Research On Indoor Positioning Technology Based On The Fusion Of UWB And BLE

With the development of the Internet of Things and big data,location-based indoor positioning systems have been widely used in factories,warehouses,hospitals,smart homes,and high-security areas,but traditional indoor positioning systems are not only costly but also need to be improved in positioning accuracy.Therefore,reducing the cost of indoor positioning and improving the accuracy of indoor positioning are urgent problems to be solved.In order to solve these problems of indoor positioning,wireless sensor networks(WSN)have been widely used to solve indoor positioning problems in the past decade.Commonly used indoor positioning wireless sensor networks include WiFi,Bluetooth Low Energy(BLE),Ultra Wideband(UWB),Radio Frequency Identification(RFID)and ZigBee.This paper analyzes and compares commonly used wireless sensors,selects UWB and BLE to build indoor positioning systems,and proposes the fusion positioning of UWB and BLE.Analysis of the signals propagation characteristics and ranging error of the UWB and BLE,improve the ranging model of UWB and BLE.Therefore,the positioning accuracy of UWB and BLE fusion is improved.Design and implement an indoor positioning system based on Narrow Band-Internet of Things(NB-IoT),use NB-IoT to build an indoor positioning communication network,and build a complete set of low-cost,high-precision and flexible networking indoor positioning system.The main research work of this article is as follows:(1)Use the Single Side-Two Way Ranging(SS-TWR)algorithm to perform UWB ranging and eliminate the clock synchronization problem between UWB nodes.Analysis the result of UWB ranging,an error correction model is proposed based on ranging SS-TWR.Then using a least squares fitting error correction function,which reduce the UWB ranging error.Analyze the logarithmic distance path attenuation model based on Received Signal Strength Indication(RSSI),and propose a BLE ranging model based on segmentation parameters,which improves the accuracy and stability of BLE ranging.Analyze and use the Extended Kalman Filter(EKF)algorithm to fuse the improved UWB and BLE ranging models,which improve the positioning accuracy of UWB and BLE fusion.(2)Designed and implemented an indoor positioning system based on NB-IoT.It is divided into the design of positioning base station and the design of positioning tag.The positioning base station is divided into UWB base station and BLE beacon.The UWB base station uses ST's 32-bit controller STM32F103C8T6 as the main control,and Decawave's DWM1000 module as the UWB transceiver to complete the corresponding hardware and software design.BLE beacon uses TI's Bluetooth 5.0 chip CC2640R2F to complete the corresponding software and hardware design.The positioning tag combines the UWB module and the Bluetooth chip on the basis of the UWB base station and the BLE beacon,and uses NB-IoT to build a communication network.The coverage problem of the system network has realized the wide area coverage of indoor positioning.And when combined with a satellite positioning system,it can achieve seamless connection of indoor and outdoor positioning,expanding the coverage area and application field of indoor positioning technology.(3)Design system positioning experiment.The three positioning base stations required for two-dimensional positioning are divided into four combinations,namely:three all UWB base stations;two UWB base stations,one BLE beacon;one UWB base station,and two BLE beacons;three all BLE beacons.The traditional trilateral positioning algorithm and the EKF positioning algorithm analyzed in this paper are used to verify the effectiveness of the improved ranging model for positioning accuracy.Experiments show that the average positioning accuracy of the trilateral positioning algorithm of the four combinations before model improvement is 13.6 cm,42 cm,107.4 cm and 133.1 cm.After the model improvement,they are 9.5 cm,37.7 cm,81.6 cm and 100.1 cm,which are improved by 30%,10.2%,24%and 24.8%respectively.The average positioning accuracy of the EKF positioning algorithm of the four combinations before model improvement is 12.2 cm,34.3 cm,100 cm,and 121 cm.After the model improvement,they are 6.8 cm,29 cm,71 cm,and 83 cm,which are improved by 44.3%.34.3%,15.5%and 29%respectively.