矿井人员融合定位系统

Mine personnel fusion location system

  • 摘要: 针对基于传统接收信号强度指示(RSSI)指纹定位算法的井下人员定位系统在离线采样阶段指纹数据库采集工作量大、易受井下环境影响,基于行人航迹推算(PDR)算法的定位系统存在误差累计的问题,设计了一种基于改进RSSI指纹定位算法和PDR算法的矿井人员融合定位系统。该系统采用GS1011控制器和MPU9150惯性传感器构成智能终端,将采集的惯性传感器、RSSI和时间戳数据通过井下WiFi网络上传至地面监控中心定位服务器;定位服务器采用扩展卡尔曼滤波对RSSI指纹定位算法和PDR算法的定位信息进行融合,实现井下人员定位。试验结果表明,该系统平均定位误差为1.79 m,小于单独采用RSSI指纹定位算法或PDR算法的系统定位误差,定位精度满足井下人员定位要求。

     

    Abstract: For problems that mine personnel location system based on traditional received signal strength indication (RSSI) fingerprint location algorithm had heavy workload in fingerprint database collection during off-line stage and was easily influenced by underground environment, and the location system based on pedestrian dead reckoning (PDR) algorithm had accumulative error, a mine personnel fusion location system was proposed which was based on an improved RSSI fingerprint location algorithm and PDR algorithm. The system uses intelligent terminals consisting of GS1011 controller and MPU9150 inertial sensor to send the data of inertial sensor, RSSI and timestamp to location server on the ground through underground WiFi network. The location server fuses location information of RSSI fingerprinting location algorithm and PDR algorithm by use of extended Kalman filter, so as to realize underground personnel location. The test result shows that the average location error of the system is 1.79 m and smaller than the one of RSSI fingerprint location algorithm or PDR algorithm, and location accuracy satisfies underground personnel location requirement.

     

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