近距离原始和重建的地面SAR数据
Filip Turčinović1, Marin Kačan1, Dario Bojanjac1
1University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10 000 Zagreb, Croatia.
Data in brief
|October 12, 2023
概括
本研究介绍了用于材料分类的两个GBSAR数据集. 这些数据有助于使用稀疏的雷达信息来区分,玻璃和塑料等材料.
科学领域:
- 雷达遥感雷达是一种遥感雷达.
- 电磁波的传播方式
- 材料科学 是一种材料科学.
背景情况:
- 基于地面的合成孔径雷达 (GBSAR) 系统提供高分辨率成像能力.
- 使用频率调制连续波 (FMCW) 雷达,运行在24 GHz,带宽为700 MHz.
- 欧米茄-K算法是重建GBSAR图像的常用方法.
研究的目的:
- 为材料分类创建一个 GBSAR 数据的小数据集.
- 以稀疏的雷达数据来区分不同的材料.
- 支持基于雷达的物体识别研究.
主要方法:
- 获取原始 GBSAR 数据 (RealSAR-RAW 数据集).
- 使用Omega-K算法 (RealSAR-IMG数据集) 重建GBSAR图像.
- 数据收集涉及三种测试对象 (瓶子),由各种配置的,玻璃和塑料制成.
主要成果:
- 创建了两个不同的数据集,即RealSAR-RAW和RealSAR-IMG.
- 这些数据集包含未经处理的雷达数据和重建的雷达图像.
- 实验设置允许通过1厘米的步骤尺寸进行详细的场景观测.
结论:
- 开发的数据集对于培训和测试材料分类算法非常有价值.
- 稀少的GBSAR数据可以有效地用于材料识别.
- 这项工作有助于推进基于雷达的传感应用.
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