In view of small radar scattering area and weak echo energy of weak targets, which lead to a large number of false-alarm clutters in the tracking process and the problem of false tracking and missed tracking, this paper proposes a GM-PHD algorithm assisted by amplitude information.By establishing amplitude likelihood functions of the weak target and the false-alarm clutter, the algorithm uses the amplitude information to improve the recognition rate of the target and the clutter, and improves the state estimation and potential estimation of the multiple targets.In addition, the algorithm is extended by Unscented Kalman Filtering (UKF) to adapt to nonlinear tracking.The simulation results show that the proposed algorithm has better performance on the multi-target's state estimation and potential estimation than the traditional algorithm of Gaussian mixture probability hypothesis filtering.