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Sea-floor characterization related to object-detection performance of sonar systems: a case study

机译:与声纳系统的对象检测性能相关的海底特征:一个案例研究

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In this study, we use lacunarity maps in order to predict the influence of seafloor characteristics in the object-detection performance of high resolution imagery sonar systems. Three different synthetic aperture sonar (SAS) systems have been used to collect acoustic data. They will be referred as SAS1, SAS2 and SAS3 to avoid drawing a comparison. A test area on the Belgian Continental Shelf, between the Thorton bank and the Goote Bank, is selected based on the long term stability of its physical characteristics. Different objects (exercise-mines and friendly-objects) have been deployed in this area and acoustic data are collected during object-detection trails. Results demonstrate a relation between the difficulty of detecting a target and the environmental parameters, in accordance with other analysis presented in the literature.
机译:在这项研究中,我们使用Lovarity图来预测海底特性在高分辨率图像声纳系统的对象检测性能中的影响。三种不同的合成孔径声纳(SAS)系统已被用于收集声学数据。它们将被称为SAS1,SAS2和SAS3,以避免绘制比较。基于其物理特征的长期稳定性,选择了比利时欧式货架上的测试区域。在该区域中部署了不同的对象(锻炼 - 地雷和友好物体),在对象检测路径期间收集声学数据。结果证明了根据文献中提出的其他分析检测目标和环境参数之间的关系。

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