Robust wireless LAN location fingerprinting by SVD-based noise reduction

The essential challenging in wireless LAN localization is the severe fluctuation of the receive signal strength (RSS) even for the stationary client. The time-varying RSS which resulted from noise deteriorates the system accuracy drastically. In this paper, we present a new approach to improve the positioning accuracy by Singular Value Decomposition (SVD) based noise reduction technique. In the proposed positioning system, the Hankel-form matrix constructed from RSS of available access points (APs) is decomposed into two subspaces. Then the noise reduction is obtained by suppressing the noise-related subspace and reconstructing RSS from the signal subspace only. Experiments in a real-world indoor environment, where the realistic RSS data is collected, show that more than 43% reduction of positoning error is obtained based on the proposed technique.