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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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NASA NTRS1984

A SAR correlation algorithm which accommodates large-range migration

This paper presents an algorithm for azimuth correlation of synthetic aperture radar (SAR) data with extraordinarily large-range migration which cannot be accommodated by the existing frequency domain interpolation approach used in current Seasat SAR processing. A mathematical model is provided for the SAR range-correlated point-target response both in the spatial and frequency domains. A simple and efficient processing algorithm derived from the exact two-dimensional correlation algorithm is given. This algorithm enables azimuth correlation by two cascaded one-dimensional correlation steps. The first step is to transform the range-correlated SAR data into the frequency domain in azimuth, followed by a newly developed range convolution filter to correct the range-dispersed spectrum of the range-correlated point-target response (RCPTR). The second step is the frequency-domain range migration correction approach for the azimuth compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large-range migration whereas previous methods were subject to a broadening of the impulse response along range.

Jin, M. Y.↗
NASA NTRS2007

Advanced Control Algorithms for Compensating the Phase Distortion Due to Transport Delay in Human-Machine Systems

The desire to create more complex visual scenes in modern flight simulators outpaces recent increases in processor speed. As a result, simulation transport delay remains a problem. New approaches for compensating the transport delay in a flight simulator have been developed and are presented in this report. The lead/lag filter, the McFarland compensator and the Sobiski/Cardullo state space filter are three prominent compensators. The lead/lag filter provides some phase lead, while introducing significant gain distortion in the same frequency interval. The McFarland predictor can compensate for much longer delay and cause smaller gain error in low frequencies than the lead/lag filter, but the gain distortion beyond the design frequency interval is still significant, and it also causes large spikes in prediction. Though, theoretically, the Sobiski/Cardullo predictor, a state space filter, can compensate the longest delay with the least gain distortion among the three, it has remained in laboratory use due to several limitations. The first novel compensator is an adaptive predictor that makes use of the Kalman filter algorithm in a unique manner. In this manner the predictor can accurately provide the desired amount of prediction, while significantly reducing the large spikes caused by the McFarland predictor. Among several simplified online adaptive predictors, this report illustrates mathematically why the stochastic approximation algorithm achieves the best compensation results. A second novel approach employed a reference aircraft dynamics model to implement a state space predictor on a flight simulator. The practical implementation formed the filter state vector from the operator s control input and the aircraft states. The relationship between the reference model and the compensator performance was investigated in great detail, and the best performing reference model was selected for implementation in the final tests. Theoretical analyses of data from offline simulations with time delay compensation show that both novel predictors effectively suppress the large spikes caused by the McFarland compensator. The phase errors of the three predictors are not significant. The adaptive predictor yields greater gain errors than the McFarland predictor for short delays (96 and 138 ms), but shows smaller errors for long delays (186 and 282 ms). The advantage of the adaptive predictor becomes more obvious for a longer time delay. Conversely, the state space predictor results in substantially smaller gain error than the other two predictors for all four delay cases.

Guo, Liwen↗
NASA NTRS2006

Advances in Measurement of Skin Friction in Airflow

The surface interferometric skin-friction (SISF) measurement system is an instrument for determining the distribution of surface shear stress (skin friction) on a wind-tunnel model. The SISF system utilizes the established oil-film interference method, along with advanced image-data-processing techniques and mathematical models that express the relationship between interferograms and skin friction, to determine the distribution of skin friction over an observed region of the surface of a model during a single wind-tunnel test. In the oil-film interference method, a wind-tunnel model is coated with a thin film of oil of known viscosity and is illuminated with quasi-monochromatic, collimated light, typically from a mercury lamp. The light reflected from the outer surface of the oil film interferes with the light reflected from the oil-covered surface of the model. In the present version of the oil-film interference method, a camera captures an image of the illuminated model and the image in the camera is modulated by the interference pattern. The interference pattern depends on the oil-thickness distribution on the observed surface, and this distribution can be extracted through analysis of the image acquired by the camera. The oil-film technique is augmented by a tracer technique for observing the streamline pattern. To make the streamlines visible, small dots of fluorescentchalk/oil mixture are placed on the model just before a test. During the test, the chalk particles are embedded in the oil flow and produce chalk streaks that mark the streamlines. The instantaneous rate of thinning of the oil film at a given position on the surface of the model can be expressed as a function of the instantaneous thickness, the skin-friction distribution on the surface, and the streamline pattern on the surface; the functional relationship is expressed by a mathematical model that is nonlinear in the oil-film thickness and is known simply as the thin-oil-film equation. From the image data acquired as described, the time-dependent oil-thickness distribution and streamline pattern are extracted and by inversion of the thin-oil-film equation it is then possible to determine the skin-friction distribution. In addition to a quasi-monochromatic light source, the SISF system includes a beam splitter and two video cameras equipped with filters for observing the same area on a model in different wavelength ranges, plus a frame grabber and a computer for digitizing the video images and processing the image data. One video camera acquires the interference pattern in a narrow wavelength range of the quasi-monochromatic source. The other video camera acquires the streamline image of fluorescence from the chalk in a nearby but wider wavelength range. The interference- pattern and fluorescence images are digitized, and the resulting data are processed by an algorithm that inverts the thin-oil-film equation to find the skin-friction distribution.

Brown, James L.↗
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 NTRS1985

Mathematical analysis study for radar data processing and enchancement. Part 2: Modeling of propagation path errors

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.

James, R.↗
NASA NTRS2000

Optimization of Microelectronic Devices for Sensor Applications

The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

Cwik, Tom↗
NASA NTRS2004

Validation and Improvement of SRTM Performance over Rugged Terrain

We have previously reported work related to basic technique development in phase unwrapping and generation of digital elevation models (DEM). In the final year of this work we have applied our technique work to the improvement of DEM's produced by SRTM. In particular, we have developed a rigorous mathematical algorithm and means to fill in missing data over rough terrain from other data sets. We illustrate this method by using a higher resolution, but globally less accurate, DEM produced by the TOPSAR airborne instrument over the Galapagos Islands to augment the SRTM data set in this area, We combine this data set with SRTM to use each set to fill in holes left over by the other imaging system. The infilling is done by first interpolating each data set using a prediction error filter that reproduces the same statistical characterization as exhibited by the entire data set within the interpolated region. After this procedure is implemented on each data set, the two are combined on a point by point basis with weights that reflect the accuracy of each data point in its original image. In areas that are better covered by SRTM, TOPSAR data are weighted down but still retain TOPSAR statistics. The reverse is true for regions better covered by TOPSAR. The resulting DEM passes statistical tests and appears quite feasible to the eye, but as this DEM is the best available for the region we cannot fully veri@ its accuracy. Spot checks with GPS points show that locally the technique results in a more comprehensive and accurate map than either data set alone.

Zebker, Howard A.↗
NASA NTRS2003

NASA Tech Briefs, October 2003

Topics covered include: Cryogenic Temperature-Gradient Foam/Substrate Tensile Tester; Flight Test of an Intelligent Flight-Control System; Slat Heater Boxes for Thermal Vacuum Testing; System for Testing Thermal Insulation of Pipes; Electrical-Impedance-Based Ice-Thickness Gauges; Simulation System for Training in Laparoscopic Surgery; Flasher Powered by Photovoltaic Cells and Ultracapacitors; Improved Autoassociative Neural Networks; Toroidal-Core Microinductors Biased by Permanent Magnets; Using Correlated Photons to Suppress Background Noise; Atmospheric-Fade-Tolerant Tracking and Pointing in Wireless Optical Communication; Curved Focal-Plane Arrays Using Back-Illuminated High-Purity Photodetectors; Software for Displaying Data from Planetary Rovers; Software for Refining or Coarsening Computational Grids; Software for Diagnosis of Multiple Coordinated Spacecraft; Software Helps Retrieve Information Relevant to the User; Software for Simulating a Complex Robot; Software for Planning Scientific Activities on Mars; Software for Training in Pre-College Mathematics; Switching and Rectification in Carbon-Nanotube Junctions; Scandia-and-Yttria-Stabilized Zirconia for Thermal Barriers; Environmentally Safer, Less Toxic Fire-Extinguishing Agents; Multiaxial Temperature- and Time-Dependent Failure Model; Cloverleaf Vibratory Microgyroscope with Integrated Post; Single-Vector Calibration of Wind-Tunnel Force Balances; Microgyroscope with Vibrating Post as Rotation Transducer; Continuous Tuning and Calibration of Vibratory Gyroscopes; Compact, Pneumatically Actuated Filter Shuttle; Improved Bearingless Switched-Reluctance Motor; Fluorescent Quantum Dots for Biological Labeling; Growing Three-Dimensional Corneal Tissue in a Bioreactor; Scanning Tunneling Optical Resonance Microscopy; The Micro-Arcsecond Metrology Testbed; Detecting Moving Targets by Use of Soliton Resonances; and Finite-Element Methods for Real-Time Simulation of Surgery.

Source record↗
NASA NTRS2012

Characterization of Material Response During Arc-Jet Testing with Optical Methods Status and Perspectives

The characterization of ablation and recession of heat shield materials during arc jet testing is an important step towards understanding the governing processes during these tests and therefore for a successful extrapolation of ground test data to flight. The behavior of ablative heat shield materials in a ground-based arc jet facility is usually monitored through measurement of temperature distributions (across the surface and in-depth), and through measurement of the final surface recession. These measurements are then used to calibrate/validate materials thermal response codes, which have mathematical models with reasonably good fidelity to the physics and chemistry of ablation, and codes thus calibrated are used for predicting material behavior in flight environments. However, these thermal measurements only indirectly characterize the pyrolysis processes within an ablative material pyrolysis is the main effect during ablation. Quantification of pyrolysis chemistry would therefore provide more definitive and useful data for validation of the material response codes. Information of the chemical products of ablation, to various levels of detail, can be obtained using optical methods. Suitable optical methods to measure the shape and composition of these layers (with emphasis on the blowing layer) during arc jet testing are: 1) optical emission spectroscopy (OES) 2) filtered imaging 3) laser induced fluorescence (LIF) and 4) absorption spectroscopy. Several attempts have been made to optically measure the material response of ablative materials during arc-jet testing. Most recently, NH and OH have been identified in the boundary layer of a PICA ablator. These species are suitable candidates for a detection through PLIF which would enable a spatially-resolved characterization of the blowing layer in terms of both its shape and composition. The recent emission spectroscopy data will be presented and future experiments for a qualitative and quantitative characterization of the material response of ablative materials during arc-jet testing will be discussed.

Winter, Michael↗
NASA NTRS1992

Linear polarization sensitivity specifications for space-borne instruments

The radiometric accuracy of space-borne instruments such as radiometers and spectroradiometers which make measurements of the earth and other celestial objects can be compromised by the linear polarization sensitivity (LPS) induced by the optical system. Most of these optical systems contain optical elements whose reflectance or transmission is polarization dependent, such as diffraction gratings, folding and scanning mirrors, dichroic filters, and optical fibers. Optical system incorporating such elements generally display linear polarization sensitivity; different linear polarization states incident with equal radiometric power will be measured as different power levels. If the incident polarization state is unknown, the linear polarization sensitivity cannot be compensated during the data reduction. The light reflected from the earth and other planets and moons is usually partially linearly polarized, but in a random distribution. Thus, to make accurate radiometric measurements of these bodies, a radiometer or spectrometer should have a low level of linear polarization sensitivity. This paper contains a mathematical description of LPS, contains references to systems which have imposed a LPS specification, describes some of the sources of LPS, describes how to model LPS by polarization ray tracing, and discusses methods to reduce the LPS of an optical system.

Maymon, Peter W.↗
NASA NTRS2012

Anomaly Detection in Test Equipment via Sliding Mode Observers

Nonlinear observers were originally developed based on the ideas of variable structure control, and for the purpose of detecting disturbances in complex systems. In this anomaly detection application, these observers were designed for estimating the distributed state of fluid flow in a pipe described by a class of advection equations. The observer algorithm uses collected data in a piping system to estimate the distributed system state (pressure and velocity along a pipe containing liquid gas propellant flow) using only boundary measurements. These estimates are then used to further estimate and localize possible anomalies such as leaks or foreign objects, and instrumentation metering problems such as incorrect flow meter orifice plate size. The observer algorithm has the following parts: a mathematical model of the fluid flow, observer control algorithm, and an anomaly identification algorithm. The main functional operation of the algorithm is in creating the sliding mode in the observer system implemented as software. Once the sliding mode starts in the system, the equivalent value of the discontinuous function in sliding mode can be obtained by filtering out the high-frequency chattering component. In control theory, "observers" are dynamic algorithms for the online estimation of the current state of a dynamic system by measurements of an output of the system. Classical linear observers can provide optimal estimates of a system state in case of uncertainty modeled by white noise. For nonlinear cases, the theory of nonlinear observers has been developed and its success is mainly due to the sliding mode approach. Using the mathematical theory of variable structure systems with sliding modes, the observer algorithm is designed in such a way that it steers the output of the model to the output of the system obtained via a variety of sensors, in spite of possible mismatches between the assumed model and actual system. The unique properties of sliding mode control allow not only control of the model internal states to the states of the real-life system, but also identification of the disturbance or anomaly that may occur.

Solano, Wanda M.↗
NASA NTRS1998

Signal Analysis of Helicopter Blade-Vortex-Interaction Acoustic Noise Data

Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.

Rogers, James C.↗
NASA NTRS1980

Satellite power system (SPS) magnetron tube assessment study

Taks performed to extend the data base and to define a technology development program for the magnetron directional amplifier for the SPS are reviewed. These include: (1) demonstrating the tracking of phase and amplitude of the microwave output to phase and amplitude references; (2) expanding the range of power over which the directional amplifier will operate; (3)recognizing the importance of amplitude control in overall system design and in simplifying power conditioning; (4) developing a preliminary design for the overall architecture of the power module; (5) demonstrating magnetron starting using the amplitude control system; (6) mathematically modelling and performing a computerized study of the pyrolytic graphite radiating fin; (7) defining the mass of the magnetic circuit for the SPS tube; (8) noise measurement; (9) achieving harmonic suppression by notch reflection filters; (10) estimating the mass of the transmitting antenna; (11) developing a magnetron package with power generation, phase control, and power condition functions; and (12) projecting magnetron package characteristics.

Source record↗
NASA NTRS2003

Software Searches for Better Spacecraft-Navigation Models

ADAPT is a computer program that searches for better mathematical models for spacecraft navigation. The task of tuning trajectory-determination models for interplanetary navigation is complex, requiring an intensive search of multiple dynamical and nondynamical models that yield trajectory solutions with minimal errors. By automating the search, ADAPT eases the task of human analysts and enables them to consider wider ranges of potential solutions. ADAPT uses genetic algorithms to search a range of relevant parameters in a user-selected design space to arrive at values for those parameters that best fit the measured spacecraft-tracking data. The user s guide for ADAPT reviews the theoretical basis of the program and presents two example applications. One example is that of selecting a solar-radiation model for the Mars Pathfinder (MPF) mission using MPF tracking data and an extended Kalman filter from prior spacecraft-navigation software. The second example is of the use of tracking data from the Stardust spacecraft mission combined with a pseudo-epoch-state batch filter and an empirical small-forces model to find improved impulse models for use during Stardust attitude adjustments.

Ely, Todd↗
NASA NTRS2007

POD Model Reconstruction for Gray-Box Fault Detection

Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.

Park, Han↗
NASA NTRS2010

Flexible Modes Control Using Sliding Mode Observers: Application to Ares I

The launch vehicle dynamics affected by bending and sloshing modes are considered. Attitude measurement data that are corrupted by flexible modes could yield instability of the vehicle dynamics. Flexible body and sloshing modes are reconstructed by sliding mode observers. The resultant estimates are used to remove the undesirable dynamics from the measurements, and the direct effects of sloshing and bending modes on the launch vehicle are compensated by means of a controller that is designed without taking the bending and sloshing modes into account. A linearized mathematical model of Ares I launch vehicle was derived based on FRACTAL, a linear model developed by NASA/MSFC. The compensated vehicle dynamics with a simple PID controller were studied for the launch vehicle model that included two bending modes, two slosh modes and actuator dynamics. A simulation study demonstrated stable and accurate performance of the flight control system with the augmented simple PID controller without the use of traditional linear bending filters.

Shtessel, Yuri B.↗
NASA NTRS2004

Pseudo-Linear Attitude Determination of Spinning Spacecraft

This paper presents the overall mathematical model and results from pseudo linear recursive estimators of attitude and rate for a spinning spacecraft. The measurements considered are vector measurements obtained by sun-sensors, fixed head star trackers, horizon sensors, and three axis magnetometers. Two filters are proposed for estimating the attitude as well as the angular rate vector. One filter, called the q-Filter, yields the attitude estimate as a quaternion estimate, and the other filter, called the D-Filter, yields the estimated direction cosine matrix. Because the spacecraft is gyro-less, Euler s equation of angular motion of rigid bodies is used to enable the estimation of the angular velocity. A simpler Markov model is suggested as a replacement for Euler's equation in the case where the vector measurements are obtained at high rates relative to the spacecraft angular rate. The performance of the two filters is examined using simulated data.

Bar-Itzhack, Itzhack Y.↗
NASA NTRS1983

A mathematical model for efficient estimation of aircraft motions

In the usual formulation of the aircraft state-estimation problem, motions along a flight trajectory are represented by a plant consisting of nonlinear state and measurement models. Problem solution using this formulation requires that both state- and measurement-dependent Jacobian matrices be evaluated along any trajectory. In this paper it is shown that a set of state variables can be chosen to realize a linear state model of very simple form, such that all nonlinearities appear in the measurement model. The potential advantage of the new formulation is computational: the Jacobian matrix corresponding to a linear state model is constant, a feature that should outweigh the fact that the measurement model is more complicated than in the conventinal formulation. To compare the modeling methods, aircraft motions from typical flight-test and accident data were estimated, using each formulation with the same off-line (smoothing) algorithm. The results of these experiments, reported in the paper, demonstrate clearly the computational superiority of the linear state-variable formulation. The procedure advocated here may be extended to other nonlinear estimation problems, including on-line (filtering) applications.

Bach, R. E., Jr.↗