Wi-Fi positioning system (WPS) can provide position in certain situations (such as indoors) by taking advantage of the rapid growth of wireless access points (WAPs) in urban areas. A provider of this type of service maintains a public database and can determine the position for a device based on the specific access points accessible from the device in each specific location. The localization technique used for positioning with wireless access points is based on measuring the intensity of the received signal (Received Signal Strength or “RSS”) to more uniquely identify each location (usually arranged in a grid comprising a plurality of tiles) using RF fingerprint locating methodologies (hereinafter referred to as “fingerprinting”). Naturally, the accuracy of such approaches depends on the number of positions that have been entered into the database. The possible signal fluctuations that may occur, however, can increase errors and inaccuracies in the path of the user. To minimize fluctuations in the received signal, certain techniques can be applied to filter this kind of “noise.”
However, in practical applications, conventional fingerprinting approaches are difficult to scale and implement. For example, conventional approaches rarely make effective use of crowd-sourced-only data and thus often require labor-intensive calibration in the local environment. Moreover, such approaches generally do not make of use of non-RF related information that may help improve performance, thus hindering the use of better alternative location methods because accuracy of conventional fingerprinting is difficult to evaluate without using external data.