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Full title—Machine Learning-Based Parameterized Fingerprinting for Unknown Number of Transmitters
This paper presents a novel framework that self-organizes to classify and jointly localize sets of stationary transmitters emitting SOP. Inference of spatial multilateration features allows for the joint estimation of classification outcomes with respect to several unknown parameters, including the number of transmitters, source transmitters for each signal, the underlying multilateration distribution, and the transmitter locations.
Signals transmitted by vehicular Tire Pressure Monitoring System (TPMS) wireless beacons were observed by a custom-built WSN test bed to produce Received Signal Strength Indicators (RSS) features.
Full Article: IEEE Open Journal of Vehicular Technology, Early Access
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