基于渐消卡尔曼滤波的井下人员定位模型研究  

Study on Model of Personnel Orientation in Coal Mine Based on Fading Kalman Filter

作　　者：杨宜辰[1] 李敬兆[1] 詹林[1] 

机构地区：[1]安徽理工大学计算机科学与工程学院,安徽淮南232001

出　　处：《计算机测量与控制》2014年第2期513-515,共3页Computer Measurement &Control

基　　金：国家自然科学基金(61170060);安徽省自然科学基金(11040606M135);安徽省高等学校自然科学基金重点项目(KJ2011A083)资助

摘　　要：对井下人员的准确定位是煤矿安全生产的必要条件之一,也是当前的研究热点问题.传统的定位算法精度较低,为了达到准确定位的目的,文章以无线传感网络中基于RSSI测距算法为基础,利用最大似然估计定位算法及渐消卡尔曼滤波算法,提出新的井下人员定位模型,并进行仿真实验;实验结果表明,相同实验环境下,该模型的定位误差在1 m左右,精度达到96%以上,均优于传统定位算法;该模型能够精确地对未知节点进行定位,验证了其有效性及正确性.Accurate personnel orientation is one of the conditions for safety production in coal mine, many research has focused on it. Traditional algorithms for locating have a low precision, in order to obtain a higher precision, a new model bases on the RSSI algorithm in wireless sensor network, the algorithm of maximum likelihood estimation and fading Kalman filter was presented for personnel orientation in coal mine. Simulation results show the model can locate unknown node accurately with an error about lm and the accuracy is more than 96%, it is better than the traditional one, and proved the model is effective and correct.

关 键 词：RSSI 卡尔曼滤波 人员定位 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]