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Geometrical Correction of Side-scan Sonar Images

机译:侧面扫描声纳图像的几何校正

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The underwater environment makes object-detection missions difficult. Side-scan Sonar (SSS) has been found to be suitable for seabed scanning missions, however the sonar images acquired from SSS often suffer from considerable noise and geometrical distortion, which changes the understanding of the texture, size, and shape of seabed objects. In order to identify seabed objects, it is thus vital to reconstruct the actual shape by reducing distortion. This paper proposes a process for correcting and reconstructing the sonar image map that utilizes intensity normalization, slant range correction, yaw and pitch correction, and speed and location correction. This is done using navigation and inertial data acquired by the autonomous underwater vehicle sensors.
机译:水下环境使目标探测任务变得困难。已发现侧面扫描声纳(SSS)适合海底扫描任务,但是从SSS获取的声纳图像通常会遭受相当大的噪声和几何失真,从而改变了对海底物体的纹理,大小和形状的理解。为了识别海底物体,因此至关重要的是通过减少变形来重建实际形状。本文提出了一种利用强度归一化,倾斜范围校正,偏航和俯仰校正以及速度和位置校正来校正和重建声纳图像图的过程。这是通过自主水下航行器传感器获取的导航和惯性数据完成的。

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