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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Estimation of the accuracy of dynamic flight-determined coefficients

This paper discusses means of assessing the accuracy of maximum likelihood parameter estimates obtained from dynamic flight data. The commonly used analytical predictors of accuracy are compared from both statistical and simplified geometric standpoints. Emphasizing practical considerations, such as modeling error, the accuracy predictions are evaluated with real and simulated data. Improved computations of the Cramer-Rao bound to correct large discrepancies caused by colored noise and modeling error are presented. This corrected Cramer-Rao bound is the best available analytical predictor of accuracy. Engineering judgement, aided by such analytical tools, is the final arbiter of accuracy estimation.

Maine, R. E.↗
NASA NTRS1989

Summary of longitudinal stability and control parameters as determined from Space Shuttle Challenger flight test data

Estimates of longitudinal stability and control parameters for the space shuttle were determined by applying a maximum likelihood parameter estimation technique to Challenger flight test data. The parameters for pitching moment coefficient, C(m sub alpha), (at different angles of attack), pitching moment coefficient, C(m sub delta e), (at different elevator deflections) and the normal force coefficient, C(z sub alpha), (at different angles of attack) describe 90 percent of the response to longitudinal inputs during Space Shuttle Challenger flights with C(m sub delta e) being the dominant parameter. The values of C(z sub alpha) were found to be input dependent for these tests. However, when C(z sub alpha) was set at preflight predictions, the values determined for C(m sub delta e) changed less than 10 percent from the values obtained when C(z sub alpha) was estimated as well. The preflight predictions for C(z sub alpha) and C(m sub alpha) are acceptable values, while the values of C(z sub delta e) should be about 30 percent less negative than the preflight predictions near Mach 1, and 10 percent less negative, otherwise.

Suit, William T.↗
DOE OSTI2023

Coupled primary production and respiration in a large river contrasts with smaller rivers and streams

Abstract Although time series in ecosystem metabolism are well characterized in small and medium rivers, patterns in the world's largest rivers are almost unknown. Large rivers present technical difficulties, including depth measurements, gas exchange (, ) estimates, and the presence of large dams, which can supersaturate gases. We estimated reach‐scale metabolism for the Hanford Reach of the Columbia River (Washington state, USA), a free‐flowing stretch with an average discharge of 3173 . We calculated from semi‐empirical models and directly estimated it from tracer measurements. We fixed at the median value from these calculations (0.5 ), and used maximum likelihood to estimate reach‐scale, open‐channel metabolism. Both gross primary production (GPP) and ecosystem respiration (ER) were high (GPP range: 0.3–30.8 g , ER range: 0.8–30.6 g ), with peak GPP and ER occurring in the late summer or early fall. GPP increased exponentially with temperature, consistent with metabolic theory, while light was seasonally saturating. Annual average GPP, estimated at 1500 g carbon , was in the top 2% of estimates for other rivers. GPP and ER were tightly coupled and 90% of GPP was immediately respired, resulting in net ecosystem production near 0. Patterns in the Hanford Reach contrast with those in small‐medium rivers, suggesting that metabolism magnitudes and patterns in large rivers may not be simply scaled from knowledge of smaller rivers.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Bit error probability calculations for convolutional codes with short constraint lengths on very noisy channels

A technique for estimating convolutional code performance on very noisy channels is considered. Specifically, the performance of short constraint length codes operating near the channel cutoff rate is estimated. Decoding convolutional codes with a sliding window decoder (SWD) are considered. This decoder is an optimal (maximum likelihood) symbol decoder as the window size grows toward infinity, while the Viterbi decoder is the maximum-likelihood sequence estimator. The difference in the decoded BERs (bit error rates) between the two decoders is very small and approaches zero asymptotically as the channel BER decreases. Therefore, an estimate on the decoded BER for the SWD can also be used as an estimate of the decoded BER for Viterbi decoding.

Herro, Mark A.↗
NASA NTRS1991

On the estimation of climatological Z-R relationships

A statistical framework for climatological Z-R parameter estimation is developed and simulation experiments are conducted to examine sampling properties of the estimators. Both parametric and nonparametric models are considered. For parametric models, it is shown that Z-R parameters can be estimated by maximum likelihood, a procedure with optimal large sample properties. A general nonparametric framework for climatological Z-R estimation is also developed. Nonparametric procedures are attractive because of their flexibility in dealing with certain types of measurement errors common to radar data. Simulation experiments show that even under favorable assumptions on error characteristics of radar and raingages, large datasets are required to obtain accurate Z-R parameter estimates. Another important conclusion is that estimation results are generally quite sensitive to radar and raingage measurement thresholds. For fixed sample size, the simulation results can be used to provide quantitative assessments of the accuracy of Z-R model parameter estimates. These results are particularly useful for error analysis of precipitation products that are derived using climatological Z-R relations. One example is the large-area rainfall estimates derived using the height-area rainfall threshold (HART) technique.

Krajewski, Witold F.↗
NASA NTRS1980

Development of advanced acreage estimation methods

The use of the AMOEBA clustering/classification algorithm was investigated as a basis for both a color display generation technique and maximum likelihood proportion estimation procedure. An approach to analyzing large data reduction systems was formulated and an exploratory empirical study of spatial correlation in LANDSAT data was also carried out. Topics addressed include: (1) development of multiimage color images; (2) spectral spatial classification algorithm development; (3) spatial correlation studies; and (4) evaluation of data systems.

Guseman, L. F., Jr.↗
NASA NTRS2007

Real-time Signal-to-noise Ratio (SNR) Estimation for BPSK and QPSK Modulation Using the Active Communications Channel

Method and apparatus for estimating signal-to-noise ratio (SNR) gamma of a composite input signal e(t) on a phase modulated (e.g., BPSK) communications link. A first demodulator receives the composite input signal and a stable carrier signal and outputs an in-phase output signal; a second demodulator receives the composite input signal and a phase-shifted version of the carrier signal and outputs a quadrature-phase output signal; and phase error theta(sub E)(t) contained within the composite input signal e(t) is calculated from the outputs of the first and second demodulators. A time series of statistically independent phase error measurements theta(sub E)(t(sub 1)), theta (sub E)(t(sub 2)),..., theta (sub E)(t(sub k)) is obtained from the composite input signal subtending a time interval delta t = t(sub k) - t(sub 1) whose value is small enough such that gamma(t) and sigma(t) can be taken to be constant in delta t. A biased estimate gamma(sup *) for the signal-to-noise ratio (SNR) gamma if the composite input signal is calculated using maximum likelihood (ML) estimation techniques, and an unbiased estimate gamma(sup ^) for the signal-to-noise ratio (SNR) gamma of the composite input signal is determined from the biased estimate gamma(sup *), such as by use of a look-up table.

Manning, Robert M.↗
NASA NTRS1999

Coherent Lidar Design and Performance for Space Missions

This report represents the final report for three years of research in the performance of coherent Doppler lidar for use during space missions and the effectiveness of its use for research into wind turbulence. Included are summaries of each year's results, and the publications derived from that years research. The research for year one determined the performance of coherent Doppler Lidar in the weak signal regime, and improved algorithms for extracting the performance velocity estimators with wind turbulence. Year two reviewed the performance of coherent Doppler Lidar for a shuttle mission, worked to improve a maximum likelihood velocity estimator which permits more accurate measurements when the signal level is not known, and in situ atmospheric measurements were conducted. Using a computer simulation the performance of the coherent Doppler lidar for space missions was determined during the third year's research.

Frehlich, Rod↗
NASA NTRS2006

Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation

Various practical aspects of the equation-error approach to aircraft parameter estimation were examined. The analysis was based on simulated flight data from an F-16 nonlinear simulation, with realistic noise sequences added to the computed aircraft responses. This approach exposes issues related to the parameter estimation techniques and results, because the true parameter values are known for simulation data. The issues studied include differentiating noisy time series, maximum likelihood parameter estimation, biases in equation-error parameter estimates, accurate computation of estimated parameter error bounds, comparisons of equation-error parameter estimates with output-error parameter estimates, analyzing data from multiple maneuvers, data collinearity, and frequency-domain methods.

Morelli, Eugene a.↗
NASA NTRS1988

A comparison of frequency estimation techniques for high-dynamic trajectories

A comparison is presented for four different estimation techniques applied to the problem of continuously estimating the parameters of a sinusoidal Global Positioning System (GPS) signal, observed in the presence of additive noise, under extremely high-dynamic conditions. Frequency estimates are emphasized, although phase and/or frequency rate are also estimated by some of the algorithms. These parameters are related to the velocity, position, and acceleration of the maneuvering transmitter. Estimated performance at low carrier-to-noise ratios and high dynamics is investigated for the purpose of determining the useful operating range of an approximate Maximum Likelihood (ML) estimator, an Extended Kalman Filter (EKF), a Cross-Product Automatic Frequency Control (CPAFC) loop, and a digital phase-locked loop (PPL). Numerical simulations are used to evaluate performance while tracking a common trajectory exhibiting high dynamics.

Vilnrotter, V. A.↗
NASA NTRS1992

Going through a quantum phase

Phase measurements on a single-mode radiation field are examined from a system-theoretic viewpoint. Quantum estimation theory is used to establish the primacy of the Susskind-Glogower (SG) phase operator; its phase eigenkets generate the probability operator measure (POM) for maximum likelihood phase estimation. A commuting observables description for the SG-POM on a signal x apparatus state space is derived. It is analogous to the signal-band x image-band formulation for optical heterodyne detection. Because heterodyning realizes the annihilation operator POM, this analogy may help realize the SG-POM. The wave function representation associated with the SG POM is then used to prove the duality between the phase measurement and the number operator measurement, from which a number-phase uncertainty principle is obtained, via Fourier theory, without recourse to linearization. Fourier theory is also employed to establish the principle of number-ket causality, leading to a Paley-Wiener condition that must be satisfied by the phase-measurement probability density function (PDF) for a single-mode field in an arbitrary quantum state. Finally, a two-mode phase measurement is shown to afford phase-conjugate quantum communication at zero error probability with finite average photon number. Application of this construct to interferometric precision measurements is briefly discussed.

Shapiro, Jeffrey H.↗
NASA NTRS2014

Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal processing of the photocurrent processes at the outputs of the two detectors is to perform log-matched filtering followed by a summation and peak detection. This implies that neither difference detection, nor Fourier-domain peak detection, which are the staples of the state-of-the-art systems, is optimal when a weak local oscillator is employed.

Erkmen, Baris I.↗
NASA NTRS2013

Self-configurable radio receiver system and method for use with signals without prior knowledge of signal defining characteristics

A method, radio receiver, and system to autonomously receive and decode a plurality of signals having a variety of signal types without a priori knowledge of the defining characteristics of the signals is disclosed. The radio receiver is capable of receiving a signal of an unknown signal type and, by estimating one or more defining characteristics of the signal, determine the type of signal. The estimated defining characteristic(s) is/are utilized to enable the receiver to determine other defining characteristics. This in turn, enables the receiver, through multiple iterations, to make a maximum-likelihood (ML) estimate for each of the defining characteristics. After the type of signal is determined by its defining characteristics, the receiver selects an appropriate decoder from a plurality of decoders to decode the signal.

Hamkins, Jon↗
NASA NTRS1974

Single-tone parameter estimation from discrete-time observations

Estimation of the parameters of a single-frequency complex tone from a finite number of noisy discrete-time observations is discussed. The appropriate Cramer-Rao bounds and maximum-likelihood (ML) estimation algorithms are derived. Some properties of the ML estimators are proved. The relationship of ML estimation to the discrete Fourier transform is exploited to obtain practial algorithms. The threshold effect of one algorithm is analyzed and compared to simulation results. Other simulation results verify other aspects of the analysis.

Rife, D. C.↗
NASA NTRSDate not supplied

Frequency Domain Quasi Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

In this paper a quasi maximum likelihood method for estimating a low order model of a flexible vehicle has been developed and demonstrated. The quasi maximum likelihood method uses a large number of sensors to estimate the parameters and covariance in a method consistent with the maximum likelihood filter-error method. The cost function has been defined in a frequency domain to improve computational efficiency and to enable estimation of an unstable plant. The method has been demonstrated using flight data from the National Aeronautics and Space Administration X-56A Multi-Utility Technology Testbed flex wing tests, which include unstable flutter modes. The method was able to effectively estimate the frequency and damping of the dynamics of the aircraft and generate a transfer function that is useful for control system evaluations.

Jeffrey Ouellette↗
DOE OSTI2020

A New Estimator to Correct for Bias from Tag Rate Expansion on Natural-Origin Fish Attributes in Mixed-Stock Analysis Using Parentage-Based Tagging

Abstract In fisheries where hatchery- and natural-origin conspecifics occur as mixed stocks, it is often important to estimate both the natural-origin proportion of the mixture and the composition of attributes within the natural-origin portion (e.g., genetic stock, sex, and age-class). These estimates are facilitated by parentage-based tagging, which allows large numbers of hatchery fish to be efficiently tagged and later identified. When tag rates are less than 100%, the untagged fish in the mixture include both untagged hatchery fish and natural-origin fish. Unbiased estimation of the abundance and attribute composition of the natural-origin portion requires an estimator that accounts for tag rates. Two estimators are described: one “accounting-style” estimator similar to previously described approaches and one maximum likelihood method. These estimators were evaluated and compared using simulations mimicking estimation of the composition of fish migrating past a dam. The two estimators performed similarly at reducing bias when tag rates were high, but the maximum likelihood method had smaller mean square error when tag rates were low. We provide an R package to allow usage of this estimator in a wide variety of fisheries applications.

Delomas, Thomas A. (ORCID:000000015154759X)↗
DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data

Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.

distribution system state estimation↗