Exploring scatterer anisotrophy in synthetic aperture radar via sub-aperture analysis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 189-193).Scattering from man-made objects in SAR imagery exhibits aspect and frequency dependencies which are not always well modeled by standard SAR imaging techniques based on the ideal point scattering model. This is particularly the case for highresolution wide-band and wide-aperture data where model deviations are even more pronounced. If ignored, these deviations will reduce recognition performance due to the model mismatch, but when appropriately accounted for, these deviations from the ideal point scattering model can be exploited as attributes to better distinguish scatterers and their respective targets. With this in mind, this thesis develops an efficient modeling framework based on a sub-aperture pyramid to utilize scatterer anisotropy for the purpose of target classification. Two approaches are presented to exploit scatterer anisotropy using the sub-aperture pyramid. The first is a nonparametric classifier that learns the azimuthal dependencies within an image and makes a classification decision based on the learned dependencies. The second approach is a parametric attribution of the observed anisotropy characterizing the azimuthal location and concentration of the scattering response. Working from the sub-aperture scattering model, we develop a hypothesis test to characterize anisotropy. We start with an isolated scatterer model which produces a test with an intuitive interpretation. We then address the problem of robustness to interfering scatterers by extending the model to account for neighboring scatterers which corrupt the anisotropy attribution.(cont.) The development of the anisotropy attribution culminates with an iterative attribution approach that identifies and compensates for neighboring scatterers. In the course of the development of the anisotropy attribution, we also study the relationship between scatterer phenomenology and our anisotropy attribution. This analysis reveals the information provided by the anisotropy attribution for two common sources of anisotropy. Furthermore, the analysis explicitly demonstrates the benefit of using wide-aperture data to produce more stable and more descriptive characterizations of scatterer anisotropy.y Andrew J. Kim.Ph.D

Earth resources: A continuing bibliography, issue 46

This bibliography lists 467 reports, articles and other documents introdcued into the NASA scientific and technical information system between April 1 and June 30, 1985. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental cultural resources geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Array Manifold Calibration for Multichannel SAR Sounders

This dissertation demonstrates airborne synthetic aperture radar (SAR) sounder array manifold calibration to improve outcomes in two-dimensional and three-dimensional image formation of ice sheet and glacier subsurfaces. The methodology relies on the creation of snapshot databases that aid in both the identification of calibration pixels as well as the validation of proposed calibration strategies. A parametric estimator of nonlinear SAR sounder manifold parameters is derived given a superset of statistically independent and spatially diverse subsets, assuming knowledge of the manifold model. Both measurements-based and computational electromagnetic modeling (CEM) approaches are pursued in obtaining a parametric representation of the manifold that enables the application of this estimator. The former relies on a principal components based characterization of SAR sounder manifolds. By incorporating a subspace clustering technique to identify pixels with a single dominant source, the algorithm circumvents an assumption of single source observations that underlies the formulation of nonparametric methods and traditionally limits the applicability of these techniques to the SAR sounder problem. Three manifolds are estimated and tested against a nominal manifold model in angle estimation and tomography. Measured manifolds on average reduce angle estimation error by a factor of 4.8 and lower vertical elevation uncertainty of SAR sounder derived digital elevation models by a factor of 3.7. Application of the measured manifolds in angle estimation produces 3-D images with more focused scattering signatures and higher intensity pixels that improve automated surface extraction outcomes. Measured manifolds are studied against Method of Moments predictions of the array's response to plane wave excitation obtained with a detailed model of the sounder's array that includes the airborne platform and fairing housing. CEM manifolds reduce angle estimation uncertainty off nadir on average by a factor of 3 when applied to measurements, providing initial confirmation of the utility of the CEM model in predicting angle estimation performance of the sounder's airborne arrays. The research findings of this dissertation indicate that SAR sounder manifold calibration will significantly increase the scientific value of legacy ice sheet and glacier sounding data sets and lead to optimized designs of future remote sensing instrumentation for surveying the cryosphere

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

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

A laboratory investigation into microwave backscattering from sea ice

The sources of scattering of artificial sea ice were determined, backscatter measurements semi-quantitatively were compared with theoretical predictions, and inexpensive polarimetric radars were developed for sea ice backscatter studies. A brief review of the dielectric properties of sea ice and of commonly used surface and volume scattering theories is presented. A description is provided of the backscatter measurements performed and experimental techniques used. The development of inexpensive short-range polarimetric radars is discussed. The steps taken to add polarimetric capability to a simple FM-W radar are considered as are sample polarimetric phase measurements of the radar. Ice surface characterization data and techniques are discussed, including computation of surface rms height and correlation length and air bubble distribution statistics. A method is also presented of estimating the standard deviation of rms height and correlation length for cases of few data points. Comparisons were made of backscatter measurements and theory. It was determined that backscatter from an extremely smooth saline ice surface at C band cannot be attributed only to surface scatter. It was found that snow cover had a significant influence on backscatter from extremely smooth saline ice at C band