In response to the problem of heterogeneous multi aircraft collaborative task allocation and route estimation, a heterogeneous multi aircraft collaborative task allocation and route estimation model is constructed by comprehensively considering task time, task timing, onboard performance, route feasibility, route smoothness, and multi aircraft collaborative constraints. The model is coupled with task slicing and embedded with continuous quantum locust optimization algorithm to estimate route range, and external discrete quantum annealing algorithm to coordinate task allocation, ensuring tight coupling between collaborative task allocation and route estimation, and overall optimizing the cost and benefits of multi aircraft collaborative operations. The simulation results show that this method can pseudo synchronize the allocation of reasonable task objectives and effective navigation routes for each aircraft, in order to maximize the collaborative operation efficiency of drone formations. This method serves the centralized unmanned aerial vehicle formation control system and can provide optimization instructions for formation coordination.