This paper shows the feasibility of a passive forward scatter radar (PFSR) based on WiFi transmissions for automatic classification of surface vehicles. To this purpose, proper automatic classification schemes are employed, able to exploit the forward scatter target signatures in the time domain. The considered approaches have been extensively tested against experimental data sets. The reported results prove that the exploited geometry yields quite stable and diverse signatures for the considered targets despite they belong to the same cars category. This results in a remarkable classification capability for the conceived sensor, thus showing the practical applicability of the WiFi-based PFSR system for surface traffic monitoring.
Following the promising results obtained in previous studies, in this paper we address the main limitations of a WiFi-based Passive Forward Scatter Radar in vehicles monitoring applications. Specifically, the possibility to operate in the absence of a reference signal is investigated in order to avoid the need for a dedicated receiving channel and to make the sensor independent of the exploited transmitter of opportunity. Moreover, aiming at the automatic classification of surface vehicles, an effective strategy is considered to estimate the target velocity in order to properly scale the corresponding signatures for direct comparison. The proposed approaches are extensively tested against experimental datasets in order to verify their practical feasibility. This paper is a companion to another paper submitted to this conference [1]. Specifically, with the proposed approaches we complement and extend the results in [1] by providing an effective solution for a realistic implementation of the conceived sensor.
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