Wenjing Liang

Calibration With High-Order Terms of Polarimetric GPR

To provide meaningful data, polarimetric ground penetrating radar (GPR) requires accurate calibration of channel imbalance and crosstalk not only in the amplitude term but also in the phase term. Currently, calibration techniques usually ignore higher-order terms to simplify equations. These techniques, though very easy to perform, provide less accurate calibration results for the crosstalk. To improve the accuracy of calibration, we have derived a new mathematical formulation to calibrate a polarimetric GPR system. We measured several scattering matrices to obtain the necessary calibration parameters. The calibration technique was tested from measurements conducted on a 22.5° oriented dihedral corner reflector from 1 to 6 GHz with a step of 0.1 GHz. The calibrated results are found to be consistent with the theoretically values, especially for the crosstalk.

Application of Freeman decomposition to full polarimetric GPR for improving subsurface target classification

Migration technique can reconstruct the subsurface target imaging from record ground penetrating radar (GPR) data. Depending on the reconstructed imaging, we possibly distinguish subsurface target by the geometrical feature. But some different targets have similar reconstructed imaging, which will confuse us. Freeman decomposition is a technique for fitting a three-component scattering mechanism model to polarimetric synthetic aperture radar observations, which is successfully used in the classification of terrain objects. This paper applies the model-based Freeman decomposition to full polarimetric GPR data to improve the subsurface target classification. We use a full polarimetric GPR, which is constructed in laboratory with three types of antenna combinations, HH, VV and VH combinations, to acquire experiment data sets for testing the method. Metallic plate, ball, dihedral and volume scatter with many branches, are buried in the homogenous dry sand under flat ground surface, and three dimensional data sets are acquired above each buried target. After signal processing, we obtained subsurface target imaging by migration and color-coded polarimetric information by Freeman decomposition. Results showed that it can improve the classification capability of GPR for the subsurface target to use both the geometrical feature and polarimetric information. Model-based Freeman decomposition is applied to full polarimetric GPR data.Both geometrical feature and polarimetric information are used to improving the classification of subsurface target.Methodology of imaging and polarimetric decomposition of full polarimetric GPR data is introduced.

Application of freeman decomposition to full polarimetric GPR

Full-polarimetric Ground-penetrating radar (GPR) is considered as a promising sensor for detecting buried targets. However, the polarimetric decomposition technique plays a crucial role in identifying and classifying targets which are buried in the sand under the surface. The decomposition techniques of full-polarimetric Ground-penetrating radar includes four decomposition methods, namely: (1) Pauli decomposition method, (2) H-α decomposition method, (3) Freeman decomposition method and (4) polarimetric anisotropy analysis method .This paper mainly applys Freeman decomposition method to recognition of metal surface plate, dihedral and metal ball. The potential of polarimetric target decomposition techniques to metal surface plate, dihedral and metal ball characterization and classification is shown which provides valuable information.

Developing a novel full-polarimetric GPR technology

Generally GPR transmits and receives radio waves with a single polarization using two parallel antennas. But it is possible to improve the GPR ability of discrimination and imaging of subsurface targets by analyzing the backscattered wave with a variety of polarizations. So we are developing a full-polarimetric GPR system, including PC, network analyzer, rectangular coordinates robot, switch driver, and polarimetric antenna array. Polarimetric antenna array is used to transmit and receive both co-polarimetric and cross-polarimetric signals. Currently polarimetric GPR do not execute precise calibration. But good calibration can improve the classification ability of subsurface targets. So we introduced the calibration technique into the polarimetric GPR, and derived a calibration formula.

Full-polarimetric GPR system for underground targets measurement

A conventional GPR system includes PC, network analyzer, rectangular coordinates robot and a single antenna for transmission and reception, resulting in a response only to Co-Polarization signal. However, we expect that more polarimetric information can be obtained. So we developed a full-polarimetric GPR system including PC, network analyzer, position controller, switch driver and polarimetric antenna array. This antenna array can obtain CMP multi-offset data gather directly. At every measurement position, the total of three signals was collected not only in Co-Polarimetric mode but also in Cross-Polarimetric mode. Two groups of experiments have been presented. The first group is concerned with a metal dihedral which is made of two orthogonal conducting plates and a metal trihedral as the targets. The result of this experiment shows that the surface morphology of the target characteristics, the relative position and attitude have a certain influence on the measurement results. The second group is using a metal trihedral as the target. The results of experiment are shown in this presentation are consistent with the theoretical values and helps us to identify target attributes such as direction.

Radar polarimetry analysis applied to fully polarimetric Ground Penetrating Radar

Polarimetric decomposition techniques have been applied in remote sensing in the area of air-space-borne radar and have achieved much progress in recent years. However, very few apply these polarimetric decomposition techniques to the Ground Penetrating Radar (GPR).We currently apply GPR data sets to characterize and classify the subsurface targets using Pauli decomposition method. The Pauli decomposition method provided important radar polarimetry information of subsurface targets, and the Pauli decomposition method made a significant contribution to understanding the scattering mechanisms from different subsurface targets with different properties. Analyzing polarimetric attributes of subsurface targets provides facilitates for classifying subsurface targets. Because some methods only can identify the approximate outline of subsurface targets, but can not classify the targets such as imaging technique that can only identify the outline of subsurface targets, but can not classify targets. So we apply Pauli decomposition for classifying subsurface targets and this analysis result is relatively good. The decomposition technique plays a key role for classifying subsurface targets such as metal surface plate, dihedral, metal ball and other subsurface targets. This paper mainly applies Pauli decomposition method to recognize subsurface metal surface plate, subsurface dihedral, subsurface metal ball, subsurface metal bucket, and subsurface chaotic scattering target. This decomposition technique provides valuable information for the study of properties of the subsurface targets.

Developing calibration technology for full-polarimetric GPR

Polarimetric GPR requires accurate calibration of channel imbalance and crosstalk not only in the amplitude term but also in the phase term. Currently, there have some calibration techniques. Though these techniques are very easy to perform, they provide less accurate calibration results for the crosstalk. To improve on the accuracy of calibration, we have developed a mathematical formulation to calibrate polarimetric GPR data. We measured several scattering matrices to obtain the necessary calibration parameters. The calibration technique was tested from measurements conducted on dihedral corner reflector.

3D velocity model and ray tracing of antenna array GPR

Migration is an important signal processing method that can improve signal-clutter ratio and reconstruct subsurface image. Diffraction stacking migration and Kirchhoff migration sum amplitudes along the migration trajectory, which generally is hyperbolic. But when the ground surface varies acutely, the migration trajectory is not hyperbolic. To computer the migration trajectory need the technique of ray tracing. We introduce a method of ray tracing based on 3D velocity model. Firstly, we build the 3D velocity model depending on the estimation of both ground surface topography and velocities. Then we compute the travel time between transmitter, receiver and each subsurface scattering point, and search the propagation ray depending on the Fermats principle. The method is tested by an experiment data acquired by the stepped-frequency (SF) CMP antenna GPR system. The target is a metal ball that is buried under a sand mound. A nice result of ray tracing is shown in the case.

Design and performance of Full-polarimetric airborne GPR testing system

Airborne ground penetrating radar (GPR) is a suitable tool to perform cost-effective surveys of the underground of a large possibly non-accessible areas. And It is concluded that airborne GPR will receive more attention in the future. So we have developed a L-band Full-polarimetric Step-Frequency GPR acquisition system, which consists of a GPS receiver, the Vivaldi antenna, a signal amplifier and a vector network analyzer (VNA) under the control of a PC unit. The main objective of our work is to conduct some experiments to test the feasibility of this airborne testing system.

Subsurface imaging by modified migration for irregular GPR data

Handheld ground-penetrating radar (GPR) system is one of a number of technologies that has been researched as a means of improving landmine detection efficiency. However, as the measurement points are random and data are irregular for the human operator, it is difficult to display subsurface visualization imaging. Also detection of buried landmines by GPR normally suffers from very strong clutter that will decrease the image quality. To solve the problem, a modified migration algorithm was proposed to process irregular GPR data, which has both the advantage of migration that can improve signal-clutter ratio and the advantage of interpolation that produces the grid data set for visualization. An application to field data acquired in Afghanistan shows clear landmine image in both vertical profile and horizontal slice.