Super Fragmented Coprime Arrays for DOA Estimation

The coprime arrays (CA) offer attractive merits in enhancing the degrees of freedom (DOF) and reducing the mutual coupling compared to the uniform linear arrays, which improves the direction of arrival (DOA) estimation performance. However, multiple holes in the difference co-array of the CA cause a loss in DOF and estimation accuracy. This letter presents a super fragmented coprime array (SFCA) configuration, which effectively reconfigures the sensor locations of the existing fragmented coprime design and further increases the inter-subarray spacings. This minimizes the occurrence of holes and enhances the DOF, with the capability of mitigating mutual coupling effects almost identical to the fragmented coprime structure. The SFCA enjoys closed-form expressions for precise sensor locations and calculating the DOF. Simulation results confirm the benefits of the proposed SFCA over other coprime designs.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3563118
Citations
6
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
8.91
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article

Super Fragmented Coprime Arrays for DOA Estimation

Abdul Hayee Shaikh, Xiaoguang Liu
6 citations
IEEE Signal Processing Letters
Speech and Audio Processing
8.91
article

Super Fragmented Coprime Arrays for DOA Estimation

Abdul Hayee Shaikh, Xiaoguang Liu
article en
6 citations

Abstract

The coprime arrays (CA) offer attractive merits in enhancing the degrees of freedom (DOF) and reducing the mutual coupling compared to the uniform linear arrays, which improves the direction of arrival (DOA) estimation performance. However, multiple holes in the difference co-array of the CA cause a loss in DOF and estimation accuracy. This letter presents a super fragmented coprime array (SFCA) configuration, which effectively reconfigures the sensor locations of the existing fragmented coprime design and further increases the inter-subarray spacings. This minimizes the occurrence of holes and enhances the DOF, with the capability of mitigating mutual coupling effects almost identical to the fragmented coprime structure. The SFCA enjoys closed-form expressions for precise sensor locations and calculating the DOF. Simulation results confirm the benefits of the proposed SFCA over other coprime designs.

IEEE Signal Processing LettersVol. 32
Southern University of Science and Technology (CN)
Zero hunger
Openalex Percentile: Top 2%
Speech and Audio Processing
8.91
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Super Fragmented Coprime Arrays for DOA Estimation — Abdul Hayee Shaikh, Xiaoguang Liu · IEEE Signal Processing Letters (2025) | TGRS Research Map | TGRS