Refined estimation of time-varying baseline errors in airborne SAR interferometry

The processing of airborne synthetic aperture radar (SAR) data requires a precise compensation of the deviations of the platform movement from a straight line. This is usually carried out by recording the trajectory with a high-precision navigation system and correcting them during SAR focusing. However, due to the lack of accuracy in current navigation systems, residual motion errors persist in the images. Such residual motion errors are mainly noticeable in repeat-pass systems, where they are causing time-varying baseline errors, visible as artefacts in the derived phase maps. In this letter, a refined method for the estimation of time-varying baseline errors is presented. An improved multisquint processing approach is used for obtaining robust estimates of higher order baseline errors over the entire scene, even if parts of the scene are heavily decorrelated. In a subsequent step, the proposed method incorporates an external digital elevation model for detection of linear and constant components of the baseline error along azimuth. Calibration targets in the scene are not necessary.Peer Reviewe

Simultaneous Estimation of Sub-canopy Topography and Forest Height with Single-baseline Single-polarization TanDEM-X Interferometric Data Combined with ICESat-2 Data

To address the challenge of retrieving sub-canopy topography using single-baseline single-polarization TanDEM-X InSAR data, we propose a novel InSAR processing framework. Our methodology begins by employing the SINC model to estimate the penetration depth (PD). Subsequently, we establish a linear relationship between PD and phase center height (PCH) to generate a wall-to-wall PCH product. To achieve this, space-borne LiDAR data are employed to capture the elevation bias between actual ground elevation and InSAR-derived elevation. Finally, the sub-canopy topography is derived by subtracting the PCH from the conventional InSAR-based DEM. Moreover, this approach enables the simultaneous estimation of forest height from single-baseline TanDEM-X data by combining the estimated PD and PCH components. The approach has been validated against Airborne Lidar Scanning data over four diverse sites encompassing different forest types, terrain conditions, and climates. The derived sub-canopy topography in the boreal and hemi-boreal forest sites (Krycklan and Remningstorp) demonstrated notable improvement in accuracy. Additionally, the winter acquisitions outperformed the summer ones in terms of inversion accuracy. The achieved RMSEs for the winter scenarios were 2.45 m and 3.83 m, respectively, representing a 50% improvement over the InSAR-based DEMs. And the forest heights are also close to the ALS measurements, with RMSEs of 2.70 m and 3.33 m, respectively. For the Yanguas site in Spain, characterized by rugged terrain, sub-canopy topography in forest areas was estimated with an accuracy of 4.27m, a 35% improvement over the original DEM. For the denser tropical forest site, only an average elevation bias could be corrected.This work is funded by the National Key R&D Program of China (No. 2022YFB3902605), the National Natural Science Foundation of China (Nos. 42227801, 42030112, 42204024, 42104016, 42330717), the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development under Project PID2020-117303GB-C22/AEI/10.13039/501100011033, the Natural Science Foundation for Excellent Young Scholars of Hunan Province (No. 2023JJ20061), and in part by the China Scholarship Council Foundation to the Joint Ph.D. Studies at University of Alicante (No. 202106370125)

UAVSAR: A new NASA airborne SAR system for science and technology research

NASA’s Jet Propulsion Laboratory is currently building a reconfigurable, polarimetric L-band synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. Differential interferometry can provide key deformation measurements, important for studies of earthquakes, volcanoes and other dynamically changing phenomena. Using precision real-time GPS and a sensor controlled flight management system, the system will be able to fly predefined paths with great precision. The expected performance of the flight control system will constrain the flight path to be within a 10 m diameter tube about the desired flight track. The radar will be designed to be operable on a UAV (Unpiloted Arial Vehicle) but will initially be demonstrated on a on a NASA Gulfstream III. The radar will be fully polarimetric, with a range bandwidth of 80 MHz (2 m range resolution), and will support a 16 km range swath. The antenna will be electronically steered along track to assure that the antenna beam can be directed independently, regardless of the wind direction and speed. Other features supported by the antenna include elevation monopulse and pulse-to-pulse re-steering capabilities that will enable some novel modes of operation. The system will nominally operate at 45,000 ft (13800 m). The program began as an Instrument Incubator Project (IIP) funded by NASA Earth Science and Technology Office (ESTO)

Interferometric Synthetic Aperture Radar (InSAR) for Fine-resolution Basal Ice Sheet Imaging

This dissertation work was to examine the feasibility of InSAR through the ice sheets to create a fine resolution basal topography map and extraction of basal composition. InSAR was shown to be possible through the ice sheet, using data collected by the MCRDS radar around the NEEM drill site. Reflectivity maps were generated leading to the possibility of extracting useful basal composition data. Extraction of basal composition information was examined including estimating the roughness of basal topography and removing the effects of local slope

Electromagnetic Scattering Models for InSAR Correlation Measurements of Vegetation and Snow

Interferometric Synthetic Aperture Radar (InSAR) has proved successful and efficient in measuring the vertical structure of the distributed targets such as vegetation and snow, which are dominated by volume scattering. In particular, the InSAR correlation measurement has been utilized to retrieve the target vertical structural information. One existing and well-known electromagnetic scattering model of the InSAR correlation was first brought forward focusing on the single-pass InSAR observation of a sparse random medium like vegetation. However, the lack of the adaption of this InSAR scattering model for repeat-pass InSAR observation of vegetation as well as for single-pass InSAR observation of snow by considering its dense medium characteristics, essentially constrain fully exploiting InSAR\u27s capability of measuring sparse and dense medium characteristics. In this work, the well-known InSAR scattering model will be adapted to accommodate the two scenarios: 1) repeat-pass InSAR observation of vegetation and 2) single-pass InSAR observation of snow and considering its dense medium characteristics. Theoretical model derivations as well as parameter retrieval approaches are demonstrated for both of the applications, respectively. Both of the simulated and ground validation results are also presented. The InSAR scattering models along with the parameter retrieval analysis described in this work will expand InSAR\u27s capability as well as the range of vegetation and snow characteristics that can be retrieved by single-pass and/or repeat-pass InSAR systems

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version