Indoor Location Search Based on Subarea Fingerprinting and Curve Fitting

Indoor localization has become a hot topic thanks to the fast development of wireless local area networks. The basic localization scheme can be divided into two approaches: fingerprint-based and lateration-based. In this paper, we propose a novel localization method that combines the fingerprint method and lateration method. Fingerprint-based method is first used for sub area determination and lateration method is then used to estimate the mobile coordinate. Simulation results show that our proposed method is quite effective, and can achieve localization improvement of 34% and 71%, compared with the traditional fingerprint method and a peer lateration method.