Research On Indoor Location Technology Of Smart Phone Based On Bluetooth

Throughout the world,the current indoor positioning technology is developing rapidly.Bluetooth technology has become one of the most popular indoor positioning technologies with its low transmission power,low delay and other advantages.At present,all smart phones have Bluetooth function,so smartphone-based Bluetooth positioning technology is easier to popularize than other technologies.Therefore,this thesis studies the Bluetooth indoor positioning technology of smart phones.The main contents of this thesis are as follows:Firstly,this thesis expounds the research focus,relevant background and significance of this subject.This paper analyzes the main research results and development trend of domestic and foreign indoor positioning technology,and analyzes the current mainstream Bluetooth indoor location algorithm.Secondly,the low-power Bluetooth technology is introduced in detail.On this basis,a modified algorithm is used to correct the RSSI signal,and then the Kalman filter method is used to filter the RSSI signal to complete the preprocessing of the Bluetooth signal.This thesis proposes an environment-based adaptive RSSI propagation model,which improves the accuracy of indoor ranging and positioning using RSSI propagation loss model in various indoor environments.Thirdly,the Bluetooth indoor location algorithm based on RSSI is simulated and analyzed,and an adaptive trilateral centroid location algorithm based on distance weighting is proposed.The algorithm not only makes up for the shortcomings of the traditional trilateral centroid positioning algorithm,but also avoids the phenomenon of positioning lag caused by the receiver’s inability to obtain the Bluetooth signal in time.Experimental results show that this method can not only improve the positioning accuracy,but also effectively reduce the computational complexity of the algorithm.Then,based on the traditional Bluetooth fingerprint location algorithm,an adaptive WKNN location matching algorithm based on modified k-means clustering is proposed,which overcomes the problem of increasing location error caused by fixed k value of WKNN algorithm.Simulation results show that the proposed algorithm can effectively improve the localization accuracy.This paper proposes a auto-adaptation indoor positioning method based on Bluetooth according to the differences of positioning algorithms implemented in different indoor environments.The simulation results show that the algorithm can meet the positioning requirements in typical indoor environments.Then,this thesis designs and develops a set of indoor positioning demonstration system based on Bluetooth.The system is built based on wechat applet,including login subsystem,developer information acquisition subsystem,client positioning subsystem and service terminal system.This thesis establishes a test environment to test the functions of each subsystem,and the test results show that the expected effect is achieved.Finally,this thesis summarizes the research contents and prospects the future research work.