Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866914704330326016 |
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| author | Eamaz, Arian Yeganegi, Farhang Hu, Yunqiao Sun, Shunqiao Soltanalian, Mojtaba |
| author_facet | Eamaz, Arian Yeganegi, Farhang Hu, Yunqiao Sun, Shunqiao Soltanalian, Mojtaba |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_05423 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion Eamaz, Arian Yeganegi, Farhang Hu, Yunqiao Sun, Shunqiao Soltanalian, Mojtaba Signal Processing 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. |
| title | Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2312.05423 |