| 极化SAR自适应三分量分解方法 |
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| 引用本文： | 蔡永俊,张祥坤,姜景山.极化SAR自适应三分量分解方法[J].测绘学报,2016,45(9):1089-1095. |
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| 作者姓名： | 蔡永俊 张祥坤 姜景山 |
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| 作者单位： | 1. 中国科学院国家空间科学中心, 北京 100190;2. 中国科学院大学, 北京 100049 |
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| 基金项目： | Major National Science and Technology Infrastructure Construction Project (No.10FG001A)国家重大科技基础设施建设项目(10FG001A) |
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| 摘 要： | 介绍了原始极化SAR三分量分解中存在的问题,如负功率和散射机制模糊,并深入分析了其改进方法中仍然存在的缺陷,提出了一种自适应的三分量分解。该分解采用了更一般化的散射模型,并首次考虑了像素中存在不同旋转角的两个面或偶次散射目标,然后利用散射Alpha角确定除体散射之外的剩余主导散射机制,使面或偶次散射得到了更充分的保持。最后,从散射模型与极化相干矩阵自适应匹配的角度出发,提出了一种对负功率进行自适应优化的措施,使得负功率像素个数大大减少,从而分解更加准确有效。试验结果表明,该分解所得结果更符合实际地物散射过程,能更好地解决基于模型的分解方法中存在的缺陷。
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| 关 键 词： | 极化合成孔径雷达 极化分解 基于模型 一般的散射机制 自适应 |
| 收稿时间： | 2015-10-26 |
| 修稿时间： | 2016-06-10 |
Adaptive Three-component Decomposition Approach for Polarimetric SAR Data |
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| CAI Yongjun,ZHANG Xiangkun,JIANG Jingshan.Adaptive Three-component Decomposition Approach for Polarimetric SAR Data[J].Acta Geodaetica et Cartographica Sinica,2016,45(9):1089-1095. |
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| Authors: | CAI Yongjun ZHANG Xiangkun JIANG Jingshan |
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| Institution: | 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China;2. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | In this paper, the problems such as negative power and scattering mechanism ambiguity in original polarimetric SAR three-component decomposition are introduced, and the remaining flaws in its improved approaches are in depth analyzed. Based on these, an adaptive three-component decomposition is proposed, and more generalized scattering models are used. Because in one pixel there may exist two odd or double bounce scattering targets with different orientation angels, the proposed method firstly considers this situation, so that the surface and double bounce scattering can be preserved more sufficiently. And then the alpha parameter is used to identify the dominant scattering except for the volume scattering. Lastly, an optimization measure to the pixels with negative power is proposed, which significantly decreases the negative power pixels count, so the decomposition will be more accurate and more valid. The results show great improvements in real scattering characteristics extraction and the flaws in model based decomposition approaches can be better resolved. |
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| Keywords: | polarimetric synthetic aperture radar polarimetric decomposition model-based generalized scattering mechanism adaptive |
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