This paper aims at the beam scheduling management problem of phased array radar in the process of multi-target tracking, and in the traditional beam scheduling, only the target with the smallest error among all targets is optimized, which leads to the problem that some targets with larger errors will not converge or even be lost when facing high maneuvering targets.In view of this, a radar beam scheduling algorithm based on maximum average covariance is proposed, which combines the advantages of the Interactive Multi-Model (IMM) filtering algorithm with that of phased array radar without inertial sampling,to realize beam scheduling for stable tracking of multiple targets,and study the effect of expected covariance and process error covariance (noise error) on the tracking process.The simulation experiments show that the algorithm can effectively keep the covariance of multiple high maneuvering targets within the expected range and achieve dynamic convergence, and can affect the confidence and convergence speed of the tracking process by adjusting the expected covariance and process error covariance, so as to achieve stable tracking of multiple targets.