An Online Algorithm for Fingerprint-Based Location Tracking

We address the problem of fingerprint-based tracking of a moving device where training fingerprints are not available all at once but arrive sporadically in a stream manner. As such the only information that may be used to locate the device is its current fingerprint and the set of fingerprints obtained earlier impromptu. The challenge is to devise a localization algorithm that can scale with the fingerprint stream as this stream can grow limitlessly with time. We propose an online algorithm framework that requires storage of and computation based on only a constant-size sliding buffer of fingerprints, not all the fingerprints in the past. Our algorithm, therefore, is fast and efficient. In terms of localization error, it offers a good approximation when compared to the expensive batch algorithm that assumes access to the entire history of fingerprints.