We propose a high-resolution imaging radar system to enable high-fidelity four-dimensional (4D) sensing for autonomous driving, i.e., range, Doppler, azimuth, and elevation, through a joint sparsity design in frequency spectrum and array configurations. To accommodate a high number of automotive radars operating at the same frequency band while avoiding mutual interference, random sparse step-frequency waveform (RSSFW) is proposed to synthesize a large effective bandwidth to achieve high range resolution profiles. To mitigate high range sidelobes in RSSFW radars, optimal weights are designed to minimize the peak sidelobe level such that targets with a relatively small radar cross section are detectable without introducing high probability of false alarm. We extend the RSSFW concept to multi-input multi-output (MIMO) radar by applying phase codes along slow time to synthesize a two-dimensional (2D) sparse array with hundreds of virtual array elements to enable high-resolution direction finding in both azimuth and elevation. The 2D sparse array acts as a sub-Nyquist sampler of the corresponding uniform rectangular array (URA) with half-wavelength interelement spacing, and the corresponding URA response is recovered by completing a low-rank block Hankel matrix. Consequently, the high sidelobes in the azimuth and elevation spectra are greatly suppressed so that weak targets can be reliably detected. The proposed imaging radar provides point clouds with a resolution comparable to LiDAR but with a much lower cost. Numerical simulations are conducted to demonstrate the performance of the proposed 4D imaging radar system with joint sparsity in frequency spectrum and antenna arrays.

中文翻译：

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适用于自动驾驶汽车的 4D 汽车雷达传感：面向稀疏性的方法


我们提出了一种高分辨率成像雷达系统，通过频谱和阵列配置的联合稀疏设计，实现自动驾驶的高保真四维（4D）传感，即距离、多普勒、方位角和仰角。为了适应在同一频段运行的大量汽车雷达，同时避免相互干扰，提出了随机稀疏步进频率波形（RSSFW）来合成大的有效带宽，以实现高距离分辨率轮廓。为了减轻 RSSFW 雷达中的高范围旁瓣，设计了最佳权重以最小化峰值旁瓣电平，以便能够检测到雷达横截面相对较小的目标，而不会引入高概率的误报。我们将 RSSFW 概念扩展到多输入多输出 (MIMO) 雷达，通过沿慢时间应用相位码来合成具有数百个虚拟阵列元素的二维 (2D) 稀疏阵列，从而实现两个方位角的高分辨率测向和海拔。二维稀疏阵列充当相应的具有半波长元素间间距的均匀矩形阵列（URA）的子奈奎斯特采样器，并且通过完成低秩块汉克尔矩阵来恢复相应的URA响应。因此，方位角和仰角谱中的高旁瓣被大大抑制，从而可以可靠地检测到弱目标。所提出的成像雷达提供的点云的分辨率与激光雷达相当，但成本却低得多。通过数值模拟来验证所提出的具有频谱和天线阵列联合稀疏性的 4D 成像雷达系统的性能。