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NASA NTRS1974

Optimal design of an unsupervised adaptive classifier with unknown priors

An adaptive detection scheme for M hypotheses was analyzed. It was assumed that the probability density function under each hypothesis was known, and that the prior probabilities of the M hypotheses were unknown and sequentially estimated. Each observation vector was classified using the current estimate of the prior probabilities. Using a set of nonlinear transformations, and applying stochastic approximation theory, an optimally converging adaptive detection and estimation scheme was designed. The optimality of the scheme lies in the fact that convergence to the true prior probabilities is ensured, and that the asymptotic error variance is minimum, for the class of nonlinear transformations considered. An expression for the asymptotic mean square error variance of the scheme was also obtained.

Kazakos, D.↗

NASA NTRS1984

Research in computer science

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.

Ortega, J. M.↗

NASA NTRS1991

A scheme for reducing the effect of selective availability on precise geodetic measurements from the Global Positioning System

From March to August 1990, the signals transmitted by the Block II satellites of the GPS were dithered under a policy of 'Selective Availability' (SA). The dithering appears as an about 10 to the -10th deviation of the satellite oscillator frequency, which, when accumulated over several minutes, can produce an error of about 100 cycles in the model for carrier beat phase. Differencing between simultaneously sampling receivers minimizes the error. If, however, the receivers do not sample simultaneously, it is necessary to model the frequency deviation. Such a model is here applied to data collected in March 1990 by TI4100 and Minimac receivers sampling at times separated by 0.92 s. Applying the algorithm significantly improves the rms scatter of the estimated relative position vectors. The rms scatter from a data set including dithered satellites is similar for both simultaneously and nonsimultaneously sampling receivers, a result which indicates that SA can be adequately modeled.

Feigl, Kurt L.↗

NASA NTRS1984

A SEASAT SASS simulation experiment to quantify the errors related to a + or - 3 hour intermittent assimilation technique

A series of SEASAT repeat orbits over a sequence of best Low center positions is simulated by using the Seatrak satellite calculator. These Low centers are, upon appropriate interpolation to hourly positions, Located at various times during the + or - 3 hour assimilation cycle. Error analysis for a sample of best cyclone center positions taken from the Atlantic and Pacific oceans reveals a minimum average error of 1.1 deg of Longitude and a standard deviation of 0.9 deg of Longitude. The magnitude of the average error seems to suggest that by utilizing the + or - 3 hour window in the assimilation cycle, the quality of the SASS data is degraded to the Level of the background. A further consequence of this assimilation scheme is the effect which is manifested as a result of the blending of two or more more juxtaposed vector winds, generally possessing different properties (vector quantity and time). The outcome of this is to reduce gradients in the wind field and to deform isobaric and frontal patterns of the intial field.

Sylvester, W. B.↗

NASA NTRS1994

Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude

Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.

Sedlak, J.↗

NASA NTRS2004

The Wind and Temperature Spectrometer (WTS) in the Atmospheric Neutral Density Experiment (ANDE) Satellite

Miniaturization efforts in new spectrometers for ionosphere/thermosphere investigations of the ion-drifts and neutral winds and corresponding temperatures make possible very light (about 250 g) packages consuming less than 0.4 W. Previously described, our approach measures the angular and energy distributions of neutral atoms and molecules (or ions) in two perpendicular planes; using those distributions to determine the full wind vector, the temperature and the relative densities of O and N2, as required for the ANDE mission. The measurements require two separate electron impact ion sources each with its own electron beam cathode. We have developed a low-temperature thermionic emission cathode that delivers 1 mA electron current at 80 mW power, making it possible to operate neutral wind-temperature experiments for the first time with powers less than 0.5 W. Advances in the ion optics of the energy-angle spectrometer enhance the energy resolution-aperture product more than a factor of 3 to enable energy resolutions of a few percent with large apertures. With these technology improvements it is now possible to obtain the full neutral wind vector, temperature and O/N2, density ratio once per second in a 250g/0.4W package with sensitivity up to about 500 km altitude in the thermosphere. We will describe the WTS as deployed in ANDE and show simulated data with the non-linear least squares analysis to illustrate expected performance of the WTS in the estimated errors in the three components of the wind, the temperature, and the relative densities.

Herrero, F. A.↗

NASA NTRS2009

Bounded-Angle Iterative Decoding of LDPC Codes

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Dolinar, Samuel↗

NASA NTRS1992

A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

Shehadeh, Hana↗

NASA NTRS2004

ENSO Bred Vectors in Coupled Ocean-Atmosphere General Circulation Models

The breeding method has been implemented in the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Coupled General Circulation Model (CGCM) with the goal of improving operational seasonal to interannual climate predictions through ensemble forecasting and data assimilation. The coupled instability as cap'tured by the breeding method is the first attempt to isolate the evolving ENSO instability and its corresponding global atmospheric response in a fully coupled ocean-atmosphere GCM. Our results show that the growth rate of the coupled bred vectors (BV) peaks at about 3 months before a background ENSO event. The dominant growing BV modes are reminiscent of the background ENSO anomalies and show a strong tropical response with wind/SST/thermocline interrelated in a manner similar to the background ENSO mode. They exhibit larger amplitudes in the eastern tropical Pacific, reflecting the natural dynamical sensitivity associated with the presence of the shallow thermocline. Moreover, the extratropical perturbations associated with these coupled BV modes reveal the variations related to the atmospheric teleconnection patterns associated with background ENSO variability, e.g. over the North Pacific and North America. A similar experiment was carried out with the NCEP/CFS03 CGCM. Comparisons between bred vectors from the NSIPP CGCM and NCEP/CFS03 CGCM demonstrate the robustness of the results. Our results strongly suggest that the breeding method can serve as a natural filter to identify the slowly varying, coupled instabilities in a coupled GCM, which can be used to construct ensemble perturbations for ensemble forecasts and to estimate the coupled background error covariance for coupled data assimilation.

Yang, S. C.↗

NASA NTRS2008

Multichannel Networked Phasemeter Readout and Analysis

Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

Edmonds, Karina↗

NASA NTRS1985

Vector magnetic field observations with the Haleakala polarimeter

Several enhancements were recently made to the Haleakala polarimeter. Linear array detectors provide simultaneous resolution over a 3-A wavelength range, with spectral resolution of 40 mA. Optical fibers are now used to carry the intensity-modulated light from the rotating quarter-wave plate polarimeter to the echelle spectrometer, permitting its removal from the spar to a more stable environment. These changes, together with improved quarter-wave plates, reduced systematic errors to a few parts in 10,000 for routine observations. Examples of Stokes profiles and derived magnetic field maps are presented.

Mickey, D. L.↗

NASA NTRS1972

An isoparametric quadrilateral membrane element for NASTRAN

The geometric and kinematic properties of the element are described, along with development of the matrices and vectors which characterize the element. The necessity for considering small deviations from element planeness is discussed, and the approach taken to account for these deviations is described. The improved accuracy over the existing quadrilateral membrane is indicated by a sample calculation for which an analytical solution is available from beam theory. For the same finite element idealization, the errors in maximum displacement and stress were significantly reduced.

Adelman, H. M.↗

NASA NTRS1991

Solution-adaptive program SADAP3D

A generic solution-adaptive grid program based on an error equi-distribution concept has been developed for use in complex multidimensional flows. The capability of a generic, user-friendly, multidimensional algorithm is demonstrated using several complex 3D flows in high-speed regimes. A simple scheme enforces the continuity of grid spacing along each currently adapted grid line as the computation proceeds. Calculation of normal vectors at each point of a grid plane is enhanced. The grid movement is automatically controlled by reinstating grid-spacing continuity locally in the mainstream of the unidirectional computation. It is concluded that the scheme can be readily coupled with many flow solvers to enhance accuracy and efficiency of solutions.

Djomehri, M. J.↗

NASA NTRS1995

A Bayesian approach to microwave precipitation profile retrieval

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. A multivariate lognormal prior probability distribution contains the covariance information about hydrometeor distribution that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrieval method is tested with data from the Advanced Microwave Precipitation Radiometer (10, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify the retrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysical information, and future improvements to the algorithm are suggested.

Evans, K. Franklin↗

NASA NTRS2000

Enhancement of Directional Ambiguity Removal Skill in Scatterometer Data Processing Using Planetary Boundary Layer Models

Planetary boundary layer (PBL) models are utilized to enhance directional ambiguity removal skill in scatterometer data processing. The ambiguity in wind direction retrieved from scatterometer measurements is removed with the aid of physical directional information obtained from PBL models. This technique is based on the observation that sea level pressure is scalar and its field is more coherent than the corresponding wind. An initial wind field obtained from the scatterometer measurements is used to derive a pressure field with a PBL model. After filtering small-scale noise in the derived pressure field, a wind field is generated with an inverted PBL model. This derived wind information is then used to remove wind vector ambiguities in the scatterometer data. It is found that the ambiguity removal skill can be improved when the new technique is used properly in conjunction with the median filter being used for scatterometer wind dealiasing at JPL. The new technique is applied to regions of cyclone systems which are important for accurate weather prediction but where the errors of ambiguity removal are often large.

Kim, Young-Joon↗

NASA NTRS2001

Analysis of the Westland Data Set

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗

NASA NTRS2000

Condition Monitoring for Helicopter Data

In this paper the classical "Westland" set of empirical accelerometer helicopter data is analyzed with the aim of condition monitoring for diagnostic purposes. The goal is to determine features for failure events from these data, via a proprietary signal processing toolbox, and to weigh these according to a variety of classification algorithms. As regards signal processing, it appears that the autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; it has also been found that augmentation of these by harmonic and other parameters can improve classification significantly. As regards classification, several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior on training data and is thus able to quantify probability of error in an exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗

NASA NTRS1992

The spin vector of Venus determined from Magellan data

A control network of the north polar region of Venus has been established by selecting and measuring control points on full-resolution radar strips. The measurements were incorporated into a least-squares adjustment program that improved initial estimates of the coordinates of the control points, pole direction, and rotation rate of Venus. The current dataset contains 4206 measurements of 606 points on 619 radar strips. The accuracy of the determination is driven by spacecraft ephemeris errors. An accurate estimate of the rotation period of Venus was obtained by applying an ephemeris improvement technique. The second cycle closure orbits improved ephemeris solutions for 40 orbits (376-384, 520-528, 588-592, 658-668, 1002-1010, 1408-1412, 1746-1764, and 2166-2170) are included and fixed in the geodetic control computations, thus trying the network to the J2000 coordinate system.

Davies, M. E.↗