为提高稀疏的无人机自组网络中的链路稳定性,采用短时轨迹交互,提出三维空间中具有更准确节点位置预测的贪婪路由协议.根据无人机短时运动的稳定性和短时运动轨迹的可知性,各节点对自身运动轨迹三维曲线拟合后交互拟合系数和运动参数完成邻近节点间的移动性预测,进而利用移动性预测获得的拓扑信息实现贪婪转发,优化链路选择,提高数据包可达率.同时,采用携带转发策略解决稀疏场景下的路由空洞问题.仿真结果表明,与传统的GPSR路由协议相比,所提协议具有更高的数据投递率和更低的端到端传输时延.%In order to improve the link stability of sparse UAV ad hoc networks, a greedy routing protocol with more accurate node position prediction in three-dimensional space is proposed by using temporal track interaction method. According to the temporal motion stability of UAV and temporal knowable trajectory, each node shares its motion parameters and fitting coefficients of the curve, fits the three-dimensional trajectory of curve fitting, and predicts the motion of its neighbors or the destination node. Then, the greedy forwarding is realized in accordanc with the topological information acquired from motion prediction, thus to optimize link selection and improve the packet delivery rate. Meanwhile the carry-forward strategy solves the problem of routing hole in the sparse networks. Simulation results indicate that, compared with the traditional GPSR routing protocol, the proposed protocol has higher data delivery rate and lower end-to-end transmission delay.
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