DOA Estimation for Underwater Coprime Arrays with Sensor Failure Based on Segmented Array Validation and Multipath Matching Pursuit

Coprime arrays enable enhanced degrees of freedom through the construction of virtual array equivalent signals. However, the presence of large “holes” leads to discontinuous co-arrays, which severely hampers direction-of-arrival (DOA) estimation techniques that rely on uniform array structures. This paper explores the practical application of co-array domain signal processing for underwater acoustic coprime arrays. We propose a novel array configuration based on coprime minimum disordered pairs, enabling the formation of continuously connected co-arrays without interpolating. To address the challenge of limited snapshots in underwater environments, DOA estimation can be achieved by utilizing traditional multipath matching pursuit (MMP) algorithms under the proposed continuous co-array implementation scheme. In practical applications, physical array element failures are inevitable, and faulty elements can create holes in the originally continuous co-array. While interpolation techniques can mitigate small gaps, their performance deteriorates significantly in the presence of large holes or uneven data distribution. To overcome these limitations, we introduce a sparse signal recovery (SSR) method using a fragment array data validation technique for sparse DOA estimation with an underwater acoustic coprime array. Based on the designed continuous array expansion scheme, the resulting continuous co-array is used to map the positions of element failures, revealing the gaps in the co-array. A validation model is established for partially continuous sub-arrays within the discontinuous co-array, enabling signal direction estimation based on the fragmented array validation. Both simulation and sea trial results confirm that the proposed approach maximizes the utilization of co-array elements without relying on interpolation or prediction, offering a robust solution for scenarios involving sensor failures.

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Publication Details

Journal
Algorithms
Published
2026-02-04
DOI
https://doi.org/10.3390/a19020125
Primary Topic
Direction-of-Arrival Estimation Techniques
Type
article
Field-Weighted Citation Impact
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article

DOA Estimation for Underwater Coprime Arrays with Sensor Failure Based on Segmented Array Validation and Multipath Matching Pursuit

Ying Zhang, Xiao Chen
Algorithms
Direction-of-Arrival Estimation Techniques
article

DOA Estimation for Underwater Coprime Arrays with Sensor Failure Based on Segmented Array Validation and Multipath Matching Pursuit

Ying Zhang, Xiao Chen
article en

Abstract

Coprime arrays enable enhanced degrees of freedom through the construction of virtual array equivalent signals. However, the presence of large “holes” leads to discontinuous co-arrays, which severely hampers direction-of-arrival (DOA) estimation techniques that rely on uniform array structures. This paper explores the practical application of co-array domain signal processing for underwater acoustic coprime arrays. We propose a novel array configuration based on coprime minimum disordered pairs, enabling the formation of continuously connected co-arrays without interpolating. To address the challenge of limited snapshots in underwater environments, DOA estimation can be achieved by utilizing traditional multipath matching pursuit (MMP) algorithms under the proposed continuous co-array implementation scheme. In practical applications, physical array element failures are inevitable, and faulty elements can create holes in the originally continuous co-array. While interpolation techniques can mitigate small gaps, their performance deteriorates significantly in the presence of large holes or uneven data distribution. To overcome these limitations, we introduce a sparse signal recovery (SSR) method using a fragment array data validation technique for sparse DOA estimation with an underwater acoustic coprime array. Based on the designed continuous array expansion scheme, the resulting continuous co-array is used to map the positions of element failures, revealing the gaps in the co-array. A validation model is established for partially continuous sub-arrays within the discontinuous co-array, enabling signal direction estimation based on the fragmented array validation. Both simulation and sea trial results confirm that the proposed approach maximizes the utilization of co-array elements without relying on interpolation or prediction, offering a robust solution for scenarios involving sensor failures.

AlgorithmsVol. 19(2)
Dalian Maritime University (CN), Ocean University of China (CN)
Life below water
Openalex Percentile: Top 66%
Direction-of-Arrival Estimation Techniques
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DOA Estimation for Underwater Coprime Arrays with Sensor Failure Based on Segmented Array Validation and Multipath Matching Pursuit — Ying Zhang, Xiao Chen · Algorithms (2026) | TGRS Research Map | TGRS