Predicting the expected accuracy for fingerprinting based WiFi localisation systems

WiFi localisation has become very popular in recent years. Most widely used are fingerprinting based techniques where a map of received signal strengths is used to infer the position based on comparing the current signal strength measurement to this map. Most research focuses on this inference itself and on the creation of accurate fingerprinting maps. In this paper we will not address those issues in depth but focus on analysing the fingerprint maps themselves in more detail. By looking closely into the maximum likelihood estimation for the position we will derive its expected uncertainty and show that it can be calculated for every possible position in advance from the fingerprint maps alone. This allows to derive an expected localisation accuracy map of the environment that can be used to assess and optimise the WiFi design based on localisation accuracy needs rather than relying on given access point placements solely based on coverage or signal-to-noise criteria.