Resolution Improvement for Automotive Radar with Chirp Sequence Waveform

The two-dimensional fast Fourier transform (2D FFT) method is commonly used to measure range and velocity of targets for automotive frequency modulated continuous wave (FMCW) radar with chirp sequence waveform. Whereas, the resolution in range and velocity are restricted by the bandwidth and integration time, respectively. In view of the sparsity of targets in the space (SS), this paper proposes two novel models based on compressed sensing (CS) technology to address the above issue. Specifically, the first model termed CS-SS provides higher range resolution by set more mesh points along the range dimension than the samples in one chirp period. To reduce the data size for the reconstruction procedure of the first model for improving the velocity resolution simultaneously, the second model termed FFT-CS-SS, which takes a series of steps to down-sample the data after 2D FFT, is established. Simulations demonstrate the effectiveness, robustness, and the higher ranging accuracy of the proposed models.