The unmanned aerial vehicles (UAV) base station is most widely used as the emergency communication in response to emergencies. However, the performance improvement is in great demand at communication network. To improve the performance between the UAVs and the users, a novel method is proposed based on k-means++ algorithm and antenna adjusting. The established simulation platform and models are credible and reliable according to the very excellent approximation capability and the strong correlation between the simulation results and the Shannon’s formula. The transmission success rate for the three conditions (using only k-means++, antenna pointing optimization and antenna downtilt angle optimization) dramatically increases with an increase in k and all reach the maximum when k is equal to 5. The fan throughput of the proposed method is almost two times than that of the other two conditions after the k value exceeds 5. Meanwhile, the edge users’ rate and average user rate of the proposed method are all markedly increased. Overall, a novel method is provided for optimizing the performance between multi-UAVs and users, and the performance communication network for multi-UAVs is optimized by using the proposed method in this paper.
With the increasing demand for electric energy, more and more cities are constructing cable tunnels. In order to prevent the cable in the tunnel from being damaged, regular inspection of the cable tunnel is very important. However, due to the large scale of cable tunnel construction, the traditional manual inspection is difficult to meet the maintenance requirements. With the development of intelligent technology, the intelligent patrol mode of UAV has gradually replaced the traditional manual patrol mode and become the main patrol mode of cable tunnel. Therefore, the positioning and navigation method of cable tunnel UAV is studied in this paper. By using UWB localization algorithm and depth camera fusion, the positioning and navigation methods of UAVs are determined and compared with the positioning algorithm based on optical flow. Experimental comparison results show that the maximum and minimum yaw angles of UAV positioning based on the proposed algorithm are 2.41° and 0.16°, while the maximum and minimum yaw angles of UAV positioning based on the comparison algorithm are 3.11° and 1.51°. It can be seen that the integration of UWB and depth camera is of great significance for the research of positioning and navigation methods of cable tunnel UAVs.
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