Efficient recursive estimation - application to estimating the parameters of a covariance function.
Estimating parameters of covariance function with modified stochastic approximation
STATISTICAL CORRELATION↗
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A recursive approach to signal detection
Likelihood ratio analysis for detecting signals in additive non-white noise
Boorstyn, R. R.↗
Design of recursive digital filters having specified phase and magnitude characteristics
A method for a computer-aided design of a class of optimum filters, having specifications in the frequency domain of both magnitude and phase, is described. The method, an extension to the work of Steiglitz, uses the Fletcher-Powell algorithm to minimize a weighted squared magnitude and phase criterion. Results using the algorithm for the design of filters having specified phase as well as specified magnitude and phase compromise are presented.
King, R. E.↗
The estimation of the constituent densities of the upper atmosphere by means of a recursive filtering algorithm.
The structure of the upper atmosphere can be indirectly probed by light in order to determine the global density structure of ozone, aerosols, and neutral atmosphere. Scattered and directly transmitted light is measured by a satellite and is shown to be a nonlinear function of the state which is defined to be a point-wise decomposition of the density profiles. Dynamics are imposed on the state vector and a structured estimation problem is developed. The estimation of these densities is then performed using a linearized Kalman-Bucy filter and a linearized Kushner-Stratonovich filter.
Mcgarty, T. P.↗
Recursive formulas for the partial fraction expansion of a rational function with multiple poles.
The coefficients in the partial fraction expansion considered are given by Heaviside's formula. The evaluation of the coefficients involves the differential of a quotient of two polynomials. A simplified approach for the evaluation of the coefficients is discussed. Leibniz rule is applied and a recurrence formula is derived. A coefficient can also be determined from a system of simultaneous equations. Practical methods for the performance of the computational operations involved in both approaches are considered.
Chang, F.-C.↗
Evaluation of geopotential and luni-solar perturbations by a recursive algorithm
The disturbing functions due to the geopotential and Luni-solar attractions are linear and bilinear forms in spherical harmonics. Making use of recurrence relations for the solid spherical harmonics and their derivatives, recurrence formulas are obtained for high degree terms as function of lower degree for any term of those disturbing functions and their derivative with respect to any element. The equations obtained are effective when a numerical integration of the equations of motion is appropriate. In analytical theories, they provide a fast way of obtaining high degree terms starting from initial very simple functions.
Giacaglia, G. E. O.↗
Stochastic process approximation for recursive estimation with guaranteed bound on the error covariance
An approach, is proposed for the design of approximate, fixed order, discrete time realizations of stochastic processes from the output covariance over a finite time interval, was proposed. No restrictive assumptions are imposed on the process; it can be nonstationary and lead to a high dimension realization. Classes of fixed order models are defined, having the joint covariance matrix of the combined vector of the outputs in the interval of definition greater or equal than the process covariance; (the difference matrix is nonnegative definite). The design is achieved by minimizing, in one of those classes, a measure of the approximation between the model and the process evaluated by the trace of the difference of the respective covariance matrices. Models belonging to these classes have the notable property that, under the same measurement system and estimator structure, the output estimation error covariance matrix computed on the model is an upper bound of the corresponding covariance on the real process. An application of the approach is illustrated by the modeling of random meteorological wind profiles from the statistical analysis of historical data.
Menga, G.↗
A recursively formulated first-order semianalytic artificial satellite theory based on the generalized method of averaging. Volume 2: The explicit development of the first-order averaged equations of motion and for the nonspherical gravitational and nonresonant third-body perturbations
For abstract, see N78-28147.
Mcclain, W. D.↗
Geomagnetic field modeling by optimal recursive filtering
Data sets selected for mini-batches and the software modifications required for processing these sets are described. Initial analysis was performed on minibatch field model recovery. Studies are being performed to examine the convergence of the solutions and the maximum expansion order the data will support in the constant and secular terms.
Source record↗
Geomagnetic field modeling by optimal recursive filtering
Five individual 5 year mini-batch geomagnetic models were generated and two computer programs were developed to process the models. The first program computes statistics (mean sigma, weighted sigma) on the changes in the first derivatives (linear terms) of the spherical harmonic coefficients between mini-batches. The program ran successfully. The statistics are intended for use in computing the state noise matrix required in the information filter. The second program is the information filter. Most subroutines used in the filter were tested, but the coefficient statistics must be analyzed before the filter is run.
Source record↗
Adaptive identification and control of structural dynamics systems using recursive lattice filters
A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.
Sundararajan, N.↗
Adaptive modal control of structural dynamic systems using recursive lattice filters
Explore the source record for details and available documents.
Sundararajan, N.↗
Recursive Dynamic Equations For Two Robot Arms In A Closed Chain
Paper discusses use of difference equations from Kalman filtering and Bryson-Frazier smoothing to solve equations of forward dynamics of closed chain of robot-arm links. "Forward dynamics" is computation of linear and angular accelerations of joints between links, given set of applied or prescribed joint torques. Paper lays foundation for potential use of filtering and smoothing techniques in dynamics of robots and in design of controls for robots.
Rodriguez, Guillermo↗
Recursive least squares estimation and Kalman filtering by systolic arrays
One of the most promising new directions for high-throughput-rate problems is that based on systolic arrays. In this paper, using the matrix-decomposition approach, a systolic Kalman filter is formulated as a modified square-root information filter consisting of a whitening filter followed by a simple least-squares operation based on the systolic QR algorithm. By proper skewing of the input data, a fully pipelined time and measurement update systolic Kalman filter can be achieved with O(n squared) processing cells, resulting in a system throughput rate of O (n).
Chen, M. J.↗
An optimal recursive filter for the attitude determination of the Spacelab instrument pointing subsystem
The instrument pointing subsystem (IPS) is a three-axis stabilized platform developed to point various astronomical observation instruments aboard NASA's Shuttle. In order to compensate for system drifts and attitude errors, the IPS utilizes a linearized Kalman filter (LKF) with precomputed gains. Since the a priori gains are generated for an expected system configuration, any system variations result in a suboptimal estimation process. The performance of two real-time estimation filters is compared with that of the current LKF implementation. It is shown that a real-time estimation filter that reduces sensitivity to system variations and preflight computations is feasible.
West, Mark E.↗
A recursive approach to the equations of motion for the maneuvering and control of flexible multi-body systems
Interest lies in a mathematical formulation capable of accommodating the problem of maneuvering a space structure consisting of a chain of articulated flexible substructures. Simultaneously, any perturbations from the 'rigid body' maneuvering and any elastic vibration must be suppressed. The equations of motion for flexible bodies undergoing rigid body motions and elastic vibrations can be obtained conveniently by means of Lagrange's equations in terms of quasi-coordinates. The advantage of this approach is that it yields equations in terms of body axes, which are the same axes that are used to express the control forces and torques. The equations of motion are nonlinear hybrid differential quations. The partial differential equations can be discretized (in space) by means of the finite element method or the classical Rayleigh-Ritz method. The result is a set of nonlinear ordinary differential equations of high order. The nonlinearity can be traced to the rigid body motions and the high order to the elastic vibration. Elastic motions tend to be small when compared with rigid body motions.
Kwak, Moon K.↗
A real-time recursive filter for the attitude determination of the Spacelab instrument pointing subsystem
A real-time estimation filter which reduces sensitivity to system variations and reduces the amount of preflight computation is developed for the instrument pointing subsystem (IPS). The IPS is a three-axis stabilized platform developed to point various astronomical observation instruments aboard the shuttle. Currently, the IPS utilizes a linearized Kalman filter (LKF), with premission defined gains, to compensate for system drifts and accumulated attitude errors. Since the a priori gains are generated for an expected system, variations result in a suboptimal estimation process. This report compares the performance of three real-time estimation filters with the current LKF implementation. An extended Kalman filter and a second-order Kalman filter are developed to account for the system nonlinearities, while a linear Kalman filter implementation assumes that the nonlinearities are negligible. The performance of each of the four estimation filters are compared with respect to accuracy, stability, settling time, robustness, and computational requirements. It is shown, that for the current IPS pointing requirements, the linear Kalman filter provides improved robustness over the LKF with less computational requirements than the two real-time nonlinear estimation filters.
West, M. E.↗
Introduction in IND and recursive partitioning
This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, and lists the manual pages for the routines and instructions on installation.
Buntine, Wray↗