Abstract: Aiming at the problem of multi-UAV cooperative tracking dynamic targets under complex threat environment, a distributed model predictive control method with Multi-Strategy Improved Grey Wolf Optimization （MSIGWO）is proposed. By describing the problem of multi-UAV tracking dynamic flight target scenario and considering the constraints of UAV kinematics, relative kinematics, complex threats of battlefield, inter-aircraft distance and field-of-view sensors, etc., a mathematical model of multi-UAV cooperative tracking dynamic targets is established; a multi-UAV cooperative trajectory online optimization solution framework is designed based on distributed model predictive control, and an improved Grey Wolf algorithm is proposed as a distributed trajectory planning solution strategy. The diversity of population is enhanced by the control of parameter adaptive adjustment strategy, optimal position learning update strategy and jumping out of the local optimal solution strategy so as to improve the optimal solution capability of the algorithm； The effectiveness of the proposed strategy and method are validated by numerical and hardware-in-the-loop （HIL）simulations, and the simulation results show that the proposed multi-UAV distributed cooperative trajectory planning method can effectively avoid the dynamic environment obstacles and collaboratively track the dynamic target with better tracking performance.