Research On UWB Indoor Positioning Technology In Non-line-of-sight Environment

In the field of indoor positioning,UWB(Ultra Wide Band)ultra-wideband(Ultra Wide Band)indoor positioning has more mature applications due to its higher accuracy and lower power consumption.However,in non-line-of-sight environments with a lot of occlusion,the accuracy of UWB indoor positioning is low.At present,for UWB positioning in a non-line-of-sight environment,usually a non-line-of-sight environment is decomposed into multiple line-of-sight environments,and positioning is implemented in each line-of-sight environment separately.This method uses a large number of base stations,which greatly increases the cost.In order to solve this problem,this subject has designed a UWB positioning system that can be used in both line-of-sight and non-line-of-sight environments,which increases the range of ranging and achieves higher positioning accuracy with fewer base stations and low cost..The embedded software design is carried out on the label and the base station.Using STM32 as the MCU,the hardware circuits of UWB ranging module,inertial measurement module,base station and tag are designed on the hardware,and the PCB design is completed and the actual product is formed.The software uses an improved two-way bilateral ranging method to complete the UWB module ranging,and realizes the function of measuring distance and inertial information.The tag sends the measured data to the host computer via WIFI.The range and accuracy of the distance measurement are tested.The results show that the distance measurement error is within 5cm in the line-of-sight environment;the distance measurement error is kept at 30 cm in the case of the door,table and chair,and a pedestrian blocking in the non-line-of-sight environment Within the range of the door,seat and two pedestrians,the distance measurement error is about 50 cm.In terms of positioning algorithm,various errors during indoor positioning are analyzed,and the improved two-way bilateral ranging method and parameter correction method are used to reduce the ranging error of DW1000.By optimizing the placement of the base station to reduce the error introduced when calculating the distance,and reduce the occurrence of multipath effects.In order to reduce the non-line-of-sight errors,a combined positioning system was designed based on the Kalman filter.Two methods,TDOA-Kalman filter and extended Kalman filter,were proposed to solve the non-linear problem.The adaptive processing of Sage-husa was explored.influences.The simulation results show that the EKF is stable and has high accuracy during the positioning process.Compared with the TDOA algorithm that only uses distance information,the root mean square error is reduced from 4000 mm to 600 mm,and the positioning accuracy has been greatly improved.A combined positioning algorithm based on Kalman filter is used to estimate the position of the label.According to the specific situation of this subject,a set of positioning algorithm that combines distance and inertial information is designed to improve the positioning accuracy in a non-line-of-sight environment.Based on the Python-based TKinter module,the host computer software is designed to realize the functions of receiving WIFI data,displaying the location of the label in real time,loading the map,drawing the movement track,and storing data.The system was tested in its entirety.In the line-of-sight environment,the positioning accuracy is within 10cm;in the non-line-of-sight environment,most of the occlusions are not particularly serious.The positioning error is within 40 cm.When the occlusion is too serious,it can reach about 70 cm.The trajectory of movement is basically consistent with the actual route.The refresh rate is 10 times per second.