Side-scan sonar (also sometimes called side scan sonar, sidescan sonar, side imaging sonar, side-imaging sonar and bottom classification sonar) is a category of sonar system that is used to efficiently create an image of large areas of the sea floor.

Side-scan sonar is a category of active sonar system for detecting and imaging objects on the seafloor. The multiple physical sensors of the sonar — called a transducer array — send and receive the acoustic pulses that help map the seafloor or detect other objects.

側掃聲納（英文：side-scan sonar），是一種利用聲波反射的原理來提供海床水平影像的水下探勘儀器，其優點為可對海床做大範圍區域的探測調查，在海床地貌描繪、海床沉積物性質辨別、以及水中目標物搜尋等水下工作上，均扮演著極為關建的角色。

2009年1月1日 · Accurate mapping of marine benthic habitats, using acoustic technologies such as Side-Scan Sonar (SSS), is a useful tool for marine conservation and management, as well as to support zoning ...

2024年8月12日 · Side Scan Sonar. How It Works: Side scan sonar emits sound pulses to the sides, creating detailed images of the seafloor and underwater objects. Applications: Wreck detection, habitat mapping, and underwater archaeology. Limitations: Does not provide depth information directly. Example Models and Brands:

2024年5月8日 · 引入了一种新型的侧扫声纳（SSS）数据集，专门用于墙壁检测，为该领域的研究和实践提供了更加全面和专业的数据支持，从而推动了墙壁检测技术的发展和应用。 目标检测。 目标检测是计算机视觉（CV）中的基本任务，旨在数字图像中检测特定类别的视觉目标 [5]。 其目标是开发高效的算法，为CV应用提供必要的信息： “哪些目标在哪里？ ”。 这些方法的质量通过检测准确性（分类和定位）和效率（预测时间）来衡量。 这些方法力求在准确性和效率之间找 …

2022年2月7日 · Accurate segmentation of target regions in side-scan sonar images is a challenging issue due to the low-resolution and strong noise interference. To accurately and faster segment the different categories target in sonar image, a novel convolutional neural networks (CNNs) model is proposed in this study.

This handbook not only presents all the fundamentals but also explains how to interpret sidescan sonar imagery and bathymetry. It fully explores the most recent advances, both in the …

Side-scan sonar is a category of sonar system that is used to efficiently create an image of large areas of the seafloor. This tool is used for mapping the seabed for a wide variety of purposes, including creation of nautical charts and detection and identification of underwater objects and bathymetric features.

The experimental results demonstrate that our improved Deeplabv3+ algorithm achieves better performance in side-scan sonar image segmentation compared to other methods, highlighting its potential for improving the recognition and detection of underwater targets.