A non-line of sight localization method based on k-means clustering algorithm

Abstract

Wireless Sensor Networks (WSNs) is one of the front and research hotspot in the world, and it has been used more and more widely. But in the ground location, NLOS error which reduces the localization accuracy seriously has not been well-resolved. For this, a method based on K-means clustering algorithm and improved SA algorithm is proposed in this paper. The position function of unknown node based on TOA measurement model in LOS condition is established. Then identify and eliminate the measured value in NLOS condition using K-means clustering algorithm based method to improve the accuracy of the measured distance. In order to find the global optimal solution of the position function, we use an improved SA algorithm. Simulation results show that this method can reduce the effect of NLOS error and improve the location accuracy, and reduce the calculation at the same time.