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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

(abstract) Monitoring Seasonal State and Mapping Species in Alaskan Taiga Using Imaging Radar as Input to CO(sub 2) Flux Models

Changes in the seasonal CO(sub 2) flux of the boreal forests may result from increased atmospheric CO(sub 2) concentrations and associated atmospheric warming. To monitor this potential change, a combination of remote sensing information and ecophysiological models are required. In this paper we address the use of synthetic aperture radar (SAR) data to provide some of the input to the ecophysiological models: forest type, freeze/thaw state which limits the growing season for conifers, and leaf on/off state which limits the growing season for deciduous species. AIRSAR data collected in March 1988 during an early thaw event and May 1991 during spring breakup 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 and soil freeze/thaw transitions. Finally, a CO(sub 2) flux algorithm which utilizes SAR data and an ecophysiological model to estimate CO(sub 2) flux is presented. CO(sub 2) flux maps are generated from which areal estimates of CO(sub 2) flux are derived.

leaf cover boreal forests radar backscatter↗
NASA NTRS1989

Doppler centroid estimation ambiguity for synthetic aperture radars

A technique for estimation of the Doppler centroid of an SAR in the presence of large uncertainty in antenna boresight pointing is described. Also investigated is the image degradation resulting from data processing that uses an ambiguous centroid. Two approaches for resolving ambiguities in Doppler centroid estimation (DCE) are presented: the range cross-correlation technique and the multiple-PRF (pulse repetition frequency) technique. Because other design factors control the PRF selection for SAR, a generalized algorithm is derived for PRFs not containing a common divisor. An example using the SIR-C parameters illustrates that this algorithm is capable of resolving the C-band DCE ambiguities for antenna pointing uncertainties of about 2-3 deg.

Chang, C. Y.↗
NASA NTRS1996

Geocoding of AIRSAR/TOPSAR SAR Data

It has been demonstrated and recognized that radar interferometry is a promising method for the determination of digital elevation information and terrain slope from Synthetic Aperture Radar (SAR) data. An important application of Interferometric SAR (InSAR) data in areas with topographic variations is that the derived elevation and slope can be directly used for the absolute radiometric calibration of the amplitude SAR data as well as for scattering mechanisms analysis. On the other hand polarimetric SAR data has long been recognized as permitting a more complete inference of natural surfaces than a single channel radar system. In fact, imaging polarimetry provides the measurement of the amplitude and relative phase of all transmit and receive polarizations. On board the NASA DC-8 aircraft, NASA/JPL operates the multifrequency (P, L and C bands) multipolarimetric radar AIRSAR. The TOPSAR, a special mode of the AIRSAR system, is able to collect single-pass interferometric C- and/or L-band VV polarized data. A possible configuration of the AIRSAR/TOPSAR system is to acquire single-pass interferometric data at C-band VV polarization and polarimetric radar data at the two other lower frequencies. The advantage of this system configuration is to get digital topography information at the same time the radar data is collected. The digital elevation information can therefore be used to correctly calibrate the SAR data. This step is directly included in the new AIRSAR Integrated Processor. This processor uses a modification of the full motion compensation algorithm described by Madsen et al. (1993). However, the Digital Elevation Model (DEM) with the additional products such as local incidence angle map, and the SAR data are in a geometry which is not convenient, since especially DEMs must be referred to a specific cartographic reference system. Furthermore, geocoding of SAR data is important for multisensor and/or multitemporal purposes. In this paper, a procedure to geocode the new AIRSAR/TOPSAR data is presented. As an example an AIRSAR/TOPSAR image acquired in 1994 is geocoded and evaluated in terms of geometric accuracy.

Holecz, Francesco↗
NASA NTRS1994

Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth

Lack of verifiable ground truth is a common problem in remote sensing image analysis. For example, consider the synthetic aperture radar (SAR) image data of Venus obtained by the Magellan spacecraft. Planetary scientists are interested in automatically cataloging the locations of all the small volcanoes in this data set; however, the problem is very difficult and cannot be performed with perfect reliability even by human experts. Thus, training and evaluating the performance of an automatic algorithm on this data set must be handled carefully. We discuss the use of weighted free-response receiver-operating characteristics (wFROC) for evaluating detection performance when the ground truth is subjective.

Venus Magellan remote sensing image analysis autom↗
NASA NTRS1993

Analysis and Simulation for a Spotlight-Mode Aircraft SAR in Circular Flight Path

A spotlight aircraft SAR in a circular flight path can efficiently obtain an image with very high azimuth resolution or a wider azimuth viewing angle. An analysis on the spotlight SAR is made regarding the required PRF, the predicted resolution, and the computation complexity as a function of the aircraft altitude and the distance between a target and the center of the flight path projection. An efficient processing algorithm based on the exact wide beam spectrum is presented. The results of simulation indicate that the impulse responses meet the predicted resolution performance.

processing algorithm↗
NASA NTRS2021

Future SAR Imaging Systems: Goals, Plans, Challenges and Opportunities

Synthetic Aperture Radar (SAR) Earth observation data are becoming increasingly ubiquitous as new spaceborne systems become operational and their data are made available to scientists and applications users. The characteristic of active sensors like SAR to be able to observe Earth independent of weather or solar illumination, coupled with regular data acquisition, fosters reliability and encourages the investment in algorithm and product development toward a beneficial result. As SAR systems typically contain proprietary or nationally important technologies, civilian SAR systems are typically developed with a national focus, or in the case of the European Union, with the Union’s focus. As a result, when viewed from a global perspective, SAR programs can be generally viewed as independent developments, each with their own requirements, schedules, development approaches, and data policies. At the same time, these systems can be expensive, and particularly in an era of increasingly open data policies, coordination of programs could reduce redundancy in observations, increase sampling density and measurement diversity, and improve dependability of data streams in the long term. Since 2018, agency representatives from NASA, ESA, DLR, JAXA, ISRO, ASI, and CONAE have been evaluating the possibilities for programmatic and technical coordination of future SAR systems, data sharing, and scientific exploitation. In this paper, we describe the work in discovering trends and possibilities associated with flight systems, by evaluating current and future plans for SAR systems around the world, and identifying opportunities for coordination.

Zink, Manfred↗
NASA NTRS2012

The InSAR Scientific Computing Environment

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

geodetic imaging↗
NASA NTRS1984

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗
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 NTRS1981

SP mountain data analysis

An analysis of synthetic aperture radar data of SP Mountain was undertaken to demonstrate the use of digital image processing techniques to aid in geologic interpretation of SAR data. These data were collected with the ERIM X- and L-band airborne SAR using like- and cross-polarizations. The resulting signal films were used to produce computer compatible tapes, from which four-channel imagery was generated. Slant range-to-ground range and range-azimuth-scale corrections were made in order to facilitate image registration; intensity corrections were also made. Manual interpretation of the imagery showed that L-band represented the geology of the area better than X-band. Several differences between the various images were also noted. Further digital analysis of the corrected data was done for enhancement purposes. This analysis included application of an MSS differencing routine and development of a routine for removal of relief displacement. It was found that accurate registration of the SAR channels is critical to the effectiveness of the differencing routine. Use of the relief displacement algorithm on the SP Mountain data demonstrated the feasibility of the technique.

Rawson, R. F.↗
NASA NTRS1982

A statistical model for radar images of agricultural scenes

The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

Frost, V. S.↗
NASA NTRS1995

Relating Radar Backscatter to Boreal Forest Canopy Parameters

During the first intensive field campaign for the Boreal Ecosystem Atmospheric Study (BOREAS) in August of 1993, AIRSAR data were acquired over the entire BOREAS study area. On of the objectives of the AIRSAR deployment was to examine the sensitivity of the radar signal to vegetation type and biomass distribution in the boreal forest and to develop algorithms for inferring vegetation parameters. During the experiment a set of ground measurements were also made to support the AIRSAR data analysis. The dominant stands in the study area consist of black spruce, young jack pine, old jack pine, and aspen. These stands represent a wide range of biomass and canopy architectural variations which can be distinguished in SAR images.

radar backscatter↗
NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗
NASA NTRS1992

Implementation and performance of the Magellan digital correlator subsystem

The Magellan synthetic aperture radar (SAR) produces Venus surface images from data collected by the SAR carried on board the Magellan spacecraft. The core of the primary Magellan SAR processor is the digital correlator subsystem (DCS). The pipeline DSC architecture enables the Magellan primary SAR processor (PSP) to achieve real-time data processing capability. The implementation and performance of the DSC are described. Hardware (H/W) constraints that influenced the processing algorithm design are highlighted.

Chen, M.↗
NASA NTRS1993

Chirp Scaling Algorithms for SAR Processing

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

nonlinear chirp scaling.↗
NASA NTRS1992

A comparison of three SAR interference filters

Three interference filters are discussed and their ability to remove the interference while leaving target signal data is quantified. The filters are adaptive frequency-domain spike filtering; adaptive frequency-domain interference determination and masking; and interference-target correlation masking. Using Jet Propulsion Laboratory Airborne Synthetic Aperture Radar (JPL AIRSAR) data, the algorithms are applied to three data sets. The resultant compressed Stokes matrix data are compared with the normally processed interference-free image in a quantitative sense. The algorithms are evaluated by measuring the polarization signature, SNR, equivalent number of looks, and impulse response of the processed images.

Chapman, B.↗
NASA NTRS1990

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗
NASA NTRS2018

Vegetation Height Estimate in Rice Fields Using Single Polarization TanDEM-X Science Phase Data

This study presents the retrieval of rice paddy height using single polarization (single-pol) interferometric SAR (InSAR) data by means of model-based height inversion without an external DEM. A total of eight TanDEM-X (TDX) scenes were used and the TDX images were; acquired using a large cross-track baseline configuration during the TDX Science Phase (June–August 2015). A single-pol inversion approach for a flooded rice field is proposed and evaluated over the Buan test site in South Korea. A novel approach is adopted for the estimation of the ground (i.e., water level) interferometric phase within a flooded rice paddy from TDX data acquired during a period of early rice growth. It is consequently possible to apply the model-based inversion algorithm to the single-pol InSAR data. Rice height maps during the rice growth cycle presented and validated by field measurements. The results demonstrated the high performance of the inversion with a correlation coefficient of 0.78 and an RMSE of 0.10 m. The proposed methodology will be useful to monitor rice plants and to predict a gross rice yield, along with dual and fully polarimetric interferometric SAR data.

Lee, Seung-Kuk↗