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At least 667 records · Page 37

A real-time signal combining system for Ka-band feed arrays using maximum-likelihood weight estimates

A real-time digital signal combining system for use with Ka-band feed arrays is proposed. The combining system attempts to compensate for signal-to-noise ratio (SNR) loss resulting from antenna deformations induced by gravitational and atmospheric effects. The combining weights are obtained directly from the observed samples by using a sliding-window implementation of a vector maximum-likelihood parameter estimator. It is shown that with averaging times of about 0.1 second, combining loss for a seven-element array can be limited to about 0.1 dB in a realistic operational environment. This result suggests that the real-time combining system proposed here is capable of recovering virtually all of the signal power captured by the feed array, even in the presence of severe wind gusts and similar disturbances.

Vilnrotter, V. A.↗

Real-time combining of residual carrier array signals using ML weight estimates

A real-time digital signal combining system for use with array feeds is proposed. The combining system attempts to compensate for signal-to-noise ratio (SNR) loss resulting from antenna deformations induced by gravitational and atmospheric effects. The combining weights are obtained directly from the observed residual carrier samples in each channel using a 'sliding-window' implementation of a maximum-likelihood (ML) parameter estimator. It is shown that with averaging times of about 0.1 s, combining loss for a seven-element array can be limited to about 0.1 dB in a realistic operational environment. This result suggests that the real-time combining system proposed here is capable of recovering virtually all of the signal power captured by the array feed, even in the presence of severe wind gusts and similar disturbances.

Vilnrotter, Victor A.↗

Identification of the stability parameters of an aeroelastic airplane

The problem of the parameter identification of large scale dynamic systems involving a system matrix characterized by approximately 200 elements is addressed. By using phase variable transformations, a mathematical model of an aeroelastic airplane is described in a form that is amenable to partial or piecemeal acceptance of parameters estimated from flight data. A mathematical model of the U.S. Air Force Total In-Flight Simulator was computed using the FLEXSTAB digital computer program. As data became available during the progress of the flight test program, this data was processed and substituted in the mathematical model for parameters analytically obtained from the FLEXSTAB program. The results tend to show a progressive and orderly transition from an analytically defined mathematical model to one obtained from the flight tests of the actual aircraft.

Rynaski, E. G.↗

Optimum data weighting and error calibration for estimation of gravitational parameters

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Lerch, F. J.↗

Emulator-based Bayesian calibration of a subglacial drainage model

Subglacial drainage models, often motivated by the relationship between hydrology and ice flow, sensitively depend on numerous unconstrained parameters. We explore using borehole water-pressure time series to calibrate the uncertain parameters of a popular subglacial drainage model, taking a Bayesian perspective to quantify the uncertainty in parameter estimates and in the calibrated model predictions. To reduce the computation time associated with Markov Chain Monte Carlo sampling, we construct a fast Gaussian process emulator to stand in for the subglacial drainage model. We first carry out a calibration experiment using synthetic observations consisting of model simulations with hidden parameter values as a demonstration of the method. Using real borehole water pressures measured in western Greenland, we find meaningful constraints on four of the eight model parameters and a factor-of-three reduction in uncertainty of the calibrated model predictions. These experiments illustrate Gaussian process-based Bayesian inference as a useful tool for calibration and uncertainty quantification of complex glaciological models using field data. However, significant differences between the calibrated model and the borehole data suggest that structural limitations of the model, rather than poorly constrained parameters or computational cost, remain the most important constraint on subglacial drainage modelling.

58 GEOSCIENCES↗

Modeling Venus-Like Worlds Through Time: What Can They Tell Us About the the Liquid Water Habitable Zone, the Evolution of Venus' Atmosphere & Conditions Amenable to Life

Using a modern three-dimensional general circulation coupled atmosphere/ocean model [1] we recently demonstrated [2] that climatic conditions may have permitted liquid water on Venus' surface for ~2 billion years in its early history. Similar such conditions on Earth are believed amenable to the rise of life. Several assumptions were made based on what little data we have for early Venus such as; the type of solar spectrum extant at that time, orbital parameters, estimates of a shallow ocean from Pioneer Venus D/H ratios, and topography from the Magellan Mission. We also assumed that it would have had an atmosphere similar to modern day Earth: 1 bar N2, 400 ppmv CO2, 1 ppmv CH4. I will discuss the motivations behind these assumptions and additional parameter space studies with direct relevance to hypothetical exoplanetary Venus-like worlds found at the inner edge of the liquid water habitable zone. Finally, I will show how our studies demonstrate that the reason for Venus' present climatic state is unlikely to be related to the gradual warming of our sun over the past 4Gyr as is commonly believed.

Way, Michael↗

AutoBayes Program Synthesis System Users Manual

Program synthesis is the systematic, automatic construction of efficient executable code from high-level declarative specifications. AutoBayes is a fully automatic program synthesis system for the statistical data analysis domain; in particular, it solves parameter estimation problems. It has seen many successful applications at NASA and is currently being used, for example, to analyze simulation results for Orion. The input to AutoBayes is a concise description of a data analysis problem composed of a parameterized statistical model and a goal that is a probability term involving parameters and input data. The output is optimized and fully documented C/C++ code computing the values for those parameters that maximize the probability term. AutoBayes can solve many subproblems symbolically rather than having to rely on numeric approximation algorithms, thus yielding effective, efficient, and compact code. Statistical analysis is faster and more reliable, because effort can be focused on model development and validation rather than manual development of solution algorithms and code.

Schumann, Johann↗

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions, 2

The problem of obtaining numerically maximum likelihood estimates of the parameters for a mixture of normal distributions is addressed. In recent literature, a certain successive approximations procedure, based on the likelihood equations, is shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, a general iterative procedure is introduced, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. With probability 1 as the sample size grows large, it is shown that this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. The step-size which yields optimal local convergence rates for large samples is determined in a sense by the separation of the component normal densities and is bounded below by a number between 1 and 2.

Peters, B. C., Jr.↗

An adaptive Cartesian control scheme for manipulators

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Seraji, H.↗

Inverse sequential detection of parameter changes in developing time series

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Radok, Uwe↗

ILRS Analysis Activities After the Adoption of ITRF2020

"The contribution of the International Laser Ranging Service (ILRS) to the most recent realization of the International Terrestrial Reference System (ITRS) was the result of an analysis strategy with two major modifications compared to the operational products: a modeling for stations long-term systematic errors (biases reported in the ILRS Data Handling File) and an updated model of the target signature error (satellite Centre of Mass model). Both refined models were used as input information for the ILRS contribution to the ITRF2020 (International Terrestrial Reference Frame 2020). Thereafter, the ILRS Analysis Standing Committee (ASC) focused its effort on implementing the new reference frame in its operational products, define a strategy to improve the ongoing monitoring of the systematic errors, compute the ILRS contribution to the planned ITRF2020 update, and to include LARES-2 among the considered satellites for the operational products. The ILRS ASC implemented the ITRF2020/SLRF2020 into all its official operational products (TRF, Earth Orientation Parameters, predicted and combined satellite orbits) and its impact was evaluated. The operational products benefit from the continuous monitoring of the station systematic errors and the frequent updates of the Data Handling File whenever a significant change in the station systematic error is observed. In the future, a change-point detection algorithm, jointly estimating the times and the number of discontinuities, will be implemented to detect potential new discontinuities in the range bias series. The inclusion of LARES-2 among the satellites whose data are operationally analyzed will furtherly increase the robustness of the estimated parameters. Finally, the ILRS ASC activities include the benchmarking of a new analysis center (CNES) which will formally begin its own contribution in 2024."

Satellite Laser Ranging↗

Estimation of Handling Qualities Parameters of the Tu-144 Supersonic Transport Aircraft from Flight Test Data

Low order equivalent system (LOES) models for the Tu-144 supersonic transport aircraft were identified from flight test data. The mathematical models were given in terms of transfer functions with a time delay by the military standard MIL-STD-1797A, "Flying Qualities of Piloted Aircraft," and the handling qualities were predicted from the estimated transfer function coefficients. The coefficients and the time delay in the transfer functions were estimated using a nonlinear equation error formulation in the frequency domain. Flight test data from pitch, roll, and yaw frequency sweeps at various flight conditions were used for parameter estimation. Flight test results are presented in terms of the estimated parameter values, their standard errors, and output fits in the time domain. Data from doublet maneuvers at the same flight conditions were used to assess the predictive capabilities of the identified models. The identified transfer function models fit the measured data well and demonstrated good prediction capabilities. The Tu-144 was predicted to be between level 2 and 3 for all longitudinal maneuvers and level I for all lateral maneuvers. High estimates of the equivalent time delay in the transfer function model caused the poor longitudinal rating.

Curry, Timothy J.↗

Direct adaptive control of manipulators in Cartesian space

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Seraji, H.↗

Improvements in ERBS attitude determination without gyros

Previous papers have described the modification of the Earth Radiation Budget Satellite (ERBS) Attitude Determination System (ADS) to overcome the impact of on board gyro degradation and failure on attitude ground support of the mission. Two approaches were taken: implementing a Kalman filter in place of the batch-least-squares attitude estimator to account for the propagation error produced by high-noise gyro data, and modeling the ERBS attitude dynamics to restore rate information in the case of gyro failure. Both of these methods had shortcomings. In practice, the filter attitude diverged without complete sensor observability, and accurate dynamics modeling required knowledge of disturbance torque parameters that had to be determined manually. These difficulties have been overcome by improved tuning of the filter and by incorporating dynamics parameter estimation into the ERBS ADS.

Chu, D.↗

An Analytical Calibration Approach for the Polarimetric Airborne C Band Radiometer

Passive microwave remote sensing is sensitive to the quantity and distribution of water in soil and vegetation. During summer 2000, the Microwave Geophysics Group a t the University of Michigan conducted the seventh Radiobrighness Energy Balance Experiment (REBEX-7) over a corn canopy in Michigan. Long time series of brightness temperatures, soil moisture and micrometeorology on the plot were taken. This paper addresses the calibration of the NASA GSFC polarimetric airborne C band microwave radiometer (ACMR) that participated in REBEX-7. These passive polarimeters are typically calibrated using an end-to-end approach based upon a standard artificial target or a well-known geophysical target. Analyzing the major internal functional subsystems offers a different perspective. The primary goal of this approach is to provide a transfer function that not only describes the system in its entire5 but also accounts for the contributions of each subsystem toward the final modified Stokes parameters. This approach does not assume that the radiometric system is linear as it does not take polarization isolation for granted, and it also serves as a realistic instrument simulator, a useful tool for future designs. The ACMR architecture can be partitioned into functional subsystems. The characteristics of each subsystem was extensively measured and the estimated parameters were imported into the overall dosed form system model. Inversion of the model yields a calibration for the modeled Stokes parameters with uncertainties of 0.2 K for the V and H polarizations and 2.4 K for the 3rd and 4th parameters. Application to the full Stokes parameters over a senescent cornfield is presented.

Pham, Hanh↗

Estimations of model parameters for gravity wave spectra observed by MST radar

The general theory of MST radar observations of gravity wave spectra is developed. This effort extends the previous results to include anisotropy and Doppler effects for the spectra, as well as the consequences for the multibeam configuration. The relationships between the observed one- or two-dimensional spectra for the line-of-sight velocity in the gravity wave spectra are derived. Expressions for cross spectra, as well as covariances between velocities observed on different beams, are computed. Using these results, studies are carried out to show how model parameters for gravity wave spectra can be estimated from the observed quantities. Model parameters include the variance, power law indices, anisotropy parameters, Doppler parameters, mean scale sizes, etc. Cases with different numbers of beams are investigated.

Scheffler, A. O.↗

Estimation of motion parameters for a rigid body from its orthogonal projection

An estimate is presented of the motion parameters, namely, linear and angular velocities of a rigid body rotating and translating in three-dimensional-space. It is assumed that the velocities are constant and that only the orthogonal projection of the motion is observable. In particular, if (x, y, z) is the Cartesian coordinate, it is assumed that the projection of the motion on the x-y plane is observed and the information along the z coordinate is lost.

Ganguly, S.↗

General Multimechanism Reversible-Irreversible Time-Dependent Constitutive Deformation Model Being Developed

Since most advanced material systems (for example metallic-, polymer-, and ceramic-based systems) being currently researched and evaluated are for high-temperature airframe and propulsion system applications, the required constitutive models must account for both reversible and irreversible time-dependent deformations. Furthermore, since an integral part of continuum-based computational methodologies (be they microscale- or macroscale-based) is an accurate and computationally efficient constitutive model to describe the deformation behavior of the materials of interest, extensive research efforts have been made over the years on the phenomenological representations of constitutive material behavior in the inelastic analysis of structures. From a more recent and comprehensive perspective, the NASA Glenn Research Center in conjunction with the University of Akron has emphasized concurrently addressing three important and related areas: that is, 1) Mathematical formulation; 2) Algorithmic developments for updating (integrating) the external (e.g., stress) and internal state variables; 3) Parameter estimation for characterizing the model. This concurrent perspective to constitutive modeling has enabled the overcoming of the two major obstacles to fully utilizing these sophisticated time-dependent (hereditary) constitutive models in practical engineering analysis. These obstacles are: 1) Lack of efficient and robust integration algorithms; 2) Difficulties associated with characterizing the large number of required material parameters, particularly when many of these parameters lack obvious or direct physical interpretations.

Saleeb, A. F.↗