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Remarks on nonstandard least-squares problems

It is shown that after treating a least-squares problem in the standard fashion, the imposition of stochastic restrictions on certain parameters can be accomplished essentially by inverting a matrix of an order no larger than the total number of restricted parameters, and that generally there is an explicit term for correcting the unrestricted to the restricted solution. In addition, any known type of nonstandard least-squares adjustment problem can be reduced to an equivalent standard linear problem, that is, one in which there is exactly one observation per condition equation and in which the observations are not correlated.

Eichhorn, H.↗

On the method of least squares

A method for fitting models to observed data by least squares when the data appear nonlinearly in the equations of condition, where there are nonlinear constraints among model parameters, and where the observations may be correlated, is described. The method is independent of the form in which the equations of condition are expressed, and is a generalization of the classical technique. The method is nearly as simple to apply in practice as the classical method of least squares.

Jefferys, W. H.↗

Solar O I 1304-A triplet line profiles

Estimates were made of the full-disk line profiles of the solar O I resonant triplet at 1304 A, using data from the SMM and the Orbiting Solar Observatory 8 for the time period 1975-1985. The observed line profiles are parameterized using a nonlinear least squares fit of the data by a simple empirical representation of the general line shape. The derived full-disk line shape parameters may be used, in combination with an appropriate value for the line-integrated full-disk solar flux, in the analysis of planetary or cometary O I 1304-A observations under any solar conditions.

Gladstone, G. R.↗

Euler solutions for blunt bodies using triangular meshes - Artificial viscosity forms and numerical boundary conditions

A finite volume method is used to calculate compressible inviscid flows over blunt bodies using, in general, unstructured grids. Artificial viscosity forms are derived based on a simplified least squares procedure. The extra second order terms are consistent with the governing equations, hence a systematic treatment of the numerical boundary conditions can be easily implemented. A special treatment of blunt bodies may be required. The discrete equations are linearized and the resulting system is solved by a relaxation method. Preliminary results indicate that the effect of the numerical dissipation is minimal. For subsonic flows over smooth bodies, the solution is practically vorticity-free and the total pressure loss is of the same order as the truncation error. Finally, some extensions of the present method are briefly discussed.

Winterstein, R.↗

Atmospheric pressure loading parameters from very long baseline interferometry observations

Atmospheric mass loading produces a primarily vertical displacement of the Earth's crust. This displacement is correlated with surface pressure and is large enough to be detected by very long baseline interferometry (VLBI) measurements. Using the measured surface pressure at VLBI stations, we have estimated the atmospheric loading term for each station location directly from VLBI data acquired from 1979 to 1992. Our estimates of the vertical sensitivity to change in pressure range from 0 to -0.6 mm/mbar depending on the station. These estimates agree with inverted barometer model calculations (Manabe et al., 1991; vanDam and Herring, 1994) of the vertical displacement sensitivity computed by convolving actual pressure distributions with loading Green's functions. The pressure sensitivity tends to be smaller for stations near the coast, which is consistent with the inverted barometer hypothesis. Applying this estimated pressure loading correction in standard VLBI geodetic analysis improves the repeatability of estimated lengths of 25 out of 37 baselines that were measured at least 50 times. In a root-sum-square (rss) sense, the improvement generally increases with baseline length at a rate of about 0.3 to 0.6 ppb depending on whether the baseline stations are close to the coast. For the 5998-km baseline from Westford, Massachusetts, to Wettzell, Germany, the rss improvement is about 3.6 mm out of 11.0 mm. The average rss reduction of the vertical scatter for inland stations ranges from 2.7 to 5.4 mm.

Macmillan, D. S.↗

A Method to Solve Interior and Exterior Camera Calibration Parameters for Image Resection

An iterative method is presented to solve the internal and external camera calibration parameters, given model target points and their images from one or more camera locations. The direct linear transform formulation was used to obtain a guess for the iterative method, and herein lies one of the strengths of the present method. In all test cases, the method converged to the correct solution. In general, an overdetermined system of nonlinear equations is solved in the least-squares sense. The iterative method presented is based on Newton-Raphson for solving systems of nonlinear algebraic equations. The Jacobian is analytically derived and the pseudo-inverse of the Jacobian is obtained by singular value decomposition.

Samtaney, Ravi↗

A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

Jacobsen, R. T.↗

Attitude determination error analysis - General model and specific application

This paper presents a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The discussion includes models for both batch least-squares and sequential estimators, a specific dynamic model for attitude determination error analysis of a three-axis stabilized spacecraft equipped with strapdown gyros, and the incorporation of general attitude sensor observations. An analyst using this approach to perform an error analysis chooses a subset of the spacecraft parameters to be 'solve-for' parameters, which are to be estimated, and another subset to be 'consider' parameters, which are assumed to have errors but not to be estimated. The result of the error analysis is an indication of overall uncertainties in the 'solve-for' parameters, as well as the contributions of the various error sources to these uncertainties, including those of errors in the a priori 'solve-for' estimates, of measurement noise, of dynamic noise (also known as process noise or plant noise), and of 'consider' parameter uncertainties. The analysis of attitude, star tracker alignment, and gyro bias uncertainties for the Gamma Ray Observatory spacecraft provide a specific example of the use of a general-purpose software package incorporating these models.

Markley, F. Landis↗

Method for nonlinear exponential regression analysis

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

Junkin, B. G.↗

Solution of an integral equation encountered in studies on radiative transfer in completely absorbing leaf canopies

The leaf normal distribution function is related to the extinction coefficient of direct solar radiation by a Fredholm integral equation of the first kind. The integral equation is solved by the method of constrained least squares. The solutions are stable and correct only in extreme cases and, in general, it is not possible to recover an arbitrary leaf normal distribution function.

Myneni, Ranga B.↗

Constrained hierarchical least square nonlinear equation solvers

The current paper develops a constrained hierarchical least square nonlinear equation solver. The procedure can handle the response behavior of systems which possess indefinite tangent stiffness characteristics. Due to the generality of the scheme, this can be achieved at various hierarchical application levels. For instance, in the case of finite element simulations, various combinations of either degree of freedom, nodal, elemental, substructural, and global level iterations are possible. Overall, this enables a solution methodology which is highly stable and storage efficient. To demonstrate the capability of the constrained hierarchical least square methodology, benchmarking examples are presented which treat structure exhibiting highly nonlinear pre- and postbuckling behavior wherein several indefinite stiffness transitions occur.

Padovan, J.↗

Adjoint variational methods in nonconservative stability problems.

A general nonself-adjoint eigenvalue problem is examined and it is shown that the commonly employed approximate methods, such as the Galerkin procedure, the method of weighted residuals and the least square technique lack variational descriptions. When used in their previously known forms they do not yield stationary eigenvalues and eigenfunctions. With the help of an adjoint system, however, several analogous variational descriptions may be developed and it is shown in the present study that by properly restating the method of least squares, stationary eigenvalues may be obtained. Several properties of the adjoint eigenvalue problem, known only for a restricted group, are shown to exist for the more general class selected for study.

Prasad, S. N.↗

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Pan, Jianqiang↗

Comparison of Five System Identification Algorithms for Rotorcraft Higher Harmonic Control

This report presents an analysis and performance comparison of five system identification algorithms. The methods are presented in the context of identifying a frequency-domain transfer matrix for the higher harmonic control (HHC) of helicopter vibration. The five system identification algorithms include three previously proposed methods: (1) the weighted-least- squares-error approach (in moving-block format), (2) the Kalman filter method, and (3) the least-mean-squares (LMS) filter method. In addition there are two new ones: (4) a generalized Kalman filter method and (5) a generalized LMS filter method. The generalized Kalman filter method and the generalized LMS filter method were derived as extensions of the classic methods to permit identification by using more than one measurement per identification cycle. Simulation results are presented for conditions ranging from the ideal case of a stationary transfer matrix and no measurement noise to the more complex cases involving both measurement noise and transfer-matrix variation. Both open-loop identification and closed- loop identification were simulated. Closed-loop mode identification was more challenging than open-loop identification because of the decreasing signal-to-noise ratio as the vibration became reduced. The closed-loop simulation considered both local-model identification, with measured vibration feedback and global-model identification with feedback of the identified uncontrolled vibration. The algorithms were evaluated in terms of their accuracy, stability, convergence properties, computation speeds, and relative ease of implementation.

Jacklin, Stephen A.↗

Least-Squares Frequency-Acquisition Algorithm

Algorithm finds frequency and phase of sinudoidal signal in presence of noise. Algorithm is special case of more-general, adaptive-paramenter-estimation techniques. Computational requirements of algorithm comparable to corresponding fast-Fourier-transform (FFT) algorithm. Algorithm works directly in time domain, whereas FFT algorithm transforms data into frequency domain for estimation and detection and requires secondary algorithm to interpolate between frequencies.

Kumar, Rajendra↗

Interplanetary Fast Shocks and Associated Drivers Observed through the Twenty-Third Solar Minimum by WIND Over its First 2.5 Years

A list of the interplanetary (IP) shocks observed by WIND from its launch (in November 1994) to May 1997 is presented. Forty two shocks were identified. The magnetohydrodynamic nature of the shocks is investigated, and the associated shock parameters and their uncertainties are accurately computed using a practical scheme which combines two techniques. These techniques are a combination of the "pre-averaged" magnetic-coplanarity, velocity-coplanarity, and the Abraham-Schrauner-mixed methods, on the one hand, and the Vinas and Scudder [1986] technique for solving the non-linear least-squares Rankine-Hugoniot shock equations, on the other. Within acceptable limits these two techniques generally gave the same results, with some exceptions. The reasons for the exceptions are discussed. It is found that the mean strength and rate of occurrence of the shocks appears to correlated with the solar cycle. Both showed a decrease in 1996 coincident with the time of the lowest ultraviolet solar radiance, indicative of solar minimum and start of solar cycle 23, which began around June 1996. Eighteen shocks appeared to be associated with corotating interaction regions (CIRs). The distribution of their shock normals showed a mean direction peaking in the ecliptic plane and with a longitude (phi(sub n)) in that plane between perpendicular to the Parker spiral and radial from the Sun. When grouped according to the sense of the direction of propagation of the shocks the mean azimuthal (longitude) angle in GSE coordinates was approximately 194 deg for the fast-forward and approximately 20 deg for the fast-reverse shocks. Another 16 shocks were determined to be driven by solar transients, including magnetic clouds. These shocks had a broader distribution of normal directions than those of the CIR cases with a mean direction close to the Sun-Earth line. Eight shocks of unknown origin had normal orientation well off the ecliptic plane. No shock propagated with longitude phi(sub n) >= 220 +/- 10 deg, this would suggest strong hindrance to the propagation of shocks contra a rather tightly winding Parker spiral. Examination of the obliquity angle theta(sub Bn) (that between the shock normal and the upstream interplanetary magnetic field) for the full set of shocks revealed that about 58% was quasi-perpendicular, and some were very nearly perpendicular. About 32% of the shocks were oblique, and the rest (only 10%) were quasi-parallel, with one on Dec. 9, 1996 that showed field pulsations. Small uncertainty in the estimated angle theta(sub Bn) was obtained for about 10 shocks with magnetosonic Mach numbers between 1 and 2, hopefully significantly contributing to studies researching particle acceleration mechanisms at IP shocks, and to investigations where accurate values of theta(sub Bn) are crucial.

Mariani, F.↗

A parameter-estimation subroutine package

Estimation subroutine package comprises fast, efficient, and simple least-squares data-processing algorithms for use in orbit determination and related analyses. Very reliable and general algorithms have been documented. Package contains collection of streamlined subroutines that can be used to solve large variety of parameter-estimation and filtering problems. Special routines are included for problems with colored process noise and covariance (factor) mapping.

Bierman, G.↗

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Alston, D. W.↗