An Underwater Target Perception Framework for Underwater Operation Scene
An Underwater Target Perception Framework for Underwater Operation Scene
复制标题
DOI：
10.1109/iros47612.2022.9981170
复制
发表时间：
2022-10
期刊：
影响因子：
--
通讯作者：
Jue Gao;Chi Zhu
中科院分区：
文献类型：
--
作者：
Jue Gao;Chi Zhu
为了全面挖掘水下场景中的目标信息，提高水下作业的工作效率和安全性，本文提出了一种水下目标感知框架。该框架采用水柱成像、恒虚警率检测（CFAR）检测、局部特征分析等分层处理机制，准确区分水下场景中的假目标、静态目标和动态目标，获取动态目标的运动轨迹。通过对水下作业场景的仿真实验，验证了该框架的有效性。
This paper proposes an underwater target perception framework to comprehensively explore target information in underwater scenes, to improve the work efficiency and safety of underwater operations. This framework adopts a layered processing mechanism including water column imaging, constant false alarm rate detection (CFAR) detection, and local feature analysis, to accurately distinguish between false targets, static targets, and dynamic targets in the underwater scene, and obtain the motion trajectory of dynamic targets. The experiment is designed to simulate the underwater operation scene, and the results prove the effectiveness of the proposed framework.