论文标题
极度稀疏的共阵感应：低潜伏期估计不是梦想，而是一个现实
Extremely Sparse Co-Prime Sensing: Low Latency Estimation is not a Dream but a Reality
论文作者
论文摘要
共晶传感是一种用于信号获取的亚nyquist技术。文献中已经提出了对共同阵列原型阵列的几种修改。研究人员还显示出低潜伏期的估计。本文介绍了一个可调枢轴共同阵列的家族的功能。但是，主要重点是向读者介绍一个称为“极稀疏的共阵容阵列和采样器”的概念。可调节的枢轴联合阵列是极稀疏阵列的特殊情况。得出了权重函数和相关图偏置窗口的闭合形式表达式。使用极为稀疏的共晶方案证明了低潜伏期估计。此外，提出了多维和混合稀疏的共同阵列阵列，以作为1D理论的直接扩展。最后，开发了具有多个设计参数的广义极稀疏结构。大多数现有结构可能被视为广义计划的特殊情况。
Co-prime sensing is a sub-Nyquist technique for signal acquisition. Several modifications to the prototype co-prime array have been proposed in the literature. Researchers have also demonstrated low latency estimation. This paper describes the functioning of a Family of Adjustable Pivot Co-Prime Arrays. However, the main focus is to introduce the reader to a concept called Extremely Sparse Co-Prime Arrays and Samplers. Adjustable pivot co-prime arrays are a special case of the extremely sparse arrays. The closed-form expressions for the weight function and the correlogram bias window are derived. Low latency estimation is demonstrated using the extremely sparse co-prime scheme. Furthermore, a multidimensional and a hybrid extremely sparse co-prime array is proposed as a straightforward extension of the 1D-theory. Finally, a generalized extremely sparse structure is developed with several design parameters. Most existing structures may be viewed as a special case of the generalized scheme.
