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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automated Vehicle Multi-Object Tracking at Scale with CAN

Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen- sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve track- ing from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

Real Time Monitoring of Flooding from Microwave Satellite Observations

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

Galantowicz, John F.↗
NASA NTRS2010

Transfer of Satellite Rainfall Uncertainty from Gauged to Ungauged Regions at Regional and Seasonal Timescales

Hydrologists and other users need to know the uncertainty of the satellite rainfall data sets across the range of time/space scales over the whole domain of the data set. Here, uncertainty' refers to the general concept of the deviation' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, that can be achieved with these satellite rainfall data sets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially-dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar. The TRMM Multi-satellite Precipitation Analysis (TMPA) products over the US spanning a record of 6 years are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), that leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly and weekly timescales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly timescales with the error doubling from monthly to weekly.However, at very low GV data density (<20% of the domain), the transfer accuracy is too low to show any distinction as a function of the timescale of transfer.

Tang, Ling↗
NASA NTRS1985

The effect of microwave backscatter uncertainty on satellite radar altimeter accuracy

The effect of variations in ocean surface roughness characteristics with upwind/downwind direction, reported by other investigators, is used to compute radar cross section (RCS) and to assess the errors which may arise in present and planned altimeter sensors. Based on an analysis of the rough surface impulse response, the uncertainty between attitude angle and RCS asymmetry is found to cause height errors as large as 12 cm, depending on off-nadir angles and sea state. Additionally, the previously reported data in conjunction with computed facet backscatter are found to produce RCS characteristics at large off-nadir angles which are in better agreement with experimental results than those predicted by physical optics Gaussian theory.

Miller, L. S.↗
NASA NTRS1989

Low level remote sensing: Orographic winds

The orographic flow data set was obtained from a flight program to measure the influence of orographic features on turbulence momentum, heat, and moisture fluxes. The NASA B-57 aircraft instrumented with probes for measuring the three fluctuating wind speed components, temperature, and humidity was the primary measuring vehicle. Ancillary measurements were made with several ground-based sensors. These include the NOAA radar wind profilers, the Boulder wind network, the PROFS mesoscale surface network, the Boulder Atmospheric Observatory 300 m tower, special rawinsonde observations, and the NOAA/WPL Doppler lidar. The major objective of the flight program was to provide planetary boundary layer parameter information for new and current general circulation computer models. A numerical code, WINDER, based on a discrete element technique was run to numerically model the water tunnel simulated flow. Comparison of the analytical model with the experimental results is very good. Physical fluid dynamic principles embedded in the computational model and visual and hot wire anemometer measurements from the simulation are being rationalized to develop a physical understanding of the vortex flow. The results will be interpreted as they pertain to full scale atmospheric flows.

Frost, Walter↗
NASA NTRS1991

Geologic mapping in Death Valley, California/Nevada using NASA/JPL airborne systems (AVIRIS, TIMS, and AIRSAR)

A multi-sensor aircraft campaign called the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 resulted in acquisition of high quality multispectral images in the visible, near infrared, shortwave infrared, thermal infrared, and microwave regions of the electromagnetic spectrum. The airborne data sets include the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Thermal Infrared Multispectral Scanner (TIMS), and the Airborne Synthetic Aperture Radar (SAR). Ancillary data include Landsat Thematic Mapper, laboratory and field spectral measurements, and traditional geologic mapping. The GRSFE data for a site in the northern Death Valley, (California and Nevada) region were calibrated to physical units and geometrically registered to a map base. Various aspects of this experiment are briefly discussed.

Kruse, Fred A.↗
NASA NTRS1993

Analysis of Ku-band cross section at low incidence angles

This study is using airborne Ku-band data to address questions which have implications for both model function development and for advancing our physical understanding of the sea surface. Concurrent measurements of ocean directional spectra, significant wave height, and mean surface roughness are made using the capabilities of the radar ocean wave spectrometer (ROWS). The NASA/GSFC's ROWS is a 15 GHz pulse compressed radar which is a radar sensor designed to measure the direction of the long wave components using spectral analysis of the tilt induced reflectively modulation. The ROWS are modified to cycle at 50 Hz for the scanning spectrometer antenna and a wide beamwidth nadir altimeter mode. This change allows the sensor to simultaneously measure directional wave spectra, wave height, mean square slope parameter, and small scale surface roughness. The surface stress caused by the wind is widely believed to be the predominant quantity related to the Ku-band radar cross section for a wide range of incidence angles. The complete coverage in the quasi specular region provided by one sensor is essential to understand the uncertainties between the scattering model and what is happening on the surface. For this presentation, special attention is devoted to sort out some measurement of the anisotropy associated with the band of high frequencies. Using the other geophysical parameters, comparisons are then made with the classic spectral form currentlyused to describe the wind impact on the sea surface.

Chapron, B.↗
NASA NTRS2021

Confronting Future Models with Future Satellite Observations of Clouds and Aerosols

The NASA Aerosol, Clouds, Convection and Precipitation (ACCP) Study convened a workshop in November 2020 to understand the future of modeling aerosols, clouds, convection and precipitation, and how satellite data can contribute to that future. ACCP is a project to define a satellite mission to be launched late in the 2020’s to advance cloud and aerosol science, following the recommendations of the latest NASA Decadal Survey. The ACCP modeling workshop goal was to answer the following questions: 1. What will be the critical science questions for clouds and aerosols in 10 years? 2. Where will simulations of clouds and aerosols across scales of space (process models to global) and time (nowcasting to climate prediction) be in 10 years? 3. What data will be available from space? What data would provide the most benefit? 4. What are the state of the art methods for confronting models with cloud and aerosol observations, including assimilation and climatological analysis techniques? The virtual workshop was anchored by a series of pre-recorded talks. Two days of synchronous sessions focused on discussion of the talks, along with small group breakout exercises. After an introduction to the ACCP concept came a panel discussing the future of modeling clouds and aerosols across scales. Participants were then asked to contribute their ideas. On the second day, there were two panel discussions. First came a discussion of the future of satellite observing systems. Second was a discussion of model-data synthesis methods. Finally, participants were asked to develop their own model-data synthesis proposal. The meeting began with an overview of the ACCP mission concept by Graeme Stephens (NASA-JPL). ACCP is a satellite mission for clouds and aerosols, likely anchored by advanced active lidar and radar systems in space, designed to observe detailed aerosol profile and type information, as well as cloud microphysics and dynamics. ACCP will integrate across sensors and observational types to get multi-spectral views of the same scenes, with better resolution than is available today. Launch is scheduled for 2027 or 2029. ACCP is being thought of as a comprehensive mission that may comprise more than one platform and more than one orbit plane (i.e., inclined and polar), with multiple combinations of sensors.

Future Models↗
NASA NTRS2021

NASA's Surface Deformation and Change Mission Study

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five "observables" to be prioritized in NASA's program going forward. In response, NASA commissioned a multi-center Surface Deformation and Change (SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are interpreted and refined, candidate mission architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and spacecraft systems and components. The number of SAR systems, both civil and commercial, is growing rapidly, requiring that mission architectures not only consider technology, but availability of data from other missions, possible partnerships or collaborations, and even data purchase. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite constellations, which feeds into a science value framework that considers science performance, technological programmatic risks, and cost. This paper will present an overview of the ongoing study including the architectures under consideration and the technology road map needed to achieve the objectives of the mission.

Rosen, Paul↗
NASA NTRS1993

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Turner, B. J.↗
NASA NTRS1992

Geologic process studies using Synthetic Aperture Radar (SAR) data

The use of SAR data to study geologic processes for better understanding of recent tectonic activity and climate change as well as the mitigation of geologic hazards and exploration for nonrenewable resources is discussed. The geologic processes that are particularly amenable to SAR-based data include volcanism; soil erosion, degradation, and redistribution; coastal erosion and inundation; glacier fluctuations; permafrost; and crustal motions. When SAR data are combined with data from other planned spaceborne sensors including ESA ERS, the Japanese Earth Resources Satellite, and the Canadian Radarsat, it will be possible to build a time-series view of temporal changes over many regions of earth.

Evans, Diane L.↗
NASA NTRS2001

Flying the TRMM Satellite in a GCM

By incorporating the Tropical Rainfall Measurement Mission (TRMM) satellite orbital information into the Colorado State University General Circulation Model (CSU GCM), we are able to 'fly' a satellite in the GCM, and sample the simulated atmosphere in the same way as the TRMM sensors sample the real atmosphere. The TRMM-sampled statistics for precipitation and radiative fluxes at annual, intraseasonal, monthly-mean and seasonal-mean diurnal time scales are evaluated by comparing the satellite-sampled against fully-sampled simulated atmospheres. The sampling rates of the TRMM sensors are significantly affected by the sensors' swath widths. The TRMM Microwave Imager (TMI) and the Visible Infrared Scanner (VIRS) sample each 2.25 x 2.25 degree grid box in the Tropics and subtropics about once per day, but at a different local time every day, while the Precipitation Radar (PR) and the Clouds and the Earth's Radiant Energy System (CERES) sensor visit each grid box about once every three days and twice per day, respectively. Besides inadequate samplings resulting from sensors' swath widths, there is a large, systematic diurnal undersampling associated with TRMM's orbital geometry for grid boxes away from the Equator. When only one month of TRMM data are used, this diurnal undersampling can lead to more daytime samples relative to nighttime samples in one hemisphere, and more nighttime samples relative to daytime samples in the other hemisphere. The resulting sampling biases (3-6 W m(exp-2)) are very pronounced in outgoing longwave radiation (OLR) over the subtropical land masses. The sampling errors in OLR monthly- and seasonal-means are less than 8 W m(exp-2) (5%) for each 2.25 x 2.25 degree grid box. The OLR monthly- and seasonal-means are not sensitive to diurnal undersamplings associated with the TRMM orbits and sensors' swath widths. However, this is not the case for total precipitation. Diurnal undersampling could produce errors as large as 20% in the Tropics and 40% in the subtropics, for the zonally averaged monthly-mean rain rates. The TRMM orbits sample each 2.25 x 2.25 degree grid box in the Tropics and subtropics 1-6 times for each hour of the day within a single season. The seasonal-mean diurnal cycles of precipitation and OLR are not well sampled for any one grid box. By either accumulating the satellite data for a long enough period, or averaging the data over a large area with a relatively uniform diurnal signal, the diurnal cycles of precipitation and OLR can be satisfactorily sampled. The effects TRMM sampling errors on the inferred tropical-mean hydrologic cycle and radiative fluxes are also evaluated. There are strong spurious oscillations associated with TRMM's orbital geometry, with periods of 23 days and 3-4 months, in tropical-mean daily and monthly precipitation. While the relative fluctuations of the sampled-OLR are negligible, the relative fluctuations of the sampled precipitation have magnitudes similar to those of the observed climate variability. Caution must therefore be used when applying TRMM observations of tropical-mean precipitation to interpret climate variations at intraseasonal and interannual scales.

Lin, Xin↗
DOE OSTI2022

Radio frequency sensing and its innovative applications in diverse sectors: A comprehensive study

Recent advancements in radio frequency (RF) sensing technology can be attributed to the development of the Internet of Things (IoT), healthcare, RF-identification, and communication applications. RF sensing is a multidisciplinary research field that requires expertise in computing, electronics, and electromagnetics to cover all system features, including protocol development, antenna design, sensor integration, algorithm formulation, interconnection, data, and analytics. The overarching aim of this work is to present detailed information about RF technologies and their innovations and application diversity from the novel work carried out at CSI Lab1, together in one platform with an extensive survey. This study presents state-of-the art applications and RF sensing that include W-Fi, radar, and SDR and RFID-based sensing. A comprehensive survey and study of the advantages and limitations of each non-contact technology is discussed. Additionally, open research gaps have been identified as well. Decades of knowledge and experience have been put to use to meet new challenges and demands. The development and study of RF systems, IoT, RFID sensing, and research and deployment activities, are briefly discussed. The emerging research projects with industry, institutional research centers, and academic studies are also addressed. Finally, an outline of identified potential future research areas is provided, emphasizing opportunities and challenges.

47 OTHER INSTRUMENTATION↗
NASA NTRS1982

The evolution of Florida thunderstorms on 23 September 1979 as observed by an airborne passive microwave radiometer

The observations made by the aircraft are examined in order to determine sensing parameters for future satellite missions. Minimum brightness temperatures substantially below atmospheric temperatures are revealed in the data. Scattering by an ice layer within the clouds is postulated as the cause. A one-dimensional cloud model initialized with a representative local sounding gives reasonable values for the height and thickness of this ice layer. The model cloud is similar to the observed cloud in both cloud top height and radar reflectivity. A 'mystery' feature observed by the microwave sensors as an area of enhanced scattering, suggesting an updraft core of graupel that in turn is indicative of a convective tower is considered of particular interest. It is noted that this feature was masked in the visible and infrared sensors by the presence of upper-level semitransparent cirrus. The detection of this mystery feature is seen as suggesting that passive microwave sensing of convective areas may provide information regarding the location and/or strength of the more active towers which cannot be detected now with conventional visible or infrared instruments because of a uniform higher-level cloud cover.

Hakkarinen, I. M.↗
NASA NTRS1985

Advanced 2-frequency ocean sensing radar using high resolution antenna beams

The opportunity to use a large space antenna system for remote sensing applications permits the creation of an advanced ocean sensing radar that combines the abilities of previously developed techniques. The 15 meter antenna will permit much higher angular and spatial resolution at the surface that will lead to techniques of observing ocean wave heights and the directional spectrum that had not previously been feasible from space. At the same time, sensors to measure ocean surface winds can be in operation and the data from both can be combined to increase the accuracy of each individual sensor. The existing capabilities and sensor techniques with typical data characteristics for the individual measurement of sea surface quantities are outlined.

Weissman, D. E.↗
NASA NTRS1994

Windshear certification data base for forward-look detection systems

Described is an introduction to a comprehensive database that is to be used for certification testing of airborne forward-look windshear detection systems. The database was developed by NASA Langley Research Center, at the request of the Federal Aviation Administration (FAA), to support the industry initiative to certify and produce forward-looking windshear detection equipment. The database contains high-resolution three-dimensional fields for meteorological variables that may be sensed by forward-looking systems. The database is made up of seven case studies that are generated by the Terminal Area Simulation System, a state-of-the-art numerical system for the realistic modeling of windshear phenomena. The selected cases contained in the certification documentation represent a wide spectrum of windshear events. The database will be used with vendor-developed sensor simulation software and vendor-collected ground-clutter data to demonstrate detection performance in a variety of meteorological conditions using NASA/FAA pre-defined path scenarios for each of the certification cases. A brief outline of the contents and sample plots from the database documentation are included. These plots show fields of hazard factor, or F-factor (Bowles 1990), radar reflectivity, and velocity vectors on a horizontal plane overlayed with the applicable certification paths. For the plot of the F-factor field the region of 0.105 and above signify an area of hazardous, performance decreasing windshear, while negative values indicate regions of performance increasing windshear. The values of F-factor are based on 1-Km averaged segments along horizontal flight paths, assuming an air speed of 150 knots (approx. 75 m/s). The database has been released to vendors participating in the certification process. The database and associated document have been transferred to the FAA for archival storage and distribution.

Switzer, George F.↗
NASA NTRS2001

Structure and Characteristics of Precipitation Systems Observed by TRMM

Multi-sensor measurements of total lightning (in-cloud plus cloud-to-ground) from the Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been combined with passive microwave ice scattering and precipitation radar reflectivity profile information previously cataloged for precipitation features observed by TRMM. These precipitation features are defined by their surface rainfall or ice scattering signatures, with horizontal scales approx. 100 - 10000 sq km. Additionally, convective scale (approx. 100 sq km) storms are defined by the lightning data. Over the U.S. the national cloud-to-ground lightning observations are used to also determine the ratio of in-cloud to cloud-to-ground lightning, where it is hypothesized these ratios are related to the vertical profile of reflectivity and concentration of precipitation-sized ice. Combining the LIS, TRMM Microwave Imager (TMI), and Precipitation Radar (PR) for these storms allows investigation of the convective structures and convective regimes leading to observed lightning, scattering, and reflectivity signatures. Application of this approach to a global, multi-year data set (1998-2000) furthers our understanding of convective processes in different climatological regimes. The figure shows the distribution of high flash rate storms.

Goodman, Steve↗
NASA NTRS2008

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Jackson, Gail S.↗