机载高分辨率SAR图像数据建模

目前对高分辨率陆地合成孔径雷达图像数据特性尚缺乏充分研究. 该文提出K-S检验的改进方法并设计组合假设检验，验证高分辨率农田合成孔径雷达图像数据与球不变随机向量模型的相容性，提出一致区域概念对数据进行局部化处理，以简化数据的高阶统计特性分析. 实验表明，K-S检验改进算法对不独立样本数据具有良好的健壮性，农田的高分辨率合成孔径雷达图像数据与球不变随机向量模型是相容的. 通过对农田数据的分析验证了一致区域概念的合理性，并确定了给定数据集的一致区域空间尺度.

Modeling of Airborne High Resolution SAR Image Data

Considering the absence of statistical analysis on land image data of high-resolution SAR, an enhanced version of K-S test based on data pre-treatment is proposed, and composite hypothesis tests designed to validate compatibility of the cropland data with the model of spherically invariant random vector (SIRV). Definition of the consistency region is given, meaning that the image is processed locally, to resolve the problem that higher order statistical characteristics are mathematically tractable in an SIRV model. Experiments show that the enhanced method of K-S test has good robustness for non-independent samples, and the cropland data are compatible with the SIRV model. By analyzing the cropland data, rationality of coherence region concept is proved, and the space scale of consistency region for the data is found.