Direction estimation using compressive sampling array processing
Direction estimation using compressive sampling array processing
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DOI：
10.1109/ssp.2009.5278497
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
Ying Wang;G. Leus;A. Pandharipande
中科院分区：
文献类型：
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作者：
Ying Wang;G. Leus;A. Pandharipande
我们提出了一种新的结构，压缩采样(CS)阵列，用于基于阵列的应用，通过利用空域的压缩采样。通过随机投影(或选择)数组元素，我们可以将大尺寸数组转换为小尺寸数组。我们还提出了两种基于CS阵列的波达方向(DOA)估计方法，I.(联合)CS恢复和II.CS波束形成器。因此，我们可以大大降低硬件复杂性和软件复杂性，同时仍然保持所获得的高分辨率，就像使用大尺寸阵列一样。
We propose a new architecture, the compressive sampling (CS) array, for array based applications, by exploiting compressive sampling in the spatial domain. With random projections (or selections) of the array elements, we can transform a large size array into a small size array. We also propose two approaches of direction-of-arrival (DoA) estimation using our CS array, I. (joint) CS recovery, and II. CS beamformers. As a result we can greatly reduce the hardware complexity and software complexity while still maintaining the high resolution achieved as if a large size array were used.