Real Representation of the Polarimetric Scattering Matrix for Monostatic Radar
نویسندگان
چکیده
Synthetic aperture radar with polarimetric diversity is a powerful tool in remote sensing. Each pixel described by the scattering matrix corresponding to emission/reception polarization states (usually horizontal and vertical). The algebraic real representation, block symmetric form, introduced adopt more comprehensive framework (non-restricted reciprocity assumptions) mapping consimilarity equivalence relation. proposed representation can reveal potentially new information. For example, its eigenvalue decomposition, which itself necessary step obtaining transformation products, may be useful characterizing degree of reciprocity/nonreciprocity. As consequence, it employed testing compliance assumed monostatic PolSAR data. Full-wave simulated data confirm that oriented scatterers present complex eigenvalues, even geometry.
منابع مشابه
Polarimetric bistatic radar scattering behavior of the ocean surface
this paper points out the frequency dependence on the polarimetric radar scattering behavior of the ocean surface in the frequency range 1-18 GHz (Lto Ku-band). We treat this problem with a unifying scattering model named Small Slope Approximation (SSA) to evaluate the Normalized Radar Cross Section (NRCS). The calculations were made by assuming the surface-height spectrum of Elfouhaily et al f...
متن کاملClassification of polarimetric radar images based on SVM and BGSA
Classification of land cover is one of the most important applications of radar polarimetry images. The purpose of image classification is to classify image pixels into different classes based on vector properties of the extractor. Radar imaging systems provide useful information about ground cover by using a wide range of electromagnetic waves to image the Earthchr('39')s surface. The purpose ...
متن کاملPolarimetric Synthetic Aperture Radar Data Classification Using Sparse Representation
Polarimetric synthetic aperture radar (PolSAR) data contain a large amount of potential information that is very appropriate for terrain classification. In this paper we proposed sparse representation approach to classify PolSAR data. Among a large number of PolSAR parameters we have chosen the most optimum parameters to form feature vector. Using k-means algorithm feature space is divided to C...
متن کاملA Novel Field Scattering Formulation for Polarimetric Synthetic Aperture Radar: 3d Scattering and Stokes Vectors
Conventional Far-field decomposition of the scattered electromagnetic (EM) field in the [EH] plane in terms of the horizontal and vertical components (i.e., h, v), introduces ambiguity for multistatic, multi-platform and/or scene-centric polarimetric synthetic aperture radar (SAR) image exploitation. This is due to the fact that a 2-dimensional (2D) vector field can not constitute a complete sp...
متن کاملReal-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar
In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2023
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs15041037