Coprime Visible Regions Assisted Angle Unfolding for Sparse ESPRIT
Coprime Visible Regions Assisted Angle Unfolding for Sparse ESPRIT
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DOI：
10.1109/radarconf2351548.2023.10149628
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Lifan Xu;Shunqiao Sun
中科院分区：
文献类型：
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作者：
Lifan Xu;Shunqiao Sun
在许多应用中，例如自动驾驶汽车的汽车雷达，稀疏线性阵列 (SLA) 比均匀线性阵列 (ULA) 更有吸引力。 SLA不仅可以降低设计大孔径天线阵列的硬件成本，还可以减少天线元件之间的相互耦合。当通过有理不变技术 (ESPRIT) 估计信号参数应用于子阵列之间的偏移大于半波长的 SLA 时，由于角度折叠，传感器阵列的视场 (FoV) 会出现模糊。在本文中，我们提出了具有非均匀子阵列的新型 SLA 几何结构，这些子阵列不一定具有中心对称的几何结构，以及相应的互质 FoV 辅助方法来进行角度展开。稀疏阵列设计的主要目标是使用更少的传感器增加阵列孔径尺寸，同时保持平移不变的几何形状。通过按照互质关系仔细设计这些稀疏子阵列之间的移位，可以通过对不同移位子阵列分别报告的角度估计进行一致比较来唯一地解析角度。
In many applications, such as automotive radar for autonomous vehicles, a sparse linear array (SLA) is more attractive than a uniform linear array (ULA). SLAs not only make hardware costs lower to design antenna arrays with a large aperture but also reduce the mutual coupling among antenna elements. When estimation of signal parameters via rational invariance techniques (ESPRIT) is applied on SLAs with shift among subarrays being larger than half wavelength, there would be ambiguities in the field of view (FoV) of the sensor array due to angle folding. In this paper, we present novel SLA geometry with non-uniform subarrays that do not necessarily have a centrally symmetric geometry, and corresponding coprime FoV aided approach to do the angle unfolding. The main goal of the sparse array design is to increase the array aperture size using fewer sensors while maintaining shift invariant geometry. By carefully designing the shifts among these sparse subarrays following a coprime relationship, the angles can be resolved uniquely by a consistent comparison of the angle estimations reported separately by different shifted subarrays.