An Improved Multi-Centroid Localization Algorithm for WiFi Signal Source Tracking

Abstract

Fishing WiFi hotspots are highly concealed and harmful. Traditional positioning algorithms often cannot be directly applied to the tracking and positioning of illegal signal sources due to high cost, difficulty in deployment, and low flexibility. In light of this, we proposed a positioning method of WiFi signal source, which is used in the scene of detecting and tracking fake APs. After collecting the signal data onto the idea of crowdsensing, the coordinates of the centroid of multiple groups is preliminarily calculated by the triangular centroid positioning method, and then the results are processed by the k-means clustering algorithm, and the appropriate weight value is selected according to the size of each cluster, and calculate the final result. The experimental results show that when the transmission path loss factor n=2, the average error of this method is only 34.389% of the triangular centroid location algorithm, and 56.346% of the weighted centroid location method. It not only ensures the accuracy of the calculation results, but also has strong anti-interference ability.