Three-dimensional personnel safety positioning based on improved UKF under complex coal mine environment

Aiming at the problems of strong interference and poor positioning accuracy in coal mines, this paper proposes a positioning algorithm for accurate detection of personnel safety. It is of great practical significance to detect the safety movement track of underground personnel. In this paper, WSNs distributed in coal mines are divided into several clusters by clustering method. Each cluster has a certain number of sensors, which can communicate with each other to keep the estimation consistency, and send the collected data to the cluster head (CH) node. System noise includes additive noise and multiplicative noise. In order to improve the accuracy of estimation, an improved UKF algorithm is proposed. The simulation results show that the improved UKF algorithm improves the accuracy and performance of estimation, and allows better location of the underground personnel.