Research On Data Acquisition And Monitoring Scheduling Technology Based On UAV Platform

The high mobility,maneuverability,strong coverage and ease of deployment of UAVs have led to a proliferation of applications based on UAV platforms in many fields.For example,power inspection,UAV data collection and transmission,post-disaster aerial base stations,and edge computing have led to the rapid development of UAV application fields,and many products based on UAV platforms have been developed,and related UAV application scenarios are becoming more and more abundant.However,in the field of UAV coverage communication and sensor data acquisition and transmission,the limited energy of UAVs brings the limitation of endurance that shackles the application performance of UAVs.Obviously,improving the energy efficiency of UAVs in performing missions and enhancing the range of UAVs in attempting specific missions by optimizing the design under a given UAV range condition is one of the key issues that UAVs need to address.In this paper,five chapters are arranged,in which the UAV applications and research developments are introduced,the flight energy consumption and commication energy consumption characteristics of UAV performance are analyzed,the flight energy consumption of UAVs is analyzed according to the channel model and the UAV power equation,and the relationship between the flight speed and power consumption of fixed-wing UAVs and rotary-wing UAVs.Based on the above analysis,the thesis conducts an in-depth study on the data collection path planning and long-term monitoring application requirements based on the UAV platform,and proposes the deployment strategy and work plan of system of UAVs based on particle swarm algorithm for better efficiency on the basis of long-term monitoring.Chapter 3,based on the premise of a given ground sensor node,in the ground sensor because of the actual situation of the scene as well as its own energy consumption constraints,can not be networked with each other,need to fly the UAV to a certain range of points from the sensor in order to communicate,here we assume that the UAV needs to fly over the sensor in order to communicate and transmit data.Based on the energy consumption constraint of UAVs themselves,the paper proposes a node partitioning strategy,which divides a whole region into multiple disjoint regions and can reduce the path planning problem of multiple UAVs to the path planning problem of multiple single UAVs.The node partitioning strategy can also simultaneously equalize the task load of each UAV,reduce the number of UAVs required for a complete task,and ensure that each UAV completes the data collection task within the specified time.The combination of heuristic algorithm(GA)and node partitioning strategy used in this chapter ensures that each UAV adopts the shortest flight path to improve the UAV endurance,and the optional task balancing strategy can also effectively balance the task load of each UAV to improve the overall performance of the UAV system.Chapter 4 addresses the contradiction between the limited range of UAVs and the need for long-term monitoring of monitoring sites,and proposes a long-term monitoring work-charge cycle strategy based on rechargeable UAVs.Based on the communication needs of the multi-UAV system a multi-UAV work-charge cycle strategy based on the PSO algorithm is proposed,which is divided into two steps to simplify the difficulty of optimizing the algorithm operation,and optimized for the UAV deployment location and the UAV work-charge cycle strategy separately.The long endurance scheme of UAVs proposed in this chapter can make the UAS maintain long-term uninterrupted monitoring.Finally,Chapter 5 of the thesis summarizes the content of the research work in this paper based on the outlook for future research work on UAV energy efficiency optimization.