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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Cooperative Collision Avoidance Technology Demonstration Data Analysis Report

This report details the National Aeronautics and Space Administration (NASA) Access 5 Project Office Cooperative Collision Avoidance (CCA) Technology Demonstration for unmanned aircraft systems (UAS) conducted from 21 to 28 September 2005. The test platform chosen for the demonstration was the Proteus Optionally Piloted Vehicle operated by Scaled Composites, LLC, flown out of the Mojave Airport, Mojave, CA. A single intruder aircraft, a NASA Gulf stream III, was used during the demonstration to execute a series of near-collision encounter scenarios. Both aircraft were equipped with Traffic Alert and Collision Avoidance System-II (TCAS-II) and Automatic Dependent Surveillance Broadcast (ADS-B) systems. The objective of this demonstration was to collect flight data to support validation efforts for the Access 5 CCA Work Package Performance Simulation and Systems Integration Laboratory (SIL). Correlation of the flight data with results obtained from the performance simulation serves as the basis for the simulation validation. A similar effort uses the flight data to validate the SIL architecture that contains the same sensor hardware that was used during the flight demonstration.

Source record↗
NASA NTRS2006

Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps

Objectives: a) To determine the magnitude of radiometric tarp BRDF; b) To determine whether an ASD FieldSpec Pro spectroradiometer can be used to perform the experiment. Radiometric tarps with nominal reflectance values of 52%, 35%, and 3.5%, deployed for IKONOS. QuickBird, and OrbView-3 overpasses Ground-based spectroradiometric measurements of tarp and Spectralon@ panel taken during overpass using ASD FieldSpec Pro spectroradiometer, and tarp reflectance calculated. Reflectance data used in atmospheric radiative transfer model (MODTRAN) to predict satellite at-sensor radiance for radiometric calibration. Reflectance data also used to validate atmospheric correction of high-spatial-resolution multispectral image products

Knowlton, Kelly↗
NASA NTRS2012

Global and Regional Evaluation of Over-Land Spectral Aerosol Optical Depth Retrievals from SeaWiFS

This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (Sea WiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-year (1997-2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where Sea WiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record should be suitable for quantitative scientific use.

Sayer, A. M.↗
NASA NTRS2018

The Global Precipitation Measurement (GPM) Mission's Scientific Achievements and Societal Contributions: Reviewing Four Years of Advanced Rain and Snow Observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth’s atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° x 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Applications↗
NASA NTRSDate not supplied

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗
NASA NTRS2021

Evaluation of vicarious calibration for airborne sensors using RadCalNet

Vicarious calibration approaches using in-situ measurements are key techniques applied to on-orbit remote sensors. The in-situ measurements have advantages in terms of traceability and quantifiable accuracy that make them ideal for inter-consistency studies of on-orbit sensors. The Committee on Earth Observation Satellites Working Group on Calibration and Validation Infrared Visible Optical Sensors initiated the Radiometric Calibration Network (RadCalNet) to provide automated surface and top-of-atmosphere (TOA) reflectance data from multiple participating ground sites to the worldwide user community. RadCalNet standardizes protocols for collecting data, processes TOA reflectance, and provides International System of Units traceable uncertainty budgets for the five currently operating sites. RadCalNet data from the Railroad Valley Playa, Nevada, site was used to provide an SI-traceable, absolute radiometric calibration of the Enhanced MODIS Airborne Simulator as part of an overflight of opportunity during the FIREX-AQ campaign. The results shown here demonstrate the utility of RadCalNet data for absolute radiometric calibration of airborne imagers making flights of opportunity without the need for coordination with a field validation team.

Sensors↗
NASA NTRS2019

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

ocean colour↗
NASA NTRS2018

Inverse Determination of Aeroheating and Charring Ablator Response

The Mars Science Laboratory (MSL) was protected during its Mars atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA). PICA is a lightweight carbon fiber/polymeric resin material that offers excellent performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of atmospheric entry and material response. MEDLI recorded, among others, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). These measurements have been widely used in the literature as a validation benchmark for state-of-the-art ablation codes. The objective of this work is to perform an inverse estimate of the MSL heatshield material properties and aerothermal environment during Mars entry from the MISP flight data.

Aeroheating↗
NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗
NASA NTRSDate not supplied

Reconstruction of Thermal Protection System Aeroheating using a Green’s Function Approach

Inverse heat transfer (IHT) techniques are often used to reconstruct the surface heating conditions on spacecraft thermal protection systems (TPS) during atmospheric entry. Current IHT techniques for entry spacecraft applications, however, demand substantial computational resources, and are impractical for analyses such as uncertainty quantification and real-time health monitoring. In this paper, a Green’s function sensor fusion approach is used to reconstruct the TPS surface aeroheating conditions on experimental spaceflight and ground test systems from collocated temperature and heat flux sensors embedded in the TPS. The algorithm leverages Green’s functions to model the heat conduction within the spacecraft TPS and stabilizes the recovery of the surface heating condition using the direct heat flux sensor measurement. The algorithm is validated using arc-jet ground test data and applied to the reconstruction of the Mars 2020 backshell heating during Martian atmospheric entry. The performance of the algorithm is benchmarked against a current state-of-the-art IHT framework, FIAT_Opt. The Green’s function-based reconstruction algorithm recovers the net hot-wall heat flux absorbed by the TPS and the incident heat flux from the atmospheric entry environment in close agreement with FIAT_Opt. Notably, computation of the surface heating condition is completed in three orders of magnitude less time with the Green’s function sensor fusion approach using a consumer-grade PC, versus with FIAT_Opt running on a high performance computer cluster. The efficiency of the algorithm is leveraged to compute the uncertainty contributions of input parameters to the total uncertainty in reconstructed Mars 2020 backshell heating for the full atmospheric entry heat pulse. The sensitivity analysis uncovers that, at different times throughout the entry heat pulse, uncertainties in the TPS specific heat, thermal conductivity, and emissivity are all dominant drivers of the reconstruction uncertainty. These results demonstrate Green’s functions and sensor-fusion techniques as promising IHT approaches to reconstruct atmospheric entry environments from TPS-embedded measurements, and highlight how these techniques may give access to post-flight analyses previously hindered by the prohibitive cost of current methods.

Kenneth McAfee↗
NASA NTRSDate not supplied

Reconstruction of Thermal Protection System Aeroheating using a Green’s Function Approach

Inverse heat transfer (IHT) techniques are often used to reconstruct the surface heating conditions on spacecraft thermal protection systems (TPS) during atmospheric entry. Current IHT techniques for entry spacecraft applications, however, demand substantial computational resources, and are impractical for analyses such as uncertainty quantification and real-time health monitoring. In this paper, a Green’s function sensor fusion approach is used to reconstruct the TPS surface aeroheating conditions on experimental spaceflight and ground test systems from collocated temperature and heat flux sensors embedded in the TPS. The algorithm leverages Green’s functions to model the heat conduction within the spacecraft TPS and stabilizes the recovery of the surface heating condition using the direct heat flux sensor measurement. The algorithm is validated using arc-jet ground test data and applied to the reconstruction of the Mars 2020 backshell heating during Martian atmospheric entry. The performance of the algorithm is benchmarked against a current state-of-the-art IHT framework, FIAT_Opt. The Green’s function-based reconstruction algorithm recovers the net hot-wall heat flux absorbed by the TPS and the incident heat flux from the atmospheric entry environment in close agreement with FIAT_Opt. Notably, computation of the surface heating condition is completed in three orders of magnitude less time with the Green’s function sensor fusion approach using a consumer-grade PC, versus with FIAT_Opt running on a high performance computer cluster. The efficiency of the algorithm is leveraged to compute the uncertainty contributions of input parameters to the total uncertainty in reconstructed Mars 2020 backshell heating for the full atmospheric entry heat pulse. The sensitivity analysis uncovers that, at different times throughout the entry heat pulse, uncertainties in the TPS specific heat, thermal conductivity, and emissivity are all dominant drivers of the reconstruction uncertainty. These results demonstrate Green’s functions and sensor-fusion techniques as promising IHT approaches to reconstruct atmospheric entry environments from TPS-embedded measurements, and highlight how these techniques may give access to post-flight analyses previously hindered by the prohibitive cost of current methods.

Kenneth McAfee↗
NASA NTRS1976

EVAL mission requirements, phase 1

The aspects of NASA's applications mission were enhanced by utilization of shuttle/spacelab, and payload groupings which optimize the cost of achieving the mission goals were defined. Preliminary Earth Viewing Application Laboratory (EVAL) missions, experiments, sensors, and sensor groupings were developed. The major technological EVAL themes and objectives which NASA will be addressing during the 1980 to 2,000 time period were investigated. Missions/experiments which addressed technique development, sensor development, application development, and/or operational data collection were considered as valid roles for EVAL flights.

Source record↗
NASA NTRS1995

Orbital Acceleration Research Experiment: Calibration Measurements

The Orbital Acceleration Research Experiment (OARE), which has flown on STS-40, STS-50, and STS-58, contains a three-axis accelerometer with a single, nonpendulous, electrostatically suspended proofmass, which can resolve accelerations to the 10(sub -9) g level. The experiment also contains a full calibration station to permit in situ bias and scale-factor calibration. This on-orbit calibration capability eliminates the large uncertainty of ground-based calibrations encountered with accelerometers flown in the past on the Orbiter, and thus provides absolute acceleration measurement accuracy heretofore unachievable. This is the first time accelerometer scale-factor measurements have been performed on orbit. A detailed analysis of the calibration process is given, along with results of the calibration factors from the on-orbit OARE flight measurements on STS-58. In addition, the analysis of OARE flight-maneuver data used to validate the scale-factor measurements in the sensor's most sensitive range are also presented. Estimates on calibration uncertainties are discussed. These uncertainty estimates provides bounds on the STS-58 absolute acceleration measurements for future applications.

Blanchard, Robert C.↗
NASA NTRS1998

Wind-Driven Angular Dependence of Sea-Surface Reflectance Measured with an Airborne Doppler Lidar

The effects of wind-stress on the optical properties of the ocean surface have been studied for several decades. In particular, the classic study by Cox and Munk (1954) linking sea-surface wind field to wave slope statistics provides a phenomenology by which the sea-surface wind velocity can be estimated from direct measurement of the wave-modulated surface reflectance. A limited number of studies along these lines have been conducted using airborne or spaceborne lidar systems. In these instances, truthing was provided by in situ ship reports or satellite microwave remote sensing instruments (e.g., ERS scatterometer, SSM/I). During the second deployment of the MACAWS Doppler wind lidar in the summer of 1996 measurements of sea-surface reflectance as a function of azimuth- and nadir-viewing angles were acquired off the California coast. MACAWS data products include directly measured winds, as well as calibrated backscatter/reflectance profiles, thus enabling comparison of the winds inferred from sea-surface reflectance measurements with those deriving from the Doppler-processed direct line-of-sight (LOS) estimates. Additional validation data was extracted from the ERS and SSM/I satellite microwave sensor archives maintained by the JPL Physical Oceanography Distributed Active Archive Center (PO- DAAC).

Tratt, David M.↗
NASA NTRS2001

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

Fowler, Charles↗
NASA NTRS2002

The SeaWiFS Bio-Optical Archive and Storage System (SeaBASS): Current Architecture and Implementation

Satellite ocean color missions require an abundance of high-quality in situ measurements for bio-optical and atmospheric algorithm development and post-launch product validation and sensor calibration. To facilitate the assembly of a global data set, the NASA Sea-viewing Wide Field-of-view (SeaWiFS) Project developed the Seafaring Bio-optical Archive and Storage System (SeaBASS), a local repository for in situ data regularly used in their scientific analyses. The system has since been expanded to contain data sets collected by the NASA Sensor Intercalibration and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project, as part of NASA Research Announcements NRA-96-MTPE-04 and NRA-99-OES-99. SeaBASS is a well moderated and documented hive for bio-optical data with a simple, secure mechanism for locating and extracting data based on user inputs. Its holdings are available to the general public with the exception of the most recently collected data sets. Extensive quality assurance protocols, comprehensive data and system documentation, and the continuation of an archive and relational database management system (RDBMS) suitable for bio-optical data all contribute to the continued success of SeaBASS. This document provides an overview of the current operational SeaBASS system.

Werdell, P. Jeremy↗
NASA NTRS2015

Sun Safe Mode Controller Design for LADEE

This paper presents the development of sun safe controllers which are designed to keep the spacecraft power positive and thermally balanced in the event an anomaly is detected. Employed by NASA's Lunar Atmosphere and Dust Environment Explorer (LADEE), the controllers utilize the measured sun vector and the spacecraft body rates for feedback control. To improve the accuracy of sun vector estimation, the least square minimization approach is applied to process the sensor data, which is proven to be effective and accurate. To validate the controllers, the LADEE spacecraft model engaging the sun safe mode was first simulated and then compared with the actual LADEE orbital fight data. The results demonstrated the applicability of the proposed sun safe controllers.

Sun Safe Control↗
NASA NTRS1999

Synthetic Scene Generation of the Stennis V and V Target Range for the Calibration of Remote Sensing Systems

The verification and validation (V&V) target range developed at Stennis Space Center is a useful test site for the calibration of remote sensing systems. In this paper, we present a simple algorithm for generating synthetic radiance scenes or digital models of this target range. The radiation propagation for the target in the solar reflective and thermal infrared spectral regions is modeled using the atmospheric radiative transfer code MODTRAN 4. The at-sensor, in-band radiance and spectral radiance for a given sensor at a given altitude is predicted. Software is developed to generate scenes with different spatial and spectral resolutions using the simulated at-sensor radiance values. The radiometric accuracy of the simulation is evaluated by comparing simulated with AVIRIS acquired radiance values. The results show that in general there is a good match between AVIRIS sensor measured and MODTRAN predicted radiance values for the target despite the fact that some anomalies exist. Synthetic scenes provide a cost-effective way for in-flight validation of the spatial and radiometric accuracy of the data. Other applications include mission planning, sensor simulation, and trade-off analysis in sensor design.

Cao, Chang-Yong↗