系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (5): 1451-1464.doi: 10.12305/j.issn.1001-506X.2026.05.01

• 电子技术 • 上一篇    下一篇

基于深水MBES的快速运动目标的探测与重建方法

王媛1,2(), 刘晓东1,3,4,*(), 王舒文1,3   

  1. 1. 中国科学院声学研究所海洋声学技术实验室,北京 100190
    2. 中国科学院大学电子电气与通信工程学院,北京 100049
    3. 北京市海洋声学装备工程技术研究中心,北京 100190
    4. 中国科学院声学研究所声学与海洋信息全国重点实验室,北京 100190
  • 收稿日期:2025-03-04 出版日期:2026-05-27 发布日期:2026-05-27
  • 通讯作者: 刘晓东 E-mail:wangyuan18@mails.ucas.ac.cn;liuxd@mail.ioa.ac.cn
  • 作者简介:王 媛(1994—),女,博士研究生,主要研究方向为水声信号处理
    王舒文(1987—),女,副研究员,硕士,主要研究方向为海洋声学信号处理

Detection and reconstruction method of fast-moving targets based on deep-water MBES

Yuan WANG1,2(), Xiaodong LIU1,3,4,*(), Shuwen WANG1,3   

  1. 1. Laboratory of Ocean Acoustic Technology,Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China
    2. School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China
    3. Beijing Engineering Technology Research Center of Ocean Acoustic Equipment,Beijing 100190,China
    4. State Key Laboratory of Acoustics and Marine Information,Chinese Academy of Sciences,Beijing 100190,China
  • Received:2025-03-04 Online:2026-05-27 Published:2026-05-27
  • Contact: Xiaodong LIU E-mail:wangyuan18@mails.ucas.ac.cn;liuxd@mail.ioa.ac.cn

摘要:

针对走航期间气体泄漏或鱼群等变化较快的水体目标不能快速实时成像的问题,提出一种基于深水多波束测深仪(multibeam echosounder, MBES)的探测和重建方法,利用深水MBES多扇区发射的特点,增强水体实时成像能力。首先通过角度解算对目标区域的三维散射点进行归位实现实时探测,随后通过基于水体反向散射强度改进的大津阈值分割算法和基于牛顿-拉夫逊优化的基于密度带有噪声的空间聚类算法对目标点云进行重建,得到更为清晰的目标图像。所提算法通过仿真实验进行了验证,并对海试数据处理得到清晰的海底气柱图像,验证了所提算法的有效性。

关键词: 深水多波束测深仪, 三维水体, 三维点云重建, 基于牛顿-拉夫逊优化的基于密度带有噪声的空间聚类算法

Abstract:

A detection and reconstruction method based on deep-water multibeam echosounder (MBES) is proposed to address the challenge of rapidly real-time imaging fast-changing underwater targets, such as gas leaks or the shoal of fish, during navigation. The method utilizes the multi-sector emission feature of deep-water MBES to enhance the real-time imaging capability of water column. Firstly, real-time detection is achieved by repositioning the three-dimensional scattering points in the target area through angle calculations. Then, the targets point cloud is reconstructed using the Otsu threshold segmentation algorithm, improved based on water body backscattering intensity, and a density-based spatial clustering of applications with noise optimized with the Newton-Raphson-based optimizer, which leads to clearer underwater target images. The proposed method is validated through simulation experiments, and clear underwater gas column image is obtained by processing sea trial data, verifying the validity of the proposed algorithm.

Key words: deep-water multibeam echosounder (MBES), three-dimensional water body, three-dimensional point cloud reconstruction, Newton-Raphson-based optimizer-density-based spatial clustering of applications with noise

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