基于NLOS误差修正的无人车UWB/IMU组合定位研究  

Research on UWB/IMU Combined Positioning of Unmanned Vehicle Based on NLOS Error Correction

作　　者：张鸽 ZHANG Ge(School of Software,Shanxi Agricultural University,Taiyuan 030801)

机构地区：[1]山西农业大学软件学院,太原030801

出　　处：《舰船电子工程》2024年第12期55-60,共6页Ship Electronic Engineering

基　　金：山西重点研发计划项目(编号:202202140601021);山西省基础研究计划青年基金项目(编号:202203021212416);山西农业大学科技创新基金(编号:2017002)资助。

摘　　要：新兴的物联网(IoT)应用,例如智能制造和智慧农业设备,推动了对低成本、高精度室内定位导航解决方案的迫切需求;针对复杂室内环境中,UWB信号由于非视距(Non-Line-of-Sight,NLOS)误差因素导致定位精度低的问题,提出了一种基于扩展卡尔曼滤波器的UWB/IMU融合定位方法,根据UWB与IMU距离量测差值构建系统量测方程,引入新息向量和新息协方差,利用定位标签融合IMU对UWB定位过程中的NLOS误差进行修正,利用超宽带数据对IMU的位置、速度和姿态进行约束和更新;实验结果表明,该方案能够在室内环境下实现厘米级定位,满足无人车在室内环境下的定位精度需求,且表现出在解决信号缺失、抑制路径偏离等方面的优势。The emerging Internet of Things(IoT)applications,such as smart manufacturing and smart agriculture devices,are driving the urgent demand for low-cost,high-precision indoor positioning and navigation solutions.Aiming at the problem of low positioning accuracy of UWB signals due to non-line-of-sight(NLOS)errors in complex indoor environments,a novel ul⁃tra-wideband(UWB)and inertial measurement unit(IMU)fusion positioning method based on extended Kalman filter is proposed.By constructing the system measurement equation based on the differential distance measurements between UWB and IMU,incorpo⁃rating novel state vectors and covariance matrices,this algorithm corrects the non-line-of-sight(NLOS)errors in UWB positioning during fusion with IMU.Additionally,it constrains and updates the position,velocity,and attitude of IMU using UWB data,exploit⁃ing the complementary characteristics of IMU and UWB to achieve high-precision indoor localization.Experimental results demon⁃strate that this approach achieves centimeter-level accuracy in indoor environments,meeting the precision requirements for indoor localization of unmanned vehicles,and exhibiting advantages in addressing signal loss and suppressing path deviations.

关 键 词：UWB IMU NLOS误差 融合定位 无人车 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]