Accuracy-aware wireless indoor localization

Fingerprint-based indoor localization has attracted extensive research efforts due to its potential for deployment without extensive infrastructure support. However, the accuracies of these different systems vary and it is difficult to compare and evaluate these systems systematically. In this work, we propose a Gaussian process based approach that takes the radio map and the localization algorithm as an input, and outputs the expected accuracy of the localization system. With an efficient error estimation algorithm, many applications such as landmark detection, localization algorithm selection and access point subset selection can be performed. Our evaluations show that our approach provides sufficient accuracy and can serve as a useful tool for system evaluation and performance tuning when developing fingerprint-based indoor localization systems.