非视距环境下的IMU和UWB融合定位系统  

IMU and UWB Fused Positioning System in Non-line-of-sight Environment

作　　者：彭俊杰 李英华 王春琦 周小安[1] PENG Junjie;LI Yinghua;WANG Chunqi;ZHOU Xiaoan(College of Electronic and Information Engineering,Shenzhen University,Shenzhen 518060,China;National Radio Monitoring Center,Beijing 102609,China)

机构地区：[1]深圳大学电子与信息工程学院,广东深圳518060 [2]国家无线电监测中心,北京102609

出　　处：《无线电工程》2022年第6期932-939,共8页Radio Engineering

摘　　要：室内定位技术由于受非视距(Non-Line-of-Sight,NLOS)的影响,单一的传感器通常无法满足定位需求。针对该问题,提出了基于超宽带(Ultra-Wide Band,UWB)传感器和惯性传感单元(Inertial Measurement Unit,IMU)融合的定位算法,实现在NLOS场景下的高精度室内定位系统。通过对环境中传输距离的采集,基于支持向量机实现NLOS信号的分类识别。IMU基于已知的初始位置信息和方位,通过惯性导航解算出定位信息。UWB通过最小二乘算法,对基于双边双向的信号飞行时间测得的距离值进行定位解算。利用扩展卡尔曼滤波算法实现传感器的融合,提高定位精度。仿真结果表明,所提出的算法能很好地识别和缓解NLOS带来的定位误差。Since indoor positioning technology is affected by non-line-of-sight(NLOS),a single sensor usually can not meet the positioning requirement.A positioning algorithm based on the fusion of Ultra-Wide Band(UWB)and Inertial Measurement Unit(IMU)is proposed to achieve a high-precision indoor positioning system in NLOS scenarios.By collecting the transmission distances in the environment,the classification and recognition of NLOS are realized based on support vector machine.IMU calculates the location information by inertial navigation based on the known initial position information and azimuth.UWB uses the least square algorithm to locate the distance values measured based on the two-way signal time of flight.The sensor fusion is realized by the extended Kalman filter algorithm to improve the positioning accuracy.Simulation results show that the proposed algorithm can better recognize and alleviate the positioning errors caused by non-line-of-sight.

关 键 词：非视距 惯性传感单元 超宽带 室内定位系统 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]