Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion
Abstract
The design of sparse linear arrays has proven instrumental in the implementation of cost-effective and efficient automotive radar systems for high-resolution imaging. This paper investigates the impact of coarse quantization on measurements obtained from such arrays. To recover azimuth angles from quantized measurements, we leverage the low-rank properties of the constructed Hankel matrix. In particular, by addressing the one-bit Hankel matrix completion problem through a developed singular value thresholding algorithm, our proposed approach accurately estimates the azimuth angles of interest. We provide comprehensive insights into recovery performance and the required number of one-bit samples. The effectiveness of our proposed scheme is underscored by numerical results, demonstrating successful reconstruction using only one-bit data.
Cite
@article{arxiv.2312.05423,
title = {Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion},
author = {Arian Eamaz and Farhang Yeganegi and Yunqiao Hu and Shunqiao Sun and Mojtaba Soltanalian},
journal= {arXiv preprint arXiv:2312.05423},
year = {2024}
}