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基于涡旋声波的二维角域高分辨成像方法

田冠华 郝国栋 张艺杰 张鹏程 韩建宁

机械与电子2026,Vol.44Issue(7):23-30,8.
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机械与电子2026,Vol.44Issue(7):23-30,8.

基于涡旋声波的二维角域高分辨成像方法

A High-resolution Two-dimensional Angular-domain Imaging Method Based on Acoustic Vortex Waves

田冠华 1郝国栋 2张艺杰 1张鹏程 1韩建宁3

作者信息

  • 1. 中北大学信息与通信工程学院,山西 太原 030051
  • 2. 国防科技大学气象海洋学院,湖南 长沙 410073
  • 3. 山西师范大学物理与电子工程学院,山西 太原 030031
  • 折叠

摘要

Abstract

To address the heavy reliance of conventional back-projection methods on high-order orbital an-gular momentum(OAM)modes in two-dimensional angular-domain imaging with acoustic vortex waves,a high-resolution reconstruction method based on sparse Bayesian learning(SBL)is proposed.Based on an exist-ing multiple-input single-output echo model for acoustic OAM waves generated by a uniform circular ar-ray,the correlation function between adjacent scatterers is analyzed,and the relationship among elevation resolution,array aperture,and target elevation angle is derived.Furthermore,a multi-frequency and multi-mode joint observation model is then constructed to reconstruct the equivalent scattering coefficients in the two-dimen-sional angular domain,and a statistical thresholding strategy is incorporated to improve robustness under noisy con-ditions.Simulation results show that the variation in the mainlobe width of the point spread function is consistent with the theoretical analysis.In a four-point scattering target scenario,the SBL based method can effectively dis-tinguish the targets with an OAM mode range of[-10,10],whereas the conventional back-projection method requires an extended range of[-100,100]to yield comparably clear results.At a signal-to-noise ratio of 13 dB,the enhanced SBL method exhibits more stable reconstruction performance than conventional SBL.These results indicate that the proposed method can improve the resolution of two-dimensional angular-domain imaging using acoustic vortex waves even with a limited-mode conditions.

关键词

涡旋声波/轨道角动量/二维成像/稀疏贝叶斯学习

Key words

acoustic vortex waves/orbital angular momentum/two-dimensional imaging/sparse Bayes-ian learning

分类

通用工业技术

引用本文复制引用

田冠华,郝国栋,张艺杰,张鹏程,韩建宁..基于涡旋声波的二维角域高分辨成像方法[J].机械与电子,2026,44(7):23-30,8.

基金项目

山西省回国留学人员科研资助项目(2023-127) (2023-127)

山西省自然科学基金面上资助项目(20210302124201) (20210302124201)

机械与电子

1001-2257

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