分类: 地球科学 >> 空间物理学 提交时间: 2017-03-10
摘要: Cloude-Pottier incoherent target decomposition (ICTD) and Touzi ICTD has been widely applied as a popular approach to interpret the scattering characteristics of a target in polarimetric synthetic aperture radar (PolSAR) data processing. However, they have a common drawback, i.e. proliferation of parameters (PoP) is unavoidable. Paladini et al. solved this problem by developing an orientation-invariant ICTD based on the coherency matrix under circular polarization basis. As an alternative to Paladini decomposition, we proposed a novel ICTD based on the frequently used coherency matrix under linear polarization basis. The proposed method can also avoid the problem of PoP, and avoid the ambiguity of alpha angle of Paladini decomposition as well. Real PolSAR data is processed to validate the proposed decomposition.
分类: 地球科学 >> 空间物理学 提交时间: 2017-01-04
摘要: Scattering similarity was first proposed by Yang et al. to measure the similarity between two single scatterers. It was extended by Chen et al. to measure the similarity between a mixed scatterer and a single scatterer. This letter develops a random similarity parameter to further measure the similarity between two mixed scatterers. The parameter not only covers Yang's and Chen's similarities by providing a general scattering similarity measurement, but also is useful for scattering randomness description by enabling a fast alternative and a competent complementary to the entropy parameter. A novel model-based characterization scheme of mixed scatterer is then proposed by parallel combining the random similarities between the mixed scatterer and three canonical mixed volume scatterers. By further fusing with the SPAN, the scheme can characterize both the texture and the scattering information regarding a target. Comparative experiment with Chen's approach on L-band ESAR Oberpfaffenhofen data demonstrates its excellent discrimination of radar targets. �2004-2012 IEEE.
分类: 地球科学 >> 空间物理学 提交时间: 2017-03-10
摘要: The model-based decomposition that originated from Freeman-Durden three-component decomposition (FDD) has been widely applied in polarimetric synthetic aperture radar (PolSAR) data processing for its clear physical interpretation and easy implementation. Numerous improvements have been proposed to settle the twomain drawbacks of FDD, i.e., the incomplete utilization of the polarimetric information in the coherency matrix and the negative scattering power problem. Recently, Cui et al. proposed a complete model-based three-component decomposition which successfully settled the two aforementioned drawbacks. However, the three scattering components' powers are not totally derived using scattering models, and the remaining coherency matrix (RCM) obtained by subtracting the volume scattering component from the coherency matrix is not consistent with the models of surface and double-bounce scattering components. As an extension of Cui's method, this letter is dedicated to develop a novel method to discriminate the surface and double-bounce scattering components both using scattering models. With the orientation angle (OA) variation and helix angle (HA) variation compensated for the RCM, the RCM is automatically consistent with the models of surface and double-scattering components. The OA variation and HA variation compensation for the RCMis done by unitary transformations of the eigenvectors of the RCM. The powers of surface and double-bounce scattering components are positive. The effectiveness of the proposedmethod is demonstrated by processing the real PolSAR data.