Research And System Implementationon Of Indoor Location Algorithm Based On Fingerprint

Due to the wide application of the Internet of things in recent years,the indoor positioning technology has been constantly promoted by science and technology,the demand of hospitals,shopping malls,warehouses and many other public places for indoor positioning technology makes the positioning more mature.In recent years,Location fingerprint location technology based on WIFI is catched more attention by virtue of its high efficiency,universality,low cost and high positioning accuracy,and now the most urgent need for indoor positioning services is a large public places such as shopping malls.Through the comparison of the research,it is more suitable for the location fingerprint technology based on WIFI,Therefore,this article makes an in-depth study about the location fingerprint positioning technology based on WIFI.Firstly,aiming at the construction stage of off-line fingerprint database of fingerprint positioning technology based on WIFI,for the construction of traditional fingerprint database need field acquisition of fingerprint signal widely,it is difficult to achieve in a large area,a method is proposed to construct the fingerprint database based on optimal attenuation factor model.By using the model of signal propagation and computing the intensity of the signal sent from the AP node to the fingerprint nodes,the method saves the time of field layout and improves the efficiency of the fingerprint database construction.And the traditional attenuation factor model is optimized,the free space model and attenuation factor model are combined;on the other hand through the signal acquisition of some nodes,thus realizing the self-adaption of path-loss index in the attenuation factor model.Finally,the optimization was confirmed by simulating with a variety of classical propagation model.Secondly,aiming at the problem of low precision in the positioning stage of fingerprint location positioning technology based on WIFI,through the comparative study of the nearest neighbor classification algorithm(NN),K nearest neighbor classification algorithm(KNN)and Bias algorithm,and then we present a kind of weighted KNN algorithm of based on triangle correction.On the one hand,the algorithm uses the difference between the AP signal intensity value of the node and the fingerprint node to be taken as the weighting factor,and the positioning accuracy of KNN is improved by the contribution ratio of different fingerprintnodes;On the other hand,we further improve the positioning accuracy by selecting three nearest neighbor points which the unknown node must be in the triangle composed of these three points.Finally,the simulation results showed the effectiveness of the algorithm.Finally,this paper designs and achieves a simulation platform of indoor positioning based on C#,the construction method of fingerprint database with the optimal attenuation factor model and the location algorithm of trigonometric correction WKNN are applied to the platform,and the function of the platform is verified in the last.