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PolInSAR Coherence and Entropy‐Based Hybrid Decomposition Model
Earth and Space Science ( IF 2.9 ) Pub Date : 2020-09-16 , DOI: 10.1029/2020ea001279
Shahid Shuja Shafai 1 , Shashi Kumar 2
Affiliation  

Target characterization is an essential aspect of polarimetric decomposition. This technique is capable of categorizing polarimetric signatures for different types of targets based on the scattering mechanisms they follow, enabling straightforward physical interpretation of the targets. The geometric anomalies associated with human‐made targets escalate the degree of randomness in the scattering process, which causes scattering ambiguity for such targets. The second‐order model descriptors do not relate to the actual physical structure and yield predominant volume scattering power. Such urban targets are decomposed as natural targets leading to irrelevant decomposition results. The methods developed to curb the problem are unable to maintain the consistency in the decomposition modeling as they underestimate volume scattering powers for natural landcover. A hybrid decomposition model is proposed herein to solve the problem of predominant volume scattering observed from urban targets by preserving volume scattering powers for natural targets. The model uses eigenvalue‐based decomposition parameters and polarimetric interferometric synthetic aperture radar (PolInSAR) coherence to decompose ambiguous targets. The proposed model has been tested on NISAR UAVSAR PolInSAR data acquired over the Greenville region, MS, USA. The proposed model has increased the double‐bounce scattering from the urban targets and enhanced the volume scattering from natural landcover as well. By comparing the results with existing decomposition models, it is observed that the proposed model gives a more robust representation of the landcover than the compared decomposition models.

中文翻译:

基于PolInSAR相干和熵的混合分解模型

目标表征是极化分解的重要方面。这项技术能够根据其遵循的散射机制对不同类型目标的极化特征进行分类,从而可以对目标进行简单的物理解释。与人造目标相关的几何异常会加剧散射过程中的随机度,从而导致此类目标的散射模糊性。二阶模型描述子与实际的物理结构无关,并产生主要的体积散射能力。这些城市目标被分解为自然目标,从而导致无关的分解结果。为解决该问题而开发的方法无法保持分解模型的一致性,因为它们低估了自然土地覆被的体积散射能力。本文提出了一种混合分解模型,通过保留自然目标的体积散射功率来解决从城市目标观察到的主要体积散射问题。该模型使用基于特征值的分解参数和极化干涉式合成孔径雷达(PolInSAR)相干性来分解模糊目标。所提出的模型已经在美国MS格林维尔地区获得的NISAR UAVSAR PolInSAR数据上进行了测试。所提出的模型增加了城市目标的双反射散射,并增强了自然土地覆盖物的体积散射。
更新日期:2020-10-02
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