RTODO-CL与高斯滤波的井下人员定位算法
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摘要
煤矿井下环境复杂多变,影响定位准确性的因素较多。为此,在结合RFID射频技术、无线载波技术与超低频电磁波技术的基础上,以TODO三点定位算法为基础建立数学模型,加入RSSI定位算法,利用高斯滤波有效地滤掉干扰信号,通过加入CL质心算法以缩小定位区域,使人员定位更为准确。结果表明:改进后的RTODO-CL能够对煤矿井下运动人员始终进行定位区域锁定,即改进后RTODO-CL算法不存在定位盲区,且改进后RTODO-CL算法定位精度明显高于改进前RTODO算法的定位精度。该研究能够对煤矿井下运动人员进行准确实时定位,一定程度上为煤矿井下信息采集及人员定位提供借鉴。
This paper is directed at addressing negative factors affecting the positioning accuracy due to more complex and variable environment in coal mine underground and affecting factors. The study building on the combination of RFID radio frequency technology,wireless carrier technology and ultra-low frequency electromagnetic wave technology involves developing the mathematical model based on TODO three-point positioning algorithm; effectively filtering out the interference signal using the RSSI localization algorithm and gaussian filtering; and thereby narrowing the positioning area by adding the CL centroid algorithm to ensure the more accurate positioning of the personnel. The results show that the improved RTODO-CL could provide a constant location of the positioning area of the coal mine underground sports personnel,meaning that the improved RTODO-CL algorithm eliminates the positioning blind zone;and the improved RTODO-CL algorithm could offer a significantly higher positioning accuracy than is possible with existing RTODO algorithm. The research could enable accurate and real-time positioning of underground coal mine sports personnel and could serve as a reference for coal mine underground information collection and personnel positioning.
This paper is directed at addressing negative factors affecting the positioning accuracy due to more complex and variable environment in coal mine underground and affecting factors. The study building on the combination of RFID radio frequency technology,wireless carrier technology and ultra-low frequency electromagnetic wave technology involves developing the mathematical model based on TODO three-point positioning algorithm; effectively filtering out the interference signal using the RSSI localization algorithm and gaussian filtering; and thereby narrowing the positioning area by adding the CL centroid algorithm to ensure the more accurate positioning of the personnel. The results show that the improved RTODO-CL could provide a constant location of the positioning area of the coal mine underground sports personnel,meaning that the improved RTODO-CL algorithm eliminates the positioning blind zone;and the improved RTODO-CL algorithm could offer a significantly higher positioning accuracy than is possible with existing RTODO algorithm. The research could enable accurate and real-time positioning of underground coal mine sports personnel and could serve as a reference for coal mine underground information collection and personnel positioning.
引文
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[4]Bao L J.Research on coordinate extraction of astronomical positioning oriented observation target image[J].Research on Personnel Location,2018,35(4):73-75.
[5]朱光.改进RSSI加权质心算法在井下人员定位中的应用研究[J].中国矿业,2018,36(12):198-201.
[6]Dai Q,Zhai L F,Tian Y,et al.Gaussian mixture filtering with variational optimization and its application in navigation[J].Filtering on Research,2018,12(12):1-8.
[7]罗志增,金晟,李阳丹,等.基于降噪源分离的脑电信号消噪方法[J].华中科技大学学报(自然科学版):2018,46(12):60-64.