Multi-Frequency Sparse Array-Based Massive MIMO Radar for Autonomous Driving

被引:4
|
作者
Sun, Shunqiao [1 ]
Zhang, Yimin D. [2 ]
机构
[1] Univ Alabama, Dept Elect & Comp Engn, Tuscaloosa, AL 35487 USA
[2] Temple Univ, Dept Elect & Comp Engn, Philadelphia, PA 19122 USA
来源
2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS | 2020年
关键词
automotive radar; autonomous driving; multi-frequency sparse arrays; matrix completion; MIMO radar; COPRIME ARRAY; DESIGN;
D O I
10.1109/IEEECONF51394.2020.9443455
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose the concept of high-resolution massive multiple-input multiple-output (MIMO) radar with large-aperture sparse arrays for autonomous driving by exploiting multi-frequency signaling. The diversity offered by multi-frequency signals renders a high number of virtual sensors that effectively increase the degrees of freedom. Two strategies are developed to synthesize virtual sparse arrays by jointly utilizing MIMO radar sum coarray and multi-frequency signaling, respectively with and without further incorporating the difference coarray concept. As an example, we synthesize sparse arrays with an aperture of around 100 normalized half-wavelength using only 7 physical array elements in the context of the proposed multi-frequency MIMO radar.
引用
收藏
页码:1167 / 1171
页数:5
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