time-varying signal is evaluated by computer simulation for two cases, one of which is the chirp signal whose frequency varies linearly with time and the other is the chip signal with an impulsive outlier. The experimental results show that the VFM Kalman filtering estimates the parameter of the chirp signal more rapidly than the fixed fading memory one in the region of an outlier.