基于极化合成孔径雷达的舰船检测方法

特征提取是极化合成孔径雷达图像处理的一个重要问题，也是海上目标检测的关键。相似性参数和极化熵可以表征目标的电磁散射特性。为了增强目标与背景的对比，提出了一种基于特征融合的新参数。这种参数可表达区域的差异性，处理后目标与背景的对比更加明显。研究了该参量在海杂波区域的分布模型，进而提出了一种新的海上船只检测方法，该方法可用于多视情况下的舰船检测。最后用机载合成孔径雷达(airborne synthetic aperture radar, AirSAR) 数据验证了该方法的有效性。

Ship detection method based on polarimetric SAR

Feature extraction is an important problem of polarimetric synthetic aperture radar (SAR) image pressing and the key of maritime target detection. Similarity parameter and polarization entropy can represent the electromagnetic scattering characteristics of the targets. In order to enhance the contrast of targets and clutter, a new parameter is proposed based on feature parameter fusion. This parameter could express the regional differences in electromagnetic scattering characteristics. After processing, the contrast between targets and backgrounds becomes more apparent. The clutter model of this new parameter is studied, and a new method of ship detection is proposed. By using this parameter, ships are detected for the case of multi-look polarimetric SAR data. Finally the effectiveness of the proposed method is validated by airborne SAR (AirSAR) data.