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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 91 records · Page 5
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NASA NTRS1991

A finite mixtures algorithm for finding classes in images

The authors describe an algorithm for estimating the proportions of classes in a SAR (synthetic aperture radar) image without any user interaction. The method assumes that the image is a mixture of a known number of different pixel types. A maximum likelihood estimate of the parameters of the resulting mixture distribution is then used to find the proportions for the various classes. The technique was successfully applied to aircraft SAR images of sea ice. Computer simulations were used to determine the relative errors of the technique. The technique performs well even with extremely noisy images.

Samadani, Ramin↗
NASA NTRS2011

Wavelet Filter Banks for Super-Resolution SAR Imaging

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Sheybani, Ehsan O.↗
NASA NTRS1983

A novel algorithm for sea surface height estimation using complex SAR data

A method of extracting sea height information from Synthetic Aperture Radar (SAR) complex data was studied. A fundamental SAR ocean imaging model for gravity waves showed that information about the long wave is present in the SAR complex data, especially its phase. Phase demodulation algorithm followed by linear regression and filtering was employed. Only the latter two steps incorporated a priori information that might be available. A relatively simplified simulation indicated that the finite bandwidth of the SAR system imposed the apparently most serious limitation. A preliminary application to SEASAT-SAR complex imagery was encouraging. Information about the long wave, if incorporated into a more sophisticated phase demodulation structure, i.e., at an earlier point in the algorithm, could conceivably mitigate this bandwidth limitation.

Harger, R. O.↗
NASA NTRS2009

Digital Beamforming Scatterometer

This paper discusses scatterometer measurements collected with multi-mode Digital Beamforming Synthetic Aperture Radar (DBSAR) during the SMAP-VEX 2008 campaign. The 2008 SMAP Validation Experiment was conducted to address a number of specific questions related to the soil moisture retrieval algorithms. SMAP-VEX 2008 consisted on a series of aircraft-based.flights conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. Several other instruments participated in the campaign including the Passive Active L-Band System (PALS), the Marshall Airborne Polarimetric Imaging Radiometer (MAPIR), and the Global Positioning System Reflectometer (GPSR). This campaign was the first SMAP Validation Experiment. DBSAR is a multimode radar system developed at NASA/Goddard Space Flight Center that combines state-of-the-art radar technologies, on-board processing, and advances in signal processing techniques in order to enable new remote sensing capabilities applicable to Earth science and planetary applications [l]. The instrument can be configured to operate in scatterometer, Synthetic Aperture Radar (SAR), or altimeter mode. The system builds upon the L-band Imaging Scatterometer (LIS) developed as part of the RadSTAR program. The radar is a phased array system designed to fly on the NASA P3 aircraft. The instrument consists of a programmable waveform generator, eight transmit/receive (T/R) channels, a microstrip antenna, and a reconfigurable data acquisition and processor system. Each transmit channel incorporates a digital attenuator, and digital phase shifter that enables amplitude and phase modulation on transmit. The attenuators, phase shifters, and calibration switches are digitally controlled by the radar control card (RCC) on a pulse by pulse basis. The antenna is a corporate fed microstrip patch-array centered at 1.26 GHz with a 20 MHz bandwidth. Although only one feed is used with the present configuration, a provision was made for separate corporate feeds for vertical and horizontal polarization. System upgrades to dual polarization are currently under way. The DBSAR processor is a reconfigurable data acquisition and processor system capable of real-time, high-speed data processing. DBSAR uses an FPGA-based architecture to implement digitally down-conversion, in-phase and quadrature (I/Q) demodulation, and subsequent radar specific algorithms. The core of the processor board consists of an analog-to-digital (AID) section, three Altera Stratix field programmable gate arrays (FPGAs), an ARM microcontroller, several memory devices, and an Ethernet interface. The processor also interfaces with a navigation board consisting of a GPS and a MEMS gyro. The processor has been configured to operate in scatterometer, Synthetic Aperture Radar (SAR), and altimeter modes. All the modes are based on digital beamforming which is a digital process that generates the far-field beam patterns at various scan angles from voltages sampled in the antenna array. This technique allows steering the received beam and controlling its beam-width and side-lobe. Several beamforming techniques can be implemented each characterized by unique strengths and weaknesses, and each applicable to different measurement scenarios. In Scatterometer mode, the radar is capable to.generate a wide beam or scan a narrow beam on transmit, and to steer the received beam on processing while controlling its beamwidth and side-lobe level. Table I lists some important radar characteristics

Rincon, Rafael F.↗
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 NTRS1980

A digital fast correlation approach to produce SEASAT SAR imagery

This paper describes a digital processing algorithm and its associated system design for producing images from SEASAT Synthetic Aperture Radar (SAR) data. The proposed system uses the fast Fourier transform approach to perform the two-dimensional correlation process. The range migration problem, which is often a major obstacle to efficient processing, can be alleviated by approximating the locus of echoes from a point target by several linear segments. SAR data corresponding to each segment is 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 computer. Results of this implementation and examples of digitally correlated SEASAT SAR imagery are discussed

Wu, C.↗
NASA NTRS1990

Classification Of Radar Scatterers Via Polarimetric Data

Scattering mechanisms identified via polarization signatures. Algorithm automatically classifies radar-backscattering mechanisms in images produced by synthetic-aperture-radar polarimeter. Uses full polarimetric data from each picture element. These data generally expressed in terms of complex 2 by 2 scattering matrix equivalent to three independent amplitudes and three independent phases representing relationships between horizontally- and vertically-polarized components of transmitted and backscattered signals.

Van Zyl, Jakob J.↗
NASA NTRS2001

Estimation of comprehensive forest variable sets from multiparameter SAR data over a large area with diverse species

Polarimetric and multifrequency data from the NASA/JPL airborne synthetic aperture radar (AIRSAR) have been used in a multi-tier estimation algorithm to calculate a comprehensive set of forest canopy properties including branch layer moisture and thickness, trunk density, trunk water content and diameter, trunk height, and subcanapy soil moisture. The estimation algorithm takes advantage of species-specific allometric relations, and is applied to a 100Km x 100Km area in the Canadian boreal region containing many different vegetation species types. The results show very good agreement with ground measurements taken at several focused and auxiliary study sites. This paper expands on the results reported in [1] and applies the algorithm on the regional scale.

variable estimation forestry multiparameter SAR↗
NASA NTRS1996

Seasonal Characteristics of the Perennial Ice Cover of the Beaufort Sea

By definition, ice which survives the summer is classified as multiyear ice. Thus the area covered by multiyear ice during the winter should be nearly equivalent to the ice area during the previous summer's minima. This condition provides a reasonable criterion for the evaluation of ice concentration and ice type retrieval algorithms using remote-sensing data sets. From special sensor microwave imager (SSM/I) data the NASA Team algorithm estimates the multiyear, first-year, and total ice concentrations during the winter using combinations of the polarization and spectral gradient ratios. The Team algorithm provides only estimates of ice concentration in the summer. From ERS 1 synthetic aperture radar (SAR) data the remarkably stable contrast between multiyear ice and first-year ice in winter provides consistent estimates of multiyear ice concentrations. In the summer, multiyear ice concentration cannot be estimated from SAR or SSM/I data because free water on the surface effectively masks the backscatter and emissivity signature of this ice type. From SAR data a technique which takes advantage of the high backscatter of wind-roughened open water as a discrimination feature is used to estimate the total ice concentration in the summer. With a year-long (January 1992 to January 1993) data set from the Beaufort Sea we found that the multiyear ice concentration estimates from the SAR data are stable and are nearly equivalent to the ice concentration estimated at the end of the previous summer. We contrast this with the variability of the multiyear ice concentration and ice friction estimates obtained using SSM/I data. The Team algorithm produces ice concentration and multiyear ice estimates which are consistently lower than those from the SAR data. We discuss reasons for these discrepancies and the implications of the higher than previously noted multiyear ice concentrations.

Kwok, R.↗
NASA NTRS2005

On-board fault-tolerant SAR processor for spaceborne imaging radar systems

A real-time high-performance and fault-tolerant FPGA-based hardware architecture for the processing of synthetic aperture radar (SAR) images has been developed for advanced spaceborne radar imaging systems. In this paper, we present the integrated design approach, from top-level algorithm specifications, system architectures, design methodology, functional verification, performance validation, down to hardware design and implementation.

imaging Radar↗
NASA NTRS1992

Development of soil moisture retrieval algorithm for L-band SAR measurements

A study of algorithm development and testing for soil moisture retrieval for bare fields using L-band synthetic aperture radar (SAR) imagery is reported. First-order surface scattering models predict that the copolarization ratio is sensitive to soil moisture but not to surface roughness. All possible ratios of the co-polarization signals and their linear combinations are evaluated. The best sensitivity to soil moisture is achieved from measurements as predicted by the first-order surface scattering model. The effects of system noise and volume scattering of soil are evaluated. To minimize the effect of the volume scattering, an algorithm which includes both the surface and volume scattering has been developed and tested using Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) data. The results show that the estimation of soil moisture can be improved after removing the system noise and including the volume scattering effect at large incidence angles.

Shi, Jiancheng↗
NASA NTRS2022

Modeling the Errors of a Time Series Algorithm for Retrieving Soil Moisture in the NISAR Mission

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission plan to launch a SAR operating at L- and S-band with a 12-day repeat frequency. A global soil moisture product at 200 m spatial resolution derived from 200 m NISAR radar measurements is currently under development. Although several retrieval algorithms are being investigated, this paper focuses on a “time series ratio” retrieval approach. In order to understand and assess the performance of this algorithm, an error model has been developed and is reported in this paper. The model is applied to examine errors as a function of the instrument characteristics and for a given location. Initial progress in including vegetation effects and in predicting errors as a function of spatial location is also described.

NISAR↗
NASA NTRS1996

Processing Ultra Wide Band Synthetic Aperture Radar Data with Motion Detectors

Several issues makes the processing of ultra wide band (UWB) SAR data acquired from an airborne platform difficult. The character of UWB data invalidates many of the usual SAR batch processing techniques, leading to the application of wavenumber domain type processors...This paper will suggest and evaluate an algorithm which combines a wavenumber domain processing algorithm with a motion compensation procedure which enables motion compensation to be applied as a function of target range and the azimuth angle.

synthetic aperture radar sar ultra wide band sar m↗
NASA NTRS2007

Ross Sea Polynyas: Response of Ice Concentration Retrievals to Large Areas of Thin Ice

For a 3-month period between May and July of 2005, we examine the response of the Advanced Microwave Scanning Radiometer (AMSR-E) Enhanced NASA Team 2 (NT2) and AMSR-E Bootstrap (ABA) ice concentration algorithms to large areas of thin ice of the Ross Sea polynyas. Coincident Envisat Synthetic Aperture Radar (SAR) coverage of the region during this period offers a detailed look at the development of the polynyas within several hundred kilometers of the ice front. The high-resolution imagery and derived ice motion fields show bands of polynya ice, covering up to approximately 105 km(sup 2) of the Ross Sea, that are associated with wind-forced advection. In this study, ice thickness from AMSR-E 36 GHz polarization information serves as the basis for examination of the response. The quality of the thickness of newly formed sea ice (<10 cm) from AMSR-E is first assessed with thickness estimates derived from ice surface temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The effect of large areas of thin ice in lowering the ice concentration estimates from both NT2/ABA approaches is clearly demonstrated. Results show relatively robust relationships between retrieved ice concentrations and thin ice thickness estimates that differ between the two algorithms. These relationships define the approximate spatial coincidence of ice concentration and thickness isopleths. Using the 83% (ABA) and 91% (NT2) isopleths as polynya boundaries, we show that the computed coverage compares well with that using the estimated 10-cm thickness contour. The thin ice response characterized here suggests that in regions with polynyas, the retrieval results could be used to provide useful geophysical information, namely thickness and coverage.

algorithms↗
NASA NTRS1997

Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.

Comiso, Josefino C.↗
NASA NTRS1989

Segmentation of multifrequency polarimetric radar images to facilitate the inference of geophysical parameters

An unsupervised clustering algorithm is used to segment multifrequency polarimetric radar data from the NASA/JPL airborne SAR (synthetic aperture radar). Twenty-two parameters are evaluated for their discriminatory capability for each pixel of an image. A clustering analysis is then performed using different subsets of these parameters. This analysis relies on data taken as part of an intensive field experiment during the summer of 1988 in the vicinity of the Pisgah lava flow in the Mojave Desert in southern California. As part of the experiment, extensive ground truth was acquired, including dielectric constant and topography measurements. Segmentation results show good agreement with these measurements.

Burnette, C F.↗
NASA NTRS1992

More About Calibration Of Polarimetric SAR

Azimuthal symmetry is not assumed. Two sets of equations and algorithms for radiometric and polarimetric calibration of complex quadpolarization data gathered by synthetic-aperture radar (SAR) based partly on known scattering characteristics of artificial targets in scene, and partly on assumption that all other targets scatter reciprocally.

Klein, Jeffrey D.↗