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一种用于测向的直接共阵列插值方法。

A Direct Coarray Interpolation Approach for Direction Finding.

作者信息

Chen Tao, Guo Muran, Guo Limin

机构信息

College of Information and Communication Engineering, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China.

Depaprtment of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19122, USA.

出版信息

Sensors (Basel). 2017 Sep 19;17(9):2149. doi: 10.3390/s17092149.

Abstract

Sparse arrays have gained considerable attention in recent years because they can resolve more sources than the number of sensors. The coprime array can resolve O ( M N ) sources with only O ( M + N ) sensors, and is a popular sparse array structure due to its closed-form expressions for array configuration and the reduction of the mutual coupling effect. However, because of the existence of holes in its coarray, the performance of subspace-based direction of arrival (DOA) estimation algorithms such as MUSIC and ESPRIT is limited. Several coarray interpolation approaches have been proposed to address this issue. In this paper, a novel DOA estimation approach via direct coarray interpolation is proposed. By using the direct coarray interpolation, the reshaping and spatial smoothing operations in coarray-based DOA estimation are not needed. Compared with existing approaches, the proposed approach can achieve a better accuracy with lower complexity. In addition, an improved angular resolution capability is obtained by using the proposed approach. Numerical simulations are conducted to validate the effectiveness of the proposed approach.

摘要

近年来,稀疏阵列因其能分辨出比传感器数量更多的信号源而备受关注。互质阵列仅用O (M + N) 个传感器就能分辨出O (MN) 个信号源,并且由于其阵列配置的闭式表达式以及互耦效应的降低,它是一种流行的稀疏阵列结构。然而,由于其虚拟阵列中存在空洞,诸如MUSIC和ESPRIT等基于子空间的波达方向(DOA)估计算法的性能受到限制。已经提出了几种虚拟阵列插值方法来解决这个问题。本文提出了一种通过直接虚拟阵列插值的新型DOA估计方法。通过使用直接虚拟阵列插值,基于虚拟阵列的DOA估计中不需要重塑和空间平滑操作。与现有方法相比,该方法能以更低的复杂度实现更高的精度。此外,通过使用该方法还获得了改进的角分辨率能力。进行了数值模拟以验证该方法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a348/5621009/1300fe5dd10e/sensors-17-02149-g001.jpg

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