Vehicle velocity estimation based on RSS measurements

This paper presents a technique which is based on pattern recognition techniques, in order to estimate Mobile Terminal (MT) velocity. The proposed technique applies on received signal strength (RSS) measurements and more precisely on information extracted from Iub air interface, in wIDeband code-division multiple access (WCDMA) systems for transmission control purposes. Pattern recognition is performed by HIDden Markov Model (HMM), which is trained with downlink signal strength measurements for specific areas, employing Clustering LARge Applications (CLARA) like a clustering method. Accurate results from a single probe vehicle show the potential of the method, when applied to large scale of MTs.