Research On System And Key Technology Of Low-power Indoor Positioning System Based On TDOA

In recent years,due to the increasing demand for indoor positioning,however,a complete indoor positioning scheme has not been achieved in technology,so improving the reliability and accuracy of indoor positioning has become a focus of much attention.Therefore,the thesis mainly focuses on TDOA based indoor positioning system to improve the accuracy of indoor positioning,the main work is as follows.(1)The synchronization model of indoor positioning system influences the localization performance to a great extent,so it is necessary to set up a localization model that reflects the synchronization characteristics of indoor positioning system.This paper mainly discusses and studies the TDOA time synchronization and location model,and gives the distance estimation method of terminal node and terminal node based on time synchronization and location joint calculation.(2)In order to solve the problem of positioning error in terminal node movement,the theoretical premise of EKF technology is studied and the adaptive EKF algorithm is proposed.The simulation results show that the positioning error of the terminal nodes realized by the adaptive EKF algorithm is reduced by more than one third compared with the traditional EKF algorithm.The positioning error of the dynamic terminal nodes is 0.239 m and the static terminal nodes is 0.106 m.(3)Based on the classical Kalman filter location algorithm,an optimization algorithm of fusion particle filter and Kalman filter is developed for indoor location based on TDOA.This method can predict the position of terminal nodes by particle filtering and then adjust the position of terminal nodes by Kalman filtering.In indoor environment,the distance of terminal node in moving and static condition is measured respectively.The result shows that the method given in this paper has 94.5%chance of achieving the accuracy of location at the meter level.Simulation results show that the location accuracy and stability of the proposed algorithm are higher than that of the existing location estimation algorithm,and the accuracy standard of the meter level can be achieved in the relatively redundant indoor environment.The positioning error of stationary terminal node decreases by 28.7%,while that of moving terminal node decreases by 35.9%.