STAP in Automotive MIMO Radar with Transmitter Scheduling

Automotive radars often employ multiple-input multiple-output (MIMO) array to attain high angular resolution with few antenna elements. The diversity gain is generally achieved by time-division multiplexing (TDM) during the transmission of frequency-modulated continuous-wave (FMCW) signals. However, TDM mode leads to longer pulse repetition intervals and, therefore, inherently and severely limits the maximum unambiguous Doppler velocity that a radar is able to detect. In this paper, we address the Doppler ambiguity problem in TDM MIMO automotive radars through a space-time adaptive processing (STAP) approach. A direct application of STAP may lead to a high antenna sidelobe level that hampers the detection performance. We mitigate this through optimal transmitter scheduling. We formulate the problem as combinatorial optimization and solve it via reinforcement learning. Numerical and experimental results demonstrate the efficacy of our method when compared with conventional techniques,