Research Article
Artificial Intelligence-Based Wireless Sensor Network Radio Frequency Signal Positioning Method
@INPROCEEDINGS{10.1007/978-3-030-67871-5_6, author={Zhao Dan and Qu Ming-fei}, title={Artificial Intelligence-Based Wireless Sensor Network Radio Frequency Signal Positioning Method}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I}, proceedings_a={ADHIP}, year={2021}, month={2}, keywords={Artificial intelligence Wireless sensor network Radio frequency signal Doppler effect Node location}, doi={10.1007/978-3-030-67871-5_6} }- Zhao Dan
Qu Ming-fei
Year: 2021
Artificial Intelligence-Based Wireless Sensor Network Radio Frequency Signal Positioning Method
ADHIP
Springer
DOI: 10.1007/978-3-030-67871-5_6
Abstract
Aiming at the problem of low positioning accuracy of existing wireless sensor network node positioning methods, a distributed node positioning method based on radio frequency interference is proposed. Analyze the structure of the wireless sensor network, use two anchor nodes to form a radio frequency interference field, and use the movement of one of the anchor nodes to generate the Doppler effect, so that each node can obtain the instantaneous frequency indicated by its low frequency received signal field strength the angle information with the mobile anchor node, combined with the geographic location of the anchor node, the node merges multiple sets of positioning angle information to obtain the optimal position estimate. The simulation results show that, compared with other localization methods, the positioning accuracy of this method is significantly improved, and the localization time of radio frequency signal in wireless sensor networks is shortened.
