基于机器学习链路权重优化的无人机网络路由算法OACSTPCD

To accelerate communication procedure of OODA loop in the scenario of distributed mosaic warfare,we propose a novel unmanned aerial vehicle(UAV)routing algorithm based on machine learning-enabled link weight optimization in this paper.Our algorithm first constructs the communication completion time model for the procedure of OODA loop.Then,to minimize the communication completion time of OODA loop,the algorithm leverages the gradient descent method of ma-chine learning to achieve link weight optimization for UAV cluster network distributed routing.Computer simulation results show that,compared with the current UAV routing algorithm,our algorithm can observably shorten the communication time of OODA loop,and increase the rate of packet success transmission.