摘要
为解决变电站非视距(non line of sight,NLOS)严重条件下超宽带定位精度低的问题,基于现有到达时间(Time of Arrival,TOA)测距方法,提出了一种融合Taylor级数及改进容积Kalman滤波的定位算法以提高定位估计精度。所提算法首先对泰勒算法初值进行优化,并通过对加权最小二乘法(Weighted Least Square,WLS)解算的位置估计值进行野值剔除及权重计算,在保证定位精度的同时降低算法复杂度;然后针对NLOS环境下标签坐标定位结果不稳定问题,运用改进容积卡尔曼滤波(CKF)算法进一步提升定位精度及稳定性。镇江银山11万伏变电站环境实验结果表明,所提方法在变电站环境中,NLOS严重条件下可实现定位精度10 cm以内,具备工程实用性及可行性。
In order to solve the problem of low UWB positioning accuracy under the severe condition of non line of sight(NLOS)in substation,based on the existing time of arrival(TOA)ranging method,a positioning algorithm integrating Taylor series and volume Kalman filter is proposed to improve the positioning estimation accuracy.Firstly,the proposed algorithm optimizes the initial value of Taylor algorithm,and eliminates the outliers and calculates the weight of the position estimation value calculated by weighted least square(WLS),so as to ensure the positioning accuracy and reduce the complexity of the algorithm;Then,aiming at the instability of label coordinate positioning results in NLOS environment,the volumetric Kalman filter(CKF)algorithm is used to further improve the positioning accuracy.The environmental experimental results of Zhenjiang Yinshan 110000 V substation show that the proposed method can achieve positioning accuracy within 10cm under severe NLOS conditions in the substation environment,and has engineering practicability.
作者
罗珊珊
何泽家
赵军
NE Shanshan;HE Zejia;ZHAO Juan(Guowang Jiangsu Electric Power Co.,Ltd.,Electric Power Research Institute,Nanjing 211103,China)
出处
《自动化与仪器仪表》
2023年第4期85-91,共7页
Automation & Instrumentation
基金
国网江苏省电力有限公司科技项目-基于数字孪生技术的智能实训关键技术研究与应用(J2021109)。
关键词
变电站非视距定位
超宽带
容积卡尔曼滤波
泰勒算法
Non line of sight location of substation
Ultra wideband
Cubature Kalman filter
Taylor algorithm