Design Of Software For UAV Ground Control Station

Recent years, with the expansion of the research and applications of the Unmanned Aerial Vehicle (UAV) in the world, Ground Control Station (GCS) as the nerve center of an UAV system is continuously updated and developed. According to the research of functions and key technologies of GCS, a set of software was designed under the background of the actual project in this paper. Many functions were achieved in this system, such as flight monitoring, route planning, serial port communication, historical data analysis, control parameters binding and so on.Firstly, the overall software solution was introduced in concision based on in-depth analysis of functional requirements and current status of the GCS. Then a simple and intuitive human-machine interface was designed using GMS and NI virtual instrument control to provide visual data display and effective real-time control. Combined with MapX secondary development technology, the position and route of UAV can be displayed in the electronic map. A series of secure and reliable communication protocol was established, which provided end-to-end security session between UAV and GCS. Based on this protocol, serial port communication was realized by a serial communication class named CSerialPort provided by the third party. Utilizing the ADO technology to set up the interface of access database, data storage and off-line query were realized. Historical data can be processed and displayed graphically by means of the hybrid programming technology of VC++with MATLAB. In addition, the flight control parameters can be adjusted and edited on-line to improve decision efficiency.For route planning of UAV, appropriate planning space model was built. Different types of threads that may emerge during the UAV performing mission were analyzed, and the mathematical model of radar thread was established. Several common route planning algorithms were introduced, among which the A* algorithm was emphasized and improved. The global performance of the algorithm was improved by introducing constrains and self-adaptive heuristic into A* algorithm. Finally, the route planning algorithm with appropriate cost function was simulated by means of MATLAB.At the end of the paper, a series of simulations and outdoor experiments were conducted. It was proved that the entire system ran well and met the functionality and stability through practice.