基于遗传算法的目标声散射回波多方向核函数匹配

罗俊; 李秀坤; 杜金鑫

doi:10.11990/jheu.202506021

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基于遗传算法的目标声散射回波多方向核函数匹配

论文 | 更新时间：2026-03-31

- 基于遗传算法的目标声散射回波多方向核函数匹配
- Multidirection kernel function matching of target acoustic scattering echo based on genetic algorithm
- 哈尔滨工程大学学报 2025年46卷第8期页码：1574-1582
- 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：
  
  [ "罗俊, 男, 硕士研究生" ]
  [ "李秀坤, 女, 教授, 博士生导师" ]
- 基金信息：
  
  国家自然科学基金项目(U2441254)
- DOI：10.11990/jheu.202506021
  中图分类号： TN911.7
- 收稿：2025-06-09，
  
  网络首发：2025-06-26，
  
  纸质出版：2025-08-05
- 稿件说明：
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罗俊, 李秀坤, 杜金鑫. 基于遗传算法的目标声散射回波多方向核函数匹配[J]. 哈尔滨工程大学学报, 2025,46(8):1574-1582.

Jun LUO, Xiukun LI, Jinxin DU. Multidirection kernel function matching of target acoustic scattering echo based on genetic algorithm[J]. Journal of Harbin Engineering University, 2025, 46(8): 1574-1582.
罗俊, 李秀坤, 杜金鑫. 基于遗传算法的目标声散射回波多方向核函数匹配[J]. 哈尔滨工程大学学报, 2025,46(8):1574-1582. DOI： 10.11990/jheu.202506021.

Jun LUO, Xiukun LI, Jinxin DU. Multidirection kernel function matching of target acoustic scattering echo based on genetic algorithm[J]. Journal of Harbin Engineering University, 2025, 46(8): 1574-1582. DOI： 10.11990/jheu.202506021.

摘要

亮点模型将目标声散射回波视为各亮点子回波的叠加，当相邻2个散射回波成分之间的时延小于发射信号脉宽，目标回波在时频域上严重混叠，采用魏格纳分布时频分析方法处理时则存在严重的交叉项干扰，无法在时频面上准确识别各亮点。本文推导了多几何亮点模型的模糊函数，并根据其自项和交叉项分布特点，选择多方向核函数来更好地匹配自项。根据先验信息确定核函数的角度参数，以体积归一化的三阶瑞丽熵作为时频分布的评价指标，使用遗传算法优化核函数其他参数，进而利用得到的核函数对声散射回波在模糊域滤波得到高分辨力时频分布。实验结果表明：本文方法得到的时频分布可以在保证自项分辨率的同时有效减弱交叉项干扰，提高时频图像信噪比。提取的全方位声散射特征模型可为水下目标探测提供依据。

Abstract

The highlight model is predicated on the premise that target acoustic scattering echoes are the sum of individual subechoes. When the transmitted signal pulse width exceeds the time delay between adjacent scattering echo components

the target echoes overlap severely in the time-frequency domain. When WVD is employed for time-frequency analysis

it leads to substantial cross-term interference

impeding the ability to resolve individual highlights on the time-frequency plane. Therefore

this paper aims to derive the ambiguity function for the multigeometric highlight model. A multidirectional kernel function is selected to optimize the alignment between the self terms and the distribution characteristics of its self terms and cross terms. Subsequently

the angle parameters of the kernel function are determined using prior information. The volume-normalized third-order Rényi entropy is then employed as the evaluation metric for the time-frequency distribution. The genetic algorithm is employed to optimize the remaining parameters of the kernel function. The obtained kernel is then utilized to filter the acoustic scattering echo in the fuzzy domain to obtain a high-resolution time-frequency distribution. Experimental results demonstrate the efficacy of cross-term suppression

while preserving self-term resolution

thereby enhancing the signal-to-noise ratio of the time-frequency image. The extracted full-aspect acoustic scattering feature model has the potential to facilitate underwater target detection.

关键词

Keywords

references

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