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NASA NTRS2021

NOAA-20 VIIRS on-Orbit Calibration Improvements

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

NOAA-20↗

NASA NTRS2001

Bio-Optical Measurements at Ocean Boundaries in Support of SIMBIOS

The equatorial Pacific is a major component of global biogeochemical cycles, due to upwelling that occurs from the coast of South America to beyond 180 deg. This upwelling has significant implications for global CO2 fluxes, as well as primary and secondary production. In addition, this region of the world's oceans represents a large oceanic province over which validation data for Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) are necessary. This project consists of a mooring program and supporting cruise-based measurements aimed at quantifying the spectrum of biological and chemical variability in the equatorial Pacific and obtaining validation data for SeaWiFS. The project has the following general objectives: (1) to understand the relationships between physical forcing, primary production, nutrient supply and the exchange of carbon dioxide between ocean and atmosphere in the equatorial Pacific; (2) to describe the biological and chemical responses to climate and ocean variability; (3) to describe the spatial, seasonal and inter-annual variability in near surface plant pigments, primary production, carbon dioxide and nutrient distributions; and (4) to obtain near real-time bio-optical measurements for validation of SeaWiFS and subsequent ocean color sensors.

Chavez, Francisco P.↗

NASA NTRS1981

Satellite and correlative measurements of the stratospheric aerosol. I An optical model for data conversions

A description is presented of an empirically based model of stratospheric aerosol optical properties (size distributions and refractive indices) and their variations. The need for such a model arose in the data validation and archival programs for two satellite sensors, SAM II and SAGE. These programs require the ability to convert measurements of a given aerosol macroproperty (e.g., volume extinction coefficient, volume backscatter coefficient, particle number or mass per unit volume) to best estimates of other aerosol macroproperties, and to assess quantitatively the uncertainties in the conversion process. The described model provides the information on size distributions, refractive indices and their variations necessary for these tasks, and also defines a procedure for combining the model information with empirical data in a way that facilitates automatic data processing. Although the model was developed for use in the satellite validation and archival programs, it also has proven useful in other studies of stratospheric aerosol.

Russell, P. B.↗

NASA NTRS2024

Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters

The launch of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) and the Surface Biology and Geology (SBG) satellite sensors will provide increased spectral resolution compared to existing platforms. These new sensors will require robust calibration and validation datasets, but existing field-based instrumentation is limited in its availability and potential for geographic coverage, particularly for coastal and inland waters, where optical complexity is substantially greater than in the open ocean. The minimum signal-to-noise ratio (SNR) is an important metric for assessing the reliability of derived biogeochemical products and their subsequent use as proxies, such as for biomass, in aquatic systems. The SNR can provide insight into whether legacy sensors can be used for algorithm development as well as calibration and validation activities for next-generation platforms. We extend our previous evaluation of SNR and associated uncertainties for representative coastal and inland targets to include the imaging sensors PRISM and AVIRIS-NG, the airborne-deployed C-AIR radiometers, and the shipboard HydroRad and HyperSAS radiometers, which were not included in the original analysis. Nearly all the assessed hyperspectral sensors fail to meet proposed criteria for SNR or uncertainty in remote sensing reflectance (R rs ) for some part of the spectrum, with the most common failures (>20% uncertainty) below 400 nm, but all the sensors were below the proposed 17.5% uncertainty for derived chlorophyll-a. Instrument suites for both in-water and airborne platforms that are capable of exceeding all the proposed thresholds for SNR and R rs uncertainty are commercially available. Thus, there is a straightforward path to obtaining calibration and validation data for current and next-generation sensors, but the availability of suitable high spectral resolution sensors is limited.

signal-to-noise ratio↗

NASA NTRS2005

TAMDAR Sensor Validation in 2003 AIRS II

This study entails an assessment of TAMDAR in situ temperature, relative humidity and winds sensor data from seven flights of the UND Citation II. These data are undergoing rigorous assessment to determine their viability to significantly augment domestic Meteorological Data Communications Reporting System (MDCRS) and the international Aircraft Meteorological Data Reporting (AMDAR) system observational databases to improve the performance of regional and global numerical weather prediction models. NASA Langley Research Center participated in the Second Alliance Icing Research Study from November 17 to December 17, 2003. TAMDAR data taken during this period is compared with validation data from the UND Citation. The data indicate acceptable performance of the TAMDAR sensor when compared to measurements from the UND Citation research instruments.

Daniels, Taumi S.↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Park, Thomas↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

Park, Thomas↗

NASA NTRS2002

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation

This document stipulates protocols for measuring bio-optical and radiometric data for the SIMBIOS Project. It supersedes the earlier version, and is organized into four parts: Introductory Background, Instrument Characteristics, Field Measurements and Data Analysis, Data Reporting and Archival. Changes in this revision include the addition of three new chapters: (1) Fundamental Definitions, Relationships and Conventions; (2) MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols; and (3) Normalized Water-Leaving Radiance and Remote Sensing Reflectance: Bidirectional Reflectance and Other Factors. Although the present document represents another significant, incremental improvement in the ocean optics protocols, there are several protocols that have either been overtaken by recent technological progress, or have been otherwise identified as inadequate. Revision 4 is scheduled for completion sometime in 2003. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational Project. The contributions are published as submitted, after only minor editing to correct obvious grammatical or clerical errors.

Mueller, James L.↗

NASA NTRS2002

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation

Mueller, James L.↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

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NASA NTRS2002

Comparison of the EO-1 Advanced Land Imager Performance With the Landsat Data Continuity Mission Specification

The performance requirements for the Advanced Land Imager were developed under NASA's New Millennium Program and were intended to facilitate the validation of new sensor technologies and architectures for potential application in future remote sensing missions. The Advanced Land Imager (ALI) was designed and flown well before the Landsat Data Continuity Mission (LDCM) specifications were developed. Nevertheless, the science focus of the ALI technology validation was Landsat data continuity. Therefore, although exact compliance by ALI is not expected, the performance should demonstrate a path to a compliant sensor system. The performance of the ALI, as determined from preflight and flight data, is compared to the LDCM specification. Twenty-one noncompliances have been identified: four data collection, four spectral, six spatial, and seven radiometric (Table I). All but six of these are considered minor. The six major noncompliances are the result of stray light, leaky detectors, and contamination. Appendix A replicates the LDCM specification and contains ALI compliance notes where appropriate. Details of the ALI stray light, contamination, and leaky detectors are provided in Appendix B, C, and D respectively. Additional information pertaining to the calculation of the ALI edge response and coherent noise is presented in Appendix E and F. A list of ALI related publications is provided in Appendix G.

Mendenhall, J. A.↗

NASA NTRS1996

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

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NASA NTRS2011

Orion Flight Test-1 Thermal Protection System Instrumentation

The Orion Crew Exploration Vehicle (CEV) was originally under development to provide crew transport to the International Space Station after the retirement of the Space Shuttle, and to provide a means for the eventual return of astronauts to the Moon. With the current changes in the future direction of the United States human exploration programs, the focus of the Orion project has shifted to the project s first orbital flight test, designated Orion Flight Test 1 (OFT-1). The OFT-1 is currently planned for launch in July 2013 and will demonstrate the Orion vehicle s capability for performing missions in low Earth orbit (LEO), as well as extensibility beyond LEO for select, critical areas. Among the key flight test objectives are those related to validation of the re-entry aerodynamic and aerothermal environments, and the performance of the thermal protection system (TPS) when exposed to these environments. A specific flight test trajectory has been selected to provide a high energy entry beyond that which would be experienced during a typical low Earth orbit return, given the constraints imposed by the possible launch vehicles. This trajectory resulted from a trade study that considered the relative benefit of conflicting objectives from multiple subsystems, and sought to provide the maximum integrated benefit to the re-entry state-of-the-art. In particular, the trajectory was designed to provide: a significant, measureable radiative heat flux to the windward surface; data on boundary transition from laminar to turbulent flow; and data on catalytic heating overshoot on non-ablating TPS. In order to obtain the necessary flight test data during OFT-1, the vehicle will need to have an adequate quantity of instrumentation. A collection of instrumentation is being developed for integration in the OFT-1 TPS. In part, this instrumentation builds upon the work performed for the Mars Science Laboratory Entry, Descent and Landing Instrument (MEDLI) suite to instrument the OFT-1 ablative heat shield. The MEDLI integrated sensor plugs and pressure sensors will be adapted for compatibility with the Orion TPS design. The sensor plugs will provide in-depth temperature data to support aerothermal and TPS model correlation, and the pressure sensors will provide a flush air data system for validation of the entry and descent aerodynamic environments. In addition, a radiometer design will be matured to measure the radiative component of the reentry heating at two locations on the heat shield. For the back shell, surface thermocouple and pressure port designs will be developed and applied which build upon the heritage of the Space Shuttle Program for instrumentation of reusable surface insulation (RSI) tiles. The quantity and location of the sensors has been determined to balance the needs of the reentry disciplines with the demands of the hardware development, manufacturing and integration. Measurements which provided low relative value and presented significant engineering development effort were, unfortunately, eliminated. The final TPS instrumentation has been optimized to target priority test objectives. The data obtained will serve to provide a better understanding of reentry environments for the Orion capsule design, reduce margins, and potentially reduce TPS mass or provide TPS extensibility for alternative missions.

Kowal, T. John↗

NASA NTRS1996

Calibration of the Airborne Visible/Infrared Imaging Spectrometer in the Laboratory

Imaging spectrometry data must be spectrally, radiometrically and geometrically calibrated in order to: 1) derive physical parameters from measured spectral radiance, 2) compare data acquired from different regions and at different times, 3) compare and analyze the imaging spectrometry data with data acquired from other calibrated sensors, and 4) compare and analyze data with results from computer models. The calibration of AVIRIS data is the process by which laboratory characterization data are applied to raw instrument data (digitized number versus spectral channels) to produce quantitative spectra (radiance versus wavelength) for each image pixel in units of spectral radiance. The AVIRIS sensor and calibration process are described by Vane and the application of the calibration data to the raw digital data is described by Green. This calibration process is validated for in-flight performance of the sensor using a rigorous ground-truth campaign. This workshop paper reviews the laboratory characterization data set that is used in the AVIRIS calibration process. The laboratory measurements used to acquire the calibration data are divided into three classes: 1) spectral calibration, 2) radiometric calibration, and 3) spatial calibration.

Green Robert O.↗

NASA NTRSDate not supplied

Optimal Sensor Mobility Design for Target Tracking with Distributed Sensing, Communication and Computing Infrastructure

The paper presents an airborne target tracking approach with data fusion from distributed stationary and mobile sensor network transmitted through a wireless/wired communication network and using a distributed computing infrastructure. To obtain high quality measurements, sensor flight platforms' positions and orientations are optimized with respect to the available target's position and velocity estimates, and a formation control strategy is applied to derive desired trajectories for the flight platforms. As sensors move, the communication network topology switching is determined using the worst-case approach to handle uncertainties in the target's and sensors' positions, which alters communication delays for sensors' data transmission to computing centers. An optimal data migration algorithm is periodically applied to determine these communication delays for each sensor and the optimal location with minimum end-to-end latency for the target tracking algorithm execution, which is based on adaptive information fusion from multi-modal mobile and stationary sensors inside an Extended Kalman Filter framework. The approach is validated in a desktop simulation environment using synthetic sensor data generated for a simulated target's flight.

Distributed sensing↗

NASA NTRS2000

Remote Diagnosis of the International Space Station Utilizing Telemetry Data

Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

Deb, Somnath↗

NASA NTRS2018

Reflectance-Based Imaging Spectrometer Error Budget Field Practicum at the Railroad Valley Test Site, Nevada

Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.

Ong, Cindy↗

NASA NTRS1992

High-temperature strain measurement techniques: Current developments and challenges

Since 1987, a very substantial amount of R&D has been conducted in an attempt to develop reliable strain sensors for the measurements of structural strains during ground testing and hypersonic flight, at temperatures up to at least 2000 deg F. Much of the effort has been focused on requirements of the NASP Program. This presentation is limited to the current sensor development work and characterization studies carried out within that program. It is basically an assessment as to where we are now and what remains to be done in the way of technical accomplishments to meet the technical challenges posed by the requirements and constraints established for the NASP Program. The approach for meeting those requirements and constraints has been multi-disciplinary in nature. It was recognized early on that no one sensor could meet all these requirements and constraints, largely because of the large temperature range (cryogenic to at least 2000 deg F) and many other factors, including the most challenging requirement that the sensor system be capable of obtaining valid 'first cycle data'. Present candidate alloys for resistance-type strain gages include Fe-Cr-Al and Pd-Cr. Although they have superior properties regarding withstanding very high temperatures, they exhibit large apparent strains that must either be accounted for or cancelled out by various techniques, including the use of a dual-element, half-bridge dummy gage, or electrical compensation networks. A significant effort is being devoted to developing, refining, and evaluating the effectiveness of those techniques over a broad range in temperature and time. In the quest to obtain first-cycle data, ways must be found to eliminate the need to prestabilize or precondition the strain gage, before it is attached to the test article. It should be noted that present NASP constraints do not permit prestabilization of the sensor, in situ. Gages are currently being 'heat treated' during manufacture in both the wire- and foil-type resistance strain gages, and evaluation is in progress. In addition, the 'gage-on-shim' concept is being revisited. That concept will permit heat treatment of the gage during manufacture, before attachment on the test article. Also, it may permit the individual calibration of each gage regarding gage factor and apparent strain. Candidate alloys for the NASP include titanium metal-matrix and carbon-carbon composites. Although those materials have very attractive properties at elevated temperatures in terms of strength and weight, they pose significant attachment problems. Methods for making reliable strain gage and thermocouple attachments to them are currently under development. Experience to date indicates that Rokide attachment of the sensor directly to the protective coating is easier than to the base material itself. However, interpreting strain data from gages attached in this way may prove difficult because of possible cracks in the coating that form 'islands' and the mobility of those 'islands'. It is concluded, therefore, that major technical challenges lie ahead as we proceed to meet the stringent strain sensor requirements and constraints of the NASP Program.

Lemcoe, M. M.↗