Research On Sub-meter Indoor Positioning Technology Based On Bluetooth 4.0

Localization technology is one of the core technologies for Location Based Service(LBS).Outdoor positioning navigation technology is very mature.The positioning accuracy of the United States GPS system and China's Beidou system has reached meter level,which brings great convenience to people's work and life.However,with the rapid development of internet technology,human activities are increasingly confined to the interior,which makes the outdoor satellite positioning technology useless because the transmission of satellite signals is not conducive in closed construction environment.Therefore,in order to achieve the seamless positioning of indoor and outdoor positioning,indoor positioning system is popular recently.Compared with other indoor positioning technologies,bluetooth indoor positioning technology is better for cost and performance.So bluetooth indoor positioning technology is the most suitable choice for LBS.In this paper,indoor positioning is achieved by non-ranging positioning method based on the signal strength(Received Signal Strength Indication,RSSI).Because the RSSI values of the base stations are different in different indoor locations,thus the signal strength RSSI values of a plurality of i Beacon base stations collected at one location are used to compose the fingerprint data of the location.The fingerprint data of multiple locations constitute the location fingerprint Library.The system can determine the location of the point by searching its location fingerprint data in the location fingerprint Library during the positioning stage.This paper focuses on two aspects of work.Firstly,the fingerprint datas are collected offline,witch including the deployment of fingerprint data sampling,the development of mobile terminal APP and the establishment of fingerprint database on the server.Secondly,the algorithm optimization onlinein positioning stage.Establishing a complete fingerprint database during the offline sampling phase is the foundation of the online positioning phase.The accuracy of fingerprint database greatly affects the positioning accuracy.Therefore,establishing a high-precision fingerprint database is the main optimization and innovation direction of this paper.The following three aspects are used to improve the positioning accuracy.Firstly,RSSI spatial characteristics model and time fluctuation model are used as guidance to determine the deployment diagram of base station to reduce the impact of environmental factors on positioning accuracy.Secondly,the GM(1,1)model and other algorithms are used to correct the error of the position fingerprint database,and then the adaptive interpolation is used to perform feature interpolation on the position fingerprint database,and reconstruct the large-capacity position fingerprint database to obtain high efficiency and high reliability.Finally,Gaussian function is used to optimize the weight of WKNN algorithm,which is a simple and fast algorithm of classical matching and locating algorithm,thus to achieve the final high-precision positioning.The main results and significance of the research work are to improve the accuracy of indoor bluetooth positioning.From the base station deployment,the establishment of RSSI position fingerprint database,and the online matching location algorithm,this paper comprehensively improved the optimization to realize the positioning accuracy of the sub-meter.According to the simulation and experimental results,the positioning error is 0.8m,and the overall positioning accuracy is increased by about 40%.