GNSS拒止下低空无人机导航与资源分配优化

摘要：针对低空无线网络（LAWN）在全球导航卫星系统（GNSS）拒止与机载射频资源受限下面临的挑战，研究无人机自主到位及部署后受限资源下的服务问题。导航阶段，基于地面参考锚点的方位几何特征，提出纯角度制导策略，使无人机在无卫星导航信号辅助下精确抵达目标阵位。通信阶段，针对机载发射功率与射频链路受限的问题，以最大化系统有效服务用户数为目标，构建联合用户调度与波束赋形的资源分配模型，并提出一种基于交替优化（AO）、逐次凸逼近（SCA）和半定松弛（SDR）的高效算法。仿真实验验证了该方案的有效性：导航算法能以递减的角度误差实现可靠的目标捕获，且联合资源分配策略在不同功率预算与速率门限下显著提升了系统的服务性能。

关键词：LAWN；GNSS拒止；用户调度；波束赋形

Abstract: Addressing the challenges of global navigation satellite system (GNSS) denial and constrained onboard radio frequency resources in low-altitude wireless networks (LAWNs), this work investigates autonomous drone positioning and subsequent multi-user communication services under limited resources. In the navigation phase, an angle-only guidance strategy is proposed based on bearing geometry from ground reference anchors, enabling the drone to precisely reach the target location without satellite navigation signals. In the communication phase, to tackle the limitations of onboard transmit power and radio frequency links, a joint user scheduling and beamforming resource allocation model is formulated to maximize the number of effectively served users. An efficient algorithm based on alternating optimization (AO), successive convex approximation (SCA), and semidefinite relaxation (SDR) is developed. Simulation results validate the effectiveness of the proposed scheme: the navigation algorithm achieves reliable target acquisition with decreasing angle errors, and the joint resource allocation strategy significantly improves system service performance under various power budgets and rate thresholds.

Keywords: LAWN; GNSS-denied; user scheduling; beamforming