OTFS for Automotive Radars: Waveform Optimization and Ambiguity Function Analysis

Automotive radar sensors are vital for enhancing vehicle safety and autonomy, enabling functionalities such as adaptive cruise control and collision avoidance. The performance of these radar systems is highly dependent on the selected waveform. There are several waveform options for automotive radars, including Frequency Modulated Continuous Wave (FMCW), Phase Modulated Continuous Wave (PMCW), Orthogonal Frequency Division Multiplexing (OFDM), and Orthogonal Time Frequency Space (OTFS). Each offers unique benefits and tradeoffs concerning range resolution, Doppler resolution, resistance to multipath fading, and complexity. Notably, OTFS, as a promising technique in Integrated Sensing And Communication (ISAC), outperforms OFDM in high-mobility scenarios for communication systems. In this paper, we design a phase-perturbation matrix using the Coordinate Descent (CD) framework, to optimize the range Integrated Side-lobe Level (ISL) of OTFS waveform in automotive radar applications. We also examine the Ambiguity Function (AF) characteristics of OTFS compared to OFDM, PMCW, and FMCW. The simulation results demonstrate an improvement in the ISL values of the designed OTFS waveforms.