In this paper, we propose a wireless sensor network self-location improved algorithm based on the Unmanned Aerial Vehicle (UAV). The path and the signal emission mechanism of the UAV are rational planning. The k-3 covering method is used to programming the working point and the path of UAV. We also set up a wireless sensor network localization experiment platform based on the UAV and then we carry on several experimentations and curve fitting on the surface-to-surface and surface-to-air distance curve. Experimental results show that the self-location system built based on the theories this paper proposed has an air-to-surface actual distance error of 4.42m and the algorithms positioning error is 3.67m which has very high work efficiency.
Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases
