Shift-Based Symmetric Coprime Planar Arrays With Increased Degrees of Freedom and Reduced Mutual Coupling

Zexiang Zhang, Qing Shen*, Wei Liu, Kangning Li, Kejiang Wu

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

In the past decade, design of sparse planar arrays has increasingly become a focal point, driven by its superior performance in terms of degrees of freedom (DOFs) and anti-mutual-coupling effects compared to other uniform distributed planar arrays. In this paper, an innovative sparse planar array geometry is introduced for two-dimensional (2-D) direction of arrival (DOA) estimation, leveraging the difference co-array (DCA) technique to generate a virtual array with large consecutive co-arrays. At first, we propose an array structure referred to as shift-based symmetric coprime planar array (SSCPA). This design acts as a springboard, utilizing shifted coprime arrays to provide a higher uniform DOFs (uDOFs) than existing structures. To address the inherent contradiction between the high uDOFs and the low mutual coupling effect of SSCPA's parameter selection, we propose an enhanced version named improved shift-based symmetric coprime planar array (ISSCPA), holding smaller weight functions for near separated sensors. This improved design maintains the same uDOFs as offered by SSCPA while improving robustness against mutual coupling. Compared with existing array structures, simulation results confirm that our proposed structure performs better in terms of resolution and accuracy for 2-D DOA estimation.

源语言英语
期刊IEEE Transactions on Vehicular Technology
DOI
出版状态已接受/待刊 - 2025

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