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A direct identification procedure is proposed to obtain the mass and stiffness matrices based on the test measured eigenvalues and eigenvectors. The method is based on the theory of matrix perturbation in which the correct mass and stiffness matrices are expanded in terms of analytical values plus a modification matrix. The simplicity of the procedure enables real time operation during the structural testing.
An approach for identifying the dynamics of large space structures is applied to a free-free beam. In this approach the system's order is determined on-line, along with mode shapes, using recursive lattice filters which provide a least square estimate of the measurement data. The mode shapes determined are orthonormal in the space of the measurements and, hence, are not the natural modes of the structure. To determine the natural modes of the structure, a method based on the fast Fourier transform is used on the outputs of the lattice filter. These natural modes are used to obtain the modal amplitude time series which provides the input data for an output error parameter identification scheme that identifies the ARMA parameters of the difference equation model of the modes. the approach is applied to both simulated and experimental data.
A recursive, extended Kalman-filter approach is applied to the identifiction of rotor damping levels of representative helicopter dynamic systems. The general formulation of the approach is presented in the context of a typically posed stochastic estimation problem, and the method is analytically applied to determining the damping levels of a coupled rotor-body system. The identified damping covergence characteristics are studied for sensitivity to both constant-coefficient and periodic-coefficient measurement models, process-noise covariance levels, and specified initial estimates of the rotor-system damping. A second application of the method to identifying the plant model for a highly damped, isolated flapping blade with a constant-coefficient state model (hover) and a periodic-coefficient state model (forward flight) is also investigated. The parameter-identification capability is evaluated for the effect of periodicity on the plant model coefficients and the influence of different measurement noise levels.
Airborne C- and L-band radar data acquired over a test site in western kansas were analyzed to determine corn-field identification accuracies obtainable using single-channel, multichannel, and multidate radar data. An automated pattern-recognition procedure was used to classify 144 fields into three categories: corn, pasture land, and bare soil (including wheat stubble and fallow). Corn fields were identified with accuracies ranging from 85 percent for single channel, single-date data to 100 percent for single-channel, multidate data. The effects of radar parameters such as frequency, polarization, and look angle as well as the effects of soil moisture on the classification accuracy are also presented.
An algorithm for processing flight-test data to provide state estimates and instrument calibrations for aerodynamic or hydrodynamic system identification by the equation error estimation method is developed and demonstrated on synthesized data. The extended-Kalman-filter algorithm employs a locally level, north-pointing frame of reference, accounts for rotating ellipsoidal earth effects, and estimates sensor bias, scale factors, wind components, and process noise levels by maximum-likelihood parameters. The method is found to be most effective with navigation quality inertial input data. The algorithm is applied to data from a six-degree-of-freedom F-4 aircraft simulation and shown to produce state estimates in good agreement with the simulation values.
The Aerodynamic Coefficient Identification Package (ACIP) is an instrument consisting of body mounted linear accelerometers, rate gyros, and angular accelerometers for measuring the Space Shuttle vehicular dynamics. The high rate recorded data are utilized for postflight aerodynamic coefficient extraction studies. Although consistent with pre-mission accuracies specified by the manufacturer, the ACIP data were found to contain detectable levels of systematic error, primarily bias, as well as scale factor, static misalignment, and temperature dependent errors. This paper summarizes the technique whereby the systematic ACIP error sources were detected, identified, and calibrated with the use of recorded dynamic data from the low rate, highly accurate Inertial Measurement Units.
The errors in the dynamic data output from the Aerodynamic Coefficient Identification Packages (ACIP) flown on Shuttle flights 1, 3, 4, and 5 were determined using the output from the Inertial Measurement Units (IMU). A weighted least-squares batch algorithm was empolyed. Using an averaging technique, signal detection was enhanced; this allowed improved calibration solutions. Global errors as large as 0.04 deg/sec for the ACIP gyros, 30 mg for linear accelerometers, and 0.5 deg/sec squared in the angular accelerometer channels were detected and removed with a combination is bias, scale factor, misalignment, and g-sensitive calibration constants. No attempt was made to minimize local ACIP dynamic data deviations representing sensed high-frequency vibration or instrument noise. Resulting 1sigma calibrated ACIP global accuracies were within 0.003 eg/sec, 1.0 mg, and 0.05 deg/sec squared for the gyros, linear accelerometers, and angular accelerometers, respectively.
A design approach for high speed normalization of digital signals was developed. A reciprocal look up table technique is employed, where a digital value is mapped to its reciprocal via a high speed memory. This reciprocal is then multiplied with an input signal to obtain the normalized result. Normalization improves considerably the accuracy of certain feature identification algorithms. By using the concept of pipelining the multispectral sensor data processing rate is limited only by the speed of the multiplier. The breadboard system was found to operate at an execution rate of five million normalizations per second. This design features high precision, a reduced hardware complexity, high flexibility, and expandability which are very important considerations for spaceborne applications. It also accomplishes a high speed normalization rate essential for real time data processing.
Statistical procedures were developed for large area assessments using both satellite and conventional data. Crop acreages, other ground cover indices, and measures of change were the principal characteristics of interest. These characteristics are capable of being estimated from samples collected possibly from several sources at varying times, with different levels of identification. Multiyear analysis techniques were extended to include partially identified samples; the best current year sampling design corresponding to a given sampling history was determined; weights reflecting the precision or confidence in each observation were identified and utilized, and the variation in estimates incorporating partially identified samples were quantified.
This paper seeks to develop the potential of lidar for the identification of the chemical composition of atmospheric aerosols. Available numerical computations suggest that aerosols can be identified by the wavelength dependence of aerosol optical properties. Since lidar can derive the volume backscatter coefficient as a function of wavelength, a multi-wavelength lidar system may be able to provide valuable information on the composition of aerosols. This research theoretically investigates the volume backscatter coefficients for the aerosol classes, sea-salts, and sulfates, as a function of wavelength. The results show that these aerosol compositions can be characterized and identified by their backscatter wavelength dependence. A method to utilize multi-wavelength lidar measurements to discriminate between compositionally different thin aerosol layers is discussed.
In large complex structures, with several major sound transmission paths and high levels of background noise, it can be a complex task to locate and rank the contribution of an individual sound transmission path. The two microphone acoustic intensity techniques are investigated as a tool for path identification. Laboratory tests indicate that, if the intensity transmitted through a particular section of the fuselage is measured in the presence and absence of flanking paths using the face to face and side by side microphone arrangements, then no significant difference exists between the two measured intensities if the face to face microphone arrangement is used. However, if the side by side arrangement is used, then considerable difference exists between the two measured intensities.
Frequency-domain methods are used to extract the open-loop dynamics of the XV-15 tilt-rotor aircraft from flight test data for the cruise condition (V = 170 knots). The frequency responses are numerically fitted with transfer-function forms to identify equivalent model characteristics. The associated handling quality parameters meet or exceed Level 2, Category A, requirements for fixed-wing military aircraft. Step response matching is used to verify the time-domain fidelity of the transfer-function models for the cruise and hover flight conditions. The transient responses of the model and aircraft are in close agreement in all cases, except for the normal acceleration response to elevator deflection in cruise. This discrepancy is probably due to the unmodeled rotor rpm dynamics. The utility of the frequency-domain approach for dynamics identification and analysis is clearly demonstrated.
A computational algorithm for the identification of biases in discrete-time, nonlinear, stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.
It is suggested that virtually all the X-ray sources in the Einstein Observatory's Medium Sensitivity Survey flux range can be identified with objects visible on the POSS, on the basis of the complete identification of all sources north of -25 deg declination. There is no evidence for a significant population of 'blank field' X-ray sources at this flux level, and therefore no evidence for any new X-ray source class with very high L(x)/L(v). Most of the quasars detected in the present survey are spectroscopically similar to optical or radio-selected quasars. About 25 percent of the quasar sample, however, had reddish colors, and permitted lines dominated by a narrow-line component. These objects form a second sequence of active galactic nuclei, distinct in their optical properties from the broad line objects.
A generic, U.S.-based analysis approach was evaluated with respect to corn and soybean identification in Argentina. Using crop separability expectations derived from the analysis of Argentina ancillary data and U.S. spectral data, the approach was applied to Argentina spectral data by an expert analyst. Eight classes were detected and labeled independent of ground data. A high correspondence between the labels and limited ground data was achieved. It was concluded that an approach of this type could be applied to Argentina without major difficulty.
The temporal-spectral profile is a detailed indicator of the physical state of a field through time. Characteristic profiles have been observed for a variety of crops and other cover classes from Landsat data in the United States Corn Belt. These profiles contain information to support crop identification at various levels.
The results presented in this paper demonstrate a methodology for identification of a non-linear model of the AV-88 V/STOL aircraft from flight test data. Conventional aerodynamics, thrust-induced aerodynamic effects and propulsion model correction factors are identified for hover, transitional and low-speed wingborne flight conditions. A special model formulation is adopted which is continuous at zero airspeed. The identified model is validated by prediction of flight test measurements, and by comparison with wind-tunnel results.
A spectrum of a much higher quality than previously available has been obtained which shows emission features arising from S(+), S(++), S(+++), and an upper limit for O(++). The well-defined splitting of the 1729 A feature is seen as confirming its tentative identification as semiforbidden S III 5S2(0)-3P2,1. The lower contamination of S III 1199 A by H I 1216 A than in most previous IUE spectra of the Io torus makes possible an estimate of the S III 1729 A collision strength. The variation of these features with temperature and their possible presence in spectra of nebulae are discussed.