The original Moose estimator suffers from large performance degradation when there is plant-filter mismatch. To alleviate his, we propose a Moose estimator which compensates for plant-filter mismatch, and show by the Monte-Carlo simulation that the proposed estimator performs much better than the original Moose estimator in the case of plant-filter mismatch, especially when the sampling interval is relatively small.