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In this article, a specific problem of Ground-based SAR (GB-SAR) system imaging is introduced. As for GB-SAR, the illuminated area ranges from about 1 m to 1000 m. As a result, the attenuation of the echo with the range change could not be ignored. At the same time, imaging algorithms processing airborne and space-borne echo data will overlook the attenuation, so normal algorithms have deficiency...
The isotropic scattering point scattering assumption is not hold for wide angle aperture SAR. This paper introduced an image reconstruction method for the scatters objects that have narrow beam patterns and aspect-dependent scattering properties. The directional filter bank is applied to form well-matched subimages, which are noncoherently combined in the generalized likelihood ratio test (GLRT) image...
A new method is developed to validate the parameter inversion results of the empirical models proposed by Oh et al. for bare soil surface. Oh et al. developed a series of empirical models for retrieving bare soil moisture and root mean square (rms) height, while Fung et al. proposed integral equation method (IEM) to provide the relationship between backscattering coefficient and surface parameters...
Polarimetric SAR interferometry (Pol-InSAR) combines SAR interferometry (InSAR) and SAR polarimetry (PolSAR), and it helps to the generation of digital elevation models (DEMs) as well as the parameter estimation of natural volume scatters. Baseline is an important concept in conventional InSAR applications. With the introduction of polarization into InSAR, the baseline requirements of Pol-InSAR are...
In this paper, the cross validation algorithm is used to estimate the number of clusters for the unsupervised classification of fully polarimetric SAR data. Three different cross validation algorithms are applied for comparison, which are the dispersion measure method, the V-fold cross validation (VFCV) and the Monte-Carlo cross validation (MCCV). Our current experiments show that the dispersion measure...
An estimation of the number of clusters is proposed for fully polarimetric SAR data analysis, and a corresponding unsupervised segmentation algorithm is also given based on the Cloude-Pottier decomposition and the complex Wishart clustering. The Monte-Carlo Cross-Validation (MCCV) is used to estimate the optimal number of clusters to reveal the inner structure of the data. Since it is a quantitative...
An improvement is proposed for the Cloude-Pottier decomposition using H/α/SPAN and IHSL transform. Based on this decomposition, an unsupervised classification with SPAN is also given in this paper. The main advantages of this decomposition are that it uses SPAN to maintain the space information for further polarimetric analysis and provides a straight way to present the result. Our experiments show...
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