Coal mine underground personnel localization algorithm based on LQI filter and joint parameters estimation

Existing RFID-based underground personnel localization systems have the problems of low positioning accu- racy,low noise immunity and other issues. In order to enhance the accuracy and environmental adaptation of the coal mine underground personnel localization algorithm,this paper proposes a RSSI ( received signal strength indication) joint parameters estimation and localization algorithm based on LQI (link quality indication) filter in the ZigBee com- munication protocol framework. The proposed algorithm first uses the LQI as the smoothing filter to process the original RSSI data collected from ZigBee chips,and then estimates the RSSI channel parameters combined with environmental noise parameter. Moreover,the environmental noise parameter is used to compensate the estimated distance. Finally,it gets the localization results via the least square method. Through taking the potential of existing hardware equipments and paying more consideration to the effects of environment,the proposed algorithm effectively improves the accuracy of localization. The effectiveness of the algorithm is confirmed by simulation based on the ZigBee hardware platform. Compared with the original RSSI location algorithm,the mean square error of the proposed algorithm is reduced by a- bout 10% .