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<p>The mutual coupling effect between sensors is one of the key considerations in array antenna design. The presence of mutual coupling significantly degrades the performance of traditional direction of arrival (DOA) estimation algorithms. To mitigate mutual coupling between elements and enhance the accuracy of DOA estimation, a large-spacing L-shaped array is proposed. This array consists of two linear arrays with large element spacing, each of which is formed by two uniform sub-arrays featuring specific spacing relationships. Hence it can reduce the mutual coupling effect within the array effectively. Based on the proposed array, a multiple extended two-dimensional (2D) estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm is proposed. Compared to many existing similar algorithms, the proposed method exhibits automatic pairing of direction parameters, while also achieving higher estimation accuracy. The effectiveness and superiority of the algorithm are demonstrated through comprehensive simulation experiments.</p>

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A 2D DOA estimation algorithm based on a large-spacing non-uniform L-shaped array

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月31日

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  • Sheng Liu,
  • Jing Zhao,
  • Decheng Wu

摘要

The mutual coupling effect between sensors is one of the key considerations in array antenna design. The presence of mutual coupling significantly degrades the performance of traditional direction of arrival (DOA) estimation algorithms. To mitigate mutual coupling between elements and enhance the accuracy of DOA estimation, a large-spacing L-shaped array is proposed. This array consists of two linear arrays with large element spacing, each of which is formed by two uniform sub-arrays featuring specific spacing relationships. Hence it can reduce the mutual coupling effect within the array effectively. Based on the proposed array, a multiple extended two-dimensional (2D) estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm is proposed. Compared to many existing similar algorithms, the proposed method exhibits automatic pairing of direction parameters, while also achieving higher estimation accuracy. The effectiveness and superiority of the algorithm are demonstrated through comprehensive simulation experiments.