polarimetric [pəu,læri'metrik]

polarimetric的基本解释

adj.

测定偏振的

与polarimetric相关的网络例句 [注：此内容来源于网络，仅供参考]

In this dissertation, based on the extraction of meaningful polarization information, the polarimetric speckle reduction, polarimetric contrast enhancement, polarimetric classification and ship detection in polarimetric SAR images are systemically studied. During the study, some new concepts and methods are introduced, which are supported by the application to measured Pol-SAR data. The innovations of this dissertation are as follows: 1 A simplified schem is proposed to reduce the complexity of scattering-model-based speckle filtering. 2 Extend the expression of polarimetric correlation coefficient to help distinguishing targets. In addition, introduce the quantized parameters of polarimetric signature so as to show the differentiae in quantity in co-polar power, cross-polar power and shapes of polarization signatures among targets. 3 Define a new parameter of difference degree between targets, which can be used for express the difference between both coherent and distributed scatters.

论文在较系统的研究目标特征量提取方法和特征量所包含的物理意义的基础上，对极化SAR图像降斑、极化对比增强、极化SAR图像分类以及极化SAR图像中海上舰船目标检测等方面进行了研究，并提出了一些新的概念和方法，对实测数据的处理结果表明，这些新的概念和方法对于极化SAR信息处理是有效的，本文的主要创新成果包括以下方面： 1）针对基于预分类的MMSE极化降斑方法实现过程非常复杂的问题，提出了简化方案，并验证了方案的有效性； 2）扩展了极化相关系数的表示方法，这种扩展增强了极化相关系数对目标的区分效果；另外还提出了极化特征图量化参数，可以从量上表征不同目标间相同极化和交叉极化的回波功率差异和极化特征图形状差异； 3）定义了目标间的差异度参数，它不仅可以用于描述相干目标，还可以用于描述分布目标的差别程度。

All above laid a foundation for the research of polarimetric information processing and application. Then, target optimum polarization and polarimetric synthesis technique were studied. By constraining polarimetric states of transmitting and receiving antennas, co-polarized and cross-polarized signatures were obtained. Because the received wave was partially polarized, completely polarized, completely unpolarized, and total available power signatures were defined based on the power of the return wave.

接着，论文深入研究了目标最佳极化和极化合成技术，通过约束收发天线的极化状态可以得到共极化特征图和交叉极化特征图，由于雷达接收的电磁波通常是部分极化的，根据接收波的平均功率密度可以得到未极化特征图、完全极化特征图和匹配极化特征图，在极化特征图空间中搜索可以很容易地获得目标的最佳极化，这些目标最佳极化可以作为极化目标识别和分类的极化特征。

Many polarimetric target decompositions were explored, and support vector machine was applied to the classification of polarimetric SAR image. A new algorithm of target classification was presented based on polarimetric target decomposition and support vector machine. Finally, the effect of classification results was discussed by selecting different kernels and different parameters.

五系统地对各种极化目标分解方法进行了深入的探讨，并应用支持向量机对极化SAR图像进行分类研究，提出了一种基于极化目标分解和支持向量机的目标分类算法，并通过选择各种类型的核函数以及不同的参数，探讨其对地物目标分类结果的影响。