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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Parametric analysis of synthetic aperture radar data acquired over truck garden vegetation

An airborne X-band SAR acquired multipolarization and multiflight pass SAR images over a truck garden vegetation area. Based on a variety of land cover and row crop direction variations, the vertical (VV) polarization data contain the highest contrast, while cross polarization contains the least. When the radar flight path is parallel to the row direction, both horizontal (HH) and VV polarization data contain very high return which masks out the specific land cover that forms the row structure. Cross polarization data are not that sensitive to row orientation. The inclusion of like and cross polarization data help delineate special surface features (e.g., row crop against non-row-oriented land cover, very-rough-surface against highly row-oriented surface).

Wu, S. T.↗
NASA NTRS1983

Analysis of Synthetic Aperture Radar data acquired over a variety of land cover

An analysis has been conducted of two-look-angle, multipolarization X-band SAR results. On the basis of the variety of land covers studied, the vertical-vertical polarization (VV) data is judged to contain the highest degree of contrast, while the horizontal-vertical (HV) polarization contained the least. VV polarization data is accordingly recommended for forest vegetation classification in those cases where only one data channel is available. The inclusion of horizontal-horizontal polarization data, however, is noted to be capable of delineating special surface features.

Wu, S. T.↗
NASA NTRS1985

Radio phase characteristics of terrain from multipolarized synthetic aperture radar data

Recent advances in digital data acquisition and signal processing technology permit simultaneous measurement of the complex (amplitude and phase) radar backscatter from several polarization-diverse antennas. While absolute phase mesurements remain to be analyzed in detail. The differential phase of signals polarized parallel and perpendicular to the plane of incidence provide information on the scattering mechanisms that dominate the interaction of the radio waves with the terrain. Analysis of phase backscatter maps from a typical urban area yields a bimodal distribution with the two peaks separated by approximately 180 degrees, highly indicative of a dominant simple geometric one bounce-two bounce mechanism. Some maps of agricultural areas exhibit a similar distribution, however, other agricultural areas yield a distribution that, while still bimodal, consists of two peaks separated by about 110 deg. Still other agricultural areas exhibit a more complex distribution. All of the observed phase shifts appear to be independent of incidence angle from at least 20 deg to 55 deg, therefore the 110 degree shifts are inconsistent with both the geometric model used for the urban area and with common dielectric slab models.

Zebker, H. A.↗
NASA NTRS1987

Parametric analysis of synthetic aperture radar data for characterization of deciduous forest stands

The SAR sensor parameters that affect the estimation of deciduous forest stand characteristics were examined using data sets for the Gulf Coastal Plain region, acquired by the NASA/JPL multipolarization airborne SAR. In the regression analysis, the mean digital-number values of the three polarization data are used as the independent variables to estimate the average tree height (HT), basal area (BA), and total-tree biomass (TBM). The following results were obtained: (1) in the case of simple regression and using 28 plots, vertical-vertical (VV) polarization yielded the largest correlation coefficients (r) in estimating HT, BA, and TBM; (2) in the case of multiple regression, the horizontal-horizontal (HH) and VV polarization combination yielded the largest r value in estimating HT, while the VH and HH polarization combination yielded the largest r values in estimating BA and TBM. With the addition of a third polarization, the increase in r values is insignificant.

Wu, Shih-Tseng↗
NASA NTRS1988

Parametric analysis of synthetic aperture radar data for the study of forest stand characteristics

A parametric analysis of a Gulf Coast forest stand was performed using multipolarization, multipath airborne SAR data, and forest plot properties. Allometric equations were used to compute the biomass and basal area for the test plots. A multiple regression analysis with stepwise selection of independent variables was performed. It is found that forest stand characteristics such as biomass, basal area, and average tree height are correlated with SAR data.

Wu, Shih-Tseng↗
NASA NTRS1989

Multi-temporal airborne synthetic aperture radar data for crop classification

This paper presents an approach to the classification of crop type using multitemporal airborne SAR data. Following radiometric correction of the data, the accuracy of a per-field crop classification reached 90 percent for three classes using data acquired on four dates. A comparable accuracy of 88 percent could be obtained for a classification of the same classes using data acquired on only two dates. Increasing the number of classes from three to seven reduced the classification accuracies to 55 percent and 69 percent when using data from two and four dates respectively.

Foody, G. M.↗
NASA NTRS1991

Wave propagation in the marginal ice zone - Model predictions and comparisons with buoy and synthetic aperture radar data

Ocean wave dispersion relation and viscous attenuation by a sea ice cover are studied for waves propagating into the marginal ice zone (MIZ). The Labrador ice margin experiment (LIMEX), conducted on the MIZ off the east coast of Newfoundland, Canada in March 1987, provided aircraft SAR imagery, ice property and wave buoy data. Wave energy attenuation rates are estimated from SAR data and the ice motion package data that were deployed at the ice edge and into the ice pack, and compared with a model. It is shown that the model data comparisons are quite good for the ice conditions observed during LIMEX 1987.

Liu, Antony K.↗
NASA NTRS1992

Identification of sea ice types in spaceborne synthetic aperture radar data

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

Kwok, Ronald↗
NASA NTRS1995

Pipeline synthetic aperture radar data compression utilizing systolic binary tree-searched architecture for vector quantization

A system for data compression utilizing systolic array architecture for Vector Quantization (VQ) is disclosed for both full-searched and tree-searched. For a tree-searched VQ, the special case of a Binary Tree-Search VQ (BTSVQ) is disclosed with identical Processing Elements (PE) in the array for both a Raw-Codebook VQ (RCVQ) and a Difference-Codebook VQ (DCVQ) algorithm. A fault tolerant system is disclosed which allows a PE that has developed a fault to be bypassed in the array and replaced by a spare at the end of the array, with codebook memory assignment shifted one PE past the faulty PE of the array.

Chang, Chi-Yung↗
NASA NTRS2010

Creating Synthetic Coronal Observational Data From MHD Models: The Forward Technique

We present a generalized forward code for creating simulated corona) observables off the limb from numerical and analytical MHD models. This generalized forward model is capable of creating emission maps in various wavelengths for instruments such as SXT, EIT, EIS, and coronagraphs, as well as spectropolari metric images and line profiles. The inputs to our code can be analytic models (of which four come with the code) or 2.5D and 3D numerical datacubes. We present some examples of the observable data created with our code as well as its functional capabilities. This code is currently available for beta-testing (contact authors), with the ultimate goal of release as a SolarSoft package

Rachmeler, Laurel A.↗
DOE OSTI2020

Realistic Synthetic Distribution Grids: Summary of Validation Results

The presentation slides will walk us through the validation process and results of the synthetic distribution grid data. The synthetic grids for the distribution systems were developed as part of the ARPA-E funded GRIDDATA program project, SMART-DS. Three large scale datasets for US style distribution system were developed: 1) SAF: Santa Fe urban region, 2) GSO: Greensboro urban, semi-urban and industrial region, and 3) SFO: San Francisco Bay Area urban, semi-urban, industrial and rural areas. These datasets were validated using a three-pronged validation process, including statistical, operational and expert validation phases; the results of which have been summarized in this deck.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

GenAI-Based Digital Twins Aided Data Augmentation Increases Accuracy in Real-Time Cokurtosis-Based Anomaly Detection of Wearable Data

Early detection of potential infectious disease outbreaks is crucial for developing effective interventions. In this study, we introduce advanced anomaly detection methods tailored for health datasets collected from wearables, offering insights at both individual and population levels. Leveraging real-world physiological data from wearables, including heart rate and activity, we developed a framework for the early detection of infection in individuals. Despite the availability of data from recent pandemics, substantial gaps remain in data collection, hindering method development. To bridge this gap, we utilized Wasserstein Generative Adversarial Networks (WGANs) to generate realistic synthetic wearable data, augmenting our dataset for training. Subsequently, we use these augmented datasets to implement a cokurtosis-based technique for anomaly detection in multivariate time-series data. Our approach includes a comprehensive assessment of uncertainties in synthetic data compared to the actual data upon which it was modeled, as well as the uncertainty associated with fine-tuning anomaly detection thresholds in physiological measurements. Through our work, we present an enhanced method for early anomaly detection in multivariate datasets, with promising applications in healthcare and beyond. This framework could revolutionize early detection strategies and significantly impact public health response efforts in future pandemics.

Data-Driven Digital Twins↗
DOE OSTI2020

Data-driven model construction for industrial asset decision boundary classification

In some embodiments, a system model construction platform may receive, from a system node data store, system node data associated with an industrial asset. The system model construction platform may automatically construct a data-driven, dynamic system model for the industrial asset based on the received system node data. A synthetic attack platform may then inject at least one synthetic attack into the data-driven, dynamic system model to create, for each of a plurality of monitoring nodes, a series of synthetic attack monitoring node values over time that represent simulated attacked operation of the industrial asset. The synthetic attack platform may store, in a synthetic attack space data source, the series of synthetic attack monitoring node values over time that represent simulated attacked operation of the industrial asset. This information may then be used, for example, along with normal operational data to construct a threat detection model for the industrial asset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Data-Driven Method for Synthetic Extreme Weather Generation and Solar Impact Assessment: Preprint

High-resolution, high-fidelity weather datasets are essential for testing and evaluating the resilience of power systems, particularly under extreme weather conditions. However, existing extreme weather datasets are typically derived from historical events that are localized and may lack the spatial and temporal resolution or scenario diversity needed to test largescale power systems. In this work, we propose a synthetic extreme weather simulation approach capable of generating targeted extreme events, such as hurricanes, using publicly available data sources. Preliminary results demonstrate the impact of a simulated Category 1 hurricane on renewable generation and critical infrastructure in California. The work aims to provide a flexible approach for creating multiple types of extreme weather scenarios across different regions, enabling comprehensive system stress testing, training, and resilience assessment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.

54 ENVIRONMENTAL SCIENCES↗