V2V-Aided Adaptive FMCW Radar Interference Mitigation

This paper addresses the challenge of interference mitigation in frequency modulated continuous wave (FMCW) radar systems by leveraging signal processing techniques and vehicle-to-vehicle (V2V) communication. The proposed method utilizes the short-time Fourier transform (STFT) to convert 1D radar signals into a 2D domain, enabling the application of robust principal component analysis (RPCA) for interference mitigation. A novel approach is proposed to dynamically adapt the RPCA λ parameter by leveraging aggressor radar parameters shared via V2V communication. Simulation results demonstrate that increasing the number of interfering radars and their amplitudes necessitates higher λ values for effective interference mitigation. Furthermore, the findings reveal that the incorporation of interfering radar parameters enhances signal reconstruction quality, particularly for weak target signals that are otherwise masked by interference. These preliminary results highlight the potential of adaptive λ selection, informed by V2V communication, to improve radar performance in real-time and support advanced autonomous vehicle systems.