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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 307 records · Page 17

Enhancement to Non-Contacting Stress Measurement of Blade Vibration Frequency

A system for turbo machinery blade vibration has been developed that combines time-of-arrival sensors for blade vibration amplitude measurement and radar sensors for vibration frequency and mode identification. The enabling technology for this continuous blade monitoring system is the radar sensor, which provides a continuous time series of blade displacement over a portion of a revolution. This allows the data reduction algorithms to directly calculate the blade vibration frequency and to correctly identify the active modes of vibration. The work in this project represents a significant enhancement in the mode identification and stress calculation accuracy in non-contacting stress measurement system (NSMS) technology when compared to time-of-arrival measurements alone.

Platt, Michael↗

An Orbital "Virtual Radar" from TRMM Passive Microwave and Lightning Observations

The retrieval of vertical structure from joint passive microwave and lightning observations is demonstrated. Three years of data from the TRMM (Tropical Rainfall Measuring Mission) are used as a training dataset for regression and classification neural networks; the TMI (TRMM Microwave Imager) and LIS (Lightning Imaging Sensor) provide the inputs, the PR (Precipitation Radar) provides the training targets. Both vertical reflectivity profile categorization (into 9 convective, 7 stratiform, 2 mixed and 6 anvil types) and geophysical parameters (surface rainfall, vertically integrated liquid (VIL), ice water content (IWC) and echo tops) are retrieved. Retrievals are successful over both land and ocean surfaces. The benefit of using lightning observations as inputs to these retrievals is quantitatively demonstrated; lightning essentially provides an additional convective/stratiform discriminator, and is most important for isolation of midlevel (tops in the mixed phase region) convective profile types (this is because high frequency passive microwave observations already provide good convective/stratiform discrimination for deep convective profiles). This is highly relevant as midlevel convective profiles account for an extremely large fraction of tropical rainfall, and yet are most difficult to discriminate from comparable-depth stratiform profile types using passive microwave observations alone.

Boccippio, Dennis J.↗

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗

Use of 2d-video Disdrometer to Derive Mean Density-size and Ze-SR Relations: Four Snow Cases from the Light Precipitation Validation Experiment

The application of the 2D-video disdrometer to measure fall speed and snow size distribution and to derive liquid equivalent snow rate, mean density-size and reflectivity-snow rate power law is described. Inversion of the methodology proposed by Böhm provides the pathway to use measured fall speed, area ratio and '3D' size measurement to estimate the mass of each particle. Four snow cases from the Light Precipitation Validation Experiment are analyzed with supporting data from other instruments such as Precipitation Occurrence Sensor System (POSS), Snow Video Imager (SVI), a network of seven snow gauges and three scanning C9 band radars. The radar-based snow accumulations using the 2DVD-derived Ze-SR relation are in good agreement with a network of seven snow gauges and outperform the accumulations derived from a climatological Ze-SR relation used by the Finnish Meteorological Institute (FMI). The normalized bias between radar-derived and gauge accumulation is reduced from 96% when using the fixed FMI relation to 28% when using the Ze-SR relations based on 2DVD data. The normalized standard error is also reduced significantly from 66% to 31%. For two of the days with widely different coefficients of the Ze-SR power law, the reflectivity structure showed significant differences in spatial variability. Liquid water path estimates from radiometric data also showed significant differences between the two cases. Examination of SVI particle images at the measurement site corroborated these differences in terms of unrimed versus rimed snow particles. The findings reported herein support the application of Böhm's methodology for deriving the mean density-size and Ze-SR power laws using data from 2D-video disdrometer.

radar↗

Integrated display of multi-sensor geophysical and electromagnetic flight data

Low-altitude wind shear has been identified by several aviation interests as a significant hazard to the safety of flying. The hazard may be greatest when the wind shear is due to an unpredicted and short-lived microburst occurring in the immediate flight path of an aircraft during takeoff or landing. Researchers from the NASA Langley Research Center have investigated wind shear by developing a suite of remote sensing instruments and then using these instruments in an airborne wind shear detection flight program. Among these instruments were a Doppler radar, a lidar, and an infrared sensor; these were supported by in situ measurements of aircraft and environmental parameters and by ground-based Doppler radars. The basic problem addressed was the airborne detection and measurement of meteorologically-induced wind shear sufficiently ahead of the aircraft to allow avoidance. If the remote measurements of the shear and its associated radar reflectivity did not exceed set limits, the airplane then continued through the wind shear so that in situ measurements could be made for comparison. Initial detection and vectoring to the wind shear was normally given from a ground-based Doppler weather radar and most of the wind shear events were due to microbursts, both wet and dry. This paper considers the problems of sampling the wind shear event, time and space registration among the various sensors, coordination of the various sensors' beams and sampling volumes, and also various techniques for portraying the data, both for research and for presentation. Examples are given based on data from the 1991 and 1992 NASA/FAA wind shear flights, and the results and conclusions are generalized to other flight experiments involving multi-sensor electromagnetic data sets.

Delnore, V. E.↗

Comparison of surface wind stress measurements - Airborne radar scatterometer versus sonic anemometer

Sea surface wind stress measurements recorded by a sonic anemometer are correlated with airborne scatterometer measurements of ocean roughness (cross section of radar backscatter) to establish the accuracy of remotely sensed data and assist in the definition of geophysical algorithms for the scatterometer sensor aboard Seasat A. Results of this investigation are as follows: Comparison of scatterometer and sonic anemometer wind stress measurements are good for the majority of cases; however, a tendency exists for scatterometer wind stress to be somewhat high for higher wind conditions experienced in this experiment (6-9 m/s). The scatterometer wind speed algorithm tends to overcompute the higher wind speeds by approximately 0.5 m/s. This is a direct result of the scatterometer overestimate of wind stress from which wind speeds are derived. Algorithmic derivations of wind speed and direction are, in most comparisons, within accuracies defined by Seasat A scatterometer sensor specifications.

Brucks, J. T.↗

Analysis of coregistered Landsat, Seasat and SIR-A images of varied terrain types

Multisensor image data (SIR-A, Seasat SAR and Landsat MSS) over areas in nothern Algeria and eastern Utah have been coregistered in order to assess the complementary effects of the orbital sensors for geologic mapping in two very different terrains. This first attempt at registering such a data set shows that the radar backscatter information provided by the SIR-A image increases the classification accuracy of several geologic units over the Landsat image alone, and over combined Landsat and Seasat images.

Rebillard, P.↗

A fine resolution multifrequency polarimetric FM radar

A fine resolution polarimetric FM SAR was developed for optimization of polarimetric SARs and interpretation of SAR data via controlled experiments with surface-base sensors. The system is designed for collecting polarimetric data at 5.3 and 10 GHz over incidence angles from 0 to 60 deg. Features of the system include broad bandwidth to obtain fine range resolution, phase stabilization and linearization loop circuitry, and digital signal processing capability. The system is used in a research program to collect polarimetric backscatter data from artificial sea ice research and design trade-offs, laboratory and field evaluation, as well as results from experiments on artificial sea ice are presented.

Bredow, J.↗

The First Year of TRMM and its Connection to a Global Precipitation Measuring System

This presentation will focus primarily on the advances in our understanding of tropical rain systems needed to interpret the TRMM data. Global averages, as well as case studies from TRMM radar (PR), the TRMM Microwave Imager (TMI) and Visible and Infrared Sensor (VIRS) will be presented. Comparisons and contrasts among the different sensors will be drawn. The relationship between excessive cold clouds and lightning will be illustrated. Comparisons between rainfall products show fairly good agreement outside the deep tropics. The deep tropics will be examined in greater detail to highlight differences and possible sources of discrepancies. Results will also be compared to previous rainfall climatologies generated from the SSM/I instrument. Finally, the paper will focus upon the relationship between the estimates made from the TRMM sensor and those made from ground based radars and preliminary conclusions as well as steps being taken to continue improving our understanding will be presented.

Kummerow, Christian↗

An Aircraft Encounter with Turbulence in the Vicinity of a Thunderstorm

Large eddy simulations of three convective turbulence events are investigated and compared with observational data. Two events were characterized with severe turbulence and the other with moderate turbulence. Two of the events occurred during NASA s turbulence flight experiments during the spring of 2002, and the third was an event identified by the Flight Operational Quality Assurance (FOQA) Program. Each event was associated with developing or ongoing convection and was characterized by regions of low to moderate radar reflectivity. Model comparisons with observations are favorable. The data sets from these simulations can be used to test turbulence detection sensors.

Hamilton, David W.↗

Commercial Off-The-Shelf GPU Qualification for Space Applications

With increased sensor data rates, and limited downlink capability, NASA missions have increased demands for onboard processing for applications ranging from synthetic aperture radar (SAR) data reduction to hyperspectral image processing and recognition, and even artificial intelligence (AI). Graphics Processor Units (GPUs) offer an attractive processing architecture for many of the applications due to their massive parallelism. As no radiation hardened GPU devices currently exist, any near term GPU-based onboard processors must use commercially available devices. To address this need NASA GSFC is collaborating with Cubic Aerospace Incorporated to, (a) characterize the capability of GPUs to meet the demands of a candidate onboard processing application, thereby demonstrating their ability to improve mission performance, reduce spacecraft SWaP, and potentially enable new missions, and (b) evaluate the radiation tolerance of capable COTS GPU devices to determine their suitability for spaceflight applications and understand any mitigations that are needed. A candidate onboard processing image has been prototyped and evaluated on a commercial GPU board and has demonstrated significantly increased processing throughput. Radiation tests for commercial GPU devices are planned for early fiscal year 2019.

Onboard processing↗

Marketing Remote Sensing Data for North Pacific Fisheries Development and Management

Fish poaching, drug trafficking, ocean dumping, and other illegal activities are important problems on the high seas and in national economic zones. The primary thrust of the EOCAP II project, "Marketing Remote Sensing Data for North Pacific Fisheries Development and Management", was to use space-based sensors to improve the effectiveness of marine monitoring, control, and surveillance (MCS). Our initial objectives were to concentrate on the development of MCS tools using Advanced Very High Resolution Radiometry (AVHRR) and Synthetic Aperture Radar (SAR) data. Although we have successfully completed development of an initial version of our SAR-based monitoring tool (OmniVision), project activity has resulted in a much broader application of space-based assets to marine applications. Based in part on work commenced within EOCAP II, a new company, Ocean and Coastal Environmental Sensing, Inc. (OCENS), has been launched and the development of several new software products outside of the MCS arena initiated. One of those products, SeaStation, is near completion with a Fall, 1995 release date. Equity investment in OCENS now totals $70,000-with an additional amount being sought in the first round of financing. One of the pre-eminent objectives of EOCAP II is to make contributions to the US economy and job growth through the expansion of commercial uses of remotely sensed data. OCENS and the software products it is introducing into marine and coastal zone markets responds to this primary object*e. EOCAP II funding leveraged the market and technical know-how of OCENS founders into smart products that benefit marine and coastal zone users. Although technical difficulties and geopolitical shifts damaged the commercial feasibility of initial project objectives, the flexibility of the EOCAP II program now permits long-term business success. This in no small part stems from the fact that the EOCAP program recognizes the realities of small and start-up businesses and does not attempt to force these conditions to fit the apparent needs of big government. Instead, EOCAP works with those who know their market best in order to produce successful products and expanding businesses.

Source record↗

Studying the earth's poles from satellites

The use of satellite remote sensing is reviewed with respect to the investigation of polar regions and global meteorological processes. Data collected from previous and ongoing satellite missions sponsored by NASA and NOAA are discussed in terms of their ability to describe surface characteristics. Data relating to ocean/atmosphere heat transfer are obtained from microwave radiometers and synthetic aperture radars to give estimates of surface temperatures. Ocean color at several frequencies can be measured to estimate chlorophyll content, and optical and infrared sensors aid in the detection of short- and long-term variance in solar irradiance and earth radiation flux. The geophysical variables collected from satellite data at high latitudes can be used to understand the global climate, atmospheric warming, and other significant mechanisms.

Thomas, Robert H.↗

Orbit Determination of LEO Satellites for a Single Pass through a Radar: Comparison of Methods

The problem of determining the orbit of a space object from measurements based on one pass through the field of view of a radar is not a new one. Extensive research in this area has been carried out in the USA and Russia since the late 50s when these countries started the development of ballistic missile defense (BMD) and Early Warning systems. In Russia these investigations got additional stimulation in the early 60s after the decision to create a Space Surveillance System, whose primary task would be the maintenance of the satellite catalog. These problems were the focus of research interest until the middle 70s when the appropriate techniques and software were implemented for all radars. Then for more than 20 years no new research papers appeared on this subject. This produced an impression that all the problems of track determination based on one pass had been solved and there was no need for further research. In the late 90s interest in this problem arose again in relation to the following. It was estimated that there would be greater than 100,000 objects with size greater than 1-2 cm and collision of an operational spacecraft with any of these objects could have catastrophic results. Thus, for prevention of hazardous approaches and collisions with valuable spacecraft the existing satellite catalog should be extended by at least an order of magnitude This is a very difficult scientific and engineering task. One of the issues is the development of data fusion procedures and the software capable of maintaining such a huge catalog in near real time. The number of daily processed measurements (of all types, radar and optical) for such a system may constitute millions, thus increasing the number of measurements by at least an order of magnitude. Since we will have ten times more satellites and measurements the computer effort required for the correlation of measurements will be two orders of magnitude greater. This could create significant problems for processing data close to real time even for modern computers. Preliminary "compression" of data for one pass through the field of view of a sensor can significantly reduce the requirements to computers and data communication. This compression will occur when all the single measurements of the sensor are replaced by the orbit determined on their basis. The single measurement here means the radar parameters (range, azimuth, elevation, and in some cases range rate) measured by a single pulse.

Khutorovsky, Z.↗

Radar range data signal enhancement tracker

The design, fabrication, and performance characteristics are described of two digital data signal enhancement filters which are capable of being inserted between the Space Shuttle Navigation Sensor outputs and the guidance computer. Commonality of interfaces has been stressed so that the filters may be evaluated through operation with simulated sensors or with actual prototype sensor hardware. The filters will provide both a smoothed range and range rate output. Different conceptual approaches are utilized for each filter. The first filter is based on a combination low pass nonrecursive filter and a cascaded simple average smoother for range and range rate, respectively. Filter number two is a tracking filter which is capable of following transient data of the type encountered during burn periods. A test simulator was also designed which generates typical shuttle navigation sensor data.

Source record↗

An X-Band Radar Terrain Feature Detection Method for Low-Altitude SVS Operations and Calibration Using LiDAR

To enable safe use of Synthetic Vision Systems at low altitudes, real-time range-to-terrain measurements may be required to ensure the integrity of terrain models stored in the system. This paper reviews and extends previous work describing the application of x-band radar to terrain model integrity monitoring. A method of terrain feature extraction and a transformation of the features to a common reference domain are proposed. Expected error distributions for the extracted features are required to establish appropriate thresholds whereby a consistency-checking function can trigger an alert. A calibration-based approach is presented that can be used to obtain these distributions. To verify the approach, NASA's DC-8 airborne science platform was used to collect data from two mapping sensors. An Airborne Laser Terrain Mapping (ALTM) sensor was installed in the cargo bay of the DC-8. After processing, the ALTM produced a reference terrain model with a vertical accuracy of less than one meter. Also installed was a commercial-off-the-shelf x-band radar in the nose radome of the DC-8. Although primarily designed to measure precipitation, the radar also provides estimates of terrain reflectivity at low altitudes. Using the ALTM data as the reference, errors in features extracted from the radar are estimated. A method to estimate errors in features extracted from the terrain model is also presented.

Young, Steve↗

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗