Maneuvering targets are difficult for the Kalman filter to track since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a wildly maneuvering target, several schemes had been proposed and improved the tracking performance in some extent. In this paper a Kalman filter-based scheme is proposed for maneuvering target tracking. The proposed scheme estimates the target acceleration input vector directly from the feature of maneuvering target trajectories and updates the simple Kalman tracker by use of the acceleration estimates. Simulation results for various target profiles are analyzed for a comparison of the performances of our proposed scheme with that of conventional trackers.