Indoor Location Fusion Algorithm Based on Smartphone

In order to improve the accuracy of indoor localization and the convenience of the user, This paper presents a fusion positioning algorithm using the local binary patterns’ feature approach to achieve ubiquitous and accurate positioning for smartphones and tablets. It is based on loosely coupling WiFi-based positioning and image analysis, This algorithm comprised of offline stage and online stage. On the offline stage, WiFi fingerprints were collected, and a fingerprint library sampled in different positions in the coordinate system was constructed. Photos were taken in that stage to extract the image features. On the online stage, the first filter process was to determine the possible area where the user is currently by using WiFi information captured in real-time. Then a distance compensation algorithm was proposed in this paper to extract features of the real-time image taken by the user to determine the exact localized position. Experimental results show that this algorithm can effectively improve localization precision compared with traditional WiFi and image based localization methods in environments with fewer APs (Access Points) and similar layouts, thus is capable for general localization or LBS (Location-Based Service) relevant applications.