Squeeze More from Fingerprints Reporting Strategy for Indoor Localization

Recent study on Wi-Fi RSS fingerprinting based indoor localization reveals that reporting fingerprints with respect to different set of access points (APs) results in location estimations in different levels of accuracy; however, how to find the best strategy for fingerprints reporting with reasonable computational cost, and how to exploit the finding to streamline the design of the localization system are still unknown. In this paper, we revisit the design principles of the localization system with the opportunity provided by the theory of best fingerprints reporting strategy. We first present the localization reliability bounds under the best strategy, and develop algorithms to find the best strategy in practice. We then demonstrate how the best strategy theory can be utilized to improve accuracy of location estimation by resolving the issue of similar fingerprints for both faraway and close-by locations. An iterative algorithm is developed to cross check fingerprints sampled in different locations, in order to derive the best possible result of localization. Moreover, we reveal the relationship between accuracy of location estimation and coverage of Wi-Fi signals in a region, when planning deployment of APs. Experiment results are presented to validate our analysis and design.