High fidelity synthetic aperture sonar products for target analysis

R. Hansen, H. Callow, T. O. Saebo, P. E. Hagen, B. Langli
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引用次数: 10

Abstract

Synthetic aperture sonar (SAS) can produce images with centimetre-level resolution and area coverage of better than one square kilometer per hour. This makes SAS an ideal sensor for detection and classification of small targets over large areas. Fully automated target analysis allows improved autonomy when using autonomous underwater vehicles (AUVs) and saves a tedious manual analysis in post-mission analysis. Recognition of small targets in sonar imagery is, however, a difficult task. SAS imagery preserves wavenumber information. This gives the possibility for extra products in addition to high resolution imagery. We propose a two-stage processing where regions of interest are generated from reduced resolution SAS imagery and subsequently post processed images are used to generate relevant target analysis information. In this paper, we concentrate on the types of information available and their significance rather than the choice of intermediate resolution and initial detection methods. The extra processing products discussed in this paper are target-enhanced images by autofocus, shadow-enhanced images by fixed focusing, multi-aspect images, frequency-selective information and 3D shape from interferometry. We show examples of each of the additional products using data collected by the HISAS 1030 interferometric SAS carried by the HUGIN 1000-MR vehicle.
用于目标分析的高保真合成孔径声纳产品
合成孔径声纳(SAS)可以产生厘米级分辨率的图像,每小时的覆盖面积超过一平方公里。这使得SAS成为检测和分类大面积小目标的理想传感器。在使用自主水下航行器(auv)时,全自动目标分析可以提高自主性,并在任务后分析中节省繁琐的人工分析。然而,在声纳图像中识别小目标是一项艰巨的任务。SAS图像保留波数信息。这为高分辨率图像之外的其他产品提供了可能性。我们提出了一种两阶段的处理方法,其中从降低分辨率的SAS图像中生成感兴趣的区域,随后使用后处理图像生成相关的目标分析信息。在本文中,我们专注于可用信息的类型及其意义,而不是中间分辨率和初始检测方法的选择。本文讨论的额外处理产品包括自动对焦的目标增强图像、固定对焦的阴影增强图像、多向图像、频率选择信息和干涉测量的三维形状。我们使用HUGIN 1000-MR车辆携带的HISAS 1030干涉SAS收集的数据展示了每个附加产品的示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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