Strong noise interference suppression of a passive towed linear array based on sparse coefficient reconstruction after eroding and smoothing

Yi ZHENG; Donghu NIE; Zongxin SUN; Dongqi LI; Gang QIAO; Feng ZHOU

doi:10.11990/jheu.202506008

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Strong noise interference suppression of a passive towed linear array based on sparse coefficient reconstruction after eroding and smoothing

Research Article | 更新时间：2026-03-31

- Strong noise interference suppression of a passive towed linear array based on sparse coefficient reconstruction after eroding and smoothing
- Journal of Harbin Engineering University Vol. 46, Issue 8, Pages: 1618-1624(2025)
- 作者机构：
  
  1.哈尔滨工程大学水声技术全国重点实验室，黑龙江哈尔滨 150001
  2.海洋信息获取与安全工信部重点实验室(哈尔滨工程大学) 工业和信息化部，黑龙江哈尔滨 150001
  3.哈尔滨工程大学水声工程学院，黑龙江哈尔滨 150001
  4.哈尔滨工程大学三亚南海创新发展基地，海南三亚 572024
- 作者简介：
- 基金信息：
- DOI：10.11990/jheu.202506008
  CLC： TB566
- Received：05 June 2025，
  
  Online First：24 June 2025，
  
  Published：05 August 2025
- 稿件说明：
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Yi ZHENG, Donghu NIE, Zongxin SUN, et al. Strong noise interference suppression of a passive towed linear array based on sparse coefficient reconstruction after eroding and smoothing[J]. Journal of Harbin Engineering University, 2025, 46(8): 1618-1624.
DOI：

Yi ZHENG, Donghu NIE, Zongxin SUN, et al. Strong noise interference suppression of a passive towed linear array based on sparse coefficient reconstruction after eroding and smoothing[J]. Journal of Harbin Engineering University, 2025, 46(8): 1618-1624. DOI： 10.11990/jheu.202506008.

摘要

针对水声强噪声干扰会导致被动拖线阵目标方位估计性能严重下降的问题，本文提出了一种稀疏系数腐蚀平滑后重构的强噪声干扰抑制方法。利用宽带阵列信号频域压缩感知方法，对拖线阵数据进行空间稀疏表示，引入数字图像处理中的腐蚀和平滑方法，对稀疏系数表示的方位历程图进行处理，估计降噪加权因子并对稀疏系数进行修正，修正后的稀疏系数进行重构得到降噪后的数据。仿真和海试数据处理结果表明：在本文参数条件下，所提方法能够有效抑制接收数据中的强噪声干扰，处理后的仿真和海试数据中的噪声干扰功率有明显的降低，为提高后续目标检测性能打下基础。

Abstract

To address the issue of significant performance degradation in bearing estimation of passive towed linear arrays caused by strong acoustic noise interference underwater

a novel method for noise suppression is proposed to reconstruct sparse coefficients after eroding and smoothing. This method leverages spatial sparse representation of towed linear array data through the application of a compressed sensing technique at signal frequency domains of a wideband array. By incorporating erosion and smoothing algorithms that are commonly utilized in digital image processing

the bearing-time recording represented by sparse coefficients was processed to estimate a noise reduction weighting factor. Subsequently

the sparse coefficients were adjusted accordingly

resulting in the reconstruction of denoised data. The simulation and sea trial data analysis demonstrated the efficacy of the proposed method in mitigating significant noise interference in the received data within the specified parameters. The noise interference power in the processed simulation data and sea trial data was observed to be considerably reduced. These findings provide a basis for enhancing the performance of target detection in the future.

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references

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