Abstract: ‍ ‍In the process of multi-target tracking， when the targets have high maneuvering characteristics， it is difficult for traditional target tracking algorithms using fixed-motion models or interactive multi-models to accurately match the target motion model in real time， resulting in low tracking accuracy for high-maneuvering targets. To solve this problem， this paper proposes a high-mobility multi-target tracking algorithm based on adaptive updating of a target motion state model. In the process of multi-target tracking， a multi-feature clustering fusion algorithm is used to estimate the target motion model， and performs a state-transition matrix decision-making update based on the fluctuation parameters of each target being tracked. At the same time， the algorithm utilizes joint probabilistic data association to adaptively update the associated tracking of the multi-maneuvering target state transition matrix， thereby solving the problem of the low tracking accuracy caused by the mismatch of the target motion models in traditional multi-target tracking algorithms. In the sensor selection of the target tracking algorithm， passive sensors do not radiate energy， and have good low intercept probability performance， but their tracking accuracy is limited， and often cannot meet the multi-target high-tracking-accuracy requirements. As an active sensor， radar has high tracking accuracy. However， the external radiation energy of the radar makes it easy for a defender to intercept. In order to solve this problem， this paper proposes a multi-sensor cooperative management target-tracking algorithm based on passive sensor target tracking and supplementary active-radar intermittent tracking. The algorithm allocates sensors optimally by determining the intrinsic stacking error of the target tracking， and updates the state transition matrix based on the magnitude of the fluctuation parameters. Simulation results verified that the multi-sensor cooperative high-maneuvering target tracking algorithm proposed in this paper could effectively improve the low intercept-probability performance of radar while meeting the high-maneuvering target-tracking accuracy requirement.