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Marine Floating Raft Aquaculture Back Scattering Feature Analysis Based On ISAR Imagery

机译:基于ISAR图像的海上浮筏水产养殖反向散射特征分析

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Synthetic Aperture Radar (SAR) is an important composition on remote sensing. Computer intelligence is widely used in SAR data classification, this addresses the importance of studying the back scatter feature of the studied object. In this paper, Inverse Synthetic Aperture Radar (ISAR) images of floating raft aquaculture (FRA) are designed to analyze detail scattering features of FRA. And the Pierson-Moskowitz (P-M) sea wave spectrum is adopted to imitate sea surface under a certain wind speed. Commercial E-M software FEKO is used for calculate the back scatter data of combined scenario. And polar format algorithm is used to generate ISAR images. After that, the ISAR images of different circumstances combined with FRA and sea are compared and analyzed. The results demonstrate that proposed method is capable of exhibiting the changes of back scatter feature in different scenarios. And the backscatter feature of FRA is correlated with the height above the sea surface.
机译:合成孔径雷达(SAR)是遥感技术的重要组成部分。计算机智能被广泛用于SAR数据分类中,这解决了研究被研究对象的反向散射特征的重​​要性。本文设计了浮筏养殖(FRA)的逆合成孔径雷达(ISAR)图像,以分析FRA的详细散射特征。并采用Pierson-Moskowitz(P-M)海浪谱来模拟一定风速下的海面。商业E-M软件FEKO用于计算组合场景的后向散射数据。并采用极坐标格式算法生成ISAR图像。然后,比较和分析了结合FRA和海洋的不同情况的ISAR图像。结果表明,该方法能够在不同场景下展现出反向散射特征的变化。 FRA的反向散射特征与海平面以上的高度相关。

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