A radar-based, non-contact, marker-less bridge dynamic displacement estimation approach from oscillating platforms is proposed. The proposed approach makes use of a multiple-input multiple-output (MIMO) radar device to generate two-dimensional (2D) images of the bridge at short time intervals, in combination with radar interferometry techniques. Additionally, we propose a novel dynamic motion error compensation (DMEC) process to compensate for platform-induced phase errors. The DMEC is a data-driven approach that does not require any auxiliary data and applies corrections in the spatial domain for each interferogram, leveraging the 2D imaging capability of the MIMO radar. The proposed method was validated using simulated synthetic aperture radar (SAR) datasets of bridge under controlled conditions, demonstrating significant enhancement in displacement signatures and enabling the detection of both deflection and modal vibrations with high precision. Field validation experiments were also conducted using an oscillating MIMO radar to observe a simply supported girder bridge. The results showed that the system could detect sub-millimeter deflection signals induced by vehicle live loads—much smaller than platform oscillations—with the minimum observed deflection amplitude of -152.7 μm.

Failure of the retaining wall of a residential building resulted in the collapse of the structure and raised the risk of additional damage to the surrounding area. This study demonstrates the monitoring of residential area affected by retaining wall failure using ground-based synthetic aperture radar (GB-SAR) to provide early warnings for potential secondary failure events. A Ku-band GB-SAR system operating at 17.2 GHz was installed on the rooftop of the building. This installed SAR system continuously monitors the displacement of the target area in near-real time. The estimated results depict a noticeable displacement pattern, reaching a maximum of 15mm during the five-month monitoring period.

This letter proposes a new atmospheric phase screen (APS) compensation method for ground-based synthetic aperture radar interferometry (InSAR). Conventionally, the APS trend is retrieved employing the assumption that the displacement component is a high spatial frequency component, thus making it separable from the APS trend and easy to be identified as outliers during the trend estimation whether using least squares or spectral analysis. However, landslides generally occur over a wide area forming a low spatial frequency component similar to the atmospheric component, which could give significant bias during the parameter estimation. This led to the suppression of the observed displacement from its true since it was partly misidentified as the APS. This specific APS misidentification issue is rarely mentioned in previous literature regarding APS compensation. A robust method to address this issue is proposed in this letter, dubbed best subsample consensus (BeSSaC). This method employs a robust estimation technique using the least median absolute residual criteria, it is shown that a wide-displacement component can be effectively separated from the APS using this technique.

Application of fully polarimetric synthetic aperture radar (PolSAR) for detection of archaeological site in Muaro Jambi, Indonesia, is presented. Scale mode of manmade structure is constructed and is measured using setup reproducing ALOS PALSAR2 full polarization strip map mode. The backscattered signal is then decomposed and analyzed for each scattering mechanism. Both scale model and satellite measurement is analyzed. It is shown that the scattering mechanism of scale model confirms theoretical and real measurement of satellite data.

This study evaluates and quantifies the atmospheric phase screen (APS) effects in a 79 GHz multi-input multi-output (MIMO) radar system. In addition to the 79 GHz radar measurement, the 17 GHz ground-based synthetic aperture radar (GB-SAR) measurement was performed simultaneously for comparison. We conducted a 24-hours continuous experiment in an outdoor environment with a maximum range distance of 130m. We deployed nine stationary corner reflectors (CR) to investigate the sensitivity to atmospheric disturbance. Our analysis revealed that the effect of APS in 79 GHz radar was more pronounced than in 17 GHz GB-SAR. Nonetheless, appropriate APS compensation led to smaller residual APS than 17 GHz radar. The feasibility of using a 79 GHz low-cost small radar system for long-range environmental displacement monitoring would partly be shown in the presented study.

The south coast of Java is located in an active subduction zone where the Indo-Australian plate is beneath the Eurasian plate with a velocity of 7,0 cm/year. The phenomena lead to the area front of disaster, especially earthquakes and tsunami. Some areas along the coast of JAVA are being pressed (subsidence) or lifted due to the tectonic activity of the plate. Also, the activity can result in the creation of areas that have the potential to experience ground movement. However, information about it with scientific evidence is still inadequate. Therefore it is necessary to observe the effects of tectonic activity in southern Java on land surface changes along the coastline and estimate the potential epicenter of earthquakes due to this activity. In this study, we observed land deformation along the southern coast of Java to determine which areas experienced significant deformation. Based on the result, we can estimate the future earthquake's potential epicenter and the land movement area. Also, we analyzed the duration required since the last observation of earthquake events or land movement in the area. The land deformation observation uses satellite radar SAR data of ALOS-2 PALSAR-2 provided by JAXA. The type of SAR data is a stripmap with a 3 x 8-meter resolution. The time acquisition varied for each area observed from 2017 to 2020. The covered area of studies is spread from West to East (Pandagelang, Lebak, Sukabumi, Cianjur, Garut, Pangandaran, Banjar, Cilacap, Kebumen, Purworejo, and Bantul).

In Indonesia, extensive tropical peatland has been facing land degradation due to deforestation and drainage canal construction. Such activities lead to the decrease of groundwater level (GWL), accelerating the peat decomposition, followed by peatland subsidence. This study addresses to estimate a three-year (from Jan. 2018 to Jan. 2020) tropical peatland subsidence over Kalimantan, Indonesia, using the time-series interferometric synthetic aperture radar (TlnSAR) technique by Sentinel-IA. TlnSAR analysis revealed the apparent large displacement found in 2019 due to a significant decline of GWL caused by positive Indian-Ocean dipole mode (IOD) event compared to other years. Furthermore, we employed GWL derived from satellite-based remote sensing data to investigate the relationship between subsidence and GWL and showed a mutual relationship.

In multitemporal interferometric synthetic aperture radar (InSAR) applications, propagation delay in the troposphere introduces a major source of disturbance known as atmospheric phase screen (APS). This study proposes a novel framework to compensate for the APS from multitemporal ground-based InSAR data. The proposed framework first performs time-series clustering in accordance with the temporal APS behavior realized by the$k$-means clustering approach. In the second step, joint estimation of the APS and displacement velocity is performed. For this purpose, a novel interferometric signal model, including the APS modeled by the median profiles defined in each cluster, is proposed. The proposed framework is validated with the Ku-band ground-based synthetic aperture radar data sets measured over a mountainous area in Kumamoto, Japan. Tests on these data sets reveal that compared with the conventional approach, the presented approach improves displacement estimation accuracy under severe atmospheric conditions.

In the above paper[1], there are errors in the following twoequations (7) and (8):

Propagation delay in the atmosphere is the most important artifact that has to be mitigated in the interferometric SAR applications for displacement estimates. In the case of 3D spatial heterogeneous refractivity distribution, propagation delay in the atmosphere known as atmospheric phase screen (APS) is difficult to be corrected without a priori knowledge of displacement location. Especially for ground-based radar interferometric (GRI) measurement in the mountainous area suffers from a significant effect of APS which is difficult to fully be compensated by conventional compensation methods. This paper presents a novel approach to compensate for the APS, especially for the GRI application. In this framework, the time-series clustering approach is proposed to identify the local APS pattern due to the heterogeneity of refractivity. The correlation of each couple of temporal profiles is employed to cluster phase profiles by the rational of the k-means clustering approach. The proposed method further compensates the residual APS by estimating the temporal behavior of each cluster. Synthetic displacements are generated to assess the performances of the method in disentangling terrain displacements and propagation delay in the atmosphere.

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 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.

In this paper, we attempt to develop the soil moisture retrieval method taking into account a wide variety of vegetation variations for the sparsely vegetated area. The method is constructed by introducing generalized volume scattering model into the polarimetric two-scale two-component model (PTSTCM). The proposed method was applied to L-band fully polarimetric ALOS-2 SAR datasets obtained over tropical peatland, Indonesia. The retrieved results were validated by simultaneously measured in-situ soil moisture. The proposed method yields more improved results than original PTSTCM with specific types of volume model (i.e., randomly, horizontally, and vertically oriented volume models) regarding the root-mean-square-error (RMSE) as well as inversion rate.

Circularly polarized (CP) synthetic aperture radar (SAR) is a recent state of art SAR that adopts CP-antennas on both a transmitter and a receiver (end-to-end circular polarization). For use of this SAR configuration practically and precisely, in this paper, we propose two types of point target-based polarimetric calibration methods modified by existing calibration for the linearly polarized (LP) radar. Two proposed methods are applied to a ground-based (GB) CP-SAR system to assess the calibration capability on a polarimetric application. The proposed methods yield more accurate entropy-alpha (H-α) distributions than uncalibrated data. The proposed point target-based polarimetric calibration methods can be applied to the wide-frequency bandwidth CP GB-SAR application.

This paper proposes the phase error compensation algorithm of the wide band chirp generator for the synthetic aperture radar (SAR) use. The proposed algorithm dynamically calculates the phase error of transmitting chirp to reduce spurious of signal. In addition, it uses the curve fitting method and feedback when the desired signal are set by user. Numerical results show that the proposed algorithm can enhance the impulse response function (IRF) results such as the peak to side-lobe ratio (PSLR) and the integrated side-lobe ratio (ISLR) up to −0.1561 dB and −0.0548 dB respectively. Furthermore, the spurious has been reduced by compared to the conventional direct digital frequency synthesizer (DDFS) chirp generators.