An Adaptive UWB/MEMS-IMU Complementary Kalman Filter for Indoor Location in NLOS Environment
An Adaptive UWB/MEMS-IMU Complementary Kalman Filter for Indoor Location in NLOS Environment
复制标题
用于非视距环境室内定位的自适应 UWB/MEMS-IMU 互补卡尔曼滤波器
DOI：
10.3390/rs11222628
复制
发表时间：
2019-11-02
期刊：
影响因子：
5
通讯作者：
Zhang, Jixian
中科院分区：
文献类型：
--
作者：
Liu, Fei;Li, Xin;Zhang, Jixian
非视距环境下超宽带(UWB)的高精度定位是目前室内定位研究的热点问题之一。提出了一种利用互补卡尔曼滤波(CKF)对超宽带(UWB)和惯性测量单元(IMU)数据进行融合和滤波，并跟踪位置、速度、方向等变量误差的方法。基于磁强计和加速度计的不确定度，动态计算磁强计和加速度计的噪声协方差矩阵，然后自适应地设置磁力计数据的权重，以校正陀螺仪的方向误差。根据UWB距离观测值的不确定性，动态计算UWB测量噪声的协方差矩阵，然后自适应地设置UWB数据观测值的权重，以修正位置误差。通过UWB和IMU的融合，对位置、速度和方向误差进行校正。实验结果表明，该算法可以减小磁噪声和运动噪声对陀螺仪的影响，从而改善方位估计，提高超宽带测距噪声的定位精度。
High precision positioning of UWB (ultra-wideband) in NLOS (non-line-of-sight) environment is one of the hot issues in the direction of indoor positioning. In this paper, a method of using a complementary Kalman filter (CKF) to fuse and filter UWB and IMU (inertial measurement unit) data and track the errors of variables such as position, speed, and direction is presented. Based on the uncertainty of magnetometer and acceleration, the noise covariance matrix of magnetometer and accelerometer is calculated dynamically, and then the weight of magnetometer data is set adaptively to correct the directional error of gyroscope. Based on the uncertainty of UWB distance observations, the covariance matrix of UWB measurement noise is calculated dynamically, and then the weight of UWB data observations is set adaptively to correct the position error. The position, velocity and direction errors are corrected by the fusion of UWB and IMU. The experimental results show that the algorithm can reduce the gyroscope deviation with magnetic noise and motion noise, so that the orientation estimates can be improved, as well as the positioning accuracy can be increased with UWB ranging noise.