摘要
在室内定位领域,惯性测量单元(IMU)、里程计等常见传感器存在累积误差,且无法利用全球卫星导航系统(GNSS)提供位置校准服务,而采用基于蓝牙信号的阵列天线定位结果易受到非视距(NLOS)误差影响。针对上述问题,提出基于蓝牙阵列/IMU/里程计组合的扩展卡尔曼滤波(EKF)模型。根据惯性导航的误差推算模型,同时利用里程计运动特性与单基站阵列天线测角定位原理,构造了速度观测及2维位置观测信息,从而提高组合导航性能。基于轮式移动测量平台的室内实测结果表明:该组合方法有效减小IMU、里程计存在的误差累计以及蓝牙阵列NLOS误差影响,整体运动轨迹与真实轨迹较为符合,能够为运动载体提供准确且丰富的位姿信息。
In the field of indoor positioning,common sensors such as inertial measurement units(IMU) and odometers have cumulative errors and cannot use the global navigation satellite system(GNSS) to provide position calibration services, while array antenna positioning results based on bluetooth signals are easily affected by non-line-of-sight(NLOS) errors. In view of the above problems,In this paper, an extended Kalman filter(EKF) model based on the combination of bluetooth array/IMU/odometer is proposed. According to the error estimation model of inertial navigation,the velocity observation and two-dimensional position observation information are constructed by using the motion characteristics of odometer and the principle of angle measuremen t of single base station array antenna,so as to improve the performance of integrated navigation.The actual measurement results based on the wheeled mobile measurement platform show that the combined method can effectively reduce the error accumulation of IMU and odometer and the influence of the NLOS error of the bluetooth array, The overall motion trajectory is more consistent with the real trajectory, and can provide accurate and rich pose information for the motion carrier.
作者
常康龙
甄杰
李晨辉
杨文东
CHANG Kanglong;ZHEN Jie;LI Chenhui;YANG Wendong(Chinese Academy of Surveying and Mapping,Beijing 100036,China;School of Geomatics,Liaoning Technical University,Fuxin,Liaoning 123000,China)
出处
《导航定位学报》
CSCD
2022年第6期88-96,共9页
Journal of Navigation and Positioning
基金
国家重点研发计划项目(2016YFB0502201)。
关键词
组合导航
扩展卡尔曼滤波
惯性导航
里程计
蓝牙阵列
integrated navigation
extended Kalman filter
inertial navigation
odometer
bluetooth array
作者简介
第一作者:常康龙(1997-),男,河南商丘人,硕士研究生,研究方向为室内定位。
