Multiple Target Tracking (MTT) is one of the most challenging topics in radar target tracking. In addition to conventional position measurements, the integration of target Doppler and power information can offer valuable insights into a target’s kinematic state, thereby improving tracking performance. This article discusses a tracking approach that incorporates those components into the measurement enhancement process and assesses the advantages of the proposed strategy. Firstly, we investigated an improved data association scheme that exploits statistical features of position, Doppler and power. The estimated Doppler value calculated from the target range and timestamp will be compared with the measured Doppler to deal with the Doppler ambiguity situation. Secondly, we studied an augmented unscented Kalman filter (UKF) algorithm using position, Doppler measures, and the indirect measure of radial velocity in the linear domain. The experimental results show that the proposed solution has good performance in terms of reduced number of false tracks and improving the accuracy of the target state estimation.