Slow-Time Mimo-Fmcw Automotive Radar Detection With Imperfect Waveform Separation

This paper considers object detection in the case of imperfect waveform separation, in the context of automotive radars that employ a slow-time MIMO-FMCW signaling scheme. We develop an explicit signal model that accounts for waveform separation residuals and propose a Kronecker subspace-based object detector in the framework of generalized likelihood ratio test (GLRT). Our exact theoretical analysis under both hypotheses shows that the proposed detector holds the desired property of constant false alarm rate (CFAR). Our numerical simulations validate our proposed object detection scheme.