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At least 397 records · Page 22

Dynamic data acquisition, reduction, and analysis for the identification of high-speed compressor component post-stability characteristics

A compressor test was conducted in which transient data were obtained for the purpose of identifying the high-speed post-stability characteristics. The transient, surge-cycle nature of high-speed post-stability operation precludes the possibility of obtaining the characteristics in a steady-state manner, as is possible during low-speed poststability operation, which is characterized by quasi-steady rotating-stall behavior. Specialized compressor instrumentation was developed and was used to obtain the necessary surge-cycle performance data, which were then digitized, filtered, and analyzed. The high-speed post-stability characteristics were obtained through the use of a maximum likelihood-parameter estimation technique. The estimated characteristics were found to be insensitive to the presence of measurement noise and unmodelled system dynamics, but the compressor time-response constants, which were also estimated, were more sensitive to these same disturbances.

Dvorak, S. D.↗

Guest Investigator Studies with the Compton Gamma Ray Observatory

The cumulative all-sky survey by the Compton Gamma Ray Observatory (CGRO), composed of data acquired during the first three years of the mission, included a number of regions of very limited exposure. The most glaring deficiency in coverage was toward the region of the South Galactic Pole (SGP), which received significantly less exposure than other directions- by a factor of at least 2 to 3. Furthermore, nearly all of the SGP exposure was accumulated during the first year of the mission. Since blazars are known to be time-variable, and of unknown duty cycle, a pointing of the CCRO in that direction was considered highly desirable, and long overdue. In addition, data gathered from a pointing toward the SGP and its comparison with comprehensive data available for the North Galactic Pole would be extremely valuable to investigators studying the extragalactic diffuse emission. The reasons outlined above prompted our initiation of a Cycle 4 campaign to systematically search with EGRET and COMPTEL for gamma-ray emission from sources near the South Galactic Pole. The Cycle 4 SGP campaign consisted of tnvo 14-day observations separated in in time by approximately 10 months. The temporal separation of the observations was requested to allow a test for possible variations in the detected sources. Our primary targets were 38 FSRQs which lie within 30 degrees of the SGP, and which satisfy the basic criteria for candidate gamma-ray AGNs,flat-spectrum radio sources, many of which exhibit blazar-type properties). These targets were selected from the standard references, and from the available on-line databases (e.g., the NASA Extragalactic Database, NED), as the most promising AGN targets in the vicinity of the SGP. A 30 radius from the SGP was chosen as the boundary of our survey, since the selected targets would then fall within the most sensitive portion of the fields of view of EGRET and COMPTEL (i.e., within a 30 zenith angle), for a CGRO pointing directed exactly at the SGP. Our South Galactic Pole Survey yielded a number of exciting results. The EGRET data were analyzed using the maximum likelihood techniques to estimate the intensity, spectrum, and position of gamma-ray sources in the field of view. Our analysis revealed four sources at energies greater than 100 MeV with likelihood ratios corresponding to greater than 30 detections (Vestrand et al. 1996). One of the sources is associated with the well known gamma-ray blazar PKS 0208-512, but the other three were previously unknown. Among the new detections was PKS 2155-304 which is often considered a prototype of the x-ray selected BL Lacs. PKS 2155-304, which was also detected at hard x-ray energies by CGRO/OSSE, is one of the brightest BL Lac objects in the sky at optical through x-ray energies and has a history of rapid, strong multiwavelength variability. As such, it has been the subject of intensive, contemporaneous, multiwavelength monitoring covering radio frequencies to x-ray energies.

Vestrand, W. T.↗

Historical Study of Radiation Exposures and the Incidence of Cataracts in Astronauts

For over 35 years, astronauts in low Earth orbit or on missions to the moon have been exposed to space radiation comprised of high-energy protons, heavy ions, and secondary neutrons. We reviewed the radiation exposures received by astronauts in space and on Earth, and presented results from the first epidemiological study of cataract incidence in the astronauts. Our data suggested an increased risk for cataracts from space radiation exposures. Using parametric survival analysis and the maximum likelihood method, we estimated the dose-response and age distribution for cataract incidence in astronauts by space radiation. Considering the high-LET dose contributions on specific space missions as well as data from animal studies with neutrons and heavy ions, suggested a linear response with no dose-threshold for cataracts. However, there are unanswered questions related to the importance and the definition of clinically significant cataracts commonly used in radiation protection, especially in light of epidemiological data suggesting that the probability that sub-clinical cataracts will progress is highly dependent on the age at which cataracts appear. We briefly describe a new study that will address the measurement of cataract progression-rates in astronauts and a ground-based comparison group.

Cucinotta, F. A.↗

Historical Study of Radiation Exposures and the Incidence of Cataracts in Astronauts

For over 35 years, astronauts in low Earth orbit or on missions to the moon have been exposed to space radiation comprised of high-energy protons, heavy ions, and secondary neutrons. We reviewed the radiation exposures received by astronauts in space and on Earth, and presented results from the first epidemiological study of cataract incidence in the astronauts. Our data suggested an increased risk for cataracts from space radiation exposures*. Using parametric survival analysis and the maximum likelihood method, we estimated the dose-response and age distribution for cataract incidence in astronauts by space radiation. Considering the high-LET dose contributions on specific space missions as well as data from animal studies with neutrons and heavy ions, suggested a linear response with no dose-threshold for cataracts. However, there are unanswered questions related to the importance and the definition of "clinically significant" cataracts commonly used in radiation protection, especially in light of epidemiological data suggesting that the probability that "sub-clinical" cataracts will progress is highly dependent on the age at which cataracts appear. We briefly describe a new study that will address the measurement of cataract progression-rates in astronauts and a ground-based comparison group.

Cucinotta, F. A.↗

Selecting class weights to minimize classification bias in acreage estimation

Preliminary results of experiments being performed to select optimal class weights for use with the maximum likelihood classifier in acreage estimation using remote sensor imagery are presented. These weights will be optimal in the sense that the bias will be minimized in the proportion estimate obtained from the classification results by sample counting. The procedure was tested using Landsat MSS data from an 8 by 9.6 km area of ground truth in Finney County, Kansas.

Belcher, W. M.↗

Bayesian estimation of normal mixture parameters

A Bayesian, or penalized maximum likelihood, approach to the problem of estimating the parameters of a mixture of multivariate normal distributions is proposed. The Bayesian formulation eliminates the problem of singularities in the likelihood function and results in an attractive EM-like procedure. Although the question of consistency is not settled, it is suggested that the proposed method has certain advantages over both the constrained and unconstrained maximum likelihood procedures.

Peters, C.↗

On-line estimation of error covariance parameters for atmospheric data assimilation

A simple scheme is presented for on-line estimation of covariance parameters in statistical data assimilation systems. The scheme is based on a maximum-likelihood approach in which estimates are produced on the basis of a single batch of simultaneous observations. Simple-sample covariance estimation is reasonable as long as the number of available observations exceeds the number of tunable parameters by two or three orders of magnitude. Not much is known at present about model error associated with actual forecast systems. Our scheme can be used to estimate some important statistical model error parameters such as regionally averaged variances or characteristic correlation length scales. The advantage of the single-sample approach is that it does not rely on any assumptions about the temporal behavior of the covariance parameters: time-dependent parameter estimates can be continuously adjusted on the basis of current observations. This is of practical importance since it is likely to be the case that both model error and observation error strongly depend on the actual state of the atmosphere. The single-sample estimation scheme can be incorporated into any four-dimensional statistical data assimilation system that involves explicit calculation of forecast error covariances, including optimal interpolation (OI) and the simplified Kalman filter (SKF). The computational cost of the scheme is high but not prohibitive; on-line estimation of one or two covariance parameters in each analysis box of an operational bozed-OI system is currently feasible. A number of numerical experiments performed with an adaptive SKF and an adaptive version of OI, using a linear two-dimensional shallow-water model and artificially generated model error are described. The performance of the nonadaptive versions of these methods turns out to depend rather strongly on correct specification of model error parameters. These parameters are estimated under a variety of conditions, including uniformly distributed model error and time-dependent model error statistics.

Dee, Dick P.↗

Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence

A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.

Mark, W. D.↗

On-line parameter estimation using a high sensitivity estimator

An on-line parameter identification method is presented. The method is based on a recursive formulation of the maximum likelihood method, with a significant modification on the gains of the state estimator. In the conventional maximum likelihood method, the Kalman gains are used in the state estimator. This produces unbiased, minimum variance parameter estimates in the presence of process noise and measurement noise, but it also slows the convergence rate when the identification is done on-line. Here we suggest choosing the gains to maximize a measure of the sensitivities of the state estimates to parameter variations. One such criterion is to minimize the trace of the inverse information matrix. This increases the convergence rate significantly. After one or two time constants, the gains are switched to the Kalman values to assure unbiased, minimum-variance estimates. The state estimate will initially be nonoptimal, and may not be adequate for control purposes. In this case, a parallel Kalman filter which uses the identifier's parameter estimates can be used. This method is applied here for the identification of a simple first-order system, and for the identification of short-period stability derivatives of an F-8 aircraft from simulated data.

Mishne, D.↗

Identifiability of unknown noise covariance matrices for some special cases of a linear, time-invariant, discrete-time dynamic system

Two off-line schemes are proposed for the identification of unknown noise covariance matrices Q and R of a discrete-time dynamic system. The first scheme is based on a maximum a posteriori cost function utilizing smoothed state estimates, while the second is based on a maximum likelihood cost function utilizing filtered state estimates. Sensitivity of the cost functions to Q and R is analyzed for the following cases: (1) single-input single-output systems; (2) multiinput single-output systems; and (3) single-input multioutput systems with a diagonal R. Identifiability criteria are presented for the cases considered and demonstrated by examples.

Tsang, W. L.↗

Effects of wing modification on an aircraft's aerodynamic parameters as determined from flight data

A study of the effects of four wing-leading-edge modifications on a general aviation aircraft's stability and control parameters is presented. Flight data from the basic aircraft configuration and configurations with wing modifications are analyzed to determine each wing geometry's stability and control parameters. The parameter estimates and aerodynamic model forms are obtained using the stepwise regression and maximum likelihood techniques. The resulting parameter estimates and aerodynamic models are verified using vortex-lattice theory and by analysis of each model's ability to predict aircraft behavior. Comparisons of the stability and control derivative estimates from the basic wing and the four leading-edge modifications are accomplished so that the effects of each modification on aircraft stability and control derivatives can be determined.

Hess, R. A.↗

Stability and Control Estimation Flight Test Results for the SR-71 Aircraft With Externally Mounted Experiments

A maximum-likelihood output-error parameter estimation technique is used to obtain stability and control derivatives for the NASA Dryden Flight Research Center SR-71A airplane and for configurations that include experiments externally mounted to the top of the fuselage. This research is being done as part of the envelope clearance for the new experiment configurations. Flight data are obtained at speeds ranging from Mach 0.4 to Mach 3.0, with an extensive amount of test points at approximately Mach 1.0. Pilot-input pitch and yaw-roll doublets are used to obtain the data. This report defines the parameter estimation technique used, presents stability and control derivative results, and compares the derivatives for the three configurations tested. The experimental configurations studied generally show acceptable stability, control, trim, and handling qualities throughout the Mach regimes tested. The reduction of directional stability for the experimental configurations is the most significant aerodynamic effect measured and identified as a design constraint for future experimental configurations. This report also shows the significant effects of aircraft flexibility on the stability and control derivatives.

Moes, Timothy R.↗

A Recommended Procedure for Estimating the Cosmic Ray Spectral Parameter of a Simple Power Law

A simple power law model consisting of a single spectral index a(f(sub i)) is believed to be an adequate description of the galactic cosmic ray (GQ proton flux at energies below 1013 eV. Two procedures for estimating a(f(sub i)), referred as (1) the method of moments, and (2) maximum likelihood, are developed and their statistical performance compared. I concluded that the maximum likelihood procedure attains the most desirable statistical properties and is hence the recommended statistic estimation procedure for estimating a1. The maximum likelihood procedure is then generalized for application to a set of real cosmic ray data and thereby makes this approach applicable to existing cosmic ray data sets. Several other important results, such as the relationship between collecting power and detector energy resolution, as well as inclusion of a non-Gaussian detector response function, are presented. These results have many practical benefits in the design phase of a cosmic ray detector because they permit instrument developers to make important trade studies in design parameters as a function of one of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose practical limits to the design envelope.

Howell, Leonard W.↗

Modeling of solar oscillation power spectra

To produce accurate estimates of the line-profile parameters of a model used to represent the spectral features in a solar oscillation power spectrum, it is necessary to (1) select the appropriate probability density function when deriving the maximum-likelihood function to be employed for the parameter estimation and (2) allow for the redistribution of spectral power caused by gaps in the data string. This paper describes a maximum-likelihood method for estimating the model parameters (based on the observed power spectrum statistics) that accounts for redistribution of spectral power caused by gaps in the data string, by convolving the model with the power spectrum of the observed window function. The accuracy and reliability of the method were tested using both artificial and authentic solar oscillation power spectrum data. A comparison of this method with various least-squares techniques is also presented.

Anderson, Edwin R.↗

Using Distributed Fiber-optic Strain Sensing to Estimate Generalized Modal Coordinates from Flight-test Data

A method for estimating the generalized modal coordinates of an aircraft during flight has been developed. The Fiber-optic Sensing System (FOSS) offers an efficient and cost-effective method of measuring the strain at thousands of points along the wings. The estimation of modal coordinates was implemented as a two-step process. First, a maximum likelihood method is used to estimate the statistical properties of the sensors and generalized modal coordinates. Second, the strain mode shapes from the finite element model are used along with the statistical properties from the first step to estimate the generalized modal coordinates over time. Using simulated data from the X-56A Multi-Utility Technology Testbed (MUTT), different methods of modal coordinate estimation were compared to demonstrate the benefits and weaknesses of each. These were compared against the exact solution and an ordinary least squares (a more traditional method) estimate. Modal coordinate estimation methods were then applied to flight-test data from the X-56A aircraft to show that the method continues to work well with actual test data. The new estimation method provides insights unavailable from more classical approaches.

Jeffrey Ouellette↗

Wind field model-based estimation of Seasat scatterometer winds

A model-based approach to estimating near-surface wind fields over the ocean from Seasat scatterometer (SASS) measurements is presented. The approach is a direct assimilation technique in which wind field model parameters are estimated directly from the scatterometer measurements of the radar backscatter of the ocean's surface using maximum likelihood principles. The wind field estimate is then computed from the estimated model parameters. The wind field model used in this approach is based on geostrophic approximation and on simplistic assumptions about the wind field vorticity and divergence but includes ageostrophic winds. Nine days of SASS data were processed to obtain unique wind estimates. Comparisons in performance to the traditional two-step (point-wise wind retrieval followed by ambiguity removal) wind estimate method and the model-based method are provided using both simulated radar backscatter measurements and actual SASS measurements. In the latter case the results are compared to wind fields determined using subjective ambiguity removal. While the traditional approach results in missing measurements and reduced effective swath width due to fore/aft beam cell coregistration problems, the model-based approach uses all available measurements to increase the effective swath width and to reduce data gaps. The results reveal that the model-based wind estimates have accuracy comparable to traditionally estimated winds with less 'noise' in the directional estimates, particularly at low wind speeds.

Long, David G.↗

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

multiscale↗

Maximum likelihood clustering with dependent feature trees

The decomposition of mixture density of the data into its normal component densities is considered. The densities are approximated with first order dependent feature trees using criteria of mutual information and distance measures. Expressions are presented for the criteria when the densities are Gaussian. By defining different typs of nodes in a general dependent feature tree, maximum likelihood equations are developed for the estimation of parameters using fixed point iterations. The field structure of the data is also taken into account in developing maximum likelihood equations. Experimental results from the processing of remotely sensed multispectral scanner imagery data are included.

Chittineni, C. B.↗