基于多尺度H/A/α分解的全极化HRRP特征提取

针对现有基于H/A/α 分解的全极化高分辨率距离像(HRRP) 特征提取方法没有考虑度量尺度对特征性能的影响问题, 引入动态互信息思想设计了度量尺度评价准则, 并提出了基于平均度量尺度、不定度量尺度和金字塔型度量尺度3 种特征提取方法. 采用两类飞机目标全极化HRRP 数据对提取的特征子集进行了有效性分析, 并通过识别多类飞机目标验证了3 种方法提取的特征子集具有良好的类别可分性和稳定性.

Feature extraction of fully polarimetric HRRP based on multi-scale H/A/α decomposition

The effect on feature performance caused by measuring scale has never been taken into consideration in the present methods of fully polarimetric high range resolution profile(HRRP) feature extraction based  on H/A/α decomposition. Therefore, the dynamic mutual information is introduced to design the evaluation criteria of measuring scale. Meanwhile, three different feature extraction methods are proposed based on mean scale, indefinite scale and pyramid scale respectively. The validity analysis of the feature subsets is performed based on the measured fully polarimetric HRRP data from two kinds of planes. The separability and stability of the subsets are validated by the recognition of multi-class plane.