Research On Indoor Visible Light Positioning Technology Based On RSS Assistance

In recent years,with the rapid development of Internet of Things and machine learning technology,accurate positioning and navigation function in complex and changeable indoor environment has become a significant research hotspot.Although the existing traditional indoor positioning technology is relatively mature,there are still some shortcomings in these methods such as high cost and low positioning accuracy.Based on this,the visible light communication(VLC)technology is proposed to overcome the limitations of the existing wireless positioning technology and provide a new technical solution for indoor positioning.The VLC technology uses the light-emitting diode(LED)to send the optical signal and transmit data information through the optical channel,which has the advantages of environmental protection,no electromagnetic interference and high security.When it is applied to the field of indoor positioning,the position information of the target to be positioned can be obtained more accurately while lighting.This thesis focuses on indoor positioning technology.After fully understanding its frontier development and theoretical basis,it pays attention to the analysis of indoor VLC positioning technology,and elaborates its positioning principle,algorithm implementation process,advantages and disadvantages.Finally,the traditional trilateral positioning method and location fingerprint positioning technology are selected as the key research contents,and in view of the problems existing in the positioning process,an optimization scheme is given.The main innovations of this thesis are as follows:(1)A trilateral localization method based on the improved differential modified localization algorithm is proposed.The method is based on the idea of differential correction,the initial positioning result of the trilateral positioning method was used as the reference point of differential correction to realize the differential positioning process.With the problem of low positioning accuracy of the traditional trilateral positioning method,the centroid weighted positioning method and the trilateral positioning method based on received signal strength selection(RSS)are selected as the basic positioning method.These two methods are derived from the trilateral positioning method,and the positioning accuracy is higher.Finally,through simulation analysis,we can find the above two methods showing better performance in positioning accuracy and stability of positioning results after differential correction.(2)To solve the problem that the excessive workload of the traditional position fingerprint algorithm,a trilateral location method based on RSS selection is applied to the algorithm position matching stage.The method combined the maximum positioning error on the positioning plane with the initial positioning result of the algorithm to determine the algorithm location matching data set,which can reduce the workload of algorithm matching and save time;On the other hand,for different targets to be located in the positioning plane,the algorithm can obtain different data sets from the same fingerprint database,which has a certain adaptability.Then,a weighted k nearest neighbor(WKNN)algorithm based on the average value of the maximum distance difference is proposed to solve the problem that the K value of the traditional WKNN algorithm is fixed in the positioning process,which affects the positioning accuracy.The algorithm dynamically reduces the K value to ensure that the K sampling points closest to the target to be located can be obtained during the process of positioning,to improve the positioning accuracy.