Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm

This paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Complementary Coprime Planar Array (CCPA) that strategical...

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Main Authors: Yunhe Shi, Xiaofei Zhang, Shengxinlai Han
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/5/1456
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author Yunhe Shi
Xiaofei Zhang
Shengxinlai Han
author_facet Yunhe Shi
Xiaofei Zhang
Shengxinlai Han
author_sort Yunhe Shi
collection DOAJ
description This paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Complementary Coprime Planar Array (CCPA) that strategically fills key holes in the virtual array. This design enhances the array’s continuous Degrees Of Freedom (DOFs) and virtual aperture, achieving improved performance in 2D-DOA estimation with fewer physical elements. The virtualization of the array further increases the available DOFs, while the hole-filling strategy ensures better spatial coverage and continuity. On the algorithmic side, we introduce a dimensionality-reduction root MUSIC algorithm tailored for uniform planar arrays after virtualization. By decomposing the two-dimensional spectral peak search into two one-dimensional polynomial root-finding problems, the proposed method significantly reduces computational complexity while maintaining high estimation accuracy. This approach effectively mitigates the challenges of 2D peak search, making it computationally efficient without sacrificing precision. Extensive simulations demonstrate the advantages of the proposed array and algorithm, including higher DOFs, reduced complexity, and superior estimation performance compared to existing methods. These results validate the effectiveness of the proposed framework in advancing sparse array design and signal processing for 2D-DOA estimation.
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spelling doaj-art-b54343cacf9345118ee7d4ef7f32759b2025-08-20T02:59:12ZengMDPI AGSensors1424-82202025-02-01255145610.3390/s25051456Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC AlgorithmYunhe Shi0Xiaofei Zhang1Shengxinlai Han2College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThis paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Complementary Coprime Planar Array (CCPA) that strategically fills key holes in the virtual array. This design enhances the array’s continuous Degrees Of Freedom (DOFs) and virtual aperture, achieving improved performance in 2D-DOA estimation with fewer physical elements. The virtualization of the array further increases the available DOFs, while the hole-filling strategy ensures better spatial coverage and continuity. On the algorithmic side, we introduce a dimensionality-reduction root MUSIC algorithm tailored for uniform planar arrays after virtualization. By decomposing the two-dimensional spectral peak search into two one-dimensional polynomial root-finding problems, the proposed method significantly reduces computational complexity while maintaining high estimation accuracy. This approach effectively mitigates the challenges of 2D peak search, making it computationally efficient without sacrificing precision. Extensive simulations demonstrate the advantages of the proposed array and algorithm, including higher DOFs, reduced complexity, and superior estimation performance compared to existing methods. These results validate the effectiveness of the proposed framework in advancing sparse array design and signal processing for 2D-DOA estimation.https://www.mdpi.com/1424-8220/25/5/1456sparse array design2-D DOA estimationcoprime planar arrayarray signal processingdegrees of freedom (DOFs)
spellingShingle Yunhe Shi
Xiaofei Zhang
Shengxinlai Han
Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
Sensors
sparse array design
2-D DOA estimation
coprime planar array
array signal processing
degrees of freedom (DOFs)
title Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
title_full Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
title_fullStr Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
title_full_unstemmed Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
title_short Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm
title_sort two dimensional doa estimation for coprime planar arrays from array structure design to dimensionality reduction root music algorithm
topic sparse array design
2-D DOA estimation
coprime planar array
array signal processing
degrees of freedom (DOFs)
url https://www.mdpi.com/1424-8220/25/5/1456
work_keys_str_mv AT yunheshi twodimensionaldoaestimationforcoprimeplanararraysfromarraystructuredesigntodimensionalityreductionrootmusicalgorithm
AT xiaofeizhang twodimensionaldoaestimationforcoprimeplanararraysfromarraystructuredesigntodimensionalityreductionrootmusicalgorithm
AT shengxinlaihan twodimensionaldoaestimationforcoprimeplanararraysfromarraystructuredesigntodimensionalityreductionrootmusicalgorithm