The unmanned aerial vehicle features with high flexibility and easy deployment. It could be used as an air base station and provide fast communication services for the ground users. It plays an important role in some special occasions such as natural disasters, emergency communications and temporary large-scale activities. A single unmanned aerial vehicle equipped with base station has limited range of services, but a multiple unmanned aerial vehicle equipped with base station network can serve a wider range of users. The research goal of unmanned aerial vehicle equipped with base station network coverage control is to maximize the network coverage under the condition of maintaining the service quality. In view of the low dynamic coverage ratio of unmanned aerial vehicle equipped with base station network, this article proposes a relative distance–based unmanned aerial vehicle equipped with base station deployment method. The unmanned aerial vehicle realizes on-demand coverage and maintains a stable network topology under the influence of three relative distances by sensing the uncovered area of the ground, the neighbouring unmanned aerial vehicles and the location of the coverage boundary or obstacles. In addition, the algorithm is also adapted to a variety of scenarios. The simulation results show that the coverage of the proposed algorithm is 22.4% higher than that of random deployment, and it is 9.9%, 4.7% and 2.1% higher than similar virtual force-oriented node, circular binary segmentation and hybrid local virtual force algorithms.

中文翻译：

---

基于相对距离的无人机车载基站传感器网络覆盖方法

该无人机具有灵活性高、部署方便等特点。它可以用作空中基站，为地面用户提供快速通信服务。在自然灾害、应急通信、临时性大型活动等特殊场合发挥着重要作用。单架配备基站的无人机服务范围有限，但配备基站网络的多架无人机可以服务更广泛的用户。无人机搭载基站网络覆盖控制的研究目标是在保持服务质量的情况下最大化网络覆盖。针对搭载基站网络的无人机动态覆盖率低，本文提出了一种基于相对距离的无人机搭载基站部署方法。无人机通过感知地面未覆盖区域、邻近无人机以及覆盖边界或障碍物的位置，实现按需覆盖，并在三个相对距离的影响下保持稳定的网络拓扑。此外，该算法还适用于多种场景。仿真结果表明，所提算法的覆盖率比随机部署算法的覆盖率高22.4%，比同类虚拟力导向节点、圆形二元分割和混合局部虚拟力算法分别高9.9%、4.7%和2.1% . 无人机通过感知地面未覆盖区域、邻近无人机以及覆盖边界或障碍物的位置，实现按需覆盖，并在三个相对距离的影响下保持稳定的网络拓扑。此外，该算法还适用于多种场景。仿真结果表明，所提算法的覆盖率比随机部署算法的覆盖率高22.4%，比同类虚拟力导向节点、圆形二元分割和混合局部虚拟力算法分别高9.9%、4.7%和2.1% . 无人机通过感知地面未覆盖区域、邻近无人机以及覆盖边界或障碍物的位置，实现按需覆盖，并在三个相对距离的影响下保持稳定的网络拓扑。此外，该算法还适用于多种场景。仿真结果表明，所提算法的覆盖率比随机部署算法的覆盖率高22.4%，比同类虚拟力导向节点、圆形二元分割和混合局部虚拟力算法分别高9.9%、4.7%和2.1% . 邻近无人机以及覆盖边界或障碍物的位置。此外，该算法还适用于多种场景。仿真结果表明，所提算法的覆盖率比随机部署算法的覆盖率高22.4%，比同类虚拟力导向节点、圆形二元分割和混合局部虚拟力算法分别高9.9%、4.7%和2.1% . 邻近无人机以及覆盖边界或障碍物的位置。此外，该算法还适用于多种场景。仿真结果表明，所提算法的覆盖率比随机部署算法的覆盖率高22.4%，比同类虚拟力导向节点、圆形二元分割和混合局部虚拟力算法分别高9.9%、4.7%和2.1% .