Abstract: With the boom of pervasive applications,indoor localization becomes more and more important.The traditionalfingerprint based positioning method requires the site survey in which the required time and workload are huge and the real-time updating needs to adapt to the changes in the room.All these factors greatly limit its scope of application.Therefore,the form of crowdsourcing was utilized to collect indoor information and record a large number of path information.The consistency of the low dimensional embedded manifold in the path were used for geographical position matching in order to establish the database of location fingerprints.Gauss particle filter denoising sensor data were used to further solve the problem of pedestrian step difference.According to the continuity of the user’s location and the path information,the reasonable nearest neighbor points were selected,and the accurate positioning was realized.The experiments have been carried out in the meeting room of 84m²,and the experiments can achieve comparable accuracy to the traditional method.The proposed method can adapt to the environmental changes in real time,and the positioning accuracy is better than the traditional positioning method after 2 weeks and even after 1 month.

Key words: Indoor localization,Crowdsourcing,Embedded manifold,Gauss particle filter,Pedestrian step difference