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In this paper, an efficient and accurate imaging algorithm is presented for Ground-Based Synthetic Aperture Radar (GB-SAR) or other radar systems that could be formed by a physical or synthetic linear aperture. The imaging algorithm is based on the fractional Fourier transform (FrFT) for the azimuth compression. A mathematical framework is derived according to the projection of a sample reflectivity image onto the pseudopolar coordinate, and its implementation was presented. With the data acquisition geometry and the pseudopolar imaging coordinate, the phase of a point target can be expressed as a quadratic phase exponential. It makes that only 1-D FrFT is needed for the azimuth compression of the time-domain backscatter data for the GB-SAR imaging problem. By further research, the optimal transformation order that represents the spatial frequency changes by the FrFT was given subsequently. Taking advantage of this optimal representation, the proposed approach avoids the large calculation that occurs in the time-domain back projection (TDBP). Comparing to the far-field pseudopolar format algorithm (FPFA), the accuracy of the proposed algorithm is much improved. Meanwhile, the proposed approach holds almost the same computational cost and complexity as the FPFA. The proposed approach keeps the advantages of the imaging quality of the TDBP and the computational cost of the FPFA that are two important aspects of the GB-SAR applications. Both the numerical simulation and the field GB-SAR experiment show that the algorithm is more suitable for the high-precision GB-SAR imaging, especially for the near field. [ABSTRACT FROM AUTHOR]

In this paper, the applicability of ground-based synthetic aperture radar (GB-SAR) as an early warning system for landslide monitoring is discussed. The effectiveness of the differential interferometric SAR (DInSAR) technique used in GB-SAR depends strongly on the geography of the monitored location. Therefore, an assessment of the system compatibility to select the most appropriate remote monitoring method is essential prior to any hardware implementation. In the preliminary part of this study, a 3D model was created using a LiDAR survey, and proposed locations for GB-SAR installation were examined. A 3D simulation was carried out to estimate the illumination from each of the proposed GB-SAR locations. The proposed model increased the efficiency of the GB-SAR positioning by minimising installation cost and time. Hardware configuration parameters, such as platform height, maximum range, and the direction and view angle of the radar line of sight were estimated by considering the optimum reflected power and ground illumination. Unlike on flat terrain, deployment of GB-SAR in a mountainous area is challenging because of surface anomalies and continuous changes in meteorological parameters, such as atmospheric temperature, pressure and relative humidity. In this study, the experimental site was located 3 km from the Aso volcano, and the weather conditions in the Aso caldera became a critical factor in accurately estimating the interferometric phase. The presence of atmospheric artefacts also compromises the applicability of the classical DInSAR technique. Here, we minimised the atmospheric phase screen by estimating the optimum data acquisition interval from GB-SAR monitoring under extreme weather conditions. The developed methodologies were then used to design a new landslide early warning system that measures real-time displacement over an area of 1 km2 within 10 s of scanning. This fully automatic monitoring system updates every 15 min and presents displacement information in a 3D interface. The system we have developed has been deployed for continuous monitoring of the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan where a large-scale landslide was triggered following the Kumamoto earthquake in 2016. [ABSTRACT FROM AUTHOR]