摘要
为解决煤矿井下动态环境下传统指纹匹配算法定位精度较低的问题,提出了基于贝叶斯模糊概率的指纹匹配定位算法。该算法在煤矿井下建立基于校准节点的可靠度机制,用校准节点发射锚节点接收的信号强度来衡量待定位区域无线信道传输环境变化的情况;将待测点的可靠度与贝叶斯后验概率作为模糊系统的输入,计算模糊概率作为参考点的权值计算出待测点的坐标。以井下巷道实测数据进行的试验仿真结果表明,基于贝叶斯模糊概率的指纹匹配定位算法的定位精度较贝叶斯指纹匹配定位算法的精度约提高17%,满足井下复杂动态环境的高定位精度。
In order to solve the problem of low positioning accuracy of traditional fingerprint matching algorithm in underground dynamic environment of coal mine,a fingerprint matching positioning algorithm based on Bayesian fuzzy probability was proposed.In this algorithm,the reliability mechanism based on calibration node was established in underground coal mine,and the signal strength received by the calibration node transmitting anchor node was used to measure the change of wireless channel transmission environment in the area to be located.The reliability of the point to be measured and Bayesian posterior probability were taken as the input of the fuzzy system,and the fuzzy probability was taken as the weight of the reference point to calculate the coordinates of the point to be measured.The simulation results based on the measured data of underground roadway show that,the positioning accuracy of the fingerprint matching algorithm based on Bayesian fuzzy probability is about 17%higher than that based on the Bayesian fingerprint matching algorithm,which can meet the high positioning accuracy of the complex dynamic environment in underground mine.
作者
崔丽珍
郭倩倩
王巧利
杨勇
CUI Lizhen;GUO Qianqian;WANG Qiaoli;YANG Yong(School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou,Inner Mongolia 014010,China)
出处
《矿业研究与开发》
CAS
北大核心
2021年第5期162-167,共6页
Mining Research and Development
基金
国家自然科学基金项目(61761038)
内蒙古自然科学基金项目(2020MS06027)
内蒙古自治区科技计划项目(2019GG328).
关键词
地下矿山
可靠度
模糊推理
贝叶斯模糊概率
指纹匹配定位
Underground mine
Reliability
Fuzzy reasoning
Bayesian fuzzy probability
Fingerprint matching positioning
