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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

IR Interference Filters Made Of Al Patterns On Si Substrates

Filters relatively thin and better accommodate convergent infrared beams. Infrared (IR) interference filters with pass bands centered at wavelength of about 70 micrometer made in form of aluminum patterns 1,000 Angstrom thick on both sides of silicon substrates 12 to 15 micrometer thick. Substrates, in turn, mounted on silicon frames 0.2 millimeter thick. Prototypes of class of miniature band-pass infrared filters small enough to be bonded to, and cooled with, infrared detectors.

Ksendzov, Alexander↗
NASA NTRS1997

A Dual-Line Detection Rayleigh Scattering Diagnostic Technique for the Combustion of Hydrocarbon Fuels and Filtered UV Rayleigh Scattering for Gas Velocity Measurements

Non-intrusive techniques for the dynamic measurement of gas flow properties such as density, temperature and velocity, are needed in the research leading to the development of new generation high-speed aircraft. Accurate velocity, temperature and density data obtained in ground testing and in-flight measurements can help understand the flow physics leading to transition and turbulence in supersonic, high-altitude flight. Such non-intrusive measurement techniques can also be used to study combustion processes of hydrocarbon fuels in aircraft engines. Reliable, time and space resolved temperature measurements in various combustor configurations can lead to a better understanding of high temperature chemical reaction dynamics thus leading to improved modeling and better prediction of such flows. In view of this, a research program was initiated at Polytechnic University's Aerodynamics Laboratory with support from NASA Lewis Research Center through grants NAG3-1301 and NAG3-1690. The overall objective of this program has been to develop laser-based, non-contact, space- and time-resolved temperature and velocity measurement techniques. In the initial phase of the program a ND:YAG laser-based dual-line Rayleigh scattering technique was developed and tested for the accurate measurement of gas temperature in the presence of background laser glare. Effort was next directed towards the development of a filtered, spectrally-resolved Rayleigh/Mie scattering technique with the objective of developing an interferometric method for time-frozen velocity measurements in high-speed flows utilizing the uv line of an ND:YAG laser and an appropriate molecular absorption filter. This effort included both a search for an appropriate filter material for the 266 nm laser line and the development and testing of several image processing techniques for the fast processing of Fabry-Perot images for velocity and temperature information. Finally, work was also carried out for the development of a new laser-based strain-rate and vorticity technique for the time-resolved measurement of vorticity and strain-rates in turbulent flows.

Otugen, M. Volkan↗
NASA NTRS1994

Optimal Correlation Filters for Images with Signal-Dependent Noise

We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

Downie, John D.↗
NASA NTRS1997

High Performance Morphological Filtering of Cirrus Emission from Infrared Images

The project was designed to explore new morphological filtering, techniques for the removal of foreground Galactic 'Cirrus' emission from NASA Infrared Astronomical Satellite (IRAS) data, especially at 100 microns, using parallel processors as the main engine for achieving this result. The ultimate aim was to provide NASA with completely filtered data by the end of the grant period for the entire IRAS 100 and possibly 60 micron database. If successful, the filtered data would reveal many new sources of IR emission, especially at low galactic latitudes, which had previously been heavily confused with diffuse Galactic 'cirrus'.

Appleton, P. N.↗
NASA NTRS1998

A Novel K-Band Tunable Microstrip Bandpass Filter Using a Thin Film HTS/Ferroelectric/ Dielectric Configuration

We report on YBCO/strontium titanate (STO) thin film K-band tunable bandpass filters on lanthanum aluminate substrates. The 2 pole filters were designed for a center frequency of 19 GHz and 4% bandwidth. Tunability is achieved through the non-linear dc electric field dependence of the relative dielectric constant of STO (epsilon-rSTO). Center frequency shifts greater than 2 GHz were obtained at a 400V bipolar dc bias at temperatures below 77K, with minimum degradation in the insertion loss of the filters.

Subramanyam, G.↗
NASA NTRS1998

Temperature Tunable Air-Gap Etalon Filter

We report on experimental measurements of a temperature tuned air-gap etalon filter. The filter exhibits temperature dependent wavelength tuning of 54 pm/C. It has a nominal center wavelength of 532 nm. The etalon filter has a 27 pm optical bandpass and 600 pm free spectral range (finesse approximately 22). The experimental results are in close agreement with etalon theory.

Krainak, Michael A.↗
NASA NTRS1999

The Kalman Filter and High Performance Computing at NASA's Data Assimilation Office (DAO)

Atmospheric data assimilation is a method of combining actual observations with model simulations to produce a more accurate description of the earth system than the observations alone provide. The output of data assimilation, sometimes called "the analysis", are accurate regular, gridded datasets of observed and unobserved variables. This is used not only for weather forecasting but is becoming increasingly important for climate research. For example, these datasets may be used to assess retrospectively energy budgets or the effects of trace gases such as ozone. This allows researchers to understand processes driving weather and climate, which have important scientific and policy implications. The primary goal of the NASA's Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. This presentation will: (1) describe ongoing work on the advanced Kalman/Lagrangian filter parallel algorithm for the assimilation of trace gases in the stratosphere; and (2) discuss the Kalman filter in relation to other presentations from the DAO on Four Dimensional Data Assimilation at this meeting. Although the designation "Kalman filter" is often used to describe the overarching work, the series of talks will show that the scientific software and the kind of parallelization techniques that are being developed at the DAO are very different depending on the type of problem being considered, the extent to which the problem is mission critical, and the degree of Software Engineering that has to be applied.

Lyster, Peter M.↗
NASA NTRS1999

Diode Laser Velocity Measurements by Modulated Filtered Rayleigh Scattering

The ability of solid-state lasers to be tuned in operating frequency at MHz rates by input current modulation, while maintaining a relatively narrow line-width, has made them useful for spectroscopic measurements. Their other advantages include low cost, reliability, durability, compact size, and modest power requirements, making them a good choice for a laser source in micro-gravity experiments in drop-towers and in flight. For their size, they are also very bright. In a filtered Rayleigh scattering (FRS) experiment, a diode laser can be used to scan across an atomic or molecular absorption line, generating large changes in transmission at the resonances for very small changes in frequency. The hyperfine structure components of atomic lines of alkali metal vapors are closely spaced and very strong, which makes such atomic filters excellent candidates for sensitive Doppler shift detection and therefore for high-resolution velocimetry. In the work we describe here we use a Rubidium vapor filter, and work with the strong D(sub 2) transitions at 780 nm that are conveniently accessed by near infrared diode lasers. The low power output of infrared laser diodes is their primary drawback relative to other laser systems commonly used for velocimetry. However, the capability to modulate the laser frequency rapidly and continuously helps mitigate this. Using modulation spectroscopy and a heterodyne detection scheme with a lock-in amplifier, one can extract sub-microvolt signals occurring at a specific frequency from a background that is orders of magnitude stronger. The diode laser modulation is simply achieved by adding a small current modulation to the laser bias current. It may also be swept repetitively in wavelength using an additional lower frequency current ramp.

Mach, J. J.↗
NASA NTRS1998

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter: Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics - Pt. 2

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

Menard, Richard↗
NASA NTRS1998

Cloud Filtering Using a Bi-Spectral Spatial Coherence Approach

The research in this paper focuses on describing a technique developed for cloud filtering using a bi-spectral approach on GOES-8/9 Imager data. The application was developed for use with infrared retrievals of geophysical parameters in mind, where cloud cover contaminates the derived product. However, numerous potential applications of the technique exist. The technique will be described and a preliminary validation of the algorithm will be presented. Although initially based on the spatial coherence approach from Coakley and Brethereton (1982), it has evolved to utilize a difference image of the I I and 3.9 micrometer channels on the GOES-8/9 Imager. This image is very similar to that produced by Nelson and Ellrod (1996). During the daytime the technique makes use of the varying solar reflectance in the 3.9 micrometer channel by clouds and land to identify cloudy pixels. While at night, the technique makes use of the varying emissivity of the clouds in the scene to discriminate between clear and cloudy pixels. The technique applies three basic threshold tests to produce the final cloud filtered image: 1) a standard deviation threshold to detect the spatial variance in the scene, 2) a difference threshold between adjacent pixels, and 3) a simple infrared temperature threshold. The first test is applied to the entire image at once, then in a second pass the next two tests are applied. The final infrared temperature threshold is only meant to identify the coldest clouds that might pass the previous tests. The technique performs well during the daytime, while nighttime performance is degraded but is promising. The technique has proven to be robust and shows great promise of meeting its original goal of cloud filtering for use in an infrared retrieval algorithm for use in climate studies.

Guillory, Anthony R.↗
NASA NTRS1998

Cloud Filtering Using a Bi-Spectral Spatial Coherence Approach

The research in this paper focuses on describing a technique developed for cloud filtering using a bi-spectral approach on GOES-8/9 Imager data. The application was developed for use with infrared retrievals of geophysical parameters in mind, where cloud cover contaminates the derived product. However, numerous potential applications of the technique exist. The technique will be described and a preliminary validation of the algorithm will be presented. Although initially based on the spatial coherence approach from Coakley and Brethereton (1982), it has evolved to utilize a difference image of the 11 and 3.9 micrometer channels on the GOES-8/9 Imager. This image is very similar to that produced by Nelson and Ellrod (1996). During the daytime the technique makes use of the varying solar reflectance in the 3.9 micrometer channel by clouds and land to identify cloudy pixels. While at night, the technique makes use of the varying emissivity of the clouds in the scene to discriminate between clear and cloudy pixels. The technique applies three basic threshold tests to produce the final cloud filtered image: 1) a standard deviation threshold to detect the spatial variance in the scene, 2) a difference threshold between adjacent pixels, and 3) a simple infrared temperature threshold. The first test is applied to the entire image at once, then in a second pass the next two tests are applied. The final infrared temperature threshold is only meant to identify the coldest clouds that might pass the previous tests. The technique performs well during the daytime, while nighttime performance is degraded but is promising. The technique has proven to be robust and shows great promise of meeting its original goal of cloud filtering for use in an infrared retrieval algorithm for use in climate studies.

Guillory, Anthony R.↗
NASA NTRS1995

Filtering Image Records Using Wavelets and the Zakai Equation

Consider the problem of detecting and localizing a faint object moving In an "essentially stationary" background, using a sequence of two-dimensional low-SNR images of the scene. A natural approach consists of "digitizing" each snapshot into a discrete set of observations, sufficiently (perhaps not exactly) matched to the object In question, then tracking the object using an appropriate stochastic filter. The tracking would be expected to make up for the low signal-to-noise ratio, this allowing one to "coherently" process successive images in order to beat down the noise and localize the object. Thus, "tracking" here does not refer to the usual notion of detecting then tracking: rather, we track in order to detect The problem then becomes one of choosing the appropriate image representation as well as the optimal (and necessarily nonlinear filter. We propose exact and approximate solutions using wavelets and the Zakai equation. The smoothness of the wavelets used is required in the derivation of the evolution equation for the conditional density giving the filter, and their orthogonality makes it possible to carry out actual computations of the Ito- and change-of-gauge-terms in the algorithm effectively.

Haddad, Ziad S.↗
NASA NTRS1998

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Truong, Son H.↗
NASA NTRS2000

An Indirect Mixed-Sensitivity Approach to Microgravity Vibration Isolation: The Exploitation of Kinematic Coupling In Frequency-weighting Design-Filter Selections

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation systems planned for use with the International Space Station have been appropriately modeled using relative position relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to these state-space models, in order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice, however, the kinematic coupling among the various states can lead, through the associated frequency-weighting-filters, to conflicting demands on the Riccati design "machinery." The results can be numerically ill-conditioned regulator and estimator Riccati equations and/or reduced intuition in the design process. In addition, kinematic coupling can result in a redundancy in the demands imposed by the frequency weights. Failure properly to account for this type of coupling can lead to an unnecessary increase in controller dimensionality and, in turn, controller complexity. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, R. David↗
NASA NTRS1999

Frequency-Weighting Filter Selection, for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation systems planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to these state-space models, in order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice, however, since there is a kinematic relationship among the various states, any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, Roy David↗
NASA NTRS2001

Attitude Representations for Kalman Filtering

The four-component quaternion has the lowest dimensionality possible for a globally nonsingular attitude representation, it represents the attitude matrix as a homogeneous quadratic function, and its dynamic propagation equation is bilinear in the quaternion and the angular velocity. The quaternion is required to obey a unit norm constraint, though, so Kalman filters often employ a quaternion for the global attitude estimate and a three-component representation for small errors about the estimate. We consider these mixed attitude representations for both a first-order Extended Kalman filter and a second-order filter, as well for quaternion-norm-preserving attitude propagation.

Markley, F. Landis↗
NASA NTRS2000

Frequency-Weighting Filter Selection for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation system planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to them state-space models, In order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice. however, since there Is a kinematic relationship among the various states. any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, R. David↗
NASA NTRS2000

An Indirect Mixed-Sensitivity Approach to Microgravity Vibration Isolation: The Exploitation of Kinematic Coupling In Frequency-Weighting Design-Filter Selections

Many space science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation systems planned for use with the International Space Station have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency design filters can be applied to these state-space models, in order to develop optimal H, or mixed-norm controllers with desired stability- and performance characteristics. In practice. however, the kinematic coupling among the various states can lead, through the associated frequency-weighting-filters, to conflicting demands on the Riccati design "machinery." The results can be numerically ill-conditioned regulator and estimator Riccati equations and/or reduced intuition in the design process. In addition, kinematic coupling can result in a redundancy in the demands imposed by the frequency weights. Failure properly to account for this type of coupling can lead to an unnecessary increase in controller dimensionality and, in turn, controller complexity. This paper suggests a rational approach to the assignment of frequency weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, R. David↗