Using the Newton Trust-Region Method to Localize in WLAN Environment

Localization systems for indoor areas using the existing wireless local area network (WLAN) infrastructure have been suggested recently. However, the current systems are not satisfactory. Common localization approaches suffer from inaccurate position tracking due to signal fluctuations in the wireless LAN. Newton trust-region method makes use of the convergence factor of a trajectory to eliminate the noise from the signal strength. In this paper, we apply a Newton trust-region (TR) algorithm to trajectory estimation based on the traditional location fingerprinting (localization) approach. Newton trust-region method optimize the location fingerprinting approach iteratively because each point in a trajectory normally falls into a region and have the same convergence in direction. Our experimental analysis shows that Newton trust-region method enhances the traditional localization approach with 15% fewer access points and is 20% more effective to achieve accurate localization. The proposed Newton trust-region method leads to substantially more accurate and robust localization system.