测绘通报 ›› 2025, Vol. 0 ›› Issue (12): 98-102,157.doi: 10.13474/j.cnki.11-2246.2025.1217

• 工程测量分会年会优选论文 • 上一篇    

基于稳健估计品质因子的广州海域海底浅地层底质分类

马力1,2,3, 叶瑞明1,2,3, 杨光1,2,3, 张弛1,2,4, 冯文江1,2,3   

  1. 1. 广州市城市规划勘测设计研究院有限公司, 广东 广州 510060;
    2. 广州市资源规划和海洋科技协同创新中心, 广东 广州 510060;
    3. 广东省城市感知与监测预警企业重点实验室, 广东 广州 510060;
    4. 广州花都规划勘测设计院有限公司, 广东 广州 510813
  • 收稿日期:2025-06-26 发布日期:2025-12-31
  • 通讯作者: 张弛。E-mail:zhangchi9502@outlook.com
  • 作者简介:马力(1985—),男,硕士,高级工程师,主要从事摄影测量与遥感、工程测量方面的工作。E-mail:278607790@qq.com
  • 基金资助:
    广州市资源规划和海洋科技协同创新中心项目(2023B04J0301;2023B04J0191);广东省基础与应用基础研究基金(2023A1515110276);河南省科技攻关项目(252102320089)

Sub-bottom shallow stratum sediment classification in Guangzhou sea areas based on a robust estimated quality factor

MA Li1,2,3, YE Ruiming1,2,3, YANG Guang1,2,3, ZHANG Chi1,2,4, FENG Wenjiang1,2,3   

  1. 1. Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China;
    2. Collaborative Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China;
    3. Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China;
    4. Guangzhou Huadu Planning Survey and Design Institute Co., Ltd., Guangzhou 510813, China
  • Received:2025-06-26 Published:2025-12-31

摘要: 回波信号因海域水体状态存在不同降质,导致利用品质因子的传统浅地层底质分类方法普遍存在不准确、自动化程度低的问题,因此亟须对品质因子进行准确重构。基于此,本文结合变分模态分解与相关性分析,通过声信号的先验特性选择恰当频带范围对品质因子进行稳健估计,并对海底浅地层底质进行准确分类。试验结果验证了品质因子在区分和表征不同类别间的显著性,联立无监督分类方法弥补了传统方法在底质分类自动化方面的不足,实现了浅地层底质的自动分类。

关键词: 品质因子, 变分模态分解, 相关性分析, 浅地层底质分类

Abstract: To address the issues of inaccuracy and low automation in traditional sub-bottom sediment classification methods based on the quality factor (Q-factor),this study utilizes variational mode decomposition (VMD)and correlation analysis to achieve accurate reconstruction of echo signals.By leveraging the prior characteristics of acoustic signals,an optimal frequency band is selected for computation,enabling robust estimation of the Q-factor.The study verifies the significance and accuracy of the Q-factor in distinguishing and characterizing different sediment types.Combined with unsupervised classification methods,it overcomes the limitations of traditional approaches in automation,achieving automatic classification of shallow sub-bottom sediments.

Key words: quality factor, variational mode decomposition, correlation analysis, sub-bottom sediment classification

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