Discrete-time linear time-varying systems are modeled by discrete-time wavelets. The output of the unknown system is corrupted by noise. The system model parameters are estimated by the least-squares method applied to the output error. Conditions are derived that provide vanishing influence of the output noise to the parameter estimates. Due to the time-frequency selectivity of wavelets, parameter estimates can be robust to narrow-band noise and/or impulse noise. This robustness is confirmed by simulations.