Research On Indoor Location Technology Based On WIFI Location Fingerprint Algorithm

With the development of radio communication technology,mobile Internet technology and the improvement of hardware performance of mobile terminal devices,Location Based Service(LBS)is gradually becoming a new star in the mobile Internet era.With the enhancement of LBS service capabilities,LBS has played an important role in large complex indoor environments such as hospitals,airports,and shopping malls.In the indoor environment,signals are affected by building obstructions and multipath effects.The positioning accuracy of the Global Navigation Satellite System(GNSS)is severely restricted and cannot meet the needs of indoor location services.Therefore,how to provide high-quality indoor location services has become a research hotspot today.Through reading a large number of literatures,this paper systematically analyzes the positioning principle,technology classification system and positioning method of the current mainstream indoor positioning technology.The WIFI-based indoor positioning is mainly used to locate the WIFI signal in the process of propagation in which the signal strength attenuates as the distance changes.According to its positioning principle can be divided into two main categories: based on the signal propagation model positioning and location based fingerprinting.This article focuses on indoor positioning based on WIFI location fingerprinting algorithm.The main research content is as follows:First of all,through the theoretical and experimental analysis,the problem of the influence of noise on the WIFI signal acquisition in the two phases of offline building and online positioning in the actual environment is analyzed.When collecting WIFI signals offline,it uses multiple acquisitions in four directions,then Gaussian filtering is performed on the collected data,and then average filtering is performed,which effectively reduces the influence of noise and improves the indoor positioning accuracy.Secondly,there are many indoor fingerprint localization algorithms based on WIFI.Nearest neighbor algorithm is widely used because of its simple implementation and universal applicability,and it does not need to consider parameters and many hypotheses.However,this method has low positioning accuracy and low fingerprint matching efficiency.problem.To solve this problem,an improved algorithm based on nearest neighbor method is proposed in this paper.Based on the weighted K-nearest neighbor method,a data classification strategy is proposed.Experimental results show that the improved algorithm can effectively improve the matching efficiency of position fingerprints and improve the indoor positioning accuracy.Finally,in order to verify the effectiveness of the proposed strategy,a WIFI position fingerprint indoor positioning system prototype based on Android platform was developed and designed using JAVA language.The system is mainly divided into an offline database building module and an online positioning module.The offline database building module simplifies the work of building a database and improves the efficiency of building a database.The online positioning module is based on the improved algorithm proposed in this paper.The effectiveness of the proposed strategy is verified through experiments.