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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Uterine Contraction Modeling and Simulation

Building a training system for medical personnel to properly interpret fetal heart rate tracing requires developing accurate models that can relate various signal patterns to certain pathologies. In addition to modeling the fetal heart rate signal itself, the change of uterine pressure that bears strong relation to fetal heart rate and provides indications of maternal and fetal status should also be considered. In this work, we have developed a group of parametric models to simulate uterine contractions during labor and delivery. Through analysis of real patient records, we propose to model uterine contraction signals by three major components: regular contractions, impulsive noise caused by fetal movements, and low amplitude noise invoked by maternal breathing and measuring apparatus. The regular contractions are modeled by an asymmetric generalized Gaussian function and least squares estimation is used to compute the parameter values of the asymmetric generalized Gaussian function based on uterine contractions of real patients. Regular contractions are detected based on thresholding and derivative analysis of uterine contractions. Impulsive noise caused by fetal movements and low amplitude noise by maternal breathing and measuring apparatus are modeled by rational polynomial functions and Perlin noise, respectively. Experiment results show the synthesized uterine contractions can mimic the real uterine contractions realistically, demonstrating the effectiveness of the proposed algorithm.

Liu, Miao↗
NASA NTRS1977

Optimal estimation for discrete time jump processes

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Vaca, M. V.↗
NASA NTRS1994

Parameter dimension of turbulence-induced phase errors and its effects on estimation in phase diversity

The method of phase diversity has been used in the context of incoherent imaging to estimate jointly an object that is being imaged and phase aberrations induced by atmospheric turbulence. The method requires a parametric model for the phase-aberration function. Typically, the parameters are coefficients to a finite set of basis functions. Care must be taken in selecting a parameterization that properly balances accuracy in the representation of the phase-aberration function with stability in the estimates. It is well known that over parameterization can result in unstable estimates. Thus a certain amount of model mismatch is often desirable. We derive expressions that quantify the bias and variance in object and aberration estimates as a function of parameter dimension.

Thelen, Brian J.↗
NASA NTRS1945

Method of expanding noise autocorrelation function in a power series

Under certain conditions the normalized autocorrelation function ρ(τ) of stationary random noise may be expanded as a power series about the point τ = 0. This paper indicates that the coefficients of the expansion are rather simply related to the average rate of occurrence of zeros in the noise function and its derivatives. The expansion of academic interest in providing another perspective of the relationships among the noise function, its power spectrum, and its autocorrelation function. It may also be of practical interest in providing a quick means of estimating the normalized autocorrelation function from a noise record over the range of τ in which the power series converges rapidly. The class of noise spectrum for which convergent series expansion is not possible is of interest in pointing up necessary physical characteristics of noise signals which have such spectra.

F W Lehan↗
NASA NTRS1982

Electric propulsion

An alternative propulsion subsystem for MSAT is presented which has a potential of reducing the satellite weight by more than 15%. The characteristics of pulsed plasma and ion engines are described and used to estimate of the mass of the propellant and thrusters for attitude control and stationkeeping functions for MSAT. Preliminary estimates indicate that the electric propulsion systems could also replace the large momentum wheels necessary to counteract the solar pressure; however, the fine pointing wheels would be retained. Estimates also show that either electric propulsion system can save approximately 18% to 20% of the initial 4,000 kg mass. The issues that require further experimentation are mentioned.

Source record↗
NASA NTRS2012

Achievable Precision for Optical Ranging Systems

Achievable RMS errors in estimating the phase, frequency, and intensity of a direct-detected intensity-modulated optical pulse train are presented. For each parameter, the Cramer-Rao-Bound (CRB) is derived and the performance of the Maximum Likelihood estimator is illustrated. Approximations to the CRBs are provided, enabling an intuitive understanding of estimator behavior as a function of the signaling parameters. The results are compared to achievable RMS errors in estimating the same parameters from a sinusoidal waveform in additive white Gaussian noise. This establishes a framework for a performance comparison of radio frequency (RF) and optical science. Comparisons are made using parameters for state-of-the-art deep-space RF and optical links. Degradations to the achievable errors due to clock phase noise and detector jitter are illustrated.

estimation theory↗
NASA NTRS2012

Phase Function Determination in Support of Orbital Debris Size Estimation

To recover the size of a space debris object from photometric measurements, it is necessary to determine its albedo and basic shape: if the albedo is known, the reflective area can be calculated; and if the shape is known, the shape and area taken together can be used to estimate a characteristic dimension. Albedo is typically determined by inferring the object s material type from filter photometry or spectroscopy and is not the subject of the present study. Object shape, on the other hand, can be revealed from a time-history of the object s brightness response. The most data-rich presentation is a continuous light-curve that records the object s brightness for an entire sensor pass, which could last for tens of minutes to several hours: from this one can see both short-term periodic behavior as well as brightness variations with phase angle. Light-curve interpretation, however, is more art than science and does not lend itself easily to automation; and the collection method, which requires single-object telescope dedication for long periods of time, is not well suited to debris survey conditions. So one is led to investigate how easily an object s brightness phase function, which can be constructed from the more survey-friendly point photometry, can be used to recover object shape. Such a recovery is usually attempted by comparing a phase-function curve constructed from an object s empirical brightness measurements to analytically-derived curves for basic shapes or shape combinations. There are two ways to accomplish this: a simple averaged brightness-versus phase curve assembled from the empirical data, or a more elaborate approach in which one is essentially calculating a brightness PDF for each phase angle bin (a technique explored in unpublished AFRL/RV research and in Ojakangas 2011); in each case the empirical curve is compared to analytical results for shapes of interest. The latter technique promises more discrimination power but requires more data; the former can be assembled in its essentials from fewer measurements but will be less definitive in its assignments. The goal of the present study is to evaluate both techniques under debris survey conditions to determine their relative performance and, additionally, to learn precisely how a survey should be conducted in order to maximize their performance. Because the distendedness of objects has more of an effect than their precise shape in calculating a characteristic dimension, one is interested in the techniques discrimination ability to distinguish between an elongated rectangular prism and a short rectangular prism or cube, or an elongated cylinder from a squat cylinder or sphere. Sensitivity studies using simulated data will be conducted to determine discrimination power for both techniques as a function of amount of data collected and range (and specific region) of phase angles sampled. Empirical GEODSS photometry data for distended objects (dead payloads with solar panels, rocket bodies) and compact objects (cubesats, calibration spheres, squat payloads) will also be used to test this discrimination ability. The result will be a recommended technique and data collection paradigm for debris surveys in order to maximize this type of discrimination.

Hejduk, M. D.↗
NASA NTRS1971

A stochastic constrained optimization technique and its application to detector array processing.

A stochastic projected gradient algorithm is proposed which can be used for finding a constrained optimum point for a concave or convex objective function subject to nonlinear constraints which form a connected region even when only a noisy estimate of the objective function is available. For a constraint described by a single linear equation, convergence to the constrained optimum value is proved, and the rate of convergence of the algorithm to the constrained optimum value is determined. The algorithm is applied to the nonlinear problem of obtaining automatically an array of detectors which forms a beam in a desired direction in space in the presence of interfering noise so as to maximize the SNR subject to a constraint on the super-gain ratio.

Winkler, L. P.↗
NASA NTRS1991

Retrieval of monthly rainfall indices from microwave radiometric measurements using probability distribution functions

An algorithm for the estimation of monthly rain totals for 5 deg cells over the ocean from histograms of SSM/I brightness temperatures has been developed. There are three novel features to this algorithm. First, it uses knowledge of the form of the rainfall intensity probability density function to augment the measurements. Second, a linear combination of the 19.35 and 22.235 GHz channels has been employed to reduce the impact of variability of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35- and 22.235-GHz brightness temperature histograms. Comparison with climatologies and the GATE radar observations suggest that the estimates are reasonable in spite of not having a beam-filling correction. By-products of the retrievals indicate that the SSM/I instrument noise level and calibration stability are quite good.

Wilheit, Thomas T.↗
NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗
NASA NTRS1982

A model for estimating time-variant rainfall infiltration as a function of antecedent surface moisture and hydrologic soil type

Recent research indicates that the use of remote sensing techniques for the measurement of near surface soil moisture could be practical in the not too distant future. Other research shows that infiltration rates, especially for average or frequent rainfall events, are extremely sensitive to the proper definition and consideration of the role of the soil moisture at the beginning of the rainfall. Thus, it is important that an easy to use, but theoretically sound, rainfall infiltration model be available if the anticipated remotely sensed soil moisture data is to be optimally utilized for hydrologic simulation. A series of numerical experiments with the Richards' equation for an array of conditions anticipated in watershed hydrology were used to develop functional relationships that describe temporal infiltration rates as a function of soil type and initial moisture conditions.

Wilkening, H. A.↗
NASA NTRS1982

Least-squares sequential parameter and state estimation for large space structures

This paper presents the formulation of simultaneous state and parameter estimation problems for flexible structures in terms of least-squares minimization problems. The approach combines an on-line order determination algorithm, with least-squares algorithms for finding estimates of modal approximation functions, modal amplitudes, and modal parameters. The approach combines previous results on separable nonlinear least squares estimation with a regression analysis formulation of the state estimation problem. The technique makes use of sequential Householder transformations. This allows for sequential accumulation of matrices required during the identification process. The technique is used to identify the modal prameters of a flexible beam.

Thau, F. E.↗
NASA NTRS1985

Estimation of finite mixtures using the empirical characteristic function

A problem which occurs in analyzing LANDSAT scenes is the problem of separating the components of a finite mixture of several distinct probability distributions. A review of the literature indicates this is a problem which occurs in many disciplines, such as engineering, biology, physiology and economics. Many approaches to this problem have appeared in the literature; however, most are very restrictive in their assumptions or have met with only a limited degree of success when applied to realistic situations. A proceudre is investigated with combines the k-L procedure of (Feurverger and McDunnough, 1981) with the MAICE procedure of (Akaike, 1974). The feasibility of this approach is being investigated numerically via the development of a computer software package enabling a simulation study and comparison with other procedures.

Anderson, C.↗
NASA NTRS2012

Satellite Material Type and Phase Function Determination in Support of Orbital Debris Size Estimation

In performing debris surveys of deep-space orbital regions, the considerable volume of the area to be surveyed and the increased orbital altitude suggest optical telescopes as the most efficient survey instruments; but to proceed this way, methodologies for debris object size estimation using only optical tracking and photometric information are needed. Basic photometry theory indicates that size estimation should be possible if satellite albedo and shape are known. One method for estimating albedo is to try to determine the object's material type photometrically, as one can determine the albedos of common satellite materials in the laboratory. Examination of laboratory filter photometry (using Johnson BVRI filters) on a set of satellite material samples indicates that most material types can be separated at the 1-sigma level via B-R versus R-I color differences with a relatively small amount of required resampling, and objects that remain ambiguous can be resolved by B-R versus B-V color differences and solar radiation pressure differences. To estimate shape, a technique advanced by Hall et al. [1], based on phase-brightness density curves and not requiring any a priori knowledge of attitude, has been modified slightly to try to make it more resistant to the specular characteristics of different materials and to reduce the number of samples necessary to make robust shape determinations. Working from a gallery of idealized debris shapes, the modified technique identifies most shapes within this gallery correctly, also with a relatively small amount of resampling. These results are, of course, based on relatively small laboratory investigations and simulated data, and expanded laboratory experimentation and further investigation with in situ survey measurements will be required in order to assess their actual efficacy under survey conditions; but these techniques show sufficient promise to justify this next level of analysis.

Hejduk, M. D.↗
NASA NTRS2012

Model-based prognostics for batteries which estimates useful life and uses a probability density function

This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices.

Saha, Bhaskar↗
NASA NTRS2000

New Developments in Quaternion Estimation from Vector Observations

This paper contains a critical comparison of estimators minimizing Wahba's loss function. Some new results are presented for the QUaternion ESTimator (QUEST) and EStimators of the Optimal Quaternion (ESOQ and ESOQ2) to avoid the computational burden of sequential rotations in these algorithms. None of these methods is as robust in principle as Davenport's q method or the Singular Value Decomposition (SVD) method, which are significantly slower. Robustness is only an issue for measurements with widely differing accuracies, so the fastest estimators, the modified ESOQ and ESOQ2, are well suited to sensors that track multiple stars with comparable accuracies. More robust forms of ESOQ and ESOQ2 are developed that are intermediate in speed.

Markley, F. Landis↗
NASA NTRS2009

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

Dean, Bruce H.↗
NASA NTRS1993

Kalman filter estimation of attitude and gyro bias with the QUEST observation model

The loss function for the Wahba attitude estimation problem employs unit vector observations with scalar weights. It is usually associated with the QUEST observation model, where the actual sensor noise is assumed the same for all components of the observed vector, regardless of the position in the field of view. The QUEST model has the great advantage of being sensor-independent except for the scalar parameter that characterizes the sensor errors. Although efficient algorithms for solving the Wahba problem exist, extending these algorithms to estimate gyro biases or sensor alignments has had mixed success. However, it is straightforward to estimate bias and alignment parameters with a Kalman filter. This paper investigates the use of an extended Kalman filter for the attitude and gyro bias that incorporates the QUEST observation model, to be referred to as the Unit Vector Filter (UVF). The UVF results are compared with those from a more conventional filter, the Real-Time Sequential Filter (RTSF), for which the residual is the two-dimensional projection of the unit vector onto the plane perpendicular to the sensor boresight. The RTSF is similar in design to that used by Multimission Modular Spacecraft for onboard attitude determination. An apparent obstacle to the use of unit vectors as measurements is their singular noise covariance matrix. Shuster has shown that this problem should not affect filter performance. The UVF and RTSF are tested using actual flight data from the Extreme Ultraviolet Explorer (EUVE). It is found that these filters generate nearly identical attitude and gyro bias estimates, thus validating the use of unit vectors and the QUEST noise model.

Sedlak, J.↗