Non-Local Compressive Sensing Based SAR Tomography

Tomographic SAR (TomoSAR) inversion of urban areas is an inherently sparse reconstruction problem and, hence, can be solved using compressive sensing (CS) algorithms. This paper proposes solutions for two notorious problems in this field: 1) TomoSAR requires a high number of data sets, which makes the technique expensive. However, it can be shown that the number of acquisitions and the signal-to-noise ratio (SNR) can be traded off against each other, because it is asymptotically only the product of the number of acquisitions and SNR that determines the reconstruction quality. We propose to increase SNR by integrating non-local estimation into the inversion and show that a reasonable reconstruction of buildings from only seven interferograms is feasible. 2) CS-based inversion is computationally expensive and therefore barely suitable for large-scale applications. We introduce a new fast and accurate algorithm for solving the non-local L1-L2-minimization problem, central to CS-based reconstruction algorithms. The applicability of the algorithm is demonstrated using simulated data and TerraSAR-X high-resolution spotlight images over an area in Munich, Germany.Comment: 10 page

A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR

$L_1$ regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization scheme and its extensions have been widely employed in many remote sensing problems, such as image fusion, target detection, image super-resolution, and others and have led to promising results. However, solving such sparse reconstruction problems is computationally expensive and has limitations in its practical use. In this paper, we proposed a novel efficient algorithm for solving the complex-valued $L_1$ regularized least squares problem. Taking the high-dimensional tomographic synthetic aperture radar (TomoSAR) as a practical example, we carried out extensive experiments, both with simulation data and real data, to demonstrate that the proposed approach can retain the accuracy of second order methods while dramatically speeding up the processing by one or two orders. Although we have chosen TomoSAR as the example, the proposed method can be generally applied to any spectral estimation problems.Comment: 11 pages, IEEE Transactions on Geoscience and Remote Sensin

Building profile reconstruction using TerraSAR-X data time-series and tomographic techniques

This work aims to show the potentialities of SAR Tomography (TomoSAR) techniques for the 3-D characterization (height, reflectivity, time stability) of built-up areas using data acquired by the satellite sensor TerraSAR-X. For this purpose 19 TerraSAR-X single-polarimetric multibaseline images acquired over Paris urban area have been processed applying classical nonparametric (Beamforming and Capon) and parametric (MUSIC) spectral estimation techniques

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Elevation Extraction from Spaceborne SAR Tomography Using Multi-Baseline COSMO-SkyMed SAR Data

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area

Investigation of Sea Ice Using Multiple Synthetic Aperture Radar Acquisitions

The papers of this thesis are not available in Munin. Paper I: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Tomographic imaging of fjord ice using a very high resolution ground-based SAR system. Available in IEEE Transactions on Geoscience and Remote Sensing, 55 (2):698-714. Paper II: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Lake and fjord ice imaging using a multifrequency ground-based tomographic SAR system. Available in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(10):4457-4468. Paper III: Yitayew, T. G., Divine, D. V., Dierking, W., Eltoft, T., Ferro-Famil, L., Rosel, A. & Negrel, J. Validation of Sea ice Topographic Heights Derived from TanDEMX Interferometric SAR Data with Results from Laser Profiler and Photogrammetry. (Manuscript).The thesis investigates imaging in the vertical direction of different types of ice in the arctic using synthetic aperture radar (SAR) tomography and SAR interferometry. In the first part, the magnitude and the positions of the dominant scattering contributions within snow covered fjord and lake ice layers are effectively identified by using a very high resolution ground-based tomographic SAR system. Datasets collected at multiple frequencies and polarizations over two test sites in Tromsø area, northern Norway, are used for characterizing the three-dimensional response of snow and ice. The presented experimental results helped to improve our understanding of the interaction between radar waves and snow and ice layers. The reconstructed radar responses are also used for estimating the refractive indices and the vertical positions of the different sub-layers of snow and ice. The second part of the thesis deals with the retrieval of the surface topography of multi-year sea ice using SAR interferometry. Satellite acquisitions from TanDEM-X over the Svalbard area are used for analysis. The retrieved surface height is validated by using overlapping helicopter-based stereo camera and laser profiler measurements, and a very good agreement has been found. The work contributes to an improved understanding regarding the potential of SAR tomography for imaging the vertical scattering distribution of snow and ice layers, and for studying the influence of both sensor parameters such as its frequency and polarization and scene properties such as layer stratification, air bubbles and small-scale roughness of the interfaces on snow and ice backscattered signal. Moreover, the presented results reveal the potential of SAR interferometry for retrieving the surface topography of sea ice

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Scanning Volcanoes by Synthetic Aperture Radar

A problem with synthetic aperture radar (SAR) is that due to the poor penetrating action of electromagnetic waves within solid bodies, the ability to observe through distributed targets is precluded. In this context, indeed, imaging is only possible on targets distribute on the scene surface. This work describes an imaging method based on the analysis of micro-motions present on volcanoes and generated by the underground Earth's heat. Processing the coherent vibrational information embedded on the single SAR image, in the single-look-complex configuration, the sound information is exploited, penetrating tomographic imaging over a depth of about 3 km from the Earth's surface. Measurement results are calculated by processing a SLC image from the COSMO-SkyMed Second Generation satellite constellation of the Vesuvius. Tomographic maps reveal the presence of the magma chamber, together with the main and the secondary volcanic conduits. This technique certainly paves the way for completely new exploitation of SAR images to scan inside the Earth's surface