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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Low Complexity DFT Based DOA Estimation for Synthetic Nested Array Using Single Moving Sensor
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Low Complexity DFT Based DOA Estimation for Synthetic Nested Array Using Single Moving Sensor

机译:基于低复杂性DFT基于单流传感器的合成嵌套阵列的DOA估计

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摘要

The issue of direction of arrival (DOA) estimation for synthetic nested array is investigated in this paper. The synthetic nested array (SNA) is formed by one single sensor moving according to the configuration of the physical nested array. With the synthetic array, both high resolution DOA estimation and array aperture miniaturization requirements can be met. To reduce the computationally complexity for SNA, a discrete Fourier transform (DFT) based algorithm is proposed which needs no eigen decomposition. We first reconstruct the data matrix reshaped from the data received by moving senor to obtain the observation vector and then get the initial DOA estimates via DFT of the observation vector. At last the fine estimates can be obtained through searching for peaks corrected by phase rotation matrix over a small sector. The proposed algorithm for SNA can achieve better bearing estimation performance than spatial smoothing (SS) subspace based methods such as SS-MUSIC and SS-ESPRIT, due to the fact that it can fully utilize array aperture while SS-MUSIC and SS-ESPRIT lose a half. Besides, the proposed algorithm involves full degree of freedoms (DOF). Numerical simulations validate the efficiency and superiority of the proposed algorithm.
机译:本文研究了综合嵌套阵列的到达方向(DOA)估计问题。合成嵌套阵列(SNA)由一个单个传感器移动,根据物理嵌套阵列的配置移动。通过合成阵列,可以满足高分辨率DOA估计和阵列孔径小型化要求。为了降低SNA的计算复杂性,提出了一种基于离散的傅里叶变换(DFT)的算法,其不需要eIGEN分解。首先,首先重建从移动传票器从收到的数据中重新装入的数据矩阵以获得观察向量,然后通过观察向量的DFT获取初始DOA估计。最后,可以通过在小扇区上搜索通过相位旋转矩阵校正的峰值来获得精细估计。由于SS-Music和SS-ESPRIT丢失的事实,所提出的SNA算法可以实现比SS-Music和SS-ESPRIT等基于空间平滑(SS)子空间的估计性能一半。此外,所提出的算法涉及完整的自由度(DOF)。数值模拟验证所提出的算法的效率和优越性。

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