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<p>Coprime arrays and their improved variants employ a sparse structure with extended inter-element spacing, effectively mitigating mutual coupling (MC) effects. However, their restricted hole-filling capability yields reduced uniform degrees of freedom (uDOFs) in the difference co-array (DCA). In contrast, nested arrays and their enhanced versions achieve near-complete or full hole filling, substantially increasing uDOFs and array aperture. However, their denser element spacing exacerbates MC effects, complicating accurate direction-of-arrival (DOA) estimation in practical scenarios. In this study, we propose a novel array configuration, termed the optimal weight functions sparse array (OWSA), which comprises six subarrays. The OWSA maximizes hole filling to enhance uDOFs, while preserving sparse element distribution and optimizing weight functions, thereby reducing MC effects. This design establishes an optimal trade-off between maximizing uDOFs and minimizing MC effects, addressing key limitations in prior array designs. Numerical simulations validate that the OWSA outperforms existing array configurations in terms of: uDOFs, weight function minimization, snapshot efficiency, performance under low signal-to-noise ratio (SNR) conditions, and DOA estimation accuracy in challenging environments.</p>

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An Optimal Weight Functions Sparse Array with Minimal Coupling for DOA Estimation

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • Yujie Han,
  • Lanmei Wang,
  • Yu Che,
  • Guibao Wang,
  • Xianghui Wang

摘要

Coprime arrays and their improved variants employ a sparse structure with extended inter-element spacing, effectively mitigating mutual coupling (MC) effects. However, their restricted hole-filling capability yields reduced uniform degrees of freedom (uDOFs) in the difference co-array (DCA). In contrast, nested arrays and their enhanced versions achieve near-complete or full hole filling, substantially increasing uDOFs and array aperture. However, their denser element spacing exacerbates MC effects, complicating accurate direction-of-arrival (DOA) estimation in practical scenarios. In this study, we propose a novel array configuration, termed the optimal weight functions sparse array (OWSA), which comprises six subarrays. The OWSA maximizes hole filling to enhance uDOFs, while preserving sparse element distribution and optimizing weight functions, thereby reducing MC effects. This design establishes an optimal trade-off between maximizing uDOFs and minimizing MC effects, addressing key limitations in prior array designs. Numerical simulations validate that the OWSA outperforms existing array configurations in terms of: uDOFs, weight function minimization, snapshot efficiency, performance under low signal-to-noise ratio (SNR) conditions, and DOA estimation accuracy in challenging environments.