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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Analysis and application of minimum variance discrete time system identification

An on-line minimum variance parameter identifier was developed which embodies both accuracy and computational efficiency. The new formulation resulted in a linear estimation problem with both additive and multiplicative noise. The resulting filter is shown to utilize both the covariance of the parameter vector itself and the covariance of the error in identification. It is proven that the identification filter is mean square covergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kotob, S.↗
NASA NTRS1975

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗
NASA NTRS1975

Minimum variance system identification with application to digital adaptive flight control

A new on-line minimum variance filter for the identification of systems with additive and multiplicative noise is described which embodies both accuracy and computational efficiency. The resulting filter is shown to use both the covariance of the parameter vector itself and the covariance of the error in identification. A bias reduction scheme can be used to yield asymptotically unbiased estimates. Experimental results for simulated linearized lateral aircraft motion in a digital closed loop mode are presented, showing the utility of the identification schemes.

Kotob, S.↗
NASA NTRS1975

Finite difference identification of noisy distributed systems using scanning measurements

Most of the present-day literature concerned with identification theory and techniques is directed toward lumped parameter systems, and many comprehensive surveys of the field are available. Relatively little has appeared in the literature concerning distributed identification, and even more noticeable is the scarcity of papers dealing with systems described by the one-dimensional wave equation. Perdeauville and Goodson were perhaps the first researchers with a workable but time consuming method for the identification of coefficients of the wave equation. Fairman and Shen, also considering the wave equation, used the technique of finite differencing to approximate spatial derivatives, and Poisson filter chains to approximate temporal derivatives.

Hughes, R. O.↗
NASA NTRS1977

On the optical identifications of five X-ray sources

The data from a recently completed survey of the galactic plane with the SAS-3 modulation collimators provide precise (20 to 60 arcsec) celestial positions of galactic X-ray sources. Preliminary positions of 60-arcsec precision are reported for five sources. One of these led to the identification of the star, Gamma Cas, as an X-ray source, and the others lend substantial confidence to previously proposed optical identifications: 3U 0352+30 = X Per, 3U 1145-61 = HEN 715, GX301-2 = WRA977, and GX304-1 = MMV star. These identifications seem to establish the existence of a previously suggested class of Be-star X-ray emitters.

Bradt, H. V.↗
NASA NTRS1977

Crop identification and area estimation by computer-aided analysis of Landsat data

This report describes the results of a study involving the use of computer-aided analysis techniques applied to Landsat MSS data for identification and area estimation of winter wheat in Kansas and corn and soybeans in Indiana. Key elements of the approach included use of aerial photography for classifier training, stratification of Landsat data and extension of training statistics to areas without training data, and classification of a systematic sample of pixels from each county. Major results and conclusions are: (1) Landsat data was adequate for accurate identification and area estimation of winter wheat in Kansas, but corn and soybean estimates for Indiana were less accurate; (2) computer-aided analysis techniques can be effectively used to extract crop identification information from Landsat MSS data, and (3) systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county as well as district and state levels.

Bauer, M. E.↗
NASA NTRS1979

The list of the stars from the Two-micron sky survey: A preliminary catalog by G. N. Neugebauer et al (IRC), the identification of which is not correct

Two tables are published. The first presents the numbers of stars according to the Catalog IRC for which all or part of the identification with the Catalogs BS-HR, GC or DM is incorrect. The second table presents the numbers of stars in the IRC catalog, for which the identifications with variable stars printed with them are erroneous, whereas other identifications are usually correct.

Kukarkin, B. V.↗
NASA NTRS1978

Rotorcraft system identification techniques for handling qualities and stability and control evaluation

An integrated approach to rotorcraft system identification is described. This approach consists of sequential application of (1) data filtering to estimate states of the system and sensor errors, (2) model structure estimation to isolate significant model effects, and (3) parameter identification to quantify the coefficient of the model. An input design algorithm is described which can be used to design control inputs which maximize parameter estimation accuracy. Details of each aspect of the rotorcraft identification approach are given. Examples of both simulated and actual flight data processing are given to illustrate each phase of processing. The procedure is shown to provide means of calibrating sensor errors in flight data, quantifying high order state variable models from the flight data, and consequently computing related stability and control design models.

Hall, W. E., Jr.↗
NASA NTRS1981

A nonparametric identification method for a class of non-linear systems

A relatively simple nonparametric method for the identification of a class of close-coupled nonlinear multi-degree-of-freedom systems has been developed. The identification of arbitrary memoryless nonlinearities is possible through knowledge of the accelerations, velocities, and displacements of the various masses. These quantities are used to obtain the surfaces of the restoring forces as functions of the intermass displacements and velocities. The method was demonstrated by application to a four-degree-of-freedom system to identify the restoring forces. It is found that the identification results are relatively insensitive to measurement noise.

Udwadia, F. E.↗
NASA NTRS1980

Maximum likelihood estimation of label imperfection probabilities and its use in the identification of mislabeled patterns

Estimating label imperfections and the use of estimations in the identification of mislabeled patterns are discussed. Expressions are presented for the asymptotic variances of the probability of correct classification and proportion, and for the maximum likelihood estimates of classification errors and a priori probabilities. Models are developed for imperfections in the labels and classification errors, and expressions are derived for the probability of imperfect label identification schemes resulting in wrong decisions. The expressions are used in computing thresholds and the techniques are given practical applications. The imperfect label identification scheme in the multiclass case is found to amount to establishing a region around each decision surface, and decisions of the label correction scheme are found in close agreement with the analyst-interpreter interpretations of the imagery films. As an example, the application of the maximum likelihood estimation to the processing of Landsat MSS data is discussed.

Chittineni, C. B.↗
NASA NTRS1982

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Molusis, J. A.↗
NASA NTRS1983

Non-intrusive parameter identification procedure user's guide

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Hanson, G. D.↗
NASA NTRS1982

Mineral identification from orbit - Initial results from the Shuttle multispectral infrared radiometer

The Shuttle multispectral IR radiometer (SMIRR) was designed to obtain surface reflectance data in ten spectral bands in order to evaluate the usefulness of a future imaging system for remote mineral identification. Attention was given to the 2.0-2.4 micron region, which has a wealth of spectral absorption features and appeared to have potential for the identification of CO3- and OH-bearing minerals such as the kaolinite and montmorillonite clays. SMIRR radiances were normalized by using a spectrum for dune sand collected in the Kharga Depression in Egypt. Direct identifications have been made of kaolinite-containing and carbonate material, indicating an exceptional potential for future orbital platform narrowband spectral imaging systems for mineralogical mapping.

Goetz, A. F. H.↗
NASA NTRS1984

An on-line equivalent system identification scheme for adaptive control

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Sliwa, S. M.↗
NASA NTRS1983

Identification and estimation of the area planted with irrigated rice based on the visual interpretation of LANDSAT MSS data

The objective was to test the feasibility of the application of MSS-LANDSAT data to irrigated rice crop identification and area evaluation, within four rice growing regions of the Rio Grande do Sul state, in order to extend the methodology for the whole state. The applied methodology was visual interpretation of the following LANDSAT products: channels 5 and 7 black and white imageries and color infrared composite imageries all at the scale of 1:250.000. For crop identification and evaluation, the multispectral criterion and the seasonal variation were utilized. Based on the results it was possible to conclude that: (1) the satellite data were efficient for crop area identification and evaluation; (2) the utilization of the multispectral criterion, allied to the seasonal variation of the rice crop areas from the other crops and, (3) the large cloud cover percentage found in the satellite data made it impossible to realize a rice crop spectral monitoring and, therefore, to define the best dates for such data acquisition for rice crop assessment.

Parada, N. D. J.↗
NASA NTRS1984

Identification of quasi-steady compressor characteristics from transient data

The principal goal was to demonstrate that nonlinear compressor map parameters, which govern an in-stall response, can be identified from test data using parameter identification techniques. The tasks included developing and then applying an identification procedure to data generated by NASA LeRC on a hybrid computer. Two levels of model detail were employed. First was a lumped compressor rig model; second was a simplified turbofan model. The main outputs are the tools and procedures generated to accomplish the identification.

Nunes, K. B.↗
NASA NTRS1982

On-line methods for rotorcraft aeroelastic mode identification

The requirements for the on-line identification of rotorcraft aeroelastic blade modes from random response test data are presented. A recursive maximum likelihood (RML) technique is used in conjunction with a bandpass filter to identify isolated blade mode damping and frequency. The RML technique is demonstrated to have excellent convergence characteristics in random measurement noise and random process noise excitation. The RML identification technique uses an ARMA representation for the aeroelastic stochastic system and requires virtually no user interaction while providing accurate confidence bands on the parameter estimates. Comparisons are made with an off-line Newton type maximum likelihood algorithm which uses a state variable model representation. Results are presented from simulation random response data which quantify the identifed parameter convergence behavior for various levels of random excitation which is typical of wind tunnel turbulence levels. The RML technique is applied to hingless rotor test data from the NASA Langley Research Center Helicopter Hover Facility.

Molusis, J. A.↗