Hidden Markov Model Based Tracking of a Proxy RP in Wi-Fi Localization

In indoor localization of a mobile device (MD) in WLAN, a proxy reference point (RP) plays the role of representing the dynamically changing channel parameters between an access point (AP) and a MD. We present a hidden Markov model (HMM) based method of tracking the proxy RP for a MD. First, we examined the performance of finding the proxy RP for a stationary MD as we vary the number of APs, the deployment style of APs and the noise strength in RSS. Then, for the tracking of proxy RP for a moving MD, we developed a HMM-based algorithm, which provides the relation between the RSS vector and its proxy RP in a probabilistic manner. Both in computer simulation and in real measurements, HMM-based tracking proved to have much better performance than point-by-point decision by Euclidean distance between RSS vectors.