Improving WLAN-based indoor mobile positioning using sparsity

Growing demand for Indoor Localization and Navigation, and the increasing importance of Location Based Services (LBS) necessitates methods that can accurately estimate the position of mobile devices in environments where GPS does not work properly. In this paper, we propose a novel localization method that uses spatial sparsity to improve indoor mobile positioning. The simulation results show the high performance of the proposed method and its robustness to multipath conditions compared to other existing methods. The proposed method has less complexity, less cost and higher robustness to configuration changes compared to common methods such as RSS Fingerprinting approaches.