一种改进的煤矿井下指纹定位匹配算法  

An Improved Location Fingerprint Localization Matching Algorithm in Coal Mine

作　　者：李论[1,2] 丁恩杰[1,2] 郝丽娜[1,2] 张雷[1,2] 

机构地区：[1]中国矿业大学信息与电气工程学院,江苏徐州221116 [2]中国矿业大学物联网(感知矿山)研究中心,江苏徐州221008

出　　处：《传感技术学报》2014年第3期388-393,共6页Chinese Journal of Sensors and Actuators

基　　金：国家科技支撑计划资助项目(2012BAH12B01;2012BAH12B02);国家高技术研究发展计划(863)资助项目(2013AA06A411)

摘　　要：煤矿井下环境复杂多变,对人员精确定位技术挑战很大。目前矿井巷道中采用基于接收信号强度指示RSSI(Received Signal Strength Indication)的位置指纹定位算法存在定位目标漂移、抖动和定位精度不高等问题。提出一种改进的指纹定位匹配算法,该算法将K邻近算法和最短历史路径匹配法联合并利用速度限定位置估计补偿算法对定位精度进行修正。利用在煤矿巷道中的实测数据,对改进的匹配算法进行了验证与误差分析。仿真结果表明,改进后的算法能够提高定位精度,满足矿井人员定位、目标跟踪和目标轨迹查询等要求。The environment of coal mine is very complicated,which requires great accuracy of personnel positioning. Currently,in the mine roadway,the location of the fingerprint localization algorithm based on RSSI（ Received Signal Strength Indication） has some deficiencies, such as targeting drift, jitter, and low positioning accuracy. This paper proposes a modified matching localization algorithm. This algorithm combines K nearest neighbor algorithm with the shortest historical path matching and uses speed-limited location estimation compensation algorithm to correct the positioning accuracy. Based on the authentic-measured data from the coal mine tunnel, this article verifies and analyses the error for the improved matching algorithm. The simulation results show that the improved matching algorithm can improve positioning accuracy and meet the requirements of mine personnel positioning, target tracking,and target trajectory querying.

关 键 词：无线传感器网络 指纹定位 矿井巷道 匹配算法 

分 类 号：TP929.4[自动化与计算机技术]