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Accuracy of radar interferometry is often hindered by the atmospheric phase screen (APS). To address this limitation, the geostatistical approach known as Kriging has been employed to predict APS from sparse observations for compensation purposes. In this article, we propose an enhanced Kriging approach to achieve more accurate APS predictions in ground-based (GB) radar interferometry applications. Specifically, the Kriging system is augmented with a time-series measure through correlation analysis, effectively leveraging spatiotemporal information for APS prediction. The validity of the introduced Kriging method in the APS compensation framework was tested with Ku-band GB radar datasets collected over two different mountainous sites. A comparison of this method with simple Kriging reveals a noticeable improvement in APS prediction accuracy and temporal phase stability.

This article presents an optimization-based approach to overcome redundancy arising from the multivariables enumeration process in multiple signal classification (MUSIC). By incorporating Broyden–Fletcher–Goldfarb–Shanno (BFGS) optimization, the computational speed of the MUSIC algorithm is significantly improved while maintaining mathematical accuracy. The optimization techniques require reasonable initial values to start the iteration, while for single target imaging purposes, the initial values can be acquired by the boundary between the near field and the far field. To generate suitable initial values for the optimization, we employ a modified convolutional neural network (CNN) to approximate the boundaries between the near and far fields, which vary with array system properties. Besides, the proposed method introduces a method for the Hessian matrix and gradient initialization for the BFGS method. Using simulation results as training samples, the modified CNN successfully establishes boundary approximations. Simulation and experimentation confirm the feasibility of our proposed method, showing its advantages in both accuracy and computation speed compared to existing techniques.

In practice, the reflected EM signal cannot be clearly observed in GPR data due to the high water content and other reasons. However, the antenna coupling signal through the ground interface is dominated in all the GPR measurements. This direct coupling signal that travels through the ground interface is called a lateral wave. The properties of the lateral wave directly depend on the subsurface properties, especially electrical parameters. We have numerically analyzed a lateral wave and its velocity. Subsequently, the relationship between lateral wave and dielectric permittivity was determined by polynomial regression. Analytically, it is challenging to analyze a lateral wave due to the parameters that can influence wave propagation. Antenna characteristics, surface roughness, etc need to be considered. Numerically, we designed a GPR system with a subsurface layer and observed a lateral wave. This numerical analysis can give a chance to use a lateral wave for near-surface soil water content. This analysis gives a more precise estimation of surface water content. Moreover, we analyze the antenna height effect that influences radar signals. We numerically observed that the GPR signal is highly affected by antenna height. The antenna height effect depended on the wavelength of the applied electromagnetic wave. By adjusting the antenna height, the unobservable GPR signal can be clearly detected.

Ground-based radar interferometry is capable of measuring target displacement to sub-mm accuracy. W-band ground-based radar has recently been investigated as a potential application for structural health monitoring. On the other hand, the application of W-band ground-based radar for natural slope monitoring is considered in this study due to its advantages in portability and recent cost-effective solutions. In radar interferometry, atmospheric phase screen (APS) is the most relevant phase disturbance that should be corrected for accurate displacement measurement. However, the APS effects in W-band radar interferometry have rarely been discussed. In this context, we study and evaluate the impacts of APS and its potential correction methods for 79 GHz ground-based radar interferometry using multiple-input and multiple-output (MIMO) radar. This paper presents an experimental investigation of a 79 GHz radar system using two types of field experiments conducted in an open flat field and a quarry site. In addition to the W-band radar system, a Ku-band (17 GHz) ground-based synthetic aperture radar (GB-SAR) system was jointly tested to compare different operating frequency bands. The result confirmed the accurate displacement estimation capability of the 79 GHz radar with an appropriate APS correction.

In this article, we devise a polarimetric calibration method utilizing only three types of calibration targets, i.e., trihedral, dihedral, and a 22.5°-rotated dihedral corner reflectors and requiring no assumptions on the scene statistics. The influence of the roll angle in a 22.5°-rotated dihedral corner reflector is assessed by a full-wave numerical simulation. The effectiveness and accuracy of the method are verified with a ground-based synthetic aperture radar system and an airborne L-band Pi-SAR data. We demonstrate that an amplitude error as low as 0.5 dB and a phase error within 3° can be achieved, showing an excellent agreement between the theoretical and calibrated polarimetric signatures for the reference targets. We further exploit the calibration on the Pauli decomposition, Yamaguchi four-component decomposition, and the estimation of the polarimetric parameters derived from target scattering vector method decomposition to show the superior performance of the devised calibration method.

We investigate the applicability of the entropy (H)/ alpha $(\bar{\alpha })$ target decomposition realized by the temporally averaged coherency matrix, called temporal $H/(\bar{\alpha })$. We apply the temporal $H/\bar{\alpha }$ to ground-based synthetic aperture radar (GB-SAR) continuous monitoring data to characterize the scattering mechanism temporal change. As a case study, this work demonstrates the application of the temporal $H/\bar{\alpha }$ technique to landslide monitoring to detect and investigate the temporal scattering mechanism. The study acquired long-term GB-SAR polarimetric data over the postlandslide slope, Minami-Aso, Kumamoto, Japan. The study first investigated the property of the temporal $H/\bar{\alpha }$ parameters over selected land cover types by comparing it with that derived by spatial averaging (spatial $H/\bar{\alpha }$) to explain the landslide monitoring results. Also, the rainfall effects on the temporal H/$\bar{\alpha }$ parameters are demonstrated. The temporal H and $\bar{\alpha }$ values increase up to 0.07$^\circ $ and 13.54$^\circ $, respectively, when the rainfall rate is 52.5 mm/h. The time-series analysis of the temporal $H/\bar{\alpha }$ indicates an obvious temporal transition of the scattering mechanism and a change of the backscattering stationarity when a landslide occurs. The applicability of the temporal $H/\bar{\alpha }$ for the change-detection is discussed by comparing it with the classical spatial $H/\bar{\alpha }$ parameters.

The accuracy of surface displacements measured by differential radar interferometry is significantly degraded by the atmospheric phase screen (APS). This article presents a practical and efficient approach for APS mitigation based on the coherent pixels technique (CPT) displacement velocity estimation algorithm. In the proposed approach, all motionless coherent pixels closest to the moving area are defined as seeds surrounding the moving area at the integration step of the CPT. This arrangement consequently minimizes the integration path and the APS effect in the final velocity result. It is designed for terrestrial radar interferometry (TRI) applications. A piecewise processing chain is further introduced as a continuous operational mode processing framework to derive arbitrary temporal displacement patterns in this work. Three-day datasets measured by Ku-band TRI over a mountainous region in the canton of Valais, Switzerland, were used for validation. Through this validation, a comparative study of five algorithms was carried out. This evaluation showed the efficiency of the proposed approach. The proposed approach does not require phase unwrapping, kriging interpolation, and spatio-temporal covariance inference for APS mitigation, which is appropriate for continuous TRI operation.

A new multi-input multi-output (MIMO) antenna configuration with wideband and low sidelobe level (SLL) is introduced for ground-based synthetic aperture radar (GB-SAR). The proposed MIMO antenna has 15 transmitting and 16 receiving antenna arrays, arranged in two parallel straight lines, to synthesize a virtual array of 256 elements suitable for monitoring relatively large areas. The inter-element spaces are optimized to λ between transmitting elements and 4λ between receiving elements, to realize both low mutual coupling and an inferior SLL of lower than -37 dB for the overall MIMO antenna. The MIMO antenna element has eight rectangular patch linear arrays working at 17.1 GHz. A traveling wave-feeding network with center excitation is used to feed each element, in order to reduce the SLL and achieve a wide bandwidth of more than 300 MHz. The antenna array shows a gain of 14.3 dBi and half-power beamwidths (HPBWs) of 10° and 105° in the elevation and azimuth planes, respectively. The performance of the proposed design satisfies the GB-SAR requirements, which are validated by fabrication and measurement.

Herein, a semiempirical model is proposed to remove the atmospheric phase screen (APS) that occurs during ground-based synthetic aperture radar (GB-SAR) monitoring in steep mountainous areas with extreme weather conditions. The proposed method is based on a model-based statistical technique, which combines the topographical information and the estimated phase of interferograms. A 3-D geographical model was designed to investigate the effect of topographical irregularities, such as elevation, slope, and their correlation with the APS. The observed phases were then modeled according to the altitude and range of the 3-D topographical structure seen by the radar. A two-stage semiempirical algorithm is proposed to compensate for the APS in the spatial domain. Herein, the temporal changes in meteorological parameters, such as the atmospheric temperature, pressure, or humidity, were not considered for phase correction, drastically reducing the model background information and providing faster data processing for real-time GB-SAR monitoring. The proposed model was applied to the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan, where large-scale landslides were triggered after the Kumamoto earthquake in April 2016.

Hand-held ground penetrating radar (GPR) systems have been widely applied to landmine detections during recent decades. The accuracy of an imaging result by migration for a hand-held GPR is strongly related to the accuracy of subsurface velocity distribution obtained from multi offset data. For shallow targets like landmines, the hyperbolas are usually not distinct in 2D slices and are masked by the surface reflections. In this article, we propose a 3D migration depth focus velocity analysis method for hand-held GPRs to estimate the background velocity of the subsurface. This method is performed based on the images generated by migrations. The objective function is defined as the proportion of the target on the depth slice containing the target. After migrating a GPR radargram with different velocities, the background velocity, which minimizes the objective function, can be determined by comparing the imaging results by migration using different velocities. To test the proposed method, we apply this procedure to experimental GPR data collected with an advanced landmine imaging system (ALIS) in the laboratory. Subsequently, the velocity of the background is obtained, 3D diffraction migration with the obtained velocity achieves subsurface imaging with high quality. The accurate position and depth of the target are obtained from the optimal migration image.

As a fundamental research step for subsurface target imaging by passive ground penetrating radar, some simulation and experimental results of passive bistatic radar imaging for short-range targets by using IEEE 802.11 Wireless Fidelity (WiFi) wave as the source of illumination have been presented. As the WiFi signal only penetrates shallow layers and yet lacks bandwidth for high resolution subsurface structure mapping, the interrogation of cooperative targets with the passive bistatic radar approach is demonstrated. This strategy is achieved by inserting surface acoustic wave (SAW) delay lines acting as dedicated reflectors allowing for subsurface tagging (identification) or sensing (temperature measurement) through the fine measurement of echo delays. Experimental results show that short-range targets, such as cars and metallic plates located within 10 m, can effectively be detected and imaged. The response of the SAW delay lines can also be well probed.

In this paper, we have presented a methodology combining ground penetrating radar (GPR) and a low-cost GPS receiver for three-dimensional detection of tree roots. This research aims to provide an effective and affordable testing tool to assess the root system of a number of trees. For this purpose, a low-cost GPS receiver was used, which recorded the approximate position of each GPR track, collected with a 500 MHz RAMAC shielded antenna. A dedicated post-processing methodology based on the precise position of the satellite data, satellite clock offsets data, and a local reference Global Navigation Satellite System (GNSS) Earth Observation Network System (GEONET) Station close to the survey site was developed. Firstly, the positioning information of local GEONET stations was used to filter out the errors caused by satellite position error, satellite clock offset, and ionosphere. In addition, the advanced Kalman filter was designed to minimise receiver offset and the multipath error, in order to obtain a high precision position of each GPR track. Kirchhoff migration considering near-field effect was used to identify the three-dimensional distribution of the root. In a later stage, a novel processing scheme was used to detect and clearly map the coarse roots of the investigated tree. A successful case study is proposed, which supports the following premise: the current scheme is an affordable and accurate mapping method of the root system architecture.