Forests are vital components of the ecosystem of the Earth, regulating climate, conserving soil and water, and fostering biodiversity. Sustainable forest management offers crucial long-term benefits, but challenges such as disease threaten tree health. Disease-infected trees in both forests and urban areas pose risks to safety, property, and culture, leading to economic losses. Traditional inspection methods, such as resistance drilling, are invasive and laborious, while nondestructive techniques such as ground penetrating radar (GPR), offer promising alternatives. Although GPR shows potential, complexities such as tree structure and electromagnetic properties hinder accurate disease detection. In order to address these challenges, a new approach integrates structure-from-motion (SfM) photogrammetry with GPR measurement, and a novel holographic radar tomography processing approach has been proposed in this article. These methodologies accurately reconstruct tree trunks in 3-D, enabling precise GPR positioning and the obtaining of trunk permittivity. An arc-shaped Kirchhoff migration algorithm, moreover, helps mitigate irregular trunk shapes, enhancing data accuracy. The proposed framework demonstrates efficacy in real-tree measurement, offering high-precision disease monitoring. This innovation not only aids in preserving biodiversity but also enhances ecosystem services by promoting sustainable forest management. Effective disease monitoring ensures timely intervention, safeguarding valuable old trees and ecosystems while minimizing economic and cultural losses.

China’s Tianwen-1 successfully landed in the southern Utopian Planitia of the Martian surface on 15 May 2021. The Zhurong Rover, equipped with a high frequency full polarimetric Rover Penetrating Radar (RoPeR), travelled 1,921 m to investigate the shallow geological structure and material composition of the Martian weathered layer. In this study, we propose a new processing strategy to estimate surface relative permittivity using the HH and VV reflections of the high frequency RoPeR data. This new strategy is based on the induced field rotation effect, which occurs when orthogonally-polarised electromagnetic waves propagate into an uneven surface with incident angles. 3D time-domain finite-difference simulations were performed using random surfaces with various relative permittivities under the same geometry as the Zhurong Rover. Polarimetric alpha angle versus relative permittivity was then calculated based on the simulation results. At the same time, direct coupling removal, band-pass filtering and channel calibration were performed on the real RoPeR data and clear surface reflections were extracted. The surface reflection amplitudes of the HH and VV were then obtained and the polarimetric alpha angle calculated. Finally, relative permittivity was estimated through the relationship obtained from the simulation results. The average value of the relative permittivity estimated by the proposed approach is 3.292, with a standard deviation of 0.235. This result is consistent with that obtained by orbiting Radar Systems and the low frequency RoPeR system. This study will contribute to the further signal processing and accurate interpretation of real radar data captured by way of RoPeR on Mars.

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In recent years, trees in European countries have been increasingly endangered by emerging infectious diseases (EIDs). In the United Kingdom, this has been observed to affect whole woodlands and forests, threatening the existence of some types of trees. Although quarantine measures have been taken to limit the spreading of such diseases, this has not yet been effectively controlled leading to millions of trees affected by EIDs. Ground-penetrating radar (GPR) has proven effective in identifying critical features on diseased trees for detection of EIDs spread. However, the irregular shape of tree trunks and their complex internal structure represent real challenges for conventional GPR measurements and data processing methodologies. In this research, a dual-polarised GPR system is used to detect internal decay in tree trunks using novel signal processing methodologies. A polarimetric correlation filter based on Bragg Scattering on a 3D Pauli feature vector and an arc-shaped Kirchhoff migration are discussed in detail. The proposed polarimetric correlation filter is utilised to enhance the signal-to-noise ratio (SNR) of B-scans due to bark and tree trunk high-loss properties of tree trunks. Meanwhile, an arc-shaped Kirchhoff migration algorithm is performed to counteract the influence of the bark irregularity. The proposed data processing framework is successfully validated with measurements on a real tree trunk, where cross-sections were subsequently cut for comparison purposes. Outcomes from the proposed methodology demonstrate a high consistency with the features observed on the tree trunk cross-sections, indicating the reliability of the proposed detection scheme for assessing tree-decay associated with EIDs.

In this article, an atmospheric phase screen (APS) compensation algorithm for a near real-time ground-based interferometry synthetic aperture radar (GB-InSAR) over a mountainous area is investigated. A novel APS compensation scheme is proposed to compensate the fluctuated APS caused by a spatial 3-D inhomogeneous refractivity index distribution without any a priori knowledge of moving location. The proposed method simultaneously addresses to identify moving pixels by a criterion of absolute velocity estimated by the coherent pixels technique (CPT). The proposed method consists mainly of three steps: 1) the stratified APS compensation; 2) identification of moving pixel candidate; and 3) the residual APS [remained APS after 1)] compensation by Kriging interpolation. The steps mentioned above are iteratively applied in order to increase the accuracy of the whole process. In this framework, we develop the 2-D quadratic polynomial model of the refractivity index with respect to slant range and topographic height for modeling the stratified APS. Furthermore, a prediction of the residual APS is achieved by applying the intrinsic random function of order k (IRF-k) Kriging interpolation, taking into account the nonstationarity of the residual APS. We evaluate the proposed method using zero-baseline GB-differential InSAR (GB-DInSAR) data over a mountainous area located in Minami-Aso, Kumamoto, Japan, through the near real-time post-landslide measurement campaign.

In this article, we focus on the detection of the interlayer debonding of the asphalt airport pavement by the ground-penetrating radar (GPR) system. Since the interlayer debonding usually occurs in the shallow region of the asphalt airport pavement (several centimeters), it is difficult to interpret the anomalies or the defects from the GPR signals composed of many waves under the boundary conditions. Moreover, the wavelength of the ordinary GPR system is over several centimeters. Therefore, the spatial resolution of the system is not accurate enough to consider the millimeter thickness of the debonding layer. To overcome these problems, we propose a new method based on evaluating the lateral wave behavior of common midpoint (CMP) gathers collected by a multiple static GPR system. The multistatic GPR system is a stepped frequency continuous wave (SFCW) radar system, which consists of eight transmitting and eight receiving bowtie antennas. The system operates in the frequency range from 50 MHz to 1.5 GHz. After the validation of the simulation, the results of the interlayer debonding detection were evaluated by a field experiment obtained at Tokyo International Airport. The proposed method can detect the debonding layers which are less than 1 mm. Also, it is shown that our proposed method has a high consistency with the conventional acoustic finding method in the field measurement. It provides an innovative and effective method for the interlayer debonding detection of a partially damaged airport asphalt pavement, which is difficult to be observed by the ordinary GPR signals.

In this study, we investigated the potential use of polarimetric information to detect the land morphological changes without APS compensation. We proposed to use the APS independent descriptor and the covariance matrix likelihood ratio for APS. We validated the proposed technique by selecting the soil accumulated zone for a land elevation as a part of the restoration work at the landslide affected slope. The 24-hour processed time-series result reveals that both the APS independent descriptor and the likelihood-ratio are in agreement with the APS-compensated DInSAR result. The proposed idea shows the reasonable capability of detecting the land morphological change without APS compensation.

In this study, an anomalous atmospheric phase screen (APS) compensation in the frame of a ground-based differential synthetic aperture radar interferometry (GB-DInSAR) is investigated. The two improved methods are proposed and verified with GB-SAR data acquired at the mountain cliff exposed by a landslide. The first method adopts the piecewise multiple regression approach by assuming the inhomogeneity of the refractivity index distribution along the range direction. As for the second method, we apply nth order of two-dimensional (2D) polynomial with respect to slant range and topography height which enables the flexible fitting for the anomalous APS. In the second method, the cross-validation is employed to avoid both underfitting and overfitting problem. The applicability of both methods is validated with GB-DInSAR data which presents the anomalous APS. As a result, both methods yield significant reduction of the residual error compared to the conventional method.

To detect pavement damage of airport taxiway caused by cracks inside layer, we applied a novel method to common midpoint (CMP) dataset obtained by multistatic ground penetrating radar (GPR) system YAKUMO. Thin cracks within asphalt layers cause slight variation to the electromagnetic (EM) signal propagation velocity. The proposed method can show higher-resolution images of velocity changes of two different time set data with a small number of CMP traces. YAKUMO can acquire several parallel distributed CMP datasets at each position while moving the system linearly in real time, which makes it possible to apply this method to large-scale inspections. In this research, we acquired datasets at an airport taxi-way model with artificial damages at several times over a year. The datasets are analyzed with the proposed method to find out how the conditions of pavement changes by pressurization and time course. The results show that the method can detect not only overall change but also local area changes.

In this paper, an efficient and accurate imaging algorithm is presented for Ground-Based Synthetic Aperture Radar (GB-SAR) or other radar systems that could be formed by a physical or synthetic linear aperture. The imaging algorithm is based on the fractional Fourier transform (FrFT) for the azimuth compression. A mathematical framework is derived according to the projection of a sample reflectivity image onto the pseudopolar coordinate, and its implementation was presented. With the data acquisition geometry and the pseudopolar imaging coordinate, the phase of a point target can be expressed as a quadratic phase exponential. It makes that only 1-D FrFT is needed for the azimuth compression of the time-domain backscatter data for the GB-SAR imaging problem. By further research, the optimal transformation order that represents the spatial frequency changes by the FrFT was given subsequently. Taking advantage of this optimal representation, the proposed approach avoids the large calculation that occurs in the time-domain back projection (TDBP). Comparing to the far-field pseudopolar format algorithm (FPFA), the accuracy of the proposed algorithm is much improved. Meanwhile, the proposed approach holds almost the same computational cost and complexity as the FPFA. The proposed approach keeps the advantages of the imaging quality of the TDBP and the computational cost of the FPFA that are two important aspects of the GB-SAR applications. Both the numerical simulation and the field GB-SAR experiment show that the algorithm is more suitable for the high-precision GB-SAR imaging, especially for the near field.

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.

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.

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 Fermat's 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.