A novel indoor positioning method based on location fingerprinting

Indoor location based services (LBSs) is an emerging subject in recent years. To solve the problem of building the fingerprint database manually in the Location Fingerprinting (LF) methods, an analytical fingerprinting method is proposed in this paper. It can reduce the cost and has good properties on building database automatically and increasing the robustness against to environment. Moreover, the k nearest neighbor (k-NN) algorithm is used to search the closest fingerprint during the real-time localization phase. The simulation results are provided and the positioning performance is verified in comparison with that of classical methods. Finally, an experiment is carried out in an actual office room to verify the proposed method. Both the simulation and experiment results show that the new method is effective and can bring more accurate and robust localization substantially.