Improved Self-Location Algorithm of Wireless Sensor Network Based on Unmanned Aerial Vehicle

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 373-375)
• Pages: 367-372
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.373-375.367
• Online since: August 2013
• Authors: Yun Zhou Zhang, Dong Fei Wei, Ze Yu Wang
• Keywords: Curve Fitting, Maximum Likelihood-Estimation (MLE), Self-Localization, Unmanned Aerial Vehicle (UAV), Wireless Sensor Network (WSN)

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