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At least 307 records · Page 17

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NASA NTRS1976

Results from the Crop Identification Technology Assessment for Remote Sensing (CITARS) project

The author has identified the following significant results. It was found that several factors had a significant effect on crop identification performance: (1) crop maturity and site characteristics, (2) which of several different single date automatic data processing procedures was used for local recognition, (3) nonlocal recognition, both with and without preprocessing for the extension of recognition signatures, and (4) use of multidate data. It also was found that classification accuracy for field center pixels was not a reliable indicator of proportion estimation performance for whole areas, that bias was present in proportion estimates, and that training data and procedures strongly influenced crop identification performance.

Bauer, M. E.↗

NASA NTRS1975

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Bizzell, R. M.↗

NASA NTRS1976

Optical identification of A0620-00

Identification of the optical counterpart to the transient X-ray source A0620-00 was made using image tube photography. Spectra taken subsequent to the identification showed no stellar absorption or emission features. Photometric data gave a V magnitude of 11.2 + or - .1. This is about 8 magnitudes brighter than the object appears on the Palomar Sky Survey.

Wolfson, R.↗

NASA NTRS1975

Analysis and application of minimum variance discrete time system identification

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

Kaufman, H.↗

NASA NTRS1976

Flight data identification of six degree-of-freedom stability and control derivatives of a large crane type helicopter

Flight test data from a large 'crane' type helicopter were collected and processed for the purpose of identifying vehicle rigid body stability and control derivatives. The process consisted of using digital and Kalman filtering techniques for state estimation and Extended Kalman filtering for parameter identification, utilizing a least squares algorithm for initial derivative and variance estimates. Data were processed for indicated airspeeds from 0 m/sec to 152 m/sec. Pulse, doublet and step control inputs were investigated. Digital filter frequency did not have a major effect on the identification process, while the initial derivative estimates and the estimated variances had an appreciable effect on many derivative estimates. The major derivatives identified agreed fairly well with analytical predictions and engineering experience. Doublet control inputs provided better results than pulse or step inputs.

Tomaine, R. L.↗

NASA NTRS1976

Recursive identification and tracking of parameters for linear and non-linear multivariable systems

The problem of identifying constant and variable parameters in multi-input, multi-output, linear and nonlinear systems is considered, using the maximum likelihood approach. An iterative algorithm, leading to recursive identification and tracking of the unknown parameters and the noise covariance matrix, is developed. Agile tracking and accurate and unbiased identified parameters are obtained. Necessary conditions for a globally asymptotically stable identification process are provided; the conditions proved to be useful and efficient. Among different cases studied, the stability derivatives of an aircraft were identified and some of the results are shown as examples.

Sidar, M.↗

NASA NTRS1976

Rotor Dynamic State and Parameter Identification from Hovering Transients

State and parameter identifications based on a form of the maximum likelihood method are applied to the problem of extracting linear perturbation models, including rotor dynamic inflow effects, from transient blade flapping measurements. The estimation method is first studied in computer simulations and then applied to cyclic pitch stirring transients generated with a four-bladed rotor model operating in hovering trim conditions. The analytical perturbation models extracted from the transient test results are compared with transient and frequency response tests not used in the state and parameter identification. The identified analytical perturbation model is also compared with a simple theory. The method that is applicable both to small scale and full scale dynamic rotor testing is being extended to perturbations from forward flight trim conditions.

Hohenemser, K. H.↗

NASA NTRS1976

The revised 3C catalog of radio sources - A review of optical identifications and spectroscopy

We present a catalog of the important optical data for the radio sources in the Revised Third Cambridge Catalog. Optical positions, redshifts, magnitudes, and identifications have been included, as well as radio flux densities and spectral indices for the sample of 297 extragalactic 3CR sources. A bibliography of optical identifications, spectroscopy, and radio position/structure is also given. In addition to the literature compilation, we present new spectroscopic observations of 27 3CR radio galaxies, 25 of which do not have previously published redshifts.

Smith, H. E.↗

NASA NTRS1976

Analysis and application of minimum variance discrete time system identification

Kotob, S.↗

NASA NTRS1978

Reliable dual-redundant sensor failure detection and identification for the NASA F-8 DFBW aircraft

A technique was developed which provides reliable failure detection and identification (FDI) for a dual redundant subset of the flight control sensors onboard the NASA F-8 digital fly by wire (DFBW) aircraft. The technique was successfully applied to simulated sensor failures on the real time F-8 digital simulator and to sensor failures injected on telemetry data from a test flight of the F-8 DFBW aircraft. For failure identification the technique utilized the analytic redundancy which exists as functional and kinematic relationships among the various quantities being measured by the different control sensor types. The technique can be used not only in a dual redundant sensor system, but also in a more highly redundant system after FDI by conventional voting techniques reduced to two the number of unfailed sensors of a particular type. In addition the technique can be easily extended to the case in which only one sensor of a particular type is available.

Deckert, J. C.↗

NASA NTRS1977

F-8 DFBW sensor failure identification using analytic redundancy

The structure of a sensor failure detection and identification system designed for the NASA F-8 DFBW aircraft is outlined. The system is for use in a dual-redundant environment, and it takes maximal advantage of all functional relationships among the sensed variables. The identification logic uses the quality sequential probability ratio, which provides a useful on-line measure of confidence in the various forms of analytic redundancy. Preliminary simulation results indicate good behavior of the analytic decision statistic, based on the sequential probability ratio test.

Deckert, J. C.↗

NASA NTRS1977

Analysis and application of minimum variance discrete linear system identification

An on-line minimum variance (MV) parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise (AMN). The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean-square convergent and mean-square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kotob, S.↗

NASA NTRS1977

Comparison of continuous and discrete adaptive identification algorithms

Discretization of a popular continuous-time control algorithm is effected and an equivalent discrete-time identification law developed and compared to a published discrete identification algorithm developed from Lyapunov Theory. Results are compared as regards asymptotic stability as insured using Lyapunov theory. Some analysis and design guidelines are proposed as regards implementation and practical utility.

Colburn, B. K.↗

NASA NTRS1978

A comprehensive data processing plan for crop calendar MSS signature development from satellite imagery: Crop identification using vegetation phenology

The author has identified the following significant results. The phenological method of crop identification involves the creation of crop signatures which characterize multispectral observations as phenological growth states. The phenological signature models spectral reflectance explicitly as a function of crop maturity rather than as a function of date. A correspondence of time to growth state is established which minimizes the smallest difference between the given multispectral multitemporal vector and a category mean vector. The application of the method to the identification of winter wheat and corn shows (1) the method is capable of discriminating crop type with about the same degree of accuracy as more traditional classifiers; (2) the use of LANDSAT observations on two or more dates yields better results than the use of a single observation; and (3) some potential is demonstrated for labeling the degree of maturity of the crop, as well as the crop type.

Hlavka, C. A.↗

NASA NTRS1978

Human operator identification model and related computer programs

Four computer programs which provide computational assistance in the analysis of man/machine systems are reported. The programs are: (1) Modified Transfer Function Program (TF); (2) Time Varying Response Program (TVSR); (3) Optimal Simulation Program (TVOPT); and (4) Linear Identification Program (SCIDNT). The TV program converts the time domain state variable system representative to frequency domain transfer function system representation. The TVSR program computes time histories of the input/output responses of the human operator model. The TVOPT program is an optimal simulation program and is similar to TVSR in that it produces time histories of system states associated with an operator in the loop system. The differences between the two programs are presented. The SCIDNT program is an open loop identification code which operates on the simulated data from TVOPT (or TVSR) or real operator data from motion simulators.

Kessler, K. M.↗

NASA NTRS1977

Theoretic aspects of the identification of the parameters in the optimal control model

The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.

Vanwijk, R. A.↗

NASA NTRS1979

The new identifications of the variable stars with the stars from the ""Two-Micron Sky Survey: A Preliminary Catalog'' by G. Neugebauer etal. (IRC)

A list of 151 variable stars is presented. The identification of 148 of them is beyond any doubt. The identification of 3 stars is quite probable, but requires further checking.

Kukarkin, B. V.↗

NASA NTRS1979

Time-of-flight technique for particle identification at energies from 2 to 400 keV/nucleon

The time of flight technique for particle identification was extended to 2 keV/nucleon and the size of the start-time detector was reduced considerably by the use of carbon foils of few micrograms/cm square in thickness combined with microchannel plates for detecting secondary electrons. Time of flight telescopes incorporating this start-time device were used to measure the stopping power of a number of low energy heavy ions in thin carbon foils and the charge states of these ions emerging from such foils. Applications for the detection and identification of low energy interplanetary and magnetospheric particles are suggested.

Gloeckler, G.↗