Research And Application Of Indoor Localization Of RFID Based On RSSI And Phase

With the rapid development of the Internet,big data,cloud computing,artificial intelligence,and communication technologies,the Internet of Things technology has also been used in a large increase in demand.Logistics,express delivery,warehousing,pedestrian indoor navigation and other requirements are constantly increasing.GPS,base station and other positioning methods can no longer meet complex indoor positioning needs.Ultrasound,infrared,Wi Fi,Bluetooth,Zig Bee have not been applied on a large scale due to the high cost of their positioning systems,the limited positioning environment,and the difficulty in integrating other systems.Radio frequency identification(RFID)-based positioning technology has attracted the attention of researchers due to its low system deployment cost,diverse technology options,and numerous applicable scenarios.This thesis mainly studies the indoor positioning technology based on RFID,mainly including the following aspects:(1)This thesis aims to improve the traditional indoor positioning system LANDMARC positioning system for scenarios that require positioning in indoor environments,such as the positioning of items under storage.As RFID signals propagate in indoor environments,multi-path interference,scattering,refraction,and signal collisions between tag signals can occur at any time.The received signals will have different degrees of distortion.Gaussian filters are used to reduce the effect of data with large deviations in signal strength values on positioning accuracy.Because the received signal strength fluctuates greatly,Kalman filter is used for smoothing.Because the LANDMARC positioning algorithm has a large amount of calculation,the selection of k value has a large impact on the positioning accuracy.The support vector regression algorithm is used to improve the LANDMARC algorithm to improve the positioning accuracy.(2)This thesis addresses the need to obtain the relative position between the targets to be located in an indoor environment.For example,if the order of book placement in a library scene is wrong,manual inspection of misplaced targets has a time-consuming and labor-intensive problem.This thesis proposes an indoor relative position location algorithm based on phase and ARIMA.Due to the phase inversion problem of the phase value in the process of collecting data by moving the antenna,this thesis uses only the data in one inversion period to detect the item sequence;because the trends of phase values of different tags are roughly the same in the same scanning cycle,but some phase values may have deviations,this thesis uses the representative phase inversion point and uses the ARIMA model to predict more than ten times after a flip cycle.The phase value after the point is used as a reference for the order of the items;because the timestamps of several special phase points obtained lack a uniform problem that can measure the relative order of tags,a time-weighted solution is proposed,which improves the accuracy compared to traditional relative position positioning algorithms.(3)Aiming at the two indoor positioning algorithms proposed above for different application scenarios,an RFID indoor positioning prototype system was designed and implemented.For the positioning of items in a warehouse environment and the ordering of objects to be located in a library environment,based on the hardware environment,the overall architecture design,data storage,and database table structure design and the proposed indoor positioning algorithms,an indoor absolute positioning module and an indoor relative positioning module are designed in real positioning system,and the two different positioning modules are also tested.The implemented system and test results show that the indoor location algorithm proposed in this paper has feasibility and application prospects.