摘要
为实现车辆的准确跟踪定位,本文首次将WKNN算法与UKF算法相结合,运用超宽带技术研究车辆跟踪定位问题。针对某停车场内的监控数据,利用WKNN算法正确识别视距和非视距误差,剔除含有较大非视距误差的测量值;利用UKF算法对筛选后的测量值进行计算,得到精确位置坐标。相较于Chan定位算法,本文提出的WKNN-UKF定位算法具有更高精度,能够实现复杂场景下车辆的准确定位。
In order to ensure the accurate tracking and positioning of vehicles,ultra-wideband technology is applied to solve vehicle tracking and positioning for the first time by combining WKNN and UKF algorithm.According to the monitoring data in a parking lot,WKNN algorithm was used to properly identify the line-of-sight and NLOS errors,and the measured values of large NLOS errors were eliminated;then the UKF algorithm was used to calculate the measured values to obtain the precise position coordinates.Compared with Chan algorithm,the WKNN-UKF positioning algorithm proposed in this paper has higher accuracy and can achieve accurate vehicle positioning in complex scenes.
作者
辛秀红
陈恋
锁彤佳
吕子璇
刘伟
XIN Xiuhong;CHEN Lian;SUO Tongjia;L Zixuan;LIU Wei(School of Mathematics and Statistics Science,Ludong University,Yantai 264039,China)
出处
《鲁东大学学报(自然科学版)》
2023年第4期360-365,共6页
Journal of Ludong University:Natural Science Edition
基金
山东省本科教学改革研究重点项目(Z2022017)。