Abstract: Multifunctional phased array radar has the advantages of strong flexibility and tracking ability. In order to improve the accuracy of the phased array radar target tracker, the scientific management of energy regulation and task execution of the phased array radar is carried out. The time and resource management of searching and tracking is realized by adjusting the return rate of maneuvering targets and non-maneuvering targets reasonably. In this paper, a generalized probability data association（GPDA-IMM） algorithm is designed with a small computational load. IMM combines the features of untracked and volumetric Kalman filter and particle filter multi-model filter, and optimizes the weight factor to achieve better tracking performance. Finally, through the simulation platform, the realistic scenes of eight moving targets were simulated, and a large number of simulation experiments were carried out combining time management and target tracking to adjust the return rate, proving the effectiveness and practicability of the algorithm for different target types and maneuvering states.