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At least 703 records · Page 39

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NASA NTRS1975

Attitude estimation of earth orbiting satellites by decomposed linear recursive filters

Attitude estimation of earth orbiting satellites (including Large Space Telescope) subjected to environmental disturbances and noises was investigated. Modern control and estimation theory is used as a tool to design an efficient estimator for attitude estimation. Decomposed linear recursive filters for both continuous-time systems and discrete-time systems are derived. By using this accurate estimation of the attitude of spacecrafts, state variable feedback controller may be designed to achieve (or satisfy) high requirements of system performance.

Kou, S. R.↗

NASA NTRS1974

Nonparametric maximum likelihood estimation of probability densities by penalty function methods

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.

Demontricher, G. F.↗

NASA NTRS1976

Application of remote sensing in estimating evapotranspiration in the Platte river basin

A 'resistance model' and a mass transport model for estimating evapotranspiration (ET) were tested on large fields of naturally subirrigated alfalfa. Both models make use of crop canopy temperature data. Temperature data were obtained with an IR thermometer and with leaf thermocouples. A Bowen ratio-energy balance (BREB) model, adjusted to account for underestimation of ET during periods of strong sensible heat advection, was used as the standard against which the resistance and mass transport models were compared. Daily estimates by the resistance model were within 10% of estimates made by the BREB model. Daily estimates by the mass transport model did not agree quite as well. Performance was good on clear and cloudy days and also during periods of non-advection and strong advection of sensible heat. The performance of the mass transport and resistance models was less satisfactory for estimation of fluxes of latent heat for short term periods. Both models tended to overestimate at low LE fluxes.

Blad, B. L.↗

NASA NTRS1975

Secondary task for full flight simulation incorporating tasks that commonly cause pilot error: Time estimation

The task of time estimation, an activity occasionally performed by pilots during actual flight, was investigated with the objective of providing human factors investigators with an unobtrusive and minimally loading additional task that is sensitive to differences in flying conditions and flight instrumentation associated with the main task of piloting an aircraft simulator. Previous research indicated that the duration and consistency of time estimates is associated with the cognitive, perceptual, and motor loads imposed by concurrent simple tasks. The relationships between the length and variability of time estimates and concurrent task variables under a more complex situation involving simulated flight were clarified. The wrap-around effect with respect to baseline duration, a consequence of mode switching at intermediate levels of concurrent task distraction, should contribute substantially to estimate variability and have a complex effect on the shape of the resulting distribution of estimates.

Rosch, E.↗

NASA NTRS1976

Decentralization, stabilization, and estimation of large-scale linear systems

In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

Siljak, D. D.↗

NASA NTRS1976

Estimation of characteristics and stochastic control of an aircraft flying in atmospheric turbulence

An adaptive control technique to improve the flying qualities of an aircraft in turbulence was investigated. The approach taken was to obtain maximum likelihood estimates of the unknown coefficients of the aircraft system and then, using these estimates along with the separation principle, to define the stochastic optimal control. The maximum likelihood estimation technique that accounted for the effects of turbulence provided good estimates of the unknown coefficients and of the turbulence. The assessment of the stochastic optimal control based on the maximum likelihood estimates showed that the desired effects were attained for the regulator problem of minimizing pitch angle and the tracking problem of requiring normal acceleration to follow the pilot input.

Iliff, K. W.↗

NASA NTRS1976

Remote sensing as a tool for watershed-wide estimation of net solar radiation and water loss to the atmosphere

Results are presented for a study intended to develop a general remote sensing-aided cost-effective procedure to estimate watershed-wide water loss to the atmosphere via evapotranspiration and to estimate net solar radiation over the watershed. Evapotranspiration estimation employs a basic two-stage two-phase sample of three information resolution levels. Net solar radiation is taken as one of the variables at each level of evapotranspiration modeling. The input information for models requiring spatial information will be provided by Landsat digital data, environmental satellite data, ground meteorological data, ground sample unit information, and topographic data. The outputs of the sampling-estimation/data bank system will be in-place maps of evapotranspiration on a data resolution element basis, watershed-wide evapotranspiration isopleths, and estimates of watershed and subbasin total evapotranspiration with associated statistical confidence bounds. The methodology developed is being tested primarily on the Spanish Creek Watershed Plumas County, California.

Khorram, S.↗

NASA NTRS1977

Effects of control inputs on the estimation of stability and control parameters of a light airplane

The maximum likelihood parameter estimation technique was used to determine the values of stability and control derivatives from flight test data for a low-wing, single-engine, light airplane. Several input forms were used during the tests to investigate the consistency of parameter estimates as it relates to inputs. These consistencies were compared by using the ensemble variance and estimated Cramer-Rao lower bound. In addition, the relationship between inputs and parameter correlations was investigated. Results from the stabilator inputs are inconclusive but the sequence of rudder input followed by aileron input or aileron followed by rudder gave more consistent estimates than did rudder or ailerons individually. Also, square-wave inputs appeared to provide slightly improved consistency in the parameter estimates when compared to sine-wave inputs.

Cannaday, R. L.↗

NASA NTRS1978

Estimation of aerodynamic characteristics from dynamic flight test data

Significant effort was spent in estimating unknown aircraft coefficients, such as stability and control derivatives from dynamic flight maneuvers. The techniques used to estimate these coefficients are becoming increasingly complex; however, these techniques make it possible to obtain estimates of coefficients that in the past were nearly impossible to obtain. A survey of the investigations that were undertaken to obtain estimates of coefficients from dynamic flight maneuvers is presented. One method, the maximum likelihood estimation technique, is described briefly and some of the successful applications of the technique are presented. Possible techniques for analyzing responses obtained in the stall/spin regime are discussed. Recent data obtained in the stall/spin flight regime are presented along with a discussion of how some basic results can be obtained with simple analysis techniques.

Liff, K. W.↗

NASA NTRS1979

Large scale state estimation algorithms for DSN tracking station location determination

Estimation of precise tracking station locations for deep space navigation is based on combining state estimates derived from a multitude of planetary encounter missions with planet direction information provided by the planetary ephemeris. Procedures for reducing the dimensionality of the station location estimation problem and for analytically correcting estimates for ephemeris updates have been developed. Using Householder transforms the large scale state estimation problem is decomposed into a sequence of dynamically uncoupled problems of lower dimension. The effect of an ephemeris update is shown to be adequately approximated by Brouwer-Clemence Set III perturbations for the earth-moon barycenter and the target planet for each mission.

Ellis, J.↗

NASA NTRS1980

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Klein, V.↗

NASA NTRS1979

Self-motion magnitude estimation during linear oscillation - Changes with head orientation and following fatigue

Two types of experiments concerning the estimated magnitude of self-motion during exposure to linear oscillation on a parallel swing are described in this paper. Experiment I examined changes in magnitude estimation as a function of variation of the subject's head orientation, and Experiments II a, II b, and II c assessed changes in magnitude estimation performance following exposure to sustained, 'intense' linear oscillation (fatigue-inducting stimulation). The subjects' performance was summarized employing Stevens' power law R = k x S to the nth, where R is perceived self-motion magnitude, k is a constant, S is amplitude of linear oscillation, and n is an exponent). The results of Experiment I indicated that the exponents, n, for the magnitude estimation functions varied with head orientation and were greatest when the head was oriented 135 deg off the vertical. In Experiments II a-c, the magnitude estimation function exponents were increased following fatigue. Both types of experiments suggest ways in which the vestibular system's contribution to a spatial orientation perceptual system may vary. This variability may be a contributing factor to the development of pilot/astronaut disorientation and may also be implicated in the occurrence of motion sickness.

Parker, D. E.↗

NASA NTRS1980

Preliminary evaluation of the Environmental Research Institute of Michigan crop calendar shift algorithm for estimation of spring wheat development stage

An algorithm for estimating spectral crop calendar shifts of spring small grains was applied to 1978 spring wheat fields. The algorithm provides estimates of the date of peak spectral response by maximizing the cross correlation between a reference profile and the observed multitemporal pattern of Kauth-Thomas greenness for a field. A methodology was developed for estimation of crop development stage from the date of peak spectral response. Evaluation studies showed that the algorithm provided stable estimates with no geographical bias. Crop development stage estimates had a root mean square error near 10 days. The algorithm was recommended for comparative testing against other models which are candidates for use in AgRISTARS experiments.

Phinney, D. E.↗

NASA NTRS1981

Stability of individual loudness functions obtained by magnitude estimation and production

A correlational analysis of individual magnitude estimation and production exponents at the same frequency is performed, as is an analysis of individual exponents produced in different sessions by the same procedure across frequency (250, 1000, and 3000 Hz). Taken as a whole, the results show that individual exponent differences do not decrease by counterbalancing magnitude estimation with magnitude production and that individual exponent differences remain stable over time despite changes in stimulus frequency. Further results show that although individual magnitude estimation and production exponents do not necessarily obey the .6 power law, it is possible to predict the slope of an equal-sensation function averaged for a group of listeners from individual magnitude estimation and production data. On the assumption that individual listeners with sensorineural hearing also produce stable and reliable magnitude functions, it is also shown that the slope of the loudness-recruitment function measured by magnitude estimation and production can be predicted for individuals with bilateral losses of long duration. Results obtained in normal and pathological ears thus suggest that individual listeners can produce loudness judgements that reveal, although indirectly, the input-output characteristic of the auditory system.

Hellman, R. P.↗

NASA NTRS1981

Algorithms for onboard orbit estimation with Tracking and Data Relay Satellite System data

An investigation is carried out to determine an appropriate estimation technique for onboard orbit determination using simulated Tracking and Data Relay Satellite System (TDRSS) data. Results are presented from studies done using three estimation techniques: an extended Kalman filter, a consider filter, and a sliding batch differential corrector. These estimators are evaluated when used with both baseline and worst-case TDRSS measurement errors and with tracking configurations for two types of orbits: a high-inclination, near-circular orbit with an altitude of 700 km and a moderately inclined, lower altitude orbit. Each estimation result is evaluated by comparing the true with the estimated ephemeris.

Dunham, J. B.↗

NASA NTRS1980

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Cate, R. B.↗

NASA NTRS1981

A comparison of stratified versus regression estimators

LANDSAT data acquired over an agricultural area along with ground enumeration of the same area are used to obtain crop acreage estimates which are better (as measured in terms of bias and variance) than can be obtained from either data source alone. Two basic approaches considered within the AgRISTARS program are a stratified crop acreage estimator and a regression estimator. A statement of the problem was mathematically formulated and some theorems were proved which relate to the variance of the two estimators. For a particular set of data, the regression and stratified estimators are compared in terms of certain easily computed parameters.

Takacs, H. C.↗

NASA NTRS1982

Evaluation of spatial filtering on the accuracy of wheat area estimate

A 3 x 3 pixel spatial filter for postclassification was used for wheat classification to evaluate the effects of this procedure on the accuracy of area estimation using LANDSAT digital data obtained from a single pass. Quantitative analyses were carried out in five test sites (approx 40 sq km each) and t tests showed that filtering with threshold values significantly decreased errors of commission and omission. In area estimation filtering improved the overestimate of 4.5% to 2.7% and the root-mean-square error decreased from 126.18 ha to 107.02 ha. Extrapolating the same procedure of automatic classification using spatial filtering for postclassification to the whole study area, the accuracy in area estimate was improved from the overestimate of 10.9% to 9.7%. It is concluded that when single pass LANDSAT data is used for crop identification and area estimation the postclassification procedure using a spatial filter provides a more accurate area estimate by reducing classification errors.

Dejesusparada, N.↗