Information Extraction from Satellite-Based Polarimetric SAR Data Using Simulated Annealing and SIRT Methods and GPU Processing

The main goal of this research was to propose a new method of polarimetric SAR data decomposition that will extract additional polarimetric information from the Synthetic Aperture Radar (SAR) images compared to other existing decomposition methods. Most of the current decomposition methods are based on scattering, covariance or coherence matrices describing the radar wave-scattering phenomenon represented in a single pixel of an SAR image. A lot of different decomposition methods have been proposed up to now, but the problem is still open since it has no unique solution. In this research, a new polarimetric decomposition method is proposed that is based on polarimetric signature matrices. Such matrices may be used to reveal hidden information about the image target. Since polarimetric signatures (size 18 × 9) are much larger than scattering (size 2 × 2), covariance (size 3 × 3 or 4 × 4) or coherence (size 3 × 3 or 4 × 4) matrices, it was essential to use appropriate computational tools to calculate the results of the proposed decomposition method within an acceptable time frame. In order to estimate the effectiveness of the presented method, the obtained results were compared with the outcomes of another method of decomposition (Arii decomposition). The conducted research showed that the proposed solution, compared with Arii decomposition, does not overestimate the volume-scattering component in built-up areas and clearly separates objects within the mixed-up areas, where both building, vegetation and surfaces occur.

Reconstruction of Two-dimensional Image to Three-dimensional Point Cloud Data for Detection of Empty Rot Defects in Tree Growth

In the application of nondestructive detecting of trees, it is a technical problem to use radar waves to detect tree specimens with growth defects, how to segment defect areas after obtaining two-dimensional images, and reverse simulate the detection results with three-dimensional point cloud data. Therefore, the method of extracting boundary information according to color features is studied to extract the boundary curve of empty rot area, and the selection of higher precision extraction algorithm is determined by comparing the boundary extraction results of HSV color space and RGB color space in laboratory According to the extracted void boundary curve, the reverse modeling is carried out, and the mapping from 2D inspection gray image to 3D space is realized, The point cloud data reconstruction needed for 3D modeling of multi-curved surfaces is obtained in reverse. The boundary curve extraction algorithm in this study is used to process the images of nondestructive testing of trees. Through comparative experiments and error analysis, the accurate modeling conclusion from inversion of 2D images to 3D point cloud data reconstruction by radar wave detection is verified, and the Core issue problem of point cloud reconstruction in the ill-conditioned area of tree growth and decay detected by radar wave is solved.

Blunt hub affecting the radar cross section of rotor based on dynamic scattering method

In order to study the radar characteristics of blunt-hub rotor, a dynamic scattering method (DSM) based on physical optics and physical theory of diffraction is presented. Important influencing factors are analyzed and discussed, including rotor disk inclination, azimuth, elevation angle, and radar wave frequency. The radar cross section (RCS) of the blunt-hub rotor is used for comparison with conventional-hub rotor and sharp-hub rotor. The RCS performance of the blunt-hub rotor at different radar wave frequencies is close to that of the sharp-hub rotor. At larger positive elevation angles, the RCS∼azimuth performance of the blunt-hub rotor is not as good as the other two rotors, while the RCS performance of the blunt-hub rotor has an advantage under the larger negative elevation angle and the inclination of the rotor disk. The presented DSM is feasible and effective for learning the electromagnetic scattering characteristics of the blunt-hub rotor.

The role of electrical conductivity in radar wave reflection from glacier beds

We have examined a general expression giving the specular reflection coefficient for a radar wave approaching a reflecting interface with normal incidence. The reflecting interface separates two homogeneous isotropic media, the properties of which are fully described by three scalar quantities: dielectric permittivity, magnetic permeability, and electrical conductivity. The derived relationship indicates that electrical conductivity should not be neglected a priori in glaciological investigations of subglacial materials and in ground-penetrating radar (GPR) studies of saturated sediments and bedrock, even at the high end of typical linear radar frequencies used in such investigations (e.g., 100–400 MHz). Our own experience in resistivity surveying in Antarctica, combined with a literature review, suggests that a wide range of geologic materials can have electrical conductivity that is high enough to significantly impact the value of radar reflectivity. Furthermore, we have given two examples of prior studies in which inclusion of electrical conductivity in calculation of the radar bed reflectivity may provide an explanation for results that may be considered surprising if the impact of electrical conductivity on radar reflection is neglected. The commonly made assumption that only dielectric permittivity of the two media needs to be considered in interpretation of radar reflectivity can lead to erroneous conclusions.

Simulation and Experiments on Signals of Ground-Penetrating Radar in Soil Cement

Subgrade bedding is a key element of railway structure in stability and durability, and it is almost made of soil cement. The dielectric constant, compaction and curing ages of soil cement with different moisture contents were measured. The relation among curing ages, moisture content, compaction of soil cement and electromagnetic features was analyzed. The model of layered soil cement was established to simulate ground-penetrating radar (GPR) electromagnetic waves in the soil cement. The variation rules of dielectric constant and amplitude of radar signals were obtained. The electromagnetic features, i.e. velocity, frequency and amplitude, were analyzed. Ground-penetrating radar was used to detect the railway subgrade soil layer. Based on the center line of the subgrade, there were nine detection lines for every 1[Formula: see text]m to detect the density and smoothness of the subgrade soil layer. Based on the radar wave events and reflected waves, the subgrade condition can be judged.