Research On Indoor Location And Track Tracking Technology Based On CSI

With the development of mobile communication technologies and the Internet,indoor location-based services(LBS)have attracted more and more attention from researchers due to their social value and commercial value.Due to the complexity and particularity of the indoor environment compared to the outdoor environment,researchers have applied a variety of technologies to indoor positioning.In recent years,with the rapid development of wireless Wi-Fi technology,large public places such as shopping malls and office buildings have basically covered Wi-Fi hotspots.The Wi-Fi-based indoor positioning method has wide wireless coverage,widespread application,and low cost.The advantages of high scalability have attracted much attention.In this paper,the channel state information(CSI)of Wi-Fi signals is analyzed and studied.At the same time,amplitude phase information of CSI is used as the fingerprint feature,an off-line fingerprint database is created using the algorithm based on subcarrier weights,and an improved WKNN algorithm is used on the online stage to perform the measurement.point targets are passively located.Based on the localization algorithm,the CSI-based trajectory tracking system is generated using the simple area selection(SAS)and determined sequence trend(STD)algorithms.The experimental results show that the system has better positioned accuracy and tracking accuracy under the condition of reasonable parameter setting.The main work and contribution of this thesis are as follows:1.Due to the influence of indoor noise and other factors,there is an error in the directly collected CSI data,and the CSI data need to be processed to improve the accuracy and stability of the data.Amplitude and phase information are jointly used as the fingerprint of the discrete fingerprint to create a fingerprint database.The proposed CSI preprocessing scheme includes: Hampel filter to remove outliers in observation data,Butterworth low-pass filter to achieve denoising,and linear regression method to correct CSI phase,etc.Improve the accuracy and availability of data,and lay the foundation for the application of the CSI to the system.2.A passive indoor positioning system based on subcarrier weights was designed.The system includes two phases,off-line and on-line;off-line phase is mainly used for data acquisition,and online phase feature matching.Because different sub-carriers have great differences in environment perception,in order to reduce errors and increase accuracy,this paper gives each sub-carrier different weights to distinguish different fingerprint points,and then stores the fingerprint point classification data in the fingerprint database;The collected data is compared with the fingerprint database generated in the off-line phase;finally,the position estimation of the point to be measured is achieved by the improved WKNN algorithm.The experimental results of positioning show that if the system parameters are set properly,the average positioning accuracy of the selected 9 fingerprint points is above 90%;the average positioning error is 1.1m.3.Based on the positioning of discrete fingerprints in the indoor environment,the trajectory tracking system is further expanded according to the trend of human motion.This article applies improved SAS and STD algorithms to CSI-based trajectory tracking.The method first divides the CSI data observed by the trajectory path into several data segments,performs discrete fingerprint matching on each segment of data,and then uses the fingerprint matching results to estimate the region,and determines the path trajectory of the human through the set of vector locations formed by the continuous region estimation.Tracking the target is achieved.