A Research Of Accuracy Of UWB Position In Three-dimension Indoor

With the development of science and society,the requirement of people for location survice change from outdoor location and navigation to indoor location survice.GPS is a mature technology,but is not fit for indoor location because of the shield wall,so many indoor technology come out,such as UWB,Ultrasonic,WiFi and UHF-RFID and so on.Ultra Wide Band(UWB)technology has strong penetrability,low power dissipation,multipath effect high-resolution,high security,high location accuracy and so on.So this paper delve into distance measurement and location algorithm based on UWB,and combine differential method in order to correct location coordinate,realise high-accuracy real time location of under-test tag in three-dimentional space.First of all,my research discuss backdrop and the importance,research status at home and abroad,comparation amony wireless location technologies,current situation of algorithm,application and significance,simply summarize the definition of UWB and features,UWB location principle,evaluation methodology.By the way of combination of system software and hardware,realise two important steps of location in three-dimentional space: the first step,find the suitable distance measurement model,test the time of signal reach to base station,time difference of arrival and angle and so on.The second step is to find the suitable location algorithm,put measurement parameter into location algorithm,find the under-test tag location estimated coordinate.We expand into three-dimentional model from two-dimentional model,and analyse the merit and demerit of them,and ultimately choose TDOA as main algorithm.This paper simulate Fang and Chan algorithm,and select Chan as main algorithm because of more dispersive location by use of Fang.Analyse and simulate environment noise,use kalman filtering to data reconstruction of static and movement state in order to exclude error of non-line of sight of process of transmission,and substitute into Chan algorithm,and find the more accuracy-estimated location.However,the result have some difference from real location,so we import differential method to reduce the error of under-test tag.This paper build model of above-mentioned algorithm,and capture data in lab,and use MATLAB to simulate and analyse.This paper also use C++ to make under-test tag real time location and track on the screen.The result indicate that the RMSE,which is come out by using TDOA and Chan algorithm,reduce 37% after kalman filtering,and after differential method the RMSE reduce 69%.After large number of test in complex environment,we can find the error is 12 cm at most in single complex environment and 20 cm in multiple complex environment.