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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Radiometric correction of SAR images of varying terrain heights

The advantages and disadvantages of three different approaches to solving the problem of the radiometric correction of synthetic aperture radar (SAR) images of varying terrain heights are presented. The first approach involves registration of a digital elevation model (DEM) of the terrain to the image, determination of the local elevation and incidence angles, and appropriate radiometric correction. The second approach uses a DEM generated from interferometric SAR data to derive the elevation and incidence angle maps. In the third approach, a monopulse technique is employed to determine the elevation angle only. The relative errors in radiometric correction between these approaches are assessed. Calibration errors are estimated using corner reflectors deployed within some of the scenes imaged by the Jet Propulsion Laboratory airborne SAR (JPL AIRSAR).

Freeman, A.↗
NASA NTRS1984

Tracking ocean wave spectrum from SAR images

An end to end algorithm for recovery of ocean wave spectral peaks from Synthetic Aperture Radar (SAR) images is described. Current approaches allow precisions of 1 percent in wave number, and 0.6 deg in direction.

Goldfinger, A. D.↗
NASA NTRS1991

Automated extraction of pressure ridges from SAR images of sea ice - Comparison with surface truth

The authors estimate the characteristics of ridges and leads in sea ice from SAR (synthetic aperture radar) images. Such estimates are based on the hypothesis that bright filamentary features in SAR sea ice images correspond with pressure ridges. A data set collected in the Greenland Sea in 1987 allows this hypothesis to be evaluated for X-band SAR images. A preliminary analysis of data collected from SAR images and ice elevation (from a laser altimeter) is presented. It is found that SAR image brightness and ice elevation are clearly related. However, the correlation, using the data and techniques applied, is not strong.

Vesecky, J. F.↗
NASA NTRS1993

A new clustering algorithm applicable to multispectral and polarimetric SAR images

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

Wong, Yiu-Fai↗
NASA NTRS1991

Improved Radiometric Correction For SAR Images

Correction algorithm reversible and applicable to both detected and complex images. Method described accounts for major effects of transmitter, antenna, receiver, and certain aspects of SAR signal processing upon calibration and provides for appropriate reversible corrections applied in processing. Applicable to both detected (amplitude-only) and complex (amplitude and phase) SAR image data and provides for optional subtraction of estimated noise floor from image.

Freeman, Anthony↗
NASA NTRS1997

Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images

This paper demonstrates the use of wavelet transforms in the tracking of sequential ice features in the ERS-1 synthetic aperture radar (SAR) imagery, especially in situations where feature correlation techniques fail to yield reasonable results. Examples include the evolution of the St. Lawrence polynya and summer sea ice change in the Beaufort Sea. For the polynya, the evolution of the region of young ice growth surrounding a polynya can be easily tracked by wavelet analysis due to the large backscatter difference between the young and old ice. Also within the polynya, a 2D fast Fourier transform (FFT) is used to identify the extent of the Langmuir circulation region, which is coincident with the wave-agitated frazil ice growth region, where the sea ice experiences its fastest growth. Therefore, the combination of wavelet and FFT analysis of SAR images provides for the large-scale monitoring of different polynya features. For summer ice, previous work shows that this is the most difficult period for ice trackers due to the lack of features on the sea ice cover. The multiscale wavelet analysis shows that this method delineates the detailed floe shapes during this period, so that between consecutive images, the floe translation and rotation can be estimated.

Liu, Antony K.↗
NASA NTRS1990

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Lin, Qian↗
DOE OSTI2021

Sensitivity of back‐projection algorithm (BPA) synthetic aperture radar (SAR) image formation to initial position, velocity, and attitude navigation errors

Abstract The Back‐Projection Algorithm (BPA) is a time‐domain‐matched filtering technique to form synthetic aperture radar (SAR) images. To produce high‐quality BPA images, precise navigation data for the radar platform must be known. Errors in position, velocity, or attitude result in improperly formed images that are corrupted by shifting and blurring. The contribution of this paper is the development of analytical expressions that characterise the relationship between navigation errors and image formation errors from an inertial navigation point of view, where trajectory estimation errors in position, velocity, and attitude propagate through time and cause compounding errors in the vehicle state vector. These analytical expressions are verified via simulated image formation and real‐data image formation.

Lindstrom, Colton↗
NASA NTRS1985

Lithologic mapping in a sedimentary environment using multipolarization SAR images

Multipolarization Synthetic Aperture Radar (SAR) data from the NASA/JPL aircraft SAR were used in conjunction with LANDSAT Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and Airborne Imaging Spectrometer (AIS) data as part of a three-year research program to evaluate the utility of remote sensing measurements for analysis of sedimentary basins. The purpose of this research effort is to construct stratigraphic columns, map variations in the lithology, geometry, and structure of sedimentary rocks in the Wind River/Bighorn Basin area, Wyoming, and to integrate remote sensing data with conventional rain models of basin formation and evolution.

Evans, D. L.↗
NASA NTRS1992

Circular and linear polarization inverse SAR imaging of simple deterministic targets and statistically known randomly rough surfaces using constant and varying illumination

In order to study mechanisms of scattering and their relative contributions to synthetic aperture radar (SAR) and inverse SAR images, a special measurement facility has been constructed. It can be used to generate images in which the target is illuminated from a constant direction as the receiver is rotated in azimuth, and the target is illuminated from various directions as the receiver is rotated in azimuth. The imaging system performance is discussed, and images obtained using both approaches are compared, for a variety of simple targets and statistically known randomly rough surfaces.

Bredow, J. W.↗
NASA NTRS1988

System Turns SAR Images Into Maps

Postprocessing system for synthetic-aperture radar (SAR) transforms raw images from natural rotated and distorted SAR reference frame into geocoded images. Images automatically corrected to remove slant-range nonlinearities and Doppler skew. Produces multiple-frame mosaics for large-scale mapping. Does not require tedious manual registration of representative "tie" points in raw SAR imagery with known locations on Earth.

Curlander, J. C.↗
NASA NTRS1992

An analysis of the focusing performance of Magellan SAR image data

Synthetic aperture radar (SAR) focusing can be achieved either based on accurate ephemeris data or on an autofocusing process. For the Magellan project, such a decision must be made in the early phase of Magellan SAR system design. The analysis of the emphemeris requirement is complicated. The analysis given by the author leads to the conclusion that empheris data obtained from the Magellan navigation system provide sufficient accuracy to meet the Magellan image resolution requirement.

Jin, Michael Y.↗
NASA NTRS1992

Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

Vesecky, J. F.↗
NASA NTRS1993

A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for this particular problem are that the method must be reasonably robust and fast. Unlike most geological features, the small volcanoes of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include (1) a circular planimetric outline, (2) known diameter frequency distribution from preliminary studies, (3) a limited number of basic morphological shapes, and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Burl, M. C.↗
NASA NTRS1991

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

Mcconnell, Ross↗
NASA NTRS1982

SAR imaging - Seeing the unseen

The functional abilities and operations of synthetic aperture radar (SAR) are described. SAR employs long wavelength radio waves in bursts, imaging a target by 'listening' to the small frequency changes that result from the Doppler shift due to the relative motion of the imaging craft and the motions of the target. The time delay of the signal return allows a determination of the location of the target, leading to the build up of a two-dimensional image. The uses of both Doppler shifts and time delay enable detailed imagery which is independent of distance. The synthetic aperture part of the name of SAR derives from the beaming of multiple pulses, which result in a picture that is effectively the same as using a large antenna. Mechanisms contributing to the fineness of SAR images are outlined.

Kobrick, M.↗
NASA NTRS1990

Reducing Speckle In One-Look SAR Images

Local-adaptive-filter algorithm incorporated into digital processing of synthetic-aperture-radar (SAR) echo data to reduce speckle in resulting imagery. Involves use of image statistics in vicinity of each picture element, in conjunction with original intensity of element, to estimate brightness more nearly proportional to true radar reflectance of corresponding target. Increases ratio of signal to speckle noise without substantial degradation of resolution common to multilook SAR images. Adapts to local variations of statistics within scene, preserving subtle details. Computationally simple. Lends itself to parallel processing of different segments of image, making possible increased throughput.

Nathan, K. S.↗