Deviation maps: enhancing robustness and predictability of indoor positioning systems

Many indoor positioning methods and systems exhibit high inaccuracies and structural positioning biases, when deployed and evaluated in real-world environments. This holds especially for signal-strength-based positioning, the prevalent means for position tracking in environments, that are not suitable for GNSS positioning, such as large building complexes. In such environments though strong positioning inaccuracies and biases result from the many building elements with different attenuation properties. We propose and evaluate deviation maps as a means for capturing, and thereby reducing, positioning errors and biases as prevalent in different parts of deployment's building complex.