Compensating for Orientation Mismatch in Robust Wi-Fi Localization Using Histogram Equalization

The performance of Wi-Fi positioning systems degrades severely when the user orientation differs between locating and training phases. This paper proposes a novel approach based on histogram equalization (HEQ) to compensate for an orientation mismatch in robust Wi-Fi localization. The proposed method involves converting the temporal-spatial radio signal strength into a reference function (i.e., equalizing the histogram). By using equalized signals, the proposed algorithm improves the robustness of location estimation, even in the presence of mismatch orientation. The advantages of the proposed algorithm over traditional methods are that the assumption of user behavior is not required, and a digital compass does not need to be embedded on a mobile device. Experiments conducted in Wi-Fi networks demonstrated the effectiveness of the proposed algorithm. The results show that the proposed algorithm outperforms the orientation classifier method and provides comparable positioning accuracy to the compass-assisted approach.