Drone-Based MT-DInSAR for High-Magnitude 3-D Displacement Retrieval With Daily Revisits

Multi-Temporal Differential Interferometric Synthetic Aperture Radar (MT-DInSAR) techniques have become essential tools for monitoring ground displacement with millimeterscale precision. While widely applied to spaceborne SAR systems for global, long-term monitoring, and to Ground-Based SAR (GBSAR) for continuous tracking in localized areas, these platforms remain constrained by fixed acquisition geometries and Line-of-Sight (LOS) sensitivity. In addition, spaceborne systems face inherent limitations in capturing high-magnitude displacements due to their relatively long revisit times, often leading to temporal decorrelation in such scenarios. In this context, airborne SAR systems offer a compromise by enabling flexible acquisition geometries and on-demand revisit times, with drone platforms emerging as a cost-effective alternative to the high operational and logistical demands of conventional airborne systems. This paper presents the SAR-Drone system, a Ku-band drone-based SAR, and a coregistration and interferometric processor together with two Multi-Temporal DInSAR (MT-DInSAR) methodologies adapted to the SAR-Drone data. The first is displacement-based and designed for scenarios with moderate motion, where interferometric phase remains coherent between consecutive acquisitions; the second is velocity-based, targeting scenarios with highmagnitude displacements where decorrelation occurs even when only a few hours separate acquisitions. The displacement-based methodology is validated in a controlled experiment using corner reflectors, while the velocity-based methodology is demonstrated in a real open-pit mine, where metric-scale slope movements occur within intervals of approximately one day. The results presented in the paper demonstrate the potential of drone-based SAR to complement existing spaceborne, ground-based, and airborne systems by enabling high-resolution three-dimensional (3D) displacement tracking in complex and rapidly evolving environments.