LuTan-1 (LT-1) is the first civil L-band synthetic aperture radar (SAR) satellite constellation and comprises two identical satellites. LT-1 is designed to fulfill two main requirements, one of which the main tasks is to provide digital surface model (DSM) products covering the areas that are not available using optical satellites. The second task is to provide deformation products to support the geohazard monitoring task. For the first task, LT-1 provides a novel noninterrupted imaging technology to facilitate phase synchronization. For the second task, the orbit maintenance is implemented using a newly proposed in-plane offset semimajor axis and out-of-plane control triggered strategy. Besides, we provide the system performance analysis for the two main tasks. Finally, the first results are produced with root-mean-square-error (RMSE) of the DSM less than 0.7 m in the flat region and 6.7 m in the mountainous region. The RMSE of the first deformation products is less than 2.7 mm in the test region. The results indicate a favorable potential for terrain mapping and deformation monitoring applications.

LuTan-1(LT-1) has finished its in-orbit test in 2023. The inorbit test results show that LT-1 performed well and fulfilled the needs of the users. In order to use the data operationally for natural resources monitoring, especially for geohazard monitoring, we have established the application system for LT-1. In this paper, we have introduced the application system including the geometric technology, the standard products generation method, the basic deformation products generation method. Demonstrations of LT-1 are also provided to support the applications of the satellite data.

The Kinematics of rock glaciers is a key indicator for studying periglacial environment hydrology, climate, and disasters. Differential Interferometric Synthetic Aperture Radar (DInSAR) has been demonstrated to be an effective technique for detecting the deformation of rock glaciers. In this study, we present an investigation of the potential of the Lutan-1 (LT-1) SAR constellation for rock glacier topography mapping and deformation monitoring over a periglacial environment with complex topography using Stacking InSAR methods. Firstly, a high-resolution digital surface model (DSM) is generated by the bistatic formation data of the LT-1 SAR constellation. Compared with the ICESat GLAS points elevation product distributed in the study area, the R2reached 0.96, and the root mean square error (RMSE) reached 1.6m, indicating the accuracy of the LT-1 derived DSM product. Then, the deformation velocities of the rock glaciers were acquired from the Stacking InSAR method over the study area. The results indicated that the LOS deformation velocities of rock glaciers in the study area ranged from −0.8 m/y to approximately 0.6 m/y, with an average velocity amplitude of 0.06 m/y. With 241 of the rock glaciers exhibit active zones. The results demonstrated that the LT-1 SAR constellation could provide a new SAR data source for periglacial landform topography mapping and deformation monitoring.

2-D phase unwrapping (PU) is one of the key steps in the processing of interferometric synthetic aperture radar (InSAR) data. PU in large-gradient areas has always been a fundamental problem. The phase continuity assumption makes it difficult to obtain ideal PU results in large-gradient areas. To address this issue, in this letter, we propose a phase slicing 2-D PU method using the L1-norm that can effectively reduce the phase gradient interval. First, the study area is analyzed using an external digital elevation model (DEM) and interferometric phase information to obtain the number of phase slices and assisted phases. Then, we cut the interferometric phase to obtain the sliced interferometric phase and use the single-baseline (SB) L1-norm PU method to unwrap the sliced interferometric phase. Finally, the unwrapped phase is recovered by summing the sliced unwrapped phases and assisted phases. Experiments are conducted with simulated and TanDEM-X InSAR data sets. Compared with the representative SB-PU method, the proposed method can effectively avoid the problem of large gradients in PU.

Synthetic aperture radar (SAR), an active microwave remote sensing equipment, can provide all-day, all-weather, and high-resolution images for Earth observation. Ship monitoring using SAR is significant to fishery application, marine transportation, maritime security, and so on. Most traditional SAR ship detection methods use the amplitude information of the SAR imagery and employ the constant false alarm rate (CFAR), deep learning, and other technologies to detect the ship targets. However, in addition to the amplitude image, the SAR single-look complex (SLC) data can also be utilized for ship detection since its complex-valued information is beneficial to characterize the ship’s feature in the transforming domains. In this article, the strong scattering feature of ships in the image domain and low-rank feature in the transforming domain is studied, and on this basis, a two-step detector is proposed to detect ship targets in SAR SLC image. The first step is to identify the presence of ships, which is based on the eigen-subspace projection (ESP) technology to detect the occurrences of the ship targets in azimuth cells of the SAR data. The second step is to locate the position of ships, which is based on the low-rank and sparse matrix decomposition (LRSMD) to obtain the instantaneous frequency information of the ship targets in the time–frequency domain. Finally, the ship targets can be located in a line-by-line manner in the azimuth direction. Experimental results via European Sentinel-1A and Chinese Gaofen-3 single-pol SAR SLC data demonstrate the performance of the proposed detector.