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Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis

1,2,3, 1,2 and 4,*
1
Key Laboratory of Technology in Geospatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China
2
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
3
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China
4
School of Electronic Information Engineering, North China University of Technology, Beijing 100144, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(2), 346; https://doi.org/10.3390/s19020346
Received: 27 November 2018 / Revised: 13 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
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Abstract

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. View Full-Text
Keywords: CSAR; anisotropy; aspect entropy; discrimination CSAR; anisotropy; aspect entropy; discrimination
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Teng, F.; Hong, W.; Lin, Y. Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis. Sensors 2019, 19, 346.

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