孟俊霞,严俊.多波束声呐水柱图像中气泡羽状流目标探测研究进展[J].安徽建筑大学学报,2021,29(): |
多波束声呐水柱图像中气泡羽状流目标探测研究进展 |
Advances in the Detection of Bubble Plume Targets in Multibeam Sonar Water Column Images |
投稿时间:2020-11-29 修订日期:2020-12-29 |
DOI: |
中文关键词: 多波束声呐水柱图像 气泡羽状流 目标探测 噪声削弱 深度学习 |
英文关键词: multibeam sonar water column image bubble plume target detection denoising deep learning |
基金项目:国家自然科学基金 (41906168),安徽建筑大学博士科研启动基金(2018QD45),安徽省自然科学基金 (1908085QD161),安徽省高校自然科学研究重点项目 (KJ2019A0024) |
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中文摘要: |
多波束声呐水柱图像数据可以获得从换能器到海底的完整声学信息,通过其对气泡羽状流目标探测是发现海底可燃冰渗漏的一种重要途径,是目前海洋调查与监测中的重要观测内容。研究首先介绍多波束水柱数据的数据结构与成像原理,然后针对目前研究存在的主要问题,包括图像噪声大且成因复杂、目标识别方法效率较低、气泡羽状流目标难以准确分割等问题,依次概述当前的研究进展,为海底可燃冰的勘探与监测相关研究提供理论基础。 |
英文摘要: |
The multibeam sonar water column image data can obtain complete acoustic information from the transducer to the seafloor. The detection of bubble plume targets through it is an important way to discover the leakage of seafloor combustible ice, and it is an important observation content in ocean survey and monitoring. The research first introduces the data structure and imaging principle of multibeam water column data, and then summarizes the current research progress in order to provide a theoretical basis for the exploration and monitoring of seafloor combustible ice based on the main problems in the current research, including large image noise and complex causes, low efficiency of target recognition methods, and difficulty in accurate segmentation of bubble plume targets. |
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