Ground-based Interferometric Radar Research Articles

Evaluation of Slope Stability on Dam Using Ground-based Interferometric Radar

Dams are man-made structures built to manage water resources efficiently and prepare for natural disasters such as droughts and floods. It requires careful and continuous inspection to prevent its failure. Research reported to assess dam stability using terrestrial surveys such as ground penetration radar, electrical resistivity tomography, and remote sensing methods such as space-borne synthetic aperture radar (SAR). Differential interferometric SAR (DInSAR) calculates the phase difference between two consecutive images acquired at separate times and has been widely utilized to detect surface displacement from volcanoes, earthquakes, and ground subsidence. However, space-borne InSAR applications have limitations in acquiring flexible data for specific dates or regions due to the revisit cycle of the orbital configuration and the fixed acquisition geometry. In this feasibility study, the slope stability of the dam was evaluated using the Gamma Portable Radar Interferometer-II (GPRI-II) which has the advantage of overcoming the limitation of satellite observations. The GPRI-II is a ground-based real aperture radar that operates in the Ku-band wavelength (~1.7 cm), providing convenient portability and installation for high spatial and temporal resolution. A total of 20 GPRI-II datasets were acquired for 22 minutes on June 7, 2023, at a dam in Jeollanam-do for the DInSAR application. The displacement calculation revealed an average displacement of approximately -0.36 mm at a randomly selected point, which is negligible. The average displacement of -0.17 mm was observed for the entire dam. Our results suggest that ground-based radar interferometry could assess the dam slope stability.

Vibration Measurement of High-Speed Railway Bridges Based on GB-MIMO Interferometric Radar

As a novel type of ground-based interferometric radar, ground-based multiple-input multiple-output (GB-MIMO) interferometric radar utilizes multiple transmitting and receiving antennas to compose a specific structure and acquire a large synthetic aperture. Using electronic beam scanning instead of common mechanical scanning, GB-MIMO interferometric radar can achieve two-dimensional high-resolution imaging with image acquisition frequency at tens of Hertz, and has the ability to perform bridge health monitoring through vibration measurement. This study introduces the basic principle of the MIMO technique and the first Chinese made GB-MIMO interferometric radar. Experiments taken on a corner reflector and a high-speed railway bridge are respectively utilized to verify the vibration measurement ability of this novel type of GB-MIMO interferometric radar

Sinkhole risk mapping and early warning: the case of Camaiore (Italy)

Introduction: Sinkholes are ground collapses that can cause significant damage to infrastructure and buildings. Part of the risk represented by sinkholes is related to their abruptness and the difficulty in spotting in advance their exact location within a sinkhole-prone area. For this reason, urban planning informed by an accurate risk mapping and monitoring is one of the most effective ways to reduce the risk.Methods: In this study, we propose a two-folded procedure based on the examination of ground displacement data measured by a ground-based interferometric radar and on the generation of a sinkhole risk zonation map. We examined 11 years’ worth of ground displacement data measured by a ground-based interferometric radar to search for sinkhole precursors. The analysis was based on averaged displacement time series retrieved from high-coherence pixels scattered around Camaiore, Italy, a test site where a catastrophic sinkhole occurred in 1995. To generate a sinkhole risk map, we evaluated the susceptibility map as derived from a set of predisposing environmental parameters, the vulnerability derived from the thickness of the sedimentary cover that can be linked to the abruptness of the collapse, and the value of the elements at risk from the Italian Real Estate Market Observatory integrated with land cover information for the non-built up areas.Results: The analysis of ground displacement data revealed that Camaiore had not experienced subsidence relatable to incoming sinkholes in the monitored period. However, few cm of vertical movements, which are well correlated with water table oscillations, have been measured and are expected to be of the same order of magnitude of sinkhole precursor deformations. This implies that a phenomenon of the size and velocity of the 1995 event could have likely been detected before its final collapse. The sinkhole risk map identified specific areas that should be closely monitored using in situ and remote sensing instrumentation.Discussion: The sinkhole risk zonation map generated in this study can be used to inform urban planning and risk management strategies. The study also shows the potential of ground-based interferometric radar to detect sinkhole precursors and the importance of integrating different mitigation approaches. Overall, this study can provide insights for sinkhole risk assessment and management in sinkhole-prone areas.

Determining and Investigating the Variability of Bridges’ Natural Frequencies with Ground-Based Radar

Assessing the condition of bridge infrastructure requires estimating damage-sensitive features from reliable sensor data. This study proposes to estimate natural frequencies from displacement measurements of a ground-based interferometric radar (GBR). These frequencies are determined from the damped vibration after each vehicle crossing with least squares and compared to a Frequency Domain Decomposition result. We successfully applied the approach in an exemplary measurement campaign at a bridge near Coburg (Germany) with an additional comparison to commonly used strain sensors. Since temperature greatly influences natural frequencies, linear regression is used to correct this influence. A simulation shows that GBR, combined with the least squares approach, achieves the lowest uncertainty and variation in the linear regression, indicating better damage detection results. However, the success of the damage detection highly depends on correctly determining the temperature influence, which might vary throughout the structure. Future work should further investigate the biases and variability of this influence.

CONVOLUTIONAL NEURAL NETWORKS FOR DETECTING BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA

Abstract. This study focuses on detecting vehicle crossings (events) with ground-based interferometric radar (GBR) time series data recorded at bridges in the course of critical infrastructure monitoring. To address the challenging event detection and time series classification task, we rely on a deep learning (DL) architecture. The GBR-displacement data originates from real-world measurements at two German bridges under normal traffic conditions. As preprocessing, we only apply a low-pass filter. We develop and evaluate a one-dimensional convolutional neural network (CNN) to achieve a solely data-driven event detection. As a baseline machine learning approach, we use a Random Forest (RF) with a selected feature-based input. Both models’ performance is evaluated on two datasets by focusing on identifying events and pure bridge oscillations. Generally, the event classification results are promising, and the CNN outperforms the RF with an overall accuracy of 94.7% on the test subset. By relying on an entirely unknown second dataset, we focus on the models’ performances regarding the distinction between events and decays. On this dataset, the CNN meets this challenge successfully, while the feature-based RF classifies the majority of non-event decays as events. To sum up, the presented results reveal the potential of a data-driven DL approach concerning the detection of bridge crossing events in GBR-based displacement time series data. Based on such an event detection, a prospective assessment of bridge conditions seems feasible as an extension to previous structural health monitoring approaches.

SDR-Implemented Ground-Based Interferometric Radar for Displacement Measurement

In this article, we demonstrate the use of general software-defined radio (SDR) hardware for ground-based interferometric radar (GBIR) system development for static target imaging and displacement estimation purposes. First, a system synchronization approach is proposed within the free and open-source framework GNU Radio, followed by a frequency-domain bandwidth synthesis method used to improve the range resolution with three different waveforms. Second, data preprocessing and target imaging methods are proposed to reduce the negative influences of practical nonideal factors and get high-quality target images. Finally, various experiments are conducted to show the performance of the developed SDR-GBIR system and the proposed methods. It is shown that high-resolution target image and high-accuracy displacement measurement can be obtained by our SDR-GBIR systems.

DETECTION AND CLASSIFICATION OF BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA AND MACHINE LEARNING APPROACHES

Abstract. In this paper, we investigate the potential of detecting and classifying vehicle crossings (events) on bridges with ground-based interferometric radar (GBR) data and machine learning (ML) approaches. The GBR data and image data recorded by a unmanned aerial vehicle, used as ground truth, have been measured during field campaigns at three bridges in Germany non-invasively. Since traffic load of the bridges has taken place during the measurement, we have been able to monitor the bridge dynamics in terms of a vertical displacement. We introduce a methodological approach with three steps including preprocessing of the GBR data, feature extraction and well-chosen ML models. The impact of the preprocessing approaches as well as of the selected features on the classification results is evaluated. In case of the distinction between event and no event, adaptive boosting with low-pass filtering achieves the best classification results. Regarding the distinction between different class types of vehicles, random forest performs best utilising low-pass filtered GBR data. Our results reveal the potential of the GBR data combined with the respective methodological approach to detect and to classify events under real-world conditions. In conclusion, the preliminary results of this paper provide a basis for further improvements such as advanced preprocessing of the GBR data to extracted additional features which then can be used as input for the ML models.

Quantifying Measurement Capabilities of Ground-Based Interferometric Radar for Rockfall Hazard Applications

Abstract New ground-based remote sensing techniques developed over the past decade present solutions to many challenges associated with traditional in situ monitoring of mass movement hazards. In particular, ground-based interferometric radar (GBIR) and terrestrial laser scanners (TLSs) are ideal candidates for application to rockfall hazard monitoring, owing to high precision in displacement sensitivity and spatial resolution, respectively. Through controlled experiments with a synthetic rock specimen and measurements of induced rock movements in the field, this study aims to quantify lower bounds of repeatable displacement detection for single rock targets using GBIR and to compare the results to total station and TLS measurements. One investigation used a synthetic rock that was moved with precisely controlled displacements to determine the lower bound threshold and accuracy of the GBIR for detecting translational movements of a realistic rock-like scatterer. This study found that the GBIR system was capable of reliably measuring displacements as low as about 0.2 mm with accuracy in the range of 0.1 to 0.2 mm. A controlled study was also performed at a field site where boulders were displaced at millimeter-scale increments and measured using the GBIR, a total station, and a TLS. Results from this portion of the study showed consistent results between the three measurement techniques within measurement error bounds.

Monitoring glacier flow in Ny-Ålesund with a high temporal resolution ground-based interferometric-phased array radar

Monitoring glacier flow speed and calving rates is of interest for climate research, global sea-level studies and Arctic ship traffic. The research station in Ny-Alesund, Svalbard, offers a unique location close to multiple glacier fronts. In this study, we explore the possibilities of permanent monitoring of glaciers in the Ny-Alesund area using a ground-based interferometric radar with a significantly higher temporal resolution than what is achievable from satellites or mechanical scanning ground-based radars. Measurements were made from two different locations—Pynten and the Ny-Alesund research station—located 5 and 15 km from Kronebreen glacier, respectively. The temporal resolution of the radar is flexible, and in this experiment is limited to five images per minute, providing data with high temporal resolution of glacier flow. We calculated a geo-located two-dimensional flow map of the glacier from the radar data, extracted glacier speed profiles and identified major calving onsets. This type of near real-time data may well be used with machine-learning techniques for more advanced monitoring systems. The radar measurements agree well with previous satellite measurements at lower temporal resolution. The observed mean flow of the Kronebreen glacier front varies across the glacier from around 0.4 m/day at the edges to 3 m/day in the central part. We identify and discuss possible improvements to the radar system and conclude that Ny-Alesund is a well-suited location for radar monitoring of glacier flow velocities.

Deflection characterisation of rotary systems using ground‐based radar

In the last two decades, an increase in large rotary machines/systems has been witnessed. To ensure safe operation of these systems especially due to extreme stress caused by centrifugal forces as well as the wind or water loadings, regular structural health monitoring (SHM) of the unbalanced parameters, particularly at the blade tips is necessary. For this, the use of non-contact sensors provides the most appropriate approach; however, millimetric out-of-plane deflection monitoring using non-contact sensors at distances >1 m has not been comprehensively addressed for rotary systems, like wind turbines. This study presents a modelling environment to simulate radar returns to analyse rotary systems. Employing Sammon mapping as a dimensionality reduction procedure in conjunction with 2D visualisation, the study demonstrates the characterisation of dynamic deflection parameters using a fast, portable ground-based interferometric radar (GBR). Comparisons between the GBR results with those of a Leica AR20 GPS indicate a divergence ±12.79 mm. The study utilises SHM framework to acquire, normalise, extract, and validate GBR signals within an SHM framework for structures under test or for deflection validation of the new system. Further, it contributes to the non-contact structural fatigue damage detection during design, testing, and operating stages of rotary structures blade tips.

Optimal geometry to resolve 3D deformation from multiple GB‐DInRad

When multiple ground-based differential interferometric radar (GB-DInRad) systems are utilised together to resolve three-dimensional (3D) deformation, the resolving accuracy is related with the measurement geometry of these radar systems. This Letter focuses on how to determine an optimal geometry. Based on the resolving equation of the 3D deformation, the Geometric Dilution of Precision (GDOP) is defined. Then the minimum value of the GDOP is calculated and a detailed geometrical analysis is made to determine the geometrical conditions of the minimum GDOP. The results prove that the optimal geometry could be obtained when the unit measurement vectors of these radar systems construct a regular pyramid with a specific structure. A numerical simulation is utilised to validate the analysis conclusion.

A New Machine-Learning Prediction Model for Slope Deformation of an Open-Pit Mine: An Evaluation of Field Data

Effective monitoring of the slope deformation of an open-pit mine is essential for preventing catastrophic collapses. It is a challenging task to accurately predict slope deformation. To this end, this article proposed a new machine-learning method for slope deformation prediction. Ground-based interferometric radar (GB-SAR) was employed to collect the slope deformation data from an open-pit mine. Then, an ensemble learner, which aggregated a set of weaker learners, was proposed to mine the GB-SAR field data, delivering a slope deformation prediction model. The evaluation of the field data acquired from the Anjialing open-pit mine demonstrates that the proposed slope deformation model was able to precisely predict the slope deformation of the monitored mine. The prediction accuracy of the super learner was superior to those of all the independent weaker learners.

Ground-Based Differential Interferometric Radar Monitoring of Unstable Mountain Blocks in a Coastal Environment

In this paper, we present the results of eight years of continuous monitoring with a ground-based, interferometric, real-aperture radar of two unstable mountain blocks at Tafjord on the western coast of Norway. A real-time, interferometric, ground-based radar has the capability to provide high accuracy range measurements by using the phase of the transmitted signal, thus achieving sub-millimeter accuracy when a sufficient signal-to-noise level is present. The main challenge with long term monitoring is the variations in radio refractivity caused by changes in the atmosphere. The range variations caused by refractive changes in the atmosphere are corrected using meteorological data. We use triangular corner reflectors as references to improve the signal-to-clutter ratio and improve the accuracy of the measurements. We have also shown that by using differential interferometry, a significant part of the variation caused by radio refractivity variations is removed. The overall reduction in path length variation when using differential interferometry varies from 27 to 164 times depending on the radar-to-reflector path length. The measurements reveal cyclic seasonal variations, which are coherent with air temperature. The results show that radar measurements are as accurate as data from in situ instruments like extensometers and crack meters, making it possible to monitor inaccessible areas. The total measured displacement is between 1.2 mm and 4.7 mm for the two monitored mountain blocks.

Subsidence analysis of ELH Bridge through ground-based interferometric radar during the crossing of a subway shield tunnel underneath the bridge

ABSTRACTGround-based interferometric radar is a popular technique for the deformation monitoring and analysis of civil engineering constructions. Many researchers have applied this technique to different operative scenarios, but only a few studies have analysed deformation time series derived through ground-based interferometric radar in consideration of the effect of coloured noise. In this study, deformation information was retrieved through the joint application of ground-based interferometric radar and maximum likelihood estimation (MLE) in consideration of the effects of white and coloured noises. A case study was conducted on the subsidence of East Lake High-tech Bridge during subway shield tunnel crossing underneath this bridge (from 16 to 18 November 2016). The subsidence time series was derived through ground-based interferometric radar. Afterward, the subsidence time series was verified by levelling at an accuracy better than 0.33 mm. Furthermore, white and coloured noises were detected in the denoized subsidence time series through a spectral analysis and MLE. For the subsidence time series of Nos. 7 and 8 piers, the coloured noise amplitudes were 0.3824 and 0.6261 mm, respectively, and the white noise values were 0.0414 and 0.0610 mm, respectively. Accurate subsidence rates and accumulative subsidence were derived through MLE by using the estimated noise characteristics in the subsidence time series. The subsidence rates of Nos. 7 and 8 piers were −0.0122 ± 0.0060 and −0.0065 ± 0.0058 mm hour−1, respectively, and the accumulative subsidence values were −0.6365 and −0.3370 mm, respectively. This finding suggests that the bridge is stable and safe.

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Abstract. A big challenge in terms or landslide risk mitigation is represented by increasing the resiliency of society exposed to the risk. Among the possible strategies with which to reach this goal, there is the implementation of early warning systems. This paper describes a procedure to improve early warning activities in areas affected by high landslide risk, such as those classified as critical infrastructures for their central role in society. This research is part of the project LEWIS (Landslides Early Warning Integrated System): An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines. LEWIS is composed of a susceptibility assessment methodology providing information for single points and areal monitoring systems, a data transmission network and a data collecting and processing center (DCPC), where readings from all monitoring systems and mathematical models converge and which sets the basis for warning and intervention activities. The aim of this paper is to show how logistic issues linked to advanced monitoring techniques, such as big data transfer and storing, can be dealt with compatibly with an early warning system. Therefore, we focus on the interaction between an areal monitoring tool (a ground-based interferometric radar) and the DCPC. By converting complex data into ASCII strings and through appropriate data cropping and average, and by implementing an algorithm for line-of-sight correction, we managed to reduce the data daily output without compromising the capability for performing.

Integration of ground-based interferometry and terrestrial laser scanning for rockslide and rockfall monitoring

A rockslide in Central Italy has been monitored by means of a ground-based interferometric radar and a terrestrial laser scanner in order to monitor its displacements and to provide both an early warning system and a feedback for the restoration works. The radar furnished near real time displacement maps that were integrated with 3D models of the slope reconstructed through the laser scanner. The integration between the two techniques permitted to reconstruct a high resolution 3D displacement maps of the rockslide also in the areas where profiling works created disturbance to radar data. As a support to the safety of workers and the durability of structural interventions, several detachment areas of rockfalls were also identified and the volume of the blocks calculated.

The Variability of Refractivity in the Atmospheric Boundary Layer of a Tropical Island Volcano Measured by Ground-Based Interferometric Radar.

For 24 h we measured continuously the variability of atmospheric refractivity over a volcano on the tropical island of Montserrat using a ground-based radar interferometer. We observed variations in phase that we interpret as due to changing water vapour on the propagation path between the radar and the volcano and we present them here in the context of the behaviour of the atmospheric boundary layer over the island. The water vapour behaviour was forced by diurnal processes, the passage of a synoptic-scale system and the presence of a plume of volcanic gas. The interferometer collected images of amplitude and phase every minute. From pairs of phase images, interferograms were calculated and analyzed every minute and averaged hourly, together with contemporaneous measurements of zenith delays estimated from a network of 14 GPS receivers. The standard deviation of phase at two sites on the volcano surface spanned a range of about 1–5 radians, the lowest values occurring at night on the lower slopes and the highest values during the day on the upper slopes. This was also reflected in spatial patterns of variability. Two-dimensional profiles of radar-measured delays were modelled using an atmosphere with water vapour content decreasing upwards and water vapour variability increasing upwards. Estimates of the effect of changing water vapour flux from the volcanic plume indicate that it should contribute only a few percent to this atmospheric variability. A diurnal cycle within the lower boundary layer producing a turbulence-dominated mixed layer during the day and stable layers at night is consistent with the observed refractivity.

Special issue: terrestrial remote sensing for areal deformation monitoring

The development of new instruments, sensing techniques, and algorithms has opened a new era in the field of terrestrial deformation monitoring and related applications. Robotic total stations with reflector-less range measurement and increasingly also image assistance (Scherer and Lerma 2009), terrestrial laser scanners (Vosselman and Maas 2010), and digital photogrammetry (Barazzetti et al. 2010) allow the acquisition of dense point clouds within a short time, thus yielding detailed snapshot representations of surfaces and a basis for measuring deformations over wide areas. In addition, ground-based interferometric radar (Monserrat et al. 2014) can be used to derive differential deformation with very high resolution, in particular with respect to persistent scatterers as discussed already by Ferretti et al. (2001). The amount of data provided by these systems is typically much larger than with traditional geodetic techniques, and they potentially represent areal deformations without a need for generalization from displacements of a few carefully selected control points. However, there is no direct point-topoint correspondence between the point clouds obtained at different epochs and thus entirely new algorithms are required in order to analyze deformations (see Dermanis (2011) and Fuentes Santibanez (2012)). New concepts for areal deformation monitoring (ADM) are being developed and investigated including instrumental advances, sensor and process models, and data processing techniques. All of these require thorough validation and assessment before they can be safely applied in critical monitoring applications. This special issue features six selected contributions originally presented at the 2nd Joint International Symposium on Deformation Monitoring (JISDM) held in Nottingham on September 2013 and subsequently further elaborated for peer review and publication. They introduce new instrumental developments, compare technologies and review the state-ofthe-art with respect to their impact on areal deformation measurements, and propose new methods for deformation analysis. The affiliations of the authors of these papers are located in different countries across the globe (Germany, Greece, Italy, the Netherlands, People’s Republic of China, Switzerland, the UK), highlighting internationally recognized relevance of research into areal deformation monitoring. The first article in the special issue (Papastamos et al. 2015) describes the application of total stations for the measurement of control point 3-D displacements with nearly millimeter accuracy. During a project for the excavation of the Athens underground metro railway, this technique was exploited to assess tilting of some chimneys resulting from ground deformation due to tunneling. While such deformations are usually assumed as a 2-D effect, here the theodolite measurements pointed out the evidence of clear 3-D rigid movements of the chimneys in different directions. This outcome was in full agreement with the new theoretical models of ground deformations in the investigated area. * Alessandro Capra capra.alessandro@unimore.it

Sinkhole monitoring and early warning: an experimental application of ground-based interferometry

At Il Piano (Elba Island, Central Italy) 11 sinkhole events occurred on 9 different points on or close to a strategic road connecting Rio Marina to the rest of the island. In order to reduce the risk, a ground-based interferometric radar has been experimentally installed to detect possible precursor deformations of the ground. In this paper we present the results of a test simulating the occurrence of a sinkhole, which highlighted the criticalities of the method, and the successful prediction of a sinkhole event that could have endangered people travelling along the road. These experiences constitute a very important premise and confirm the possibility to measure precursor deformations even days before the opening of a sinkhole. This is due to the presence of a cover consisting in plastic material (clay, silt and even the street tar) that experiences a deformation before rupture as the sinkhole propagates from the bedrock.

Event scenario analysis for the design of rockslide countermeasures

The Torgiovannetto quarry (Assisi municipality, central Italy) is an example of a site where the natural equilibrium was altered by human activity, causing current slope instability phenomena which threaten two roadways important for the local transportation. The quarry front, having a height of about 140 m, is affected by a 182,000 m3 rockslide developed in intensely fractured limestone and is too large to be stabilized. In 2003 some tension cracks were detected in the vegetated area above the quarry upper sector. From then on, several monitoring campaigns were carried out by means of different instrumentations (topographic total station, extensometers, inclinometers, ground-based interferometric radar, laser scanner and infrared thermal camera), allowing researchers to accurately define the landslide area and volume. The latter’s major displacements are localized in the eastern sector. The deformational field appears to be related to the seasonal rainfall. The landslide hazard associated with the worst case scenario was evaluated in terms of magnitude, intensity and triggering mechanism. For the definition of the possible runout process the DAN 3D code was employed. The simulation results were used in order to design and construct a retaining embankment. Furthermore, in order to preserve both the safety of the personnel involved in its realization and of the roadways users, an early warning system was implemented. The early warning system is based on daily-averaged displacement velocity thresholds. The alarm level is reached if the prediction based on the methods of Saito (1969) and Fukuzono (1985) forecasts an imminent rupture.