Simulation And Optimization Of Wireless Localization Algorithm Based On Environmen Differentiation

In the context of the rapid development of the Internet of Things and communication technology,more and more location-based services have emerged at the historic moment.The location scene has gradually evolved from an open field to a high-density urban environment.The life,entertainment and health of the public are closely related to location services,which has brought new challenges to the positioning technology.The positioning technology nowadays is developing in the direction of high performance,high availability and low cost,and has also become the focus of current research.At the beginning of the design,the cellular network retained the infrastructure for positioning.With the construction of the 5G and its widespread use,the high-precision positioning of the cellular network has become possible,and has great development potential and research value.The BLE technology born after the Bluetooth 4.0 specification has the characteristics of low power consumption,easy deployment and high availability,which makes it also an excellent indoor positioning solution.Therefore,this paper studies the location algorithm in 5G NR network and BLE fingerprint location technology.The main work is as follows:(1)Extensively investigate the frame structure characteristics of BLE signal and its advantages for positioning.Introduce the development process of Bluetooth specification.The principle of fingerprint positioning has been studied.The realization idea of BLE fingerprint positioning and the factors affecting the positioning accuracy and the means to improve the positioning performance have been described.The 5G NR system architecture,positioning signal type,positioning process and other contents have been investigated.Additionally,This paper focuses on the location algorithm and strategy mentioned in 3GPP protocol.(2)The filtering technology is introduced into BLE fingerprint location.Three filtering technologies including extended Kalman filter are studied and implemented.After collecting the RSSI of BLE beacon,the RSSI sequence is passed through the filter to reduce the impact of noise factors on the location results.KNN,naive Bayes and other algorithms are implemented in the matching of fingerprint database.A suitable environment is selected to measure the BLE positioning scheme.The measurement content includes the data of each reference point when establishing the fingerprint database offline and the data received by users when positioning online.Finally,the positioning results of each filtering algorithm and using different number of BLE beacons are given.The positioning module of 5G NR positioning system has been developed.The positioning algorithms commonly used in protocols such as Taylor algorithm and particle swarm optimization algorithm have been researched and implemented.The positioning module supports the use of different measurement parameters such as TDOA,AOA or TDOA/AOA joint positioning.The positioning process of the platform,the framework of the positioning module and the implementation method are described,and the calibration results of the platform for some classic cases in TR 38.855 are given.Finally,the platform is used for public data sets,and the positioning results of traditional positioning algorithms for public data sets are given.The measured results of the subject in the BLE indoor fingerprint location can provide reference for landing applications,and the construction of the location module can provide simulation for the followup research of the location algorithm in the cellular network,which has certain practicability and reference.