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At least 217 records · Page 12

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NASA NTRS1997

Biweekly Maps of Wind Stress for the North Pacific from the ERS-1 Scatterometer

The European Remote-sensing Satellite (ERS-1) was launched in July 1991 and contained several instruments for observing the Earth's ocean including a wind scatterometer. The scatterometer measurements were processed by the European Space Agency (ESA) and the Jet Propulsion Laboratory (JPL). JPL reprocessed (Freilich and Dunbar, 1992) the ERS-1 backscatter measurements to produced a 'value added' data set that contained the ESA wind vector as well as a set of up to four ambiguities. These ambiguities were further processed using a maximum-likelihood estimation (MLE) and a median filter to produce a 'selected vector.' This report describes a technique developed to produce time-averaged wind field estimates with their expected errors using only scatterometer wind vectors. The processing described in this report involved extracting regions of interest from the data tapes, checking the quality and creating the wind field estimate. This analysis also includes the derivation of biweekly average wind vectors over the North Pacific Ocean at a resolution of 0.50 x 0.50. This was done with an optimal average algorithm temporally and an over-determined biharmonic spline spatially. There have been other attempts at creating gridded wind files from ERS-1 winds, e.g., kriging techniques (Bentamy et al., 1996) and successive corrections schemes (Tang and Liu, 1996). There are several inherent problems with the ERS-1 scatterometer. Since this is a multidisciplinary mission, the satellite is flown in different orbits optimized for each phase of the mission. The scatterometer also shares several sub-systems with the Synthetic Aperture Radar (SAR) and cannot be operated while the SAR is in operation. The scatterometer is also a single-sided instrument and only measures backscatter along the right side of the satellite. The processing described here generates biweekly wind maps during the wktwo years analysis period regardless of the satellite orbit or missing data.

SYNTHETIC APERTURE RADAR↗

NASA NTRS2010

Spotlight-Mode Synthetic Aperture Radar Processing for High-Resolution Lunar Mapping

During the 2008-2009 year, the Goldstone Solar System Radar was upgraded to support radar mapping of the lunar poles at 4 m resolution. The finer resolution of the new system and the accompanying migration through resolution cells called for spotlight, rather than delay-Doppler, imaging techniques. A new pre-processing system supports fast-time Doppler removal and motion compensation to a point. Two spotlight imaging techniques which compensate for phase errors due to i) out of focus-plane motion of the radar and ii) local topography, have been implemented and tested. One is based on the polar format algorithm followed by a unique autofocus technique, the other is a full bistatic time-domain backprojection technique. The processing system yields imagery of the specified resolution. Products enabled by this new system include topographic mapping through radar interferometry, and change detection techniques (amplitude and coherent change) for geolocation of the NASA LCROSS mission impact site.

SAR↗

DOE OSTI2026

VoroClust: Scalable Clustering for Remote Sensing

Although supervised machine learning provides a powerful framework for image classification and segmentation, it requires comprehensive consistent datasets, which are not available for many remote-sensing applications. Remote-sensing datasets are expensive to collect, and each is acquired under different environmental conditions or with significant variations in system operating parameters. Unsupervised clustering algorithms analyze the structure of each dataset independently, rather than drawing on similarities with existing “training” examples, and are thus well suited for practical remote-sensing applications. We introduce VoroClust, a fast density-based unsupervised clustering algorithm applicable to high-resolution and high-dimensional data. VoroClust runs as fast as distance-based clustering methods, while capturing complex regional geometries at least as well as current-density-based methods. It uses a data-centered sphere cover to reduce computational demands, while still capturing data topology. It then propagates clusters outward from local peaks in density. We show that VoroClust provides fast state-of-the-art clustering for both high-resolution polarimetric synthetic aperture radar and high-dimensional hyperspectral imaging datasets.

42 ENGINEERING↗

NASA NTRS1993

EOS SAR: A new approach

Viewgraphs on Earth Observing System (EOS) Synthetic Aperture Radar (SAR) are presented. The goal of the EOS is to develop the modeling and observational capabilities to predict and/or monitor atmospheric, terrestrial, and oceanic processes that are either causing global change or resulting from global change. The EOS SAR goal is to provide important geophysical products to the EOS data set to improve our understanding of the state and functioning of the Earth system. The EOS SAR strategy is to define the instrument requirements based on required input to geophysical algorithms, to provide the processing capability and algorithms to generate such products on the required spatial (global) and temporal (3-5 days) scales, and to provide the spaceborne instrumentation with international partnerships.

Way, Jobea↗

NASA NTRS1982

Geometric and rediametric distortion in spaceborne SAR imagery

Distortions inherent on synthetic aperture radio (SAR) imagery and the development to date of unsupervised postprocessing rectification techniques are described. The geometric distortion can be divided into two categories: (1) distortion derived from the radar viewing geometry, this includes such effects as ground range nonlinearities, radar foreshortening and radar layover; (2) distortion introduced during the data processing, these distortions result from approximations made during the correlation such as in estimation of the target phase history, or compensation for the earth rotation. The processor induced distortions depends on the specific correlation algorithm used for image formation. The effects are addressed on the image product resulting from assumptions during the processing and it specifically considers distortions inherent in digital imagery produced by the digital image processor.

Curlander, J. C.↗

NASA NTRS1992

Multi-frequency multi-polarization processing for spaceborne SAR

The Shuttle Imaging Radar-C (SIR-C) is the third in a series of space shuttle based synthetic aperture radars (SAR) sponsored by the National Aeronautics and Space Administration (NASA). The SIR-C ground data processing system is to process the playbacked SAR signal data into a variety of data products for distribution to the science community. An overview of the end-to-end ground data processing system with emphasis on the unique characteristics involved in the system design is presented. Included in the discussion are science requirements, radar system specifications, input data format specifications, system operations design, data products design, processing algorithm design, hardware architecture design, and software design.

Curlander, John C.↗

NASA NTRS2021

Soil Moisture Active/Passive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration Revisit: Approach and Performance

The soil moisture active passive (SMAP) microwave radiometer is a fully-polarimetric L -band radiometer flown on the SMAP satellite in a 6 AM /6 PM sun-synchronous orbit at 685-km altitude. After the SMAP L1B_TB data product version 4 was released in 2018, the radiometer has undergone further calibration and validation. The goal is to reduce the difference between antenna temperature of ascending and descending orbits during the eclipse, and to reduce the dips in the calibration drift over the cold sky (CS) during the eclipse seasons in 2017 and 2018. The postlaunch calibration algorithm has been revisited by retrieving all of the calibration parameters simultaneously with two different options for the hot calibration source (the global ocean, or the radiometer internal reference load). The performance of the two options are compared here. The option with the radiometer internal reference load has been chosen by the SMAP science team for data release version 5. In addition, a correction offset is applied to the input signal to account for offsets during the early-mission stages with the SMAP synthetic aperture radar transmitter operating alongside the radiometer.

calibration↗

NASA NTRS1992

Performance of the ice motion tracker at the Alaska SAR facility

An ice motion tracker has been implemented as part of the Ice/Ocean Geophysical Processor System (GPS) at the Alaska Synthetic Aperture Radar (SAR) Facility. The motion tracker operates in an unsupervised mode and utilizes a combination of feature-based and area-based matching to construct the displacement field from time-separated SAR imagery. The tracker is used to generate routine motion products for investigations of the kinematics and dynamics of sea ice in the polar regions. A number of filters for elimination of outliers and incorrect matches have been implemented to maintain the quality of the motion vector product. Preliminary evaluation of the tracking algorithm with European Space Agency Remote Sensing Satellite (ERS-1) data indicate that these requirements are satisfied. The performance and shortcomings of the motion tracker are discussed.

Kwok, Ronald↗

NASA NTRS1993

Segmentation Of Multifrequency, Multilook SAR Data

Segmentation of multifrequency, multilook synthetic-aperture radar (SAR) image intensity data into regions, within each of which backscattering characteristics of target scene considered homogeneous, enhanced by use of two statistical models. One represents statistics of multifrequency, multilook speckled intensities of SAR picture elements; other represents statistics of labels applied to regions into which picture elements grouped. Each region represents different type of terrain, terrain cover, or other surface; e.g., forest, agricultural land, sea ice, or water. Segmentation of image into regions of neighboring picture elements accomplished by method similar to that described in "Algorithms For Segmentation Of Complex-Amplitude SAR Data" (NPO-18524).

Rignot, Eric J.↗

NASA NTRS1991

Classification of multifrequency multilook synthetic aperture radar data

A technique for segmentation of multifrequency multilook intensity synthetic aperture radar (SAR) data into regions of homogeneous and similar backscatter characteristics is presented. Two statistical models, one for the multifrequency multilook SAR intensities and the other for the distribution of the region labels, are combined to obtain the a posteriori probability distribution function of the region labels given the multifrequency speckled intensities. As the maximization of the posterior distribution is computationally intensive, a suboptimal technique for region labeling is proposed. Several examples using both simulated and real multifrequency multilook imagery are given to illustrate the performance of the algorithm.

Rignot, Eric↗

NASA NTRS1992

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

Ranson, K. J.↗

NASA NTRS1981

Resolution requirements for a soil moisture imaging radar

Image simulation techniques were employed to establish the relationship between spatial resolution and the accuracy of soil moisture estimated by an imaging radar. A spaceborne synthetic aperture radar at an orbital altitude of 600 km, operating at 4.5 GHz with HH polarization configuration and covering a ground swath width of 143 km corresponding to an angle of incidence range extending between 7-22 degrees relative to the vertical, provided the images simulated by a 17.7 km x 19.3 km test site. The role of resolution was evaluated by simulating various sets of images with resolutions ranging from 20 m x 20 m to 1 km x 1 km. Each simulated image was subjected to a soil moisture prediction algorithm whose input is limited to the image intensity level. Results show that the 1 km x 1 km resolution provides the best prediction accuracy for most soil moisture distributions except for drought-like conditions for which the 100 m x 100 m resolution is found to be preferred. In general it was found that the soil moisture of about 90% of the pixels is predicted with an error of + or - 20% of field capacity or less.

Dobson, C.↗

NASA NTRS2008

Wavenumber Domain Focusing of Squinted SAR Data with a Curved Orbit Geometry

Synthetic Aperture Radar systems provide raw data that need focusing to achieve full-resolution imaging. Current SAR applications, including interferometry, require accurate, phase-preserving, and precisely co-registered coherent images over large ground swaths with the highest achievable resolution. In addition to these challenges, stripmap SAR data may be acquired with an off-broadside (squinted) geometry, either by design or through platform motion. The precise batch focusing of these large aperture and wide bandwidth data sets is known to require a 2D frequency processing approach. The standard wave domain focusing algorithm, however, is only exact for data acquired on a rectilinear trajectory. We investigate a generalization of the standard omega-k focusing formulation that allows curved data acquisition tracks. The new formulation can be used in conjunction with a known extension for conical, squinted imaging grids. The approximations necessary to allow the generalized geometry are analyzed to determine the range of applicability of the proposed algorithm. The theory is validated using data simulated with parameters similar to the UAVSAR L-band SAR system.

curved orbit geometry↗

NASA NTRS1995

Evaluating the Type and State of Alaska Taiga Forests with Imaging Radar for Use in Ecosystem Models

Changes in the seasonal CO2 flux of the boreal forests may result from increased atmospheric CO2 concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO2 flux and its seasonal amplitude based on meteorological data, are required. In this paper we address the use of synthetic aperture radar (SAR) to map fores type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO2 flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO2 flux. CO2 flux maps are generated, from which areal estimates of CO2 flux are derived.

Alaska↗

NASA NTRS1996

Measurements of Ocean Features With AIRSAR

Here we discuss an indirect approach for measuring ocean features from synthetic aperture radar (SAR) imagery. The approach is based on the refraction of swell that can be seen in the SAR imagery. Locally, swell refraction is due only to changes in bathymetry and surface current shear and it is easy to separate these two effects. It has been shown that linear energetic shears can be detected and measured from high resolution images of the ocean. A simple approach to measuring surface velocity and shear is to divide the imagery into smaller segments where the shear in each segment is approximately linear. The known linear algorithm would then be applied to each segment and the velocity/shear distribution can then be determined by assembling the segments with linear shear into an estimate of the actual shear/velocity distribution.

Sheres, David↗

NASA NTRS1990

Magellan radar to reveal secrets of enshrouded Venus

Imaging Venus with a synthetic aperture radar (SAR) with 70 percent global coverage at 1-km optical line-pair resolution to provide a detailed global characterization of the volcanic land-forms on Venus by an integration of image data with altimetry is discussed. The Magellan radar system uses navigation predictions to preset the radar data collection parameters. The data are collected in such a way as to preserve the Doppler signature of surface elements and later they are transmitted to the earth for processing into high-resolution radar images. To maintain high accuracy, a complex on-board filter algorithm allows the altitude control logic to respond only to a narrow range of expected photon intensity levels and only to signals that occur within a small predicted interval of time. Each mapping pass images a swath of the planet that varies in width from 20 to 25 km. Since the orbital plane of the spacecraft remains fixed in the inertial space, the slow rotation of Venus continually brings new areas into view of the spacecraft.

Saunders, R. Stephen↗

NASA NTRS1990

Synthetic aperture radar observations of the Greenland ice sheet

Results of preliminary analyses of aircraft polarimetric SAR data acquired over the Greenland Ice Sheet are presented. Data were collected in August 1989 by the Jet Propulsion Laboratory (JPL) multifrequency, polarimetric SAR using the NASA DC-8 aircraft over southern Greenland. Data of this kind are the first to be acquired over an ice sheet. They are complementary to the limited coverage provided by the SEASAT satellite SAR in 1978, and more recent aircraft X-band SAR image coverage. Frequency and polarization dependencies observed in the P-, L-, and C-band image products are attributed to large-scale variations in the snow and ice surface characteristics. At this time of year, during the ablation season, ice topography exerts a strong influence upon drainage and other hydrological features on the ice sheet surface. Systematic trends in backscatter strength observed across regions of changing snow facies are suggestive of a capability to map areas of snow wetness. Trends observed at C-band indicate that algorithms could possibly be developed which have the ability to delineate areas of significant melt.

Jezek, K.↗

NASA NTRS2012

I-FORCAST: Rapid Flight Planning Tool

I-FORCAST (Instrument - Field of Regard Coverage Analysis and Simulation Tool) is a flight planning tool specifically designed for quickly verifying the feasibility and estimating the cost of airborne remote sensing campaigns (see figure). Flights are simulated by being broken into three predefined routing algorithms as necessary: mapping in a snaking pattern, mapping the area around a point target (like a volcano) with a star pattern, and mapping the area between a list of points. The tool has been used to plan missions for radar, lidar, and in-situ atmospheric measuring instruments for a variety of aircraft. It has also been used for global and regional scale campaigns and automatically includes landings when refueling is required. The software has been compared to the flight times of known commercial aircraft route travel times, as well as a UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) campaign, and was within 15% of the actual flight time. Most of the discrepancy is due to non-optimal flight paths taken by actual aircraft to avoid restricted airspace and used to follow landing and take-off corridors.

Oaida, Bogdan↗