Feature Extraction and Spatial Interpolation for Improved Wireless Location Sensing

This paper proposes a new methodology to improve location-sensing accuracy in wireless network environments eliminating the effects of non-line-of-sight errors. After collecting bulks of anonymous location measurements from a wireless network, the preparation stage of the proposed methodology begins. Investigating the collected location measurements in terms of signal features and geometric features, feature locations are identified. After the identification of feature locations, the non-line-of-sight error correction maps are generated. During the real-time location sensing stage, each user can request localization with a set of location measurements. With respected to the reported measurements, the pre-computed correction maps are applied. As a result, localization accuracy improves by eliminating the non-line-of-sight errors. A simulation result, assuming a typical dense urban environment, demonstrates the benefits of the proposed location sensing methodology.