Key Laboratory of Technology in Geospatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China.
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China.
Sensors (Basel). 2019 Jan 16;19(2):346. doi: 10.3390/s19020346.
In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful feature. Circular SAR (CSAR) can detect the scattering variation under different azimuthal look angles by a 360-degree observation. Different targets usually have varying degrees of anisotropy, which aids in target discrimination. However, there is no effective method to quantify the degree of anisotropy. In this paper, aspect entropy is presented as a descriptor of the scattering anisotropy. The range of aspect entropy is from 0 to 1, which corresponds to anisotropic to isotropic. First, the method proposed extracts aspect entropy at the pixel level. Since the aspect entropy of pixels can discriminate isotropic and anisotropic scattering, the method prescreens the target from the isotropic clutters. Next, the method extracts aspect entropy at the target level. The aspect entropy of targets can discriminate between different types of targets. Then, the effect of noise on aspect entropy extraction is analyzed and a denoising method is proposed. The Gotcha public release dataset, an X-band circular SAR data, is used to validate the method and the discrimination capability of aspect entropy.
在传统的合成孔径雷达（SAR）工作模式中，由于视角较小，目标被假设为各向同性。然而，大多数人造目标是各向异性的。因此，当视角较大时，应该考虑各向异性。从另一个角度来看，各向异性也是一个有用的特征。圆迹 SAR（CSAR）可以通过 360 度观测来检测不同方位角视场下的散射变化。不同的目标通常具有不同程度的各向异性，这有助于目标识别。然而，目前还没有有效的方法来量化各向异性的程度。在本文中，提出了方位熵作为散射各向异性的描述符。方位熵的范围是从 0 到 1，对应于各向异性到各向同性。首先，所提出的方法在像素级提取方位熵。由于像素的方位熵可以区分各向同性和各向异性散射，因此该方法可以从各向同性杂波中预筛选目标。接下来，该方法在目标级提取方位熵。目标的方位熵可以区分不同类型的目标。然后，分析了噪声对方位熵提取的影响，并提出了一种去噪方法。使用 Gotcha 公共发布数据集（一个 X 波段圆迹 SAR 数据）验证了该方法和方位熵的判别能力。
