SEARCH · Engineering Papers

Results for “likelihood”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS1991

Likelihood estimation for distributed parameter models for NASA Mini-MAST truss

A maximum likelihood estimation for distributed parameter models of large flexible structures was formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics or finite element models. The closed form solutions for the partial differential equations with corresponding boundary conditions were derived. The closed-form expressions of sensitivity functions led to highly efficient algorithms for analyzing ground or on-orbit test results. For an illustration of this approach, experimental data of the NASA Mini-MAST truss was used. The estimations of modal properties involve lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.

Shen, Ji-Yao↗

NASA NTRS1986

Process for detecting the likelihood of ice formation, ice warning system for carrying out the process, and utilization thereof

An ice warning system comprising a diaphragm set into vibration at one of its frequencies of resonance by a piezoelectric cell. The diaphragm is coupled thermally to a metallic plate alternately cooled and heated respectively below and above the ambient temperature by Peltier elements connected to a reversible DC current generator. A microprocessor measures any variation of the resonance frequency caused by a deposit of ice on the diaphragm during the cooling or heating periods and delivers an alarm signal if this variation of frequency reaches and/ or exceeds a predetermined value. The microprocessor controls the period, intensity and direction of the current delivered by the DC current generator as a function of the ambient temperature and the temperature of the diaphragm. The ice warning system is preferably utilized in the aeronautical field for indicating the likelihood of natural ice formation on the engines and the wings of aircraft.

Martin Lustenberger↗

NASA NTRS1990

Orthogonal series generalized likelihood ratio test for failure detection and isolation

A new failure detection and isolation algorithm for linear dynamic systems is presented. This algorithm, the Orthogonal Series Generalized Likelihood Ratio (OSGLR) test, is based on the assumption that the failure modes of interest can be represented by truncated series expansions. This assumption leads to a failure detection algorithm with several desirable properties. Computer simulation results are presented for the detection of the failures of actuators and sensors of a C-130 aircraft. The results show that the OSGLR test generally performs as well as the GLR test in terms of time to detect a failure and is more robust to failure mode uncertainty. However, the OSGLR test is also somewhat more sensitive to modeling errors than the GLR test.

Hall, Steven R.↗

NASA NTRS1991

A PC-based hardware implementation of the maximum-likelihood classifier for the Shuttle Ice Detection System

A PC-based near-real time implementation of a two-channel maximum-likelihood classifier is described. The statistical distribution of the reflectance characteristics of ice, frost, and water formation on spray-on-foam-insulation, which covers the External Tank surface of the Space Shuttle, is acquired. The classification technique is based on these statistics. The computer, set in either a training or a classifying mode, learns the statistics of the various classes, or produces a color-coded image denoting the respective categories of classification. The classified results are memory-mapped for efficiency. The speed of the classification process is only limited by the speed of the digital frame grabber and the software that interfaces the frame grabber to the monitor. The process took 4 seconds for a 512 x 480 pixel image.

Jaggi, S.↗

NASA NTRS1990

Modelling default and likelihood reasoning as probabilistic reasoning

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. Likely and by default are in fact treated as duals in the same sense as possibility and necessity. To model these four forms probabilistically, a qualitative default probabilistic (QDP) logic and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequent results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance.

Buntine, Wray↗

NASA NTRS1990

Modelling default and likelihood reasoning as probabilistic

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. 'Likely' and 'by default' are in fact treated as duals in the same sense as 'possibility' and 'necessity'. To model these four forms probabilistically, a logic QDP and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequence results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance.

Buntine, Wray↗

NASA NTRS1990

Maximum likelihood estimates of polar motion parameters

Two estimators developed by Jeffreys (1940, 1968) are described and used in conjunction with polar-motion data to determine the frequency (Fc) and quality factor (Qc) of the Chandler wobble. Data are taken from a monthly polar-motion series, satellite laser-ranging results, and optical astrometry and intercompared for use via interpolation techniques. Maximum likelihood arguments were employed to develop the estimators, and the assumption that polar motion relates to a Gaussian random process is assessed in terms of the accuracies of the estimators. The present results agree with those from Jeffreys' earlier study but are inconsistent with the later estimator; a Monte Carlo evaluation of the estimators confirms that the 1968 method is more accurate. The later estimator method shows good performance because the Fourier coefficients derived from the data have signal/noise levels that are superior to those for an individual datum. The method is shown to be valuable for general spectral-analysis problems in which isolated peaks must be analyzed from noisy data.

Wilson, Clark R.↗

NASA NTRS1992

Likelihood estimation for distributed parameter models of large beam-like structures

A maximum likelihood estimation for distributed parameter models of large flexible structures was formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics or finite element models. The closed form solutions for the partial differential equations with corresponding boundary conditions were derived. The closed-form expressions of sensitivity functions led to highly efficient algorithms for analyzing ground or on-orbit test results. For an illustration of this approach, experimental data of the NASA Mini-Mast truss was used. The estimations of modal properties involve lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.

Shen, J.-Y.↗

NASA NTRS1992

Determination of the stability and control derivatives of the F/A-18 HARV from flight data using the maximum likelihood method

The research being conducted pertains to the determination of the stability and control derivatives of the F/A-18 High Alpha Research Vehicle (HARV) from flight data using the Maximum Likelihood Method. The document outlines the approach used in the parameter estimation (PID) process and briefly describes the mathematical modeling of the F/A-18 HARV and the maneuvers designed to generate a sufficient data base for the PID research.

Napolitano, Marcello R.↗

NASA NTRS1992

Incorporation of spatial information in Bayesian image reconstruction - The maximum residual likelihood criterion

We have developed a new figure of merit, a 'maximum-residual-likelihood' (MRL) statistic, for the goodness of fit for Bayesian image restoration which explicitly incorporates spatial information. The MRL constraint provides a natural means of incorporating the prior knowledge that the residuals contain no spatial structure through the autocorrelation function of the residuals. We demonstrate that this statistic follows a Chi-square distribution and that forcing this statistic to have its most probable value leads to a restored image whose residuals are consistent with the noise model. Our numerical experiments suggest that image restoration using the MRL statistic alone is numerically robust and produces results which are independent of the initial guess for the restored image. However, we caution that using the MRL statistic without an image prior can result in overresolution in low SNR portions of the image.

Pina, R. K.↗

NASA NTRS1992

An extended-source spatial acquisition process based on maximum likelihood criterion for planetary optical communications

This paper describes an extended-source spatial acquisition process based on the maximum likelihood criterion for interplanetary optical communications. The objective is to use the sun-lit Earth image as a receiver beacon and point the transmitter laser to the Earth-based receiver to establish a communication path. The process assumes the existence of a reference image. The uncertainties between the reference image and the received image are modeled as additive white Gaussian disturbances. It has been shown that the optimal spatial acquisition requires solving two nonlinear equations to estimate the coordinates of the transceiver from the received camera image in the transformed domain. The optimal solution can be obtained iteratively by solving two linear equations. Numerical results using a sample sun-lit Earth as a reference image demonstrate that sub-pixel resolutions can be achieved in a high disturbance environment. Spatial resolution is quantified by Cramer-Rao lower bounds.

Yan, Tsun-Yee↗

NASA NTRS1988

Maximum likelihood identification for large space structures

This paper examines the use of on-orbit identification based on Maximum Likelihood Estimation (MLE) to provide these high-order, high-accuracy control design models for large space structures (LSS's). First, it outlines a general MLE identification algorithm, together with a covariance-analysis procedure to assess algorithm performance in terms of systematic and stochastic errors. Next, it examines various simplifications appropriate for the LSS identification application. Simplified analytical performance results are presented, as are numerical results to support these analyses. Finally, a graphical interpretation of these results is given.

Barrett, Michael F.↗

NASA NTRS1992

Maximum likelihood techniques applied to quasi-elastic light scattering

There is a necessity of having an automatic procedure for reliable estimation of the quality of the measurement of particle size from QELS (Quasi-Elastic Light Scattering). Getting the measurement itself, before any error estimates can be made, is a problem because it is obtained by a very indirect measurement of a signal derived from the motion of particles in the system and requires the solution of an inverse problem. The eigenvalue structure of the transform that generates the signal is such that an arbitrarily small amount of noise can obliterate parts of any practical inversion spectrum. This project uses the Maximum Likelihood Estimation (MLE) as a framework to generate a theory and a functioning set of software to oversee the measurement process and extract the particle size information, while at the same time providing error estimates for those measurements. The theory involved verifying a correct form of the covariance matrix for the noise on the measurement and then estimating particle size parameters using a modified histogram approach.

Edwards, Robert V.↗

NASA NTRS1994

A Planar Approximation for the Least Reliable Bit Log-likelihood Ratio of 8-PSK Modulation

The optimum decoding of component codes in block coded modulation (BCM) schemes requires the use of the log-likelihood ratio (LLR) as the signal metric. An approximation to the LLR for the least reliable bit (LRB) in an 8-PSK modulation based on planar equations with fixed point arithmetic is developed that is both accurate and easily realizable for practical BCM schemes. Through an error power analysis and an example simulation it is shown that the approximation results in 0.06 dB in degradation over the exact expression at an E(sub s)/N(sub o) of 10 dB. It is also shown that the approximation can be realized in combinatorial logic using roughly 7300 transistors. This compares favorably to a look up table approach in typical systems.

Thesling, William H.↗

NASA NTRS1994

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Lai, Jonathan Y.↗

NASA NTRS1993

Maximum-likelihood analysis of the COBE angular correlation function

We have used maximum-likelihood estimation to determine the quadrupole amplitude Q(sub rms-PS) and the spectral index n of the density fluctuation power spectrum at recombination from the COBE DMR data. We find a strong correlation between the two parameters of the form Q(sub rms-PS) = (15.7 +/- 2.6) exp (0.46(1 - n)) microK for fixed n. Our result is slightly smaller than and has a smaller statistical uncertainty than the 1992 estimate of Smoot et al.

Seljak, Uros↗

NASA NTRS1996

Bit Error Probability for Maximum Likelihood Decoding of Linear Block Codes

In this paper, the bit error probability P(sub b) for maximum likelihood decoding of binary linear codes is investigated. The contribution of each information bit to P(sub b) is considered. For randomly generated codes, it is shown that the conventional approximation at high SNR P(sub b) is approximately equal to (d(sub H)/N)P(sub s), where P(sub s) represents the block error probability, holds for systematic encoding only. Also systematic encoding provides the minimum P(sub b) when the inverse mapping corresponding to the generator matrix of the code is used to retrieve the information sequence. The bit error performances corresponding to other generator matrix forms are also evaluated. Although derived for codes with a generator matrix randomly generated, these results are shown to provide good approximations for codes used in practice. Finally, for decoding methods which require a generator matrix with a particular structure such as trellis decoding or algebraic-based soft decision decoding, equivalent schemes that reduce the bit error probability are discussed.

Lin, Shu↗

NASA NTRS1985

An Algorithm for Efficient Maximum Likelihood Estimation and Confidence Interval Determination in Nonlinear Estimation Problems

An algorithm for maximum likelihood (ML) estimation is developed with an efficient method for approximating the sensitivities. The algorithm was developed for airplane parameter estimation problems but is well suited for most nonlinear, multivariable, dynamic systems. The ML algorithm relies on a new optimization method referred to as a modified Newton-Raphson with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. The fitted surface allows sensitivity information to be updated at each iteration with a significant reduction in computational effort. MNRES determines the sensitivities with less computational effort than using either a finite-difference method or integrating the analytically determined sensitivity equations. MNRES eliminates the need to derive sensitivity equations for each new model, thus eliminating algorithm reformulation with each new model and providing flexibility to use model equations in any format that is convenient. A random search technique for determining the confidence limits of ML parameter estimates is applied to nonlinear estimation problems for airplanes. The confidence intervals obtained by the search are compared with Cramer-Rao (CR) bounds at the same confidence level. It is observed that the degree of nonlinearity in the estimation problem is an important factor in the relationship between CR bounds and the error bounds determined by the search technique. The CR bounds were found to be close to the bounds determined by the search when the degree of nonlinearity was small. Beale's measure of nonlinearity is developed in this study for airplane identification problems; it is used to empirically correct confidence levels for the parameter confidence limits. The primary utility of the measure, however, was found to be in predicting the degree of agreement between Cramer-Rao bounds and search estimates.

Murphy, Patrick Charles↗