Abstract
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.
Highlights
Coal resources are the driving force of economic development [1]
Each cluster has a certain number of sensors, the sensors send data to the cluster head (CH) node, and the sensors nodes can communicate with each other, so as to ensure the consistency and accuracy of the estimation [15-18]
It can be seen from the figure that the estimated trajectory obtained by the improved unscented Kalman filter (UKF) algorithm is closer to the real trajectory
Summary
Coal resources are the driving force of economic development [1]. To ensure the efficient and safe production of coal industry is a very concerned issue of the state and relevant departments [1-5]. The underground positioning system based on RFID technology relies on wired transmission system, which greatly limits the expansion of network scale. In [8], a coal mine underground positioning system based on wireless sensor networks (WSNs) is adopted. In [19], a positioning method of mine personnel based on Kalman filter (KF) is proposed. In [20], an EKF algorithm based on event triggering is proposed. In [22], an improved UKF algorithm with limited communication bandwidth is proposed, only part of the measured output can be transmitted to the remote estimator. Based on the above analysis, this paper adopts an improved UKF algorithm based on three-dimensional underground personnel safety positioning. Considering the complex interference problem in coal mine environment, an improved UKF algorithm with event triggering is proposed to improve the positioning accuracy and solve the complex interference problem
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