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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

A method for overcoming the velocity space filamentation problem in collisionless plasma model solutions

The solution of filtered Vlasov-Maxwell equations, rather than the Vlasov-Maxwell equations themselves, is shown to ameliorate the velocity space filamentation problem in collisionless plasma models. Exact field solutions and filtered velocity distribution functions are obtained without introducing errors. Proper selection of the filter width is demonstrated to inhibit development of velocity space filamentation and, it is conjectured, position space filamentation. The results of sample calculations of both filtered and nonfiltered field solutions illustrate a high degree of agreement between both solutions, with significant savings in computational time and memory requirements with the filtered solutions.

Klimas, Alexander J.↗
NASA NTRS2003

Real-Time Attitude Independent Three Axis Magnetometer Calibration

In this paper new real-time approaches for three-axis magnetometer sensor calibration are derived. These approaches rely on a conversion of the magnetometer-body and geomagnetic-reference vectors into an attitude independent observation by using scalar checking. The goal of the full calibration problem involves the determination of the magnetometer bias vector, scale factors and non-orthogonality corrections. Although the actual solution to this full calibration problem involves the minimization of a quartic loss function, the problem can be converted into a quadratic loss function by a centering approximation. This leads to a simple batch linear least squares solution. In this paper we develop alternative real-time algorithms based on both the extended Kalman filter and Unscented filter. With these real-time algorithms, a full magnetometer calibration can now be performed on-orbit during typical spacecraft mission-mode operations. Simulation results indicate that both algorithms provide accurate integer resolution in real time, but the Unscented filter is more robust to large initial condition errors than the extended Kalman filter. The algorithms are also tested using actual data from the Transition Region and Coronal Explorer (TRACE).

Crassidis, John L.↗
NASA NTRS1985

Testing of a failure accommodation system on a highly flexible grid

This paper presents a scheme for on-line failure detection in systems with appreciable structural dynamics. The design is suboptimal because of extensive computational requirements of optimal schemes. To accomplish failure detection, the innovations sequence of a finite order Kalman filter is examined. Because of the heavy dependence of the system on the zero-mean character of the innovations sequence of the filter much attention has been given to the design and evaluation of the Kalman filters used. The filter designs are based on modal models of the structural dynamics. Two modal models were considered, one based on an analytic finite element model and the other based on empirically derived frequency and damping. Experiments using a grid structure are presented which illustrate operation and performance of the filter designs based on these models. The general character of the results presented is that appreciable errors exist in the filter design based on the finite element model. Substantial improvement results if the design model is modified to include empirically derived frequency and damping.

Montgomery, R. C.↗
NASA NTRS2004

Optical state estimation using wavefront data

The use of wavefront measurements to deduce the state of multiple optics in a telescope beam train - their misalignments and figure errors — can be confused by the fact that there are multiple potential sources for the same measured error. This talk applies Kalman filtering techniques as a tool for separating true telescope errors from artifactual testing errors in the alignment and testing of NASA’s James Webb Space Telescope, a large segmented-aperture cryogenic telescope to be launched after 2010.

Whitman, Tony↗
NASA NTRS2004

Broadband Wavefront Sensing for JWST Fine Phasing

An application of broadband image-based wavefront sensing is considered for JWST fine phasing. The wavefront sensing error is derived as a function of filter bandpass and then applied to determine the appropriate filter specifications for observatory fine-phasing. These specifications are defined by considering an optimization in the trade space consisting of detector integration time vs. filter bandpass subject to wavefront sensing error budget constraints.

Dean, Bruce↗
NASA NTRS1975

A Kalman filter for the Stoland system

A simple Kalman filter for potential use in STOL navigation systems is described. The mathematical formulation of all the elements of the filter, its initialization and overall operation are presented. Simulation results show that a typical approach flight to landing, the Kalman filter has much smaller errors during navigation on TACAN data and during transition from TACAN to MODILS data than a complementary filter. Summary type flow charts of the Kalman filter logic designed for the Sperry 1819A computer are presented. Also, the memory and real time requirements of the Kalman filter and complementary filter are described. The Kalman filter is shown to gain its superior performance at the expense of real time and memory required in the onboard computer.

Schmidt, S. F.↗
NASA NTRS1993

A numerical treatment of geodynamic viscous flow problems involving the advection of material interfaces

Effective numerical treatment of multicomponent viscous flow problems involving the advection of sharp interfaces between materials of differing physical properties requires correction techniques to prevent spurious diffusion and dispersion. We develop a particular algorithm, based on modern shock-capture techniques, employing a two-step nonlinear method. The first step involves the global application of a high-order upwind scheme to a hyperbolic advection equation used to model the distribution of distinct material components in a flow field. The second step is corrective and involves the application of a global filter designed to remove dispersion errors that result from the advection of discontinuities (e.g., material interfaces) by high-order, minimally dissipative schemes. The filter introduces no additional diffusion error. Nonuniform viscosity across a material interface is allowed for by the implementation of a compositionally weighted-inverse interface viscosity scheme. The combined method approaches the optimal accuracy of modern shock-capture techniques with a minimal increase in computational time and memory. A key advantage of this method is its simplicity to incorporate into preexisting codes be they finite difference, element, or volume of two or three dimensions.

Lenardic, A.↗
NASA NTRS1981

An optimal numerical filter for wide-field-of-view measurements of earth-emitted radiation

A technique is described in which all data points along an arc of the orbit may be used in an optimal numerical filter for wide-field-of-view measurements of earth emitted radiation. The statistical filter design is derived whereby the filter is required to give a minimum variance estimate of the radiative exitance at discrete points along the ground track of the satellite. An equation for the optimal numerical filter is given by minimizing the estimate error variance equation with respect to the filter weights, resulting in a discrete form of the Wiener-Hopf equation. Finally, variances of the errors in the radiant exitance can be computed along the ground track and in the cross track directions.

Smith, G. L.↗
NASA NTRS1990

Computation of the factorized error covariance of the difference between correlated estimators

A state estimation problem where some of the measurements may be common to two or more data sets is considered. Two approaches for computing the error covariance of the difference between filtered estimates (for each data set) are discussed. The first algorithm is based on postprocessing of the Kalman gain profiles of two correlated estimators. It uses UD factors of the covariance of the relative error. The second algorithm uses a square root information filter applied to relative error analysis. In the absence of process noise, the square root information filter is computationally more efficient and more flexible than the Kalman gain (covariance update) method. Both the algorithms (covariance and information matrix based) are applied to a Venus orbiter simulation, and their performances are compared.

Wolff, Peter J.↗
NASA NTRS1991

Simplification of the Kalman filter for meteorological data assimilation

The paper proposes a new statistical method of data assimilation that is based on a simplification of the Kalman filter equations. The forecast error covariance evolution is approximated simply by advecting the mass-error covariance field, deriving the remaining covariances geostrophically, and accounting for external model-error forcing only at the end of each forecast cycle. This greatly reduces the cost of computation of the forecast error covariance. In simulations with a linear, one-dimensional shallow-water model and data generated artificially, the performance of the simplified filter is compared with that of the Kalman filter and the optimal interpolation (OI) method. The simplified filter produces analyses that are nearly optimal, and represents a significant improvement over OI.

Dee, Dick P.↗
NASA NTRS1995

Determination of plasma temperatures and luminosities using multiple extreme-ultraviolet and X-ray filters

We carefully examine the techniques used to infer temperatures of stellar coronal plasmas from the count rates of several broadband instruments in the X-ray and extreme-ultraviolet spectral ranges. In particular, we determine to what extent temperatures can be constrained and the corresponding uncertainties in the luminosities and emission measures lowered by fitting simultaneously count rates from the Einstein imaging proportional counter (IPC), the ROSAT Position Sensitive Proportional Counter (PSPC), the ROSAT Wide Field Camera (WFC) (both filters), and the EXOSAT Low Energy Telescope (LET) with the 3-Lex filter. We use published plasma emissivities with solar photospheric abundances. Since it has been found that single-temperature plasmas do not fit IPC data well, we assume a two-temperature plasma model. We find that, even with count rates from all of the above filters and overly optimistic error estimates, it is still not possible to determine a unique two-temperature solution. However, since the use of count rates from many filters can reduce substantially the number of possible solutions, temperature solutions determined by other means can be tested. We carry out such an analysis on a set of 18 nearby late-type stars to determine possible two-temperature solutions using multifilter photometry, and we compare these results with the temperature solutions derived by Schmitt et al. (1990) using IPC spectral data. In general, the two-temperature fits derived from the IPC spectral data are inconsistent with our results, with our data implying that, for many stars, the two temperatures derived by the IPC may be too low by about a factor of 2. The EXOSAT transmission grating Spectrometer (TGS) spectra of capella and sigma(exp 2) CrB support this conclusion. For Procyon and 70 Oph, though, the presence of a temperature component cooler than a million degress (not detected by the IPC) is deduced. While our analysis suggests the existence of more than one temperature in the coronae of late-type stars, in many instances our WFC data appear to be inconsistent with the presence of significant emission measure over a broad temperature distribution. This, together with the success of two-temperature plasmas in fitting IPC and TGS data, implies that for many stars, the coronal emission measure distribution may in fact be dominated by two distinct temperature regimes.

Wood, Brian E.↗
NASA NTRS1985

A Kalman filter for a two-dimensional shallow-water model

A two-dimensional Kalman filter is described for data assimilation for making weather forecasts. The filter is regarded as superior to the optimal interpolation method because the filter determines the forecast error covariance matrix exactly instead of using an approximation. A generalized time step is defined which includes expressions for one time step of the forecast model, the error covariance matrix, the gain matrix, and the evolution of the covariance matrix. Subsequent time steps are achieved by quantifying the forecast variables or employing a linear extrapolation from a current variable set, assuming the forecast dynamics are linear. Calculations for the evolution of the error covariance matrix are banded, i.e., are performed only with the elements significantly different from zero. Experimental results are provided from an application of the filter to a shallow-water simulation covering a 6000 x 6000 km grid.

Parrish, D. F.↗
NASA NTRS1993

Estimate fusion for lunar rendezvous

The new derivation presented for an algorithm that fuses two Kalman filter outputs clearly demonstrates the combination of estimates to be capable of 'optimally' minimizing the trace of the fused covariance matrix. The method also furnishes an estimate whose error ellipses are contained within the intersection of the error ellipses from each filter. The 'reinitialized Kalman filter' obtained by these means is applied to the problem of lunar rendezvous.

Carpenter, J. R.↗
NASA NTRS1977

Distortion in AM-baseband telemetry

Report presents very thorough and rigorous analysis of bandwidths and filters required to achieve a specific error. Included is an investigation of contribution to error of 3- and 6-pole Chebyschev, Butterworth, and Bessel filters. Also included is methodology for designing DSB/FM telemetry system to make optimum use of available bandwidth while reducing error toward its theoretical minimum.

Salter, W. E.↗
NASA NTRS1976

On least-squares design of recursive digital filters

Time-domain methods for the design of recursive digital filters using a squared error criterion are compared with a frequency-domain technique. Levy's method, which has been used to estimate transfer functions of continuous-time systems is modified to obtain design equations for digital filters. A special case of Levy's method is shown to be essentially equivalent to the time-domain methods.

Shenoi, K.↗
NASA NTRS2013

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Eure, Kenneth W.↗
NASA NTRS1988

A general model for attitude determination error analysis

An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.

Markley, F. Landis↗