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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Radar data processing and analysis

Digitized four-channel radar images corresponding to particular areas from the Phoenix and Huntington test sites were generated in conjunction with prior experiments performed to collect X- and L-band synthetic aperture radar imagery of these two areas. The methods for generating this imagery are documented. A secondary objective was the investigation of digital processing techniques for extraction of information from the multiband radar image data. Following the digitization, the remaining resources permitted a preliminary machine analysis to be performed on portions of the radar image data. The results, although necessarily limited, are reported.

Ausherman, D.↗
NASA NTRS1985

Mathematical analysis study for radar data processing and enchancement. Part 2: Modeling of propagation path errors

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.

James, R.↗
NASA NTRS1994

Characteristics of the vertical profiles of dual-frequency, dual-polarization radar data in stratiform rain

Airborne dual-wavelength and dual-polarization radar data are analyzed for measurements taken in stratiform rain in the western Pacific during September 1990. The focus of the paper is on the vertical profiles of the linear depolarization ratio, LDR (10 GHz); the reflectivity factor, dBZ (10 GHz); and the dual-frequency ratio, DFR (10, 34.45 GHz). Statistical characterizations of the maxima of these quantities and the relative locations at which they occur suggest that the eccentricity of the melting particles is fairly large and that the shape and size of the particles are correlated. To try to explain these features, two types of simulation are presented. In the first, a set of measured drop size distributions is used in the context of a standard model of the melting layer. Variations in snow density, as well as shape, size, and orientation distributions are used to study the relationship between these parameters and the radar measurements. To reduce the amount of ambiguity in the estimation, a second type of simulation is described in which the size distribution of the snow is estimated. Comparisons between the simulated and measured profiles indicate that radar measurements can be used to derive certain characteristics of the particle size and shape distributions in the melting layer.

Meneghini, R.↗
NASA NTRS1981

SEASAT Synthetic Aperture Radar Data

The potential of radar imagery from space altitudes is discussed and the advantages of radar over passive sensor systems are outlined. Specific reference is made to the SEASAT synthetic aperture radar. Possible applications include oil spill monitoring, snow and ice reconnaissance, mineral exploration, and monitoring phenomena in the urban environment.

Henderson, F. M.↗
NASA NTRS1984

MST radar data management

One atmospheric variable which can be deduced from stratosphere-troposphere (ST) radar data other than wind speed and direction is C sub n sup 2, related to the eddy dissipation rate. The computation of C sub n sup 2 makes use of the transmitted power (average, or peak plus duty cycle), the range of the echoes, and the returned power. The returned power can be calibrated only if a noise source of known strength is imposed; e.g., in the absence of absolute calibration, one can compare the diurnal noise signal with the galactic sky temperature. Thus to compute C sub n sup 2 one needs the transmitter power, the returned signal as a function of height, and the returned noise at an altitude so high that it is not contaminated by any signal. Now C sub n sup 2 relates with the amount of energy within the inertial subrange, and for many research studies it may be desirable to relate this with background flow as well as shears or irregularities on the size of the sample volume. The latter are quantified by the spectral width.

Nastrom, G. D.↗
NASA NTRS1991

Data volume reduction for single-look polarimetric imaging radar data

An 8-b quantization scheme to reduce the data volume for single-look complex scattering matrix data measured by polarimetric imaging radar systems is described. The scattering matrices are not symmetrized before compression, thereby retaining information about background noise and system effects. The data volume is reduced by a factor of 3.2. It is shown, with measured data, that the signal to quantization noise ratio for the compression scheme is more than 35 dB for the cross-polarized channels, and more than 45 dB for the copolarized channels.

Van Zyl, Jakob J.↗
NASA NTRS1994

Intercomparison of single-frequency methods for retrieving a vertical rain profile from airborne or spaceborne radar data

This paper briefly reviews several single-frequency rain profiling methods for an airborne or spaceborne radar. The authors describe the different methods from a unified point of view starting from the basic differential equation. This facilitates the comparisons between the methods and also provides a better understanding of the physical and mathematical basis of the methods. The application of several methods to airborne radar data taken during the Convective and Precipitation/Electrification Experiment is shown. Finally, the authors consider a hybrid method that provides a smooth transition between the Hitschfeld-Bordan method, which performs well at low attenuations, and the surface reference method, for which the relative error decreases with increasing path attenuation.

Iguchi, Toshio↗
DOE OSTI2026

Adapt: A Weather Radar Data Analysis and Nowcasting Platform for Informed Adaptive Scanning

SF-26-021 Adapt is a data processing platform for real-time data analysis, short term prediction of targets convective cells and tracking for archived data. It provides tools for downloading, processing, segmenting, projecting, analyzing, and visualizing storm cell data from weather radar. The pipeline includes cell detection, motion estimation using optical flow, cell property extraction, and persistence to NetCDF and SQLite/Parquet for guiding adaptive scanning.

Raut, Bhupendra Ashokrao [Argonne National Laborat↗
NASA NTRS1992

Estimates of surface roughness derived from synthetic aperture radar (SAR) data

Radar remote sensing data provide a unique perspective of the earth's crust and the processes that have influenced its evolution. Physically based models are required, however, to relate the geophysical quantities being measured by the radar sensor to useful geologic information. In this study, synthetic aperture radar (SAR) data over the Cima volcanic field in the Mojave Desert of California are quantitatively connected with microtopography through inversion of a radar backscatter model. Changes in surface roughness inferred from the derived microtopography are modeled and found to be consistent with aeolian mantling as surfaces age. Estimated rates of aeolian deposition for the Cima area are compared to the Lunar Crater volcanic field in Nevada. Rates of deposition appear to be higher at Cima volcanic field, most likely because of its proximity to Soda Lake, the main source of the aeolian material.

Evans, Diane L.↗
NASA NTRS1980

Monthly and seasonal occurrences of potential flash flood-producing rains determined from Manually Digitized Radar data

An analysis is conducted of a small 4-year climatological data base of Manually Digitized Radar (MDR) data to infer the monthly and seasonal distributions of the relative frequency of occurrence of potential flash flood-producing rains over the Central and Eastern U.S. Some possible meteorological mechanisms for producing potential flash flooding rains are discussed in terms of the relative maxima and minima in the monthly and seasonal frequency distributions over the MDR network. Frequencies were found to be generally higher in more southern locations and lower farther north in all months and seasons. However, most locations experienced an annual cycle in the frequency of occurrence with maxima in summer and minima in winter. In given seasons and months, local areas of maximum and minimum occurrences may be related to quasi-stationary meteorological processes that trigger and organize intense convection over a common area.

Wilson, G. S.↗
DOE OSTI2022

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

58 GEOSCIENCES↗
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↗
NASA NTRS1977

Bandwidth compression of synthetic aperture radar imagery by quantization of raw radar data

A study is made of the effects of quantization of the radar returns transmitted from aircraft or spacecraft employing a synthetic aperture radar system. The study is based on the output images obtained after one-bit, two-bit, and eight-bit quantizations and comparing the results to ground truth. In this way the degradation resulting from data or bandwidth reduction is determined. Quantization is evaluated in terms of crater scene, number of looks, and transmission error rate. It is found that two-bit quantization of raw radar data from homogeneous scenes processed to 32 looks yields nearly all the details of the original. One-bit quantization of raw radar data from homogeneous scenes processed to 32 looks yields a good visual representation of the scene but some fine detail is lost and the absolute reflectivity level is not reliable. Image quality is observed to improve with more looks and video and intermediate frequency quantization are not distinguishable even for one-bit quantizations. Image quality is not influenced by bit error rates less than about 2 to the -7th power.

Lipes, R. G.↗
NASA NTRS2002

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

Lau, William K. M.↗
NASA NTRS2017

A Method for Estimating Meteorite Fall Mass from Weather Radar Data

Techniques such as weather RADAR, seismometers, and all-sky cameras allow new insights concerning the physics of meteorite fall dynamics and fragmentation during "dark flight", the period of time between the end of the meteor's luminous flight and the concluding impact on the Earth's surface. Understanding dark flight dynamics enables us to rapidly analyze the characteristics of new meteorite falls. This analysis will provide essential information to meteorite hunters to optimize recovery, increasing the frequency and total mass of scientifically important freshly-fallen meteorites available to the scientific community. We have developed a mathematical method to estimate meteorite fall mass using reflectivity data as recorded by National Oceanic and Atmospheric Administration (NOAA) Next Generation RADAR (NEXRAD) stations. This study analyzed eleven official and one unofficial meteorite falls in the United States and Canada to achieve this purpose.

Laird, C.↗