Wi-Fi positioning based on deep learning

In this paper, we propose a Wi-Fi positioning method based on Deep Learning (DL). To deal with the variant and unpredictable wireless signals, the positioning is casted in a four-layer Deep Neural Network (DNN) structure that is capable of learning reliable features from a large set of noisy samples and avoids the need for hand-engineering. Also, to maintain the temporal coherence, a Hidden Markov Model (HMM) based fine localizer is introduced to smooth the positioning result obtained from the immediate estimation of DNN-based coarse localizer. The data required for the experiments is collected from the real world in different periods to meet the actual environment. Experimental results indicate that the proposed system leads to substantial improvement on localization accuracy in case of the turbulent wireless signals.