Research On The Indoor Location Technology Using FMCW

With the development of Internet of Things(IOT)technology,location-based services and technologies have been widely used in various areas,and people's demand for positioning and navigation is rapidly increasing accordingly.Because the common satellite positioning technology cannot achieve fine accuracy in indoor environments,indoor localization and tracking systems have attracted extensive attention in academia and industry.In 2014,Professor Dina Katabi's research team at the Massachusetts Institute of Technology(MIT)proposed a positioning system based on Frequency Modulated Continuous Wave(FMCW).This system tracks the user by using radio reflections,without wearing any wireless device,can work through walls and has high accuracy,which has aroused widespread concern in academia.This article has conducted in-depth research on indoor positioning technology using FMCW reflections,focus on improving the positioning accuracy by reducing the impact of multipath propagation interferences and noise interferences.The main contributions of this dissertation can be summarized as follows:First of all,the principle of the positioning and tracking technology based on FMCW reflections is investigated,then,the computer simulation model of the indoor positioning system is established,and the simulation research on the system is carried out.Simulation results show that multipath propagation interferences and noise have an important impact on the performance of the system.Moreover,background cancellation algorithm can only eliminate static reflectors,the effects of dynamic multi-path and noise cannot be eliminated.In addition,further simulation analysis shows that the Kalman filter algorithm can effectively improve the positioning accuracy of the system in noise.To mitigate the influence of dynamic multipath propagation interferences and noise in indoor positioning systems,this paper focuses on the extraction method of direct reflections in the FMCW-based indoor positioning system.A signal detection method based on Constant False Alarm Rate(CFAR)algorithm is designed by analyzing the echo signal model under the background of Gaussian noise.The experimental results show that the CFAR detection algorithm can correctly extract the radio reflections caused by the positioning target,and effectively distinguish the noise and dynamic multi-path components.In addition,the simulation results also show that the continuous average of the signal in frequency domain can effectively improve the Signal to Noise Ratio(SNR)and improve the detection probability of the echoes.Finally,the error in the frequency estimation of the echo signal beat frequency in the positioning system is investigated.A method to modify the estimation error of the discrete Fourier transform using the Rife frequency correction algorithm is proposed to improve the positioning accuracy.The simulation results show that,under the background of Gaussian noise,the error of estimated frequency after the correction algorithm is lower than the original estimation frequency,and the accuracy of distance measurement is greatly improved,which can further improve the system positioning accuracy.