基于UKF的深井监测移动节点定位算法
发布时间：2019-08-07 16:33
【摘要】：针对线性系统理论的监测定位技术误差较大且又无法实时监测深井人员及移动设备的位置问题,提出一种基于非线性函数不敏卡尔曼滤波(UKF)移动节点定位算法(U-MPA)。在建立U-MPA监测系统及巷道模型的基础上,采用UKF方法对RSSI滤波测距,通过局部坐标系,实现对移动节点实时定位监测;同时,通过改变锚节点间距密度,实现不同定位精度要求。仿真实验表明:U-MPA算法相比RSSI算法定位误差有明显减小,U-MPA算法的平均定位偏差为RSSI算法的44%。
[Abstract]:In order to solve the problem that the monitoring and positioning technology of linear system theory has large error and can not monitor the position of deep well personnel and mobile equipment in real time, a (UKF) mobile node location algorithm based on nonlinear function unsensitive Kalman filter (U-MPA) is proposed. On the basis of establishing U-MPA monitoring system and roadway model, UKF method is used to filter distance measurement for RSSI, and real-time positioning monitoring of mobile nodes is realized through local coordinate system. At the same time, different positioning accuracy requirements are realized by changing the spacing density of anchor nodes. The simulation results show that the positioning error of U-MPA algorithm is obviously lower than that of RSSI algorithm, and the average positioning deviation of U-MPA algorithm is 44% of that of RSSI algorithm.
【作者单位】： 南华大学环境保护与安全工程学院;金属矿山安全与健康国家重点实验室;湖南省铀尾矿库退役治理技术工程技术研究中心;
【基金】：金属矿山安全与健康国家重点实验室开放基金项目(2016-JSKSSYS-04) 湖南省教育厅科研重点项目(15A161) 湖南省重点研发项目(2015SK2005) 南华大学环境保护与安全工程学院研究生科研创新项目(2017YCXXM08);南华大学大学生研究性学习和创新性实验计划项目(2017XJYZ029)
【分类号】：TD76
本文编号：2524061
[Abstract]:In order to solve the problem that the monitoring and positioning technology of linear system theory has large error and can not monitor the position of deep well personnel and mobile equipment in real time, a (UKF) mobile node location algorithm based on nonlinear function unsensitive Kalman filter (U-MPA) is proposed. On the basis of establishing U-MPA monitoring system and roadway model, UKF method is used to filter distance measurement for RSSI, and real-time positioning monitoring of mobile nodes is realized through local coordinate system. At the same time, different positioning accuracy requirements are realized by changing the spacing density of anchor nodes. The simulation results show that the positioning error of U-MPA algorithm is obviously lower than that of RSSI algorithm, and the average positioning deviation of U-MPA algorithm is 44% of that of RSSI algorithm.
【作者单位】： 南华大学环境保护与安全工程学院;金属矿山安全与健康国家重点实验室;湖南省铀尾矿库退役治理技术工程技术研究中心;
【基金】：金属矿山安全与健康国家重点实验室开放基金项目(2016-JSKSSYS-04) 湖南省教育厅科研重点项目(15A161) 湖南省重点研发项目(2015SK2005) 南华大学环境保护与安全工程学院研究生科研创新项目(2017YCXXM08);南华大学大学生研究性学习和创新性实验计划项目(2017XJYZ029)
【分类号】：TD76
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