Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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Theory and Design of a Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar

Compressed sensing (CS) is a recent mathematical technique that leverages the sparsity in certain sets of data to solve an underdetermined system and recover a full set of data from a sub-Nyquist set of measurements of the data. Given the size and sparsity of the data, radar has been a natural choice to apply compressed sensing to, typically in the fast-time and slow-time domains. Polarimetric synthetic aperture radar (PolSAR) generates a particularly large amount of data for a given scene; however, the data tends to be sparse. Recently a technique was developed to recover a dropped PolSAR channel by leveraging antenna crosstalk information and using compressed sensing. In this dissertation, we build upon the initial concept of the dropped-channel PolSAR CS in three ways. First, we determine a metric which relates the measurement matrix to the l2 recovery error. The new metric is necessary given the deterministic nature of the measurement matrix. We then determine a range of antenna crosstalk required to recover a dropped PolSAR channel. Second, we propose a new antenna design that incorporates the relatively high levels of crosstalk required by a dropped-channel PolSAR system. Finally, we integrate fast- and slow-time compression schemes into the dropped-channel model in order to leverage sparsity in additional PolSAR domains and overall increase the compression ratio. The completion of these research tasks has allowed a more accurate description of a PolSAR system that compresses in fast-time, slow-time, and polarization; termed herein as highly compressed PolSAR. The description of a highly compressed PolSAR system is a big step towards the development of prototype hardware in the future

Very High Resolution Tomographic SAR Inversion for Urban Infrastructure Monitoring — A Sparse and Nonlinear Tour

The topic of this thesis is very high resolution (VHR) tomographic SAR inversion for urban infrastructure monitoring. To this end, SAR tomography and differential SAR tomography are demonstrated using TerraSAR-X spotlight data for providing 3-D and 4-D (spatial-temporal) maps of an entire high rise city area including layover separation and estimation of deformation of the buildings. A compressive sensing based estimator (SL1MMER) tailored to VHR SAR data is developed for tomographic SAR inversion by exploiting the sparsity of the signal. A systematic performance assessment of the algorithm is performed regarding elevation estimation accuracy, super-resolution and robustness. A generalized time warp method is proposed which enables differential SAR tomography to estimate multi-component nonlinear motion. All developed methods are validated with both simulated and extensive processing of large volumes of real data from TerraSAR-X

コンプレッシブ・センシングによる合成開口レーダの高分解能化

Tohoku University佐藤源之課

Spaceborne radar observations: A guide for Magellan radar-image analysis

Geologic analyses of spaceborne radar images of Earth are reviewed and summarized with respect to detecting, mapping, and interpreting impact craters, volcanic landforms, eolian and subsurface features, and tectonic landforms. Interpretations are illustrated mostly with Seasat synthetic aperture radar and shuttle-imaging-radar images. Analogies are drawn for the potential interpretation of radar images of Venus, with emphasis on the effects of variation in Magellan look angle with Venusian latitude. In each landform category, differences in feature perception and interpretive capability are related to variations in imaging geometry, spatial resolution, and wavelength of the imaging radar systems. Impact craters and other radially symmetrical features may show apparent bilateral symmetry parallel to the illumination vector at low look angles. The styles of eruption and the emplacement of major and minor volcanic constructs can be interpreted from morphological features observed in images. Radar responses that are governed by small-scale surface roughness may serve to distinguish flow types, but do not provide unambiguous information. Imaging of sand dunes is rigorously constrained by specific angular relations between the illumination vector and the orientation and angle of repose of the dune faces, but is independent of radar wavelength. With a single look angle, conditions that enable shallow subsurface imaging to occur do not provide the information necessary to determine whether the radar has recorded surface or subsurface features. The topographic linearity of many tectonic landforms is enhanced on images at regional and local scales, but the detection of structural detail is a strong function of illumination direction. Nontopographic tectonic lineaments may appear in response to contrasts in small-surface roughness or dielectric constant. The breakpoint for rough surfaces will vary by about 25 percent through the Magellan viewing geometries from low to high Venusian latitudes. Examples of anomalies and system artifacts that can affect image interpretation are described

Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR

In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy. The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure. The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest. The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations

Technology needs of advanced Earth observation spacecraft

Remote sensing missions were synthesized which could contribute significantly to the understanding of global environmental parameters. Instruments capable of sensing important land and sea parameters are combined with a large antenna designed to passively quantify surface emitted radiation at several wavelengths. A conceptual design for this large deployable antenna was developed. All subsystems required to make the antenna an autonomous spacecraft were conceptually designed. The entire package, including necessary orbit transfer propulsion, is folded to package within the Space Transportation System (STS) cargo bay. After separation, the antenna, its integral feed mast, radiometer receivers, power system, and other instruments are automatically deployed and transferred to the operational orbit. The design resulted in an antenna with a major antenna dimension of 120 meters, weighing 7650 kilograms, and operating at an altitude of 700 kilometers

Convex Model-Based Synthetic Aperture Radar Processing

The use of radar often conjures up images of small blobs on a screen. But current synthetic aperture radar (SAR) systems are able to generate near-optical quality images with amazing benefits compared to optical sensors. These SAR sensors work in all weather conditions, day or night, and provide many advanced capabilities to detect and identify targets of interest. These amazing abilities have made SAR sensors a work-horse in remote sensing, and military applications. SAR sensors are ranging instruments that operate in a 3D environment, but unfortunately the results and interpretation of SAR images have traditionally been done in 2D. Three-dimensional SAR images could provide improved target detection and identification along with improved scene interpretability. As technology has increased, particularly regarding our ability to solve difficult optimization problems, the 3D SAR reconstruction problem has gathered more interest. This dissertation provides the SAR and mathematical background required to pose a SAR 3D reconstruction problem. The problem is posed in a way that allows prior knowledge about the target of interest to be integrated into the optimization problem when known. The developed model is demonstrated on simulated data initially in order to illustrate critical concepts in the development. Then once comprehension is achieved the processing is applied to actual SAR data. The 3D results are contrasted against the current gold- standard. The results are shown as 3D images demonstrating the improvement regarding scene interpretability that this approach provides

Phase History Decomposition for Efficient Scatterer Classification in SAR Imagery

A new theory and algorithm for scatterer classification in SAR imagery is presented. The automated classification process is operationally efficient compared to existing image segmentation methods requiring human supervision. The algorithm reconstructs coarse resolution subimages from subdomains of the SAR phase history. It analyzes local peaks in the subimages to determine locations and geometric shapes of scatterers in the scene. Scatterer locations are indicated by the presence of a stable peak in all subimages for a given subaperture, while scatterer shapes are indicated by changes in pixel intensity. A new multi-peak model is developed from physical models of electromagnetic scattering to predict how pixel intensities behave for different scatterer shapes. The algorithm uses a least squares classifier to match observed pixel behavior to the model. Classification accuracy improves with increasing fractional bandwidth and is subject to the high-frequency and wide-aperture approximations of the multi-peak model. For superior computational efficiency, an integrated fast SAR imaging technique is developed to combine the coarse resolution subimages into a final SAR image having fine resolution. Finally, classification results are overlaid on the SAR image so that analysts can deduce the significance of the scatterer shape information within the image context

Interferometric Synthetic Aperture RADAR and Radargrammetry towards the Categorization of Building Changes

The purpose of this work is the investigation of SAR techniques relying on multi image acquisition for fully automatic and rapid change detection analysis at building level. In particular, the benefits and limitations of a complementary use of two specific SAR techniques, InSAR and radargrammetry, in an emergency context are examined in term of quickness, globality and accuracy. The analysis is performed using spaceborne SAR data