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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Monitoring Land Surface Soil Moisture from Space with in-Situ Sensors Validation: The Huntsville Example

Based on recent advances in microwave remote sensing of soil moisture and in pursuit of research interests in areas of hydrology, soil climatology, and remote sensing, the Center for Hydrology, Soil Climatology, and Remote Sensing (HSCARS) conducted the Huntsville '96 field experiment in Huntsville, Alabama from July 1-14, 1996. We, researchers at the Global Hydrology and Climate Center's MSFC/ES41, are interested in using ground-based microwave sensors, to simulate land surface brightness signatures of those spaceborne sensors that were in operation or to be launched in the near future. The analyses of data collected by the Advanced Microwave Precipitation Radiometer (AMPR) and the C-band radiometer, which together contained five frequencies (6.925,10.7,19.35, 37.1, and 85.5 GHz), and with concurrent in-situ collection of surface cover conditions (surface temperature, surface roughness, vegetation, and surface topology) and soil moisture content, would result in a better understanding of the data acquired over land surfaces by the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer (AMSR), because these spaceborne sensors contained these five frequencies. This paper described the approach taken and the specific objective to be accomplished in the Huntsville '97 field experiment.

Wu, Steve Shih-Tseng↗
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

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 NTRS2003

Reflectance-Based Sensor Validation Over Ice Surfaces

During this period work was performed in the following areas. These areas are defined in the Work Schedule presented in the original proposal: BRDF development, Data acquisition and processing, THR Table generation and Presentations and Publications. BRDF development involves creating and/or modifying a reflectance model of the Antarctic surface. This model must, for a temporal and spatial average, be representative of the East Antarctic plateau and be expressed in terms of the three standard surface angles: solar zenith angle (SolZA), view zenith angle (SatZA), and relative azimuth angle (RelAZ). We successfully acquired a limited amount of NOAA-9 AVHRR data for radiance validation. The data were obtained from the Laboratory for Terrestrial Physics at Goddard Space Flight Center. We developed our own reading and unpacking software, which we used to select Channel 1 data (visible). We then applied geographic subsetting criteria (same as used for TOMS), and wrote only the relevant data to packed binary files. We proceeded with analysis of these data, which is not yet complete.

Jaross, Glen↗
NASA NTRS1991

Sensor data validation and reconstruction. Phase 1: System architecture study

The sensor validation and data reconstruction task reviewed relevant literature and selected applicable validation and reconstruction techniques for further study; analyzed the selected techniques and emphasized those which could be used for both validation and reconstruction; analyzed Space Shuttle Main Engine (SSME) hot fire test data to determine statistical and physical relationships between various parameters; developed statistical and empirical correlations between parameters to perform validation and reconstruction tasks, using a computer aided engineering (CAE) package; and conceptually designed an expert system based knowledge fusion tool, which allows the user to relate diverse types of information when validating sensor data. The host hardware for the system is intended to be a Sun SPARCstation, but could be any RISC workstation with a UNIX operating system and a windowing/graphics system such as Motif or Dataviews. The information fusion tool is intended to be developed using the NEXPERT Object expert system shell, and the C programming language.

Source record↗
NASA NTRS2010

Integrated System Health Management (ISHM) Implementation in Rocket Engine Testing

A pilot operational ISHM capability has been implemented for the E-2 Rocket Engine Test Stand (RETS) and a Chemical Steam Generator (CSG) test article at NASA Stennis Space Center. The implementation currently includes an ISHM computer and a large display in the control room. The paper will address the overall approach, tools, and requirements. It will also address the infrastructure and architecture. Specific anomaly detection algorithms will be discussed regarding leak detection and diagnostics, valve validation, and sensor validation. It will also describe development and use of a Health Assessment Database System (HADS) as a repository for measurements, health, configuration, and knowledge related to a system with ISHM capability. It will conclude with a discussion of user interfaces, and a description of the operation of the ISHM system prior, during, and after testing.

Figueroa, Fernando↗
NASA NTRS1994

Real-time sensor data validation

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

Bickmore, Timothy W.↗
NASA NTRS1992

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Guo, T. H.↗
NASA NTRS2001

High Altitude Measurements of Radiance at High Spectral and Spatial Resolution for SIMBIOS Sensor Calibration, Validation, and Intercomparisons

The successful combination of data from different ocean color sensors depends on the correct interpretation of signal from each of these sensors. Ideally, the sensor measured signals are calibrated to geophysical units of spectral radiance, and sensor artifacts are removed and corrected. The calibration process resamples the signal into a common radiometric data space so that subsequent ocean color algorithms that are applied to the data are based on physical processes and are inherently sensor independent. The objective of this project is to calibrate and validate the on-orbit radiometric characteristics of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) with underflights of NASA's calibrated Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This objective is feasible because AVIRIS measures the same spectral range as SeaWIFS at higher spectral resolution. In addition to satellite sensor underflights, the AVIRIS project has supported comparison and analysis of the radiometric calibration standards used for AVIRIS and SeaWIFS. To date, both the OCTS and SeaWIFS satellite sensors have been underflown by AVIRIS with matching spectral, spatial, geometric, radiometric, and temporal domains. The calibration and validation objective of this project is pursued for the following reasons: (1) Calibration is essential for the quantitative use of SeaWIFS and other SIMBIOS (Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies) sensor data; (2) Calibration in the laboratory of spaceborne sensors is challenging; (3) Satellite sensors are subjected aging on the ground and to trauma during launch; (4) The Earth orbit environment is significantly different than the laboratory calibration environment; (5) Through years of effort AVIRIS has been demonstrated to be well calibrated; and (6) AVIRIS can match the spectral and spatial observation characteristics near the top of the atmosphere at the time of SeaWIFS measurements.

Green, Robert O.↗
NASA NTRS2006

Efficient and Robust Data Collection Using Compact Micro Hardware, Distributed Bus Architectures and Optimizing Software

Future In-Space propulsion systems for exploration programs will invariably require data collection from a large number of sensors. Consider the sensors needed for monitoring several vehicle systems states of health, including the collection of structural health data, over a large area. This would include the fuel tanks, habitat structure, and science containment of systems required for Lunar, Mars, or deep space exploration. Such a system would consist of several hundred or even thousands of sensors. Conventional avionics system design will require these sensors to be connected to a few Remote Health Units (RHU), which are connected to robust, micro flight computers through a serial bus. This results in a large mass of cabling and unacceptable weight. This paper first gives a survey of several techniques that may reduce the cabling mass for sensors. These techniques can be categorized into four classes: power line communication, serial sensor buses, compound serial buses, and wireless network. The power line communication approach uses the power line to carry both power and data, so that the conventional data lines can be eliminated. The serial sensor bus approach reduces most of the cabling by connecting all the sensors with a single (or redundant) serial bus. Many standard buses for industrial control and sensor buses can support several hundreds of nodes, however, have not been space qualified. Conventional avionics serial buses such as the Mil-Std-1553B bus and IEEE 1394a are space qualified but can support only a limited number of nodes. The third approach is to combine avionics buses to increase their addressability. The reliability, EMI/EMC, and flight qualification issues of wireless networks have to be addressed. Several wireless networks such as the IEEE 802.11 and Ultra Wide Band are surveyed in this paper. The placement of sensors can also affect cable mass. Excessive sensors increase the number of cables unnecessarily. Insufficient number of sensors may not provide adequate coverage of the system. This paper also discusses an optimal technique to place and validate sensors.

micro hardware↗
NASA NTRS2012

Flash Detection Efficiencies of Long Range Lightning Detection Networks During GRIP

We flew our Lightning Instrument Package (LIP) on the NASA Global Hawk as a part of the Genesis and Rapid Intensification Processes (GRIP) field program. The GRIP program was a NASA Earth science field experiment during the months of August and September, 2010. During the program, the LIP detected lighting from 48 of the 213 of the storms overflown by the Global Hawk. The time and location of tagged LIP flashes can be used as a "ground truth" dataset for checking the detection efficiency of the various long or extended range ground-based lightning detection systems available during the GRIP program. The systems analyzed included Vaisala Long Range (LR), Vaisala GLD360, the World Wide Lightning Location Network (WWLLN), and the Earth Networks Total Lightning Network (ENTLN). The long term goal of our research is to help understand the advantages and limitations of these systems so that we can utilize them for both proxy data applications and cross sensor validation of the GOES-R Geostationary Lightning Mapper (GLM) sensor when it is launched in the 2015 timeframe.

Mach, Douglas M.↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRS2006

Validating Coherence Measurements Using Aligned and Unaligned Coherence Functions

This paper describes a novel approach based on the use of coherence functions and statistical theory for sensor validation in a harsh environment. By the use of aligned and unaligned coherence functions and statistical theory one can test for sensor degradation, total sensor failure or changes in the signal. This advanced diagnostic approach and the novel data processing methodology discussed provides a single number that conveys this information. This number as calculated with standard statistical procedures for comparing the means of two distributions is compared with results obtained using Yuen's robust statistical method to create confidence intervals. Examination of experimental data from Kulite pressure transducers mounted in a Pratt & Whitney PW4098 combustor using spectrum analysis methods on aligned and unaligned time histories has verified the effectiveness of the proposed method. All the procedures produce good results which demonstrates how robust the technique is.

Miles, Jeffrey Hilton↗
NASA NTRS2001

The Altus Cumulus Electrification Study (ACES): A UAV-based Investigation of Thunderstorms

The Altus Cumulus Electrification Study (ACES) is a NASA-sponsored and -led science investigation that utilizes an uninhabited aerial vehicle (UAV) to investigate thunderstorms in the vicinity of the NASA Kennedy Space Center, Florida. As part of NASA's UAV-based science demonstration program, ACES will provide a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES will employ the Altus 11 aircraft, built by General Atomics-Aeronautical Systems, Inc. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high-altitude flight (up to 55,000 feet), the Altus will be flown near, and when possible, above (but never into) thunderstorms for long periods of time, allowing investigations to be conducted over entire storm life cycles. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and (3) provide Lightning Imaging Sensor validation. The ACES payload, already developed and flown on Altus, includes electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. The ACES field campaign will be conducted during July 2002 with a goal of performing 8 to 10 UAV flights. Each flight will require about 4 to 5 hours on station at altitudes from 40,000 ft to 55,000 ft. The ACES team is comprised of scientists from the NASA Marshall Space Flight Center and NASA Goddard Space Flight Centers partnered with General Atomics and IDEA, LLC.

Blakeslee, Richard↗
NASA NTRS2008

Intelligent Sensors for Integrated Systems Health Management (ISHM)

IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

Schmalzel, John L.↗