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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Classification Of Terrain In Polarimetric SAR Images

Two algorithms processing polarimetric synthetic-aperture-radar data found effective in assigning various parts of SAR images to classes representing different types of terrain. Partially automate interpretation of SAR imagery, reducing amount of photointerpretation needed and putting whole interpretation process on more quantitative and systematic basis. First algorithm implements Bayesian classification scheme "supervised" by use of training data. Second algorithm implements classification procedure unsupervised.

Van Zyl, Jakob J.↗
NASA NTRS1980

A software-based system which produces SEASAT SAR imagery

A digital processing algorithm and its associated system design for producing images from SEASAT synthetic aperture radar (SAR) data is described. The proposed system uses the fast Fourier transform approach to perform the two dimensional correlation process. The range migration problem can be alleviated by approximating the locus of echoes from a point target by several linear segments. Data corresponding to each segment are correlated separately and the results are coherently summed to produce full resolution images. This processing approach exhibits high computation efficiency and simple processing control functions. It is particularly attractive for software implementation based on general purpose computers. Results of this implementation and examples of digitally correlated SEASAT SAR imagery are discussed.

Wu, C.↗
NASA NTRS1989

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Jin, Michael Y.↗
NASA NTRS1984

Utilization of spaceborne SAR data for mapping

Recent developments in automated processing of digital SEASAT SAR imagery have made feasible the generation of large-scale high-resolution maps. Standard preprocessing of raw data into digital images results in geometrically distorted imagery. Computer algorithms have been developed for unsupervised pixel location, geometric rectification, and mosaicking of multiple-image frames without ground control points. These algorithms utilize knowledge of the spacecraft trajectory data, the imaging geometry, and the coherent properties of the sensor to generate the required processing parameters. This paper discusses the advantages as well as the inherent limitations of this technique, analyzes the associated errors, and presents results using SEASAT SAR imagery. Also discussed are the results of the recent shuttle imaging radar (SIR-A) experiment as well as a follow-on experiment (SIR-B) planned for 1984.

Curlander, J. C.↗
NASA NTRS1981

Synthetic aperture radar and digital processing: An introduction

A tutorial on synthetic aperture radar (SAR) is presented with emphasis on digital data collection and processing. Background information on waveform frequency and phase notation, mixing, Q conversion, sampling and cross correlation operations is included for clarity. The fate of a SAR signal from transmission to processed image is traced in detail, using the model of a single bright point target against a dark background. Some of the principal problems connected with SAR processing are also discussed.

Dicenzo, A.↗
NASA NTRS1982

Geometric registration and rectification of spaceborne SAR imagery

This paper describes the development of automated location and geometric rectification techniques for digitally processed synthetic aperture radar (SAR) imagery. A software package has been developed that is capable of determining the absolute location of an image pixel to within 60 m using only the spacecraft ephemeris data and the characteristics of the SAR data collection and processing system. Based on this location capability algorithms have been developed that geometrically rectify the imagery, register it to a common coordinate system and mosaic multiple frames to form extended digital SAR maps. These algorithms have been optimized using parallel processing techniques to minimize the operating time. Test results are given using Seasat SAR data.

Curlander, J. C.↗
NASA NTRS2017

NISAR L-SAR Digital Electronics Subsystem - A Multichannel Distributed Processing System with Synchronous Timing Control for Digital Beam Forming and Multiple Echo Tracking

The NASA-ISRO Synthetic Aperture Radar (NISAR) L-band SAR instrument employs multiple digital channels to optimize resolution while keeping a large swath on a single pass. High-speed digitization with fine synchronization and digital beam forming are necessary in order to facilitate this new technique called SweepSAR. An architecture employing multiple FPGA based digital signal processors has been conceived to facilitate digital calibration on an individual channel basis as well as digital signal processing to optimize the receive signal. On-board processing and data compression has been implemented to reduce the volume of data in order to satisfy the operational requirements of near global coverage for the desired science targets. A novel command and timing architecture was developed to manage this complex system while providing detailed control of individual channel receive window timing required for digital beam forming. The NISAR L-band Digital Electronics Subsystem is the combination of the hardware, firmware and software components architected and implemented to operate this radar and return the desired quantity and quality of data for the science community.

Chuang, Chung-Lun↗
NASA NTRS1983

An improvement in SAR image interpretability provided by post-correlation signal processing

A presentation on the basis of subjective analysis of computer-generated SAR imagery depicts the improvement in interpretability obtained by post-correlation signal processing. A parametric study was conducted to determine the improvement in interpretability obtained by the application of signal weighting functions on the post-processed returns. The results suggest that a marked improvement in interpretability results from symmetrizing the exponential distribution of the fading signal. Preliminary analysis indicates that signal weighting improves the contrast ratio between the mean value of adjacent homogeneous regions in a SAR scene.

Matthews, N. D.↗
NASA NTRS1990

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗
NASA NTRS1992

Acousto-Optical/Electronic Processor For SAR

Lightweight, compact, low-power apparatus processes synthetic-aperture-radar (SAR) returns in real time, providing imagery aboard moving aircraft or spacecraft platform. Processor includes optical and electronic subsystems that, together, resolve range and azimuth coordinates of radar targets by combination of spatial and temporal integrations.

Bicknell, T. J.↗
NASA NTRS2006

Ground processing of Cassini RADAR imagery of Titan

This paper describes the ground processing of Cassini SAR data. We focus upon the unusual features of the data and how these features impact the processing. We exhibit a data dependent mechanism we have implemented for eliminating artifacts due to attitude and ephemeris knowledge error. Finally we describe how we trade-off SAR performance vs. area of coverage when we design our spacecraft pointing profiles.

remote sensing↗
NASA NTRS1986

Orbit determination using synthetic aperture radar

The use of synthetic aperture radar (SAR) images to estimate orbital parameters is studied. The SAR image formation process which requires the ability to repeatedly transmit identical signals and accurately sense the return echoes from a region of terrain is described. The orbit determination capabilities of the SAR system's observables are investigated. Five SAR observations were collected from a simulated shuttle orbit, which was circular with a latitude of 220 km and along-track velocity of 7.7 km/sec, to obtain along-track and line-of-sight direction position measurements; the simulation reveals that only three SAR observations were required to determine the position of the spacecraft to within 100 m. A prototype SAR orbit determination system was developed. The system consists of a VAX 11/780 time-shared computer, a frame buffer, topographic maps, and software for line-pixel location of an object within a SAR image and for orbit determination. The prototype is applied to the processing of a single short arc of Shuttle Imaging-Radar-B (SIR-B) data. It is observed that the SAR data is useful as orbit determination or tracking data; however, the low SNRs in the SIR-B data made feature identification difficult.

Taber, W. L.↗
NASA NTRS1989

Ice classification algorithm development and verification for the Alaska SAR Facility using aircraft imagery

The Alaska SAR Facility (ASF) at the University of Alaska, Fairbanks is a NASA program designed to receive, process, and archive SAR data from ERS-1 and to support investigations that will use this regional data. As part of ASF, specialized subsystems and algorithms to produce certain geophysical products from the SAR data are under development. Of particular interest are ice motion, ice classification, and ice concentration. This work focuses on the algorithm under development for ice classification, and the verification of the algorithm using C-band aircraft SAR imagery recently acquired over the Alaskan arctic.

Holt, Benjamin↗
NASA NTRS1993

Airborne synthetic aperture radar observations and simulations for waves in ice

The Canada Centre for Remote Sensing CV-580 aircraft collected C-band SAR data over the marginal ice zone off the east coast of Newfoundland during the Labrador Ice Margin Experiment (LIMEX) in March 1989. One component of the LIMEX '89 program was the study of ocean waves penetrating the marginal ice zone. We consider nearly coincidental observations of waves in ice by airborne SAR and wave-induced ice motion measurements. We explain the wave patterns observed in the SAR imagery, and the corresponding SAR image spectra, in terms of SAR wave imaging models. These include the well-known tilt cross-section modulation, linear, quasi-linear, and nonlinear velocity bunching forward mapping models (FMMs), and the assertion that the concept of coherence time limitation applies differently to the cases of waves in ice and open water. We modify the concept of the scene coherence time to include two parts: first, a decorrelation time deduced from the inherent azimuth cutoff in the nonlinear velocity bunching FMM; and second, the intrinsic scene coherence time which is a measure of the time scale over which an open water Bragg scattering patch retains its phase structure. Either of these coherence time scales could dominate the SAR image formation process, depending upon the environmental conditions (the wave spectrum and the wind speed, for example). Observed SAR image spectra and forward mapped ice motion package spectra are favorably compared.

Vachon, Paris W.↗
NASA NTRS1987

Automated rectification and geocoding of SAR imagery

An automated post-processing system has been developed for rectification and geocoding of SAR (Synthetic Aperture Radar) imagery. The system uses as input a raw uncorrected image from the operational SAR correlator, and produces as a standard output a rectified and geocoded product. The accurate geolocation of SAR image pixels is provided by a spatial transformation model which maps the slant range-azimuth SAR image pixels into their location on a prespecified map grid. This model predicts the geodetic location of each pixel by utilizing: the sensor platform position; a geoid model; the parameters of the data collection system and the processing parameters used in the SAR correlator. Based on their geodetic locations, the pixels are mapped by using the desired cartographic projection equations. This rectification and geocoding technique has been tested with Seasat and SIR-B images. The test results demonstrate absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 percent relative to local variations from the assumed geoid.

Kwok, R.↗
NASA NTRS1982

Computer simulation of a space SAR using a range-sequential processor for soil moisture mapping

The ability of a spaceborne synthetic aperture radar (SAR) to detect soil moisture was evaluated by means of a computer simulation technique. The computer simulation package includes coherent processing of the SAR data using a range-sequential processor, which can be set up through hardware implementations, thereby reducing the amount of telemetry involved. With such a processing approach, it is possible to monitor the earth's surface on a continuous basis, since data storage requirements can be easily met through the use of currently available technology. The Development of the simulation package is described, followed by an examination of the application of the technique to actual environments. The results indicate that in estimating soil moisture content with a four-look processor, the difference between the assumed and estimated values of soil moisture is within + or - 20% of field capacity for 62% of the pixels for agricultural terrain and for 53% of the pixels for hilly terrain. The estimation accuracy for soil moisture may be improved by reducing the effect of fading through non-coherent averaging.

Fujita, M.↗
NASA NTRS1981

Further SEASAT SAR coastal ocean wave analysis

Analysis techniques used to exploit SEASAT synthetic aperture radar (SAR) data of gravity waves are discussed and the SEASAT SAR's ability to monitor large scale variations in gravity wave fields in both deep and shallow water is evaluated. The SAR analysis techniques investigated included motion compensation adjustments and the semicausal model for spectral analysis of SAR wave data. It was determined that spectra generated from fast Fourier transform analysis (FFT) of SAR wave data were not significantly altered when either range telerotation adjustments or azimuth focus shifts were used during processing of the SAR signal histories, indicating that SEASAT imagery of gravity waves is not significantly improved or degraded by motion compensation adjustments. Evaluation of the semicausal (SC) model using SEASAT SAR data from Rev. 974 indicates that the SC spectral estimates were not significantly better than the FFT results.

Kasischke, E. S.↗
NASA NTRS1995

ScanSAR and Precision Processor Implementation at the Alaska SAR Facility

This paper summarizes the algorithm and hardware selection phases of the ScanSAR Processor (SSP) and Precision Processor (PP) implementation task for the Alaska SAR Facility (ASF). The SSP is being designed to specifically process RADARSAT ScanSAR mode SAR data while the PP is being designed to produce high precision image products from continuous mode SAR data from RADARSAT as well as ERS-1,2 and JERS-1. This paper describes the algorithms selected for the SSP and the PP; and reports on the hardware selection process in arriving at the target computing platform for these processors.

SanSAR Alaska SAR Facility↗