Indoor WLAN Localization Based on Augmented Manifold Alignment

Abstract

With the dramatic development of location-based service (LBS), indoor localization techniques have been widely used in recent years. Among them, the indoor wireless local area network (WLAN) localization technique is recognized as one of the most favored solutions due to its low maintenance overhead and high localization accuracy. In this paper, we propose a new received signal strength (RSS)-based indoor localization approach using augmented manifold alignment. First of all, we construct the objective function in manifold space for indoor localization. Second, the optimal transform matrix is used to transform the coordinates of reference points (RPs) and the corresponding RSS vectors into manifold space. Finally, we locate the target at the RP with the transformed coordinates nearest to the transformation of the newly collected RSS vector in manifold space. The experimental results demonstrate that the proposed approach is able to achieve satisfactory localization accuracy with low overhead.