Research And Implementation Of Indoor Positioning System Based On WiFi

In recent years,Wi Fi indoor positioning technology has received widely concern.For large shopping malls,parking lots and other scenes,indoor positioning technology can help users to be familiar with the indoor environment quickly,and then reach the destination.At the same time,businesses can also be within the scope of user permission to mine mass indoor location information and analyze useful data,so as to better serve the user.Therefore,Wi Fi indoor positioning technology has a high value of practical application.Positioning accuracy of the existing Wi Fi indoor positioning technology is more than 2 to 6 meters.Most technologies use a single positioning algorithm,including the probability distribution algorithm,location fingerprint algorithm,etc.Tests show that the stability of these algorithms is poor,at present,the accuracy of the existing positioning algorithm basically meets the positioning requirements.However,the locating points have a wide range on the map,which disturb users.The stability of positioning result will affect the indoor positioning technology's further promotion and use.Therefore,it is worthwhile to study the Wi Fi indoor positioning technology with higher positioning accuracy and better stability.In this paper,the K-means clustering algorithm,weighted KNN algorithm(k-nearest neighbors)and acceleration detection step algorithm are used to fuse,and a fusion algorithm is proposed,which is based on location fingerprint library.Then based on the algorithm,the indoor positioning system is designed and implemented.The main contents of this paper include:1.Study the principle and characteristics of the existing Wi Fi indoor positioning technology,and analyze the factors which affect the accuracy and stability of the positioning result.The problem of the localization result of most existing indoor positioning technology is found.To solve this problem,this paper proposes the fusion localization algorithm.The algorithm is used to filter the noise in the original data which is based on the K-means clustering algorithm in the signal collection stage.The sub-region of the anchor point is making a judgement based on the weighted KNN algorithm in the positioning phase,and then judge the reliability of results which is based on the acceleration detection step.This algorithm can effectively improve the stability of the positioning result by processing and discriminating the Wi Fi signal at all stages.2.Design and implementation of a Wi Fi-based indoor positioning system.First of all,according to the actual needs of the positioning system,the positioning system architecture and workflow is determined.Then the fusion localization algorithm is applied to the positioning system,and the client and server module are designed.3.Analyze the test results of the positioning system to verify whether the performance of the improved algorithm used in this paper is stronger than the single localization algorithm.Finally,it is concluded that the localization result of the fusion localization algorithm is more stable.What's more,it improves the localization of the existing localization algorithm.Through the above research,it is confirmed that the fusion algorithm used in this paper can improve the accuracy and stability of the positioning results effectively,which is helpful to the further popularization of Wi Fi positioning technology.