Navigation problems of unmanned air vehicles (UAVs) flying in a formation have been investigated recently, where collision avoidance is a significant issue to be addressed. In this paper, we study resource allocation and power control for radar sensing in a multi- unmanned aerial vehicle (multi-UAV) formation flight system where multiple UAVs simultaneously perform radar sensing. To cope with mutual radar interference among the UAVs, we formulate a joint channel allocation and UAV transmission power control problem to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of the radar echo signals. We then propose a computationally practical method to solve this NP-hard problem by decomposing it into two sub-problems, i.e., channel allocation and transmission power control. An iterative channel allocation and power control algorithm (ICAPCA) is proposed to jointly solve these two sub-problems. We also propose a reduced-complexity greedy channel allocation algorithm (GCAA), which can also be used to provide an initial solution to ICAPCA. Simulation results show that the proposed ICAPCA and GCAA can improve the minimum SINR and radar sensing performance significantly.

最近研究了编队飞行的无人驾驶飞行器 (UAV) 的导航问题，其中避免碰撞是一个需要解决的重要问题。在本文中，我们研究了多无人机（multi-UAV）编队飞行系统中雷达传感的资源分配和功率控制，其中多个无人机同时执行雷达传感。为了应对无人机之间的雷达相互干扰，我们制定了联合信道分配和无人机发射功率控制问题，以最大化雷达回波信号的最小信干噪比（SINR）。然后，我们提出了一种计算上实用的方法来解决这个 NP 难题，将其分解为两个子问题，即信道分配和传输功率控制。提出了一种迭代信道分配和功率控制算法（ICAPCA）来联合解决这两个子问题。我们还提出了一种降低复杂度的贪婪信道分配算法（GCAA），该算法也可用于为 ICAPCA 提供初始解决方案。仿真结果表明，提出的 ICAPCA 和 GCAA 可以显着提高最小 SINR 和雷达传感性能。