V2V Communication-Assisted Transmit-Waveform Selection for Cognitive Vehicular Radars

Vehicular radar is one of the key components for connected and autonomous vehicles (CAVs). Through adaptive transmit-waveform selection, cognitive vehicular radar (CVR) can be developed to support advanced driver assistance systems (ADAS). In this paper, we study the improvement of CVR tracking performance with the assistance of 5G vehicle-to-vehicle (V2V) communications. The model of cognitive dynamic system (CDS) and its function of cognitive risk control (CRC) is incorporated in the design. Specifically, the perceptor of CVR has flexible filtering formulation, which will take the expanded form when V2V messages are available; on the other hand, the executive of CVR has flexible operational modes, which is expanded when unexpected risk needs to be brought under control. Simulation results have shown that the proposed method will improve tracking accuracy significantly in an uncertain and dynamic environment.