Multiple-Input Multiple-Output (MIMO) radar provides much more flexibility than the traditional radar thanks to its ability to realize far more observation channels than the actual number of transmit and receive (T/R) elements. In designing the MIMO imaging radar arrays, the commonly used virtual array theory generally assumes that all elements are on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, which will result in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation. Therefore, with a MIMO array designed by this theory, there will exist inevitable high grating lobes in the imaging results of near-field edge points of the scene. To tackle these problems, this paper derives the relationship between target’s point spread function (PSF) and pattern of T/R arrays, by which the design criterion is presented for near-field imaging MIMO arrays. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by two simulations and an experiment.

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 Conventional compensation methods that simulate the AP with typical parametrical models are no longer applicable.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.

The ability of Multiple-Input Multiple-Output (MIMO) radar to provide enhanced performance has been verified in both theoretical and practical level. Through applying orthogonal waveforms, this type of system can realize far more observation channels than the actual number of transmit and receive (T/R) elements. Generally, the azimuth one-dimensional (1D) generalized ambiguity function (GAF) and resolution of a MIMO radar system are analyzed by pattern theory, which can only analyze the GAF along the equidistant curve to the radar's center. However, the two-dimensional (2D) GAF of wideband MIMO radar system shows that its sidelobes are not along the equidistant curve accurately due to the coupling effect between the range-dimension and the azimuth one. Obviously, traditional pattern theory becomes invalid in this case. To tackle this problem, the 2D GAF and the spatial spectrum of far-field targets are derived in this paper. By analyzing the 2D GAF, existence of three individual directions of side lobes (DSLs) is revealed and it is proved that every sidelobes is along a straight line in the pseudo-polar coordinate system. Furthermore, a method to calculate the 1D GAF and resolution in arbitrary direction is proposed. Finally, a simulation and two experiments have been carried out to validate the theoretic results.

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.