Time-series interferograms acquired on a deep pit with a Ground-Based Synthetic Aperture Radar (GB-SAR) system showed that the atmospheric phase (AP) could be complexly space variant due to rapid changes of the weather conditions and steep topography. Conventional compensation methods that simulate the AP with typical parametrical models are no longer applicable. Based on the theoretical path integral model of the AP, a grid partition (GP) method is proposed. By dividing one interferogram into a certain number of small grids, the refraction variation inside each grid is assumed to be a constant. A system of linear equations is first built based on sufficient permanent scatterers (PSs). Then, bounds and inequality constraints are set to limit the refraction variation of each grid. A constrained linear least-square problem is solved with two-step process to estimate and compensate the AP. To fully validate the feasibility of the GP method, simulated phase interferograms based on four conventional AP models and with the consideration of deformation areas and noise phase are first processed. Then, four experimental interferograms with different types of AP components are processed and made comparisons with the conventional parametrical methods. The quantitative comparisons of the simulated and experimental data sets both proved that the GP method can well reduce the AP errors.

This work presents the ideal combination of space-borne and ground-based (GB) Interferometric Synthetic Aperture Radar (InSAR) applications. In the absence of early investigation reporting and specialized monitoring, the Zhongbao landslide unexpectedly occurred on 25 July 2020, forming a barrier lake that caused an emergency. As an emergency measure, the GB-InSAR system was installed 1.8 km opposite the landslide to assess real-time cumulative deformation with a monitoring frequency of 3 min. A zone of strong deformation was detected, with 178 mm deformation accumulated within 15 h, and then a successful emergency warning was issued to evacuate on-site personnel. Post-event InSAR analysis of 19 images acquired by the ESA Sentinel-1 from December 2019 to August 2020 revealed that the landslide started in March 2020. However, the deformation time series obtained from satellite InSAR did not show any signs that the landslide had occurred. The results suggest that satellite InSAR is effective for mapping unstable areas but is not qualified for rapid landslide monitoring and timely warning. The GB-InSAR system performs well in monitoring and providing early warning, even with dense vegetation on the landslide. The results show the shortcomings of satellite InSAR and GB-InSAR and a clearer understanding of the necessity of combining multiple monitoring methods.

An experiment which involves the simultaneous deployment of three ground-based multiple-input multiple-output (GB-MIMO) radar systems to measure 3-D deformation of a displaceable corner reflector (DCR) is outlined in this letter. The DCR successively displaces in three mutually orthogonal directions and each radar measures 1-D deformation independently. Since the displacement directions of the DCR cannot be measured, they are estimated by solving a nonlinear equation set based on the rotation relationship between two 3-D coordinate systems, whose effectiveness is verified by simulation. Considering that the measurement accuracies of the DCR’s displacements along three axial directions of a 3-D coordinate system, that is, 3-D deformation, are related with how the coordinate system is built, the geometric dilution of precision (GDOP) is then utilized to take accuracy analysis. The measured and theoretical GDOP are rather close, which validates the feasibility of 3-D deformation measurement with three radar systems.

Based on the permanent scatterer (PS) technique, deformation measurements were taken in ground-based synthetic aperture radar (GB-SAR) applications. To realize long-term and real-time deformation monitoring, a PS processing framework is proposed. Firstly, a group selection framework is introduced. A certain number of GB-SAR images are selected as a group and different PS sets are selected. Secondly, a fluctuation factor is defined to detect abnormal images. Some images with abnormal amplitude information should not be used for deformation analysis. Thirdly, an adaptive threshold determination method to select the PSs is proposed. The PS numbers in different PS sets can be highly stable. Lastly, a real-time processing framework is introduced which can be applied for on-site monitoring. The proposed processing framework was also used to monitor an open-pit mine for about 11 days. Experimental results validated the effectiveness and reliability of the framework for long-term and real-time GB-SAR monitoring.

Dynamic deformation measurement is an important approach to monitor structure stability. Due to its rapid imaging capabilities, ground-based multi-input–multi-output (GB-MIMO) radar has shown great application potential in bridge structure monitoring. This article proposes a dynamic deformation estimation method based on radar image series. First, an improved clutter suppression method is used to overcome the estimation error in complex working status. Second, a two-step pixel extraction method is adopted to ensure both the quantity and quality of sample pixels. Finally, frequency- and time-domain environmental stimulating methods are jointly considered for stable mode shape estimation. This article systematically measured the dynamic deformations of bridge structures, including two suspension bridges and a cable-stayed bridge. The time-series deformation, deflection, vibration frequency, and amplitude on the bridge structure are obtained by image-domain measurement. For the first time, the mode shapes of bridges are obtained through GB-MIMO radar. The correctness of structure parameter measurement is verified with the finite element model (FEM). Experimental results prove that with the proposed method, stable results could be acquired against weak and complex stimulation conditions.

Ground-based synthetic aperture radar (GB-SAR) technique has been widely applied for the deformation monitoring and measurement of the natural and engineered slopes. To extend the 2-D deformation measurement from the conventional 1-D measurement along the radar-target line of sight (LOS), multiple aperture interferometry (MAI) techniques based on phase differences between interferograms of the forward-looking and backward-looking subapertures are tackled in this letter. The optimal subaperture selection is analyzed considering the typical signal-to-noise ratios and correlations in GB-SAR applications. Simulations prove that the coherent integration (CIM) can be utilized to improve the measurement accuracy of the MAI method. Besides, GB-SAR experiments are carried out to validate the feasibility and effectiveness of the 2-D deformation measurement method based on MAI. Accuracy comparison of deformation measurement with the MAI and cross correlation methods is also taken. Experimental results show that the accuracy of deformation measurement along the perpendicular direction to LOS based on MAI and CIM can reach millimeter level for displaceable corner reflector.