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At least 127 records · Page 7

Study of the use of a nonlinear, rate-limited filter on pilot control signals

The use of a nonlinear, rate limited filter for rejecting the remnant (noise) in a pilot's control signal was studied through both an analytical study using pilot models and a simulation study using experienced test pilots. The nonlinear filter was compared with a linear filter and with no filter for both attitude and altitude control tasks. The results show that the nonlinear filter does promote rapid, steady maneuvering better than either the linear filter or the no filter condition. In addition, if the rate limit in the nonlinear filter is set so that it is too restrictive, a pilot induced unstable altitude oscillation can result.

Adams, J. J.↗

Stripe filters on multispectral linear arrays

Dielectric interference filters deposited directly on top of existing 200 element charge coupled device linear imaging arrays were designed, fabricated and evaluated. The optical performance of the filters was verified with regard to crosstalk between adjacent detector elements. The filters showed an average in-band transmittance greater than 80% and a total out of band transmittance of less than 5%. Filter stability was adequate for operation in a space environment. The filter elements were definable in 12 to 25 micron element size compatible with existing silicon detectors. These type of measurement were made: (1) spectral transmission of the filter as deposited on witness plates; (2) spectral response of the silicon sensing device; (3) any optical interaction between filter and sensing device; (4) the response of the filter/sensor combination; and (5) repeatability and uniformity of filter characteristics. Detailed discussion of these evaluations are given.

Hall, J. H.↗

Optimal frequency domain textural edge detection filter

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

Townsend, J. K.↗

Robust failure detection filters

The robustness of detection filters applied to the detection of actuator failures on a free-free beam is analyzed. This analysis is based on computer simulation tests of the detection filters in the presence of different types of model mismatch, and on frequency response functions of the transfers corresponding to the model mismatch. The robustness of detection filters based on a model of the beam containing a large number of structural modes varied dramatically with the placement of some of the filter poles. The dynamics of these filters were very hard to analyze. The design of detection filters with a number of modes equal to the number of sensors was trivial. They can be configured to detect any number of actuator failure events. The dynamics of these filters were very easy to analyze and their robustness properties were much improved. A change of the output transformation allowed the filter to perform satisfactorily with realistic levels of model mismatch.

Sanmartin, A. M.↗

A further analysis for the minimum-variance deconvolution filter performance

Chi and Mendel (1984) analyzed the performance of minimum-variance deconvolution (MVD). In this correspondence, a further analysis of the performance of the MVD filter is presented. It is shown that the MVD filter performs like an inverse filter and a whitening filter as SNR goes to infinity, and like a matched filter as SNR goes to zero. The estimation error of the MVD filter is colored noise, but it becomes white when SNR goes to zero. This analysis also conects the error power-spectral density of the MVD filter with the spectrum of the causal-prediction error filter.

Chi, Chong-Yung↗

The effects of clutter-rejection filtering on estimating weather spectrum parameters

The effects of clutter-rejection filtering on estimating the weather parameters from pulse Doppler radar measurement data are investigated. The pulse pair method of estimating the spectrum mean and spectrum width of the weather is emphasized. The loss of sensitivity, a measure of the signal power lost due to filtering, is also considered. A flexible software tool developed to investigate these effects is described. It allows for simulated weather radar data, in which the user specifies an underlying truncated Gaussian spectrum, as well as for externally generated data which may be real or simulated. The filter may be implemented in either the time or the frequency domain. The software tool is validated by comparing unfiltered spectrum mean and width estimates to their true values, and by reproducing previously published results. The effects on the weather parameter estimates using simulated weather-only data are evaluated for five filters: an ideal filter, two infinite impulse response filters, and two finite impulse response filters. Results considering external data, consisting of weather and clutter data, are evaluated on a range cell by range cell basis. Finally, it is shown theoretically and by computer simulation that a linear phase response is not required for a clutter rejection filter preceeding pulse-pair parameter estimation.

Davis, W. T.↗

Filtering analysis of a direct numerical simulation of the turbulent Rayleigh-Benard problem

A filtering analysis of a turbulent flow was developed which provides details of the path of the kinetic energy of the flow from its creation via thermal production to its dissipation. A low-pass spatial filter is used to split the velocity and the temperature field into a filtered component (composed mainly of scales larger than a specific size, nominally the filter width) and a fluctuation component (scales smaller than a specific size). Variables derived from these fields can fall into one of the above two ranges or be composed of a mixture of scales dominated by scales near the specific size. The filter is used to split the kinetic energy equation into three equations corresponding to the three scale ranges described above. The data from a direct simulation of the Rayleigh-Benard problem for conditions where the flow is turbulent are used to calculate the individual terms in the three kinetic energy equations. This is done for a range of filter widths. These results are used to study the spatial location and the scale range of the thermal energy production, the cascading of kinetic energy, the diffusion of kinetic energy, and the energy dissipation. These results are used to evaluate two subgrid models typically used in large-eddy simulations of turbulence. Subgrid models attempt to model the energy below the filter width that is removed by a low-pass filter.

Eidson, T. M.↗

Effects of space exposure on optical filters

Optical transmittance characteristics of nine optical filters were remeasured after nearly six years in space aboard the NASA Long-Duration Exposure Facility. Three different filter types were included. In general, transmittance decreased for most filters. The center frequency and bandpass of a narrow-band filter under an aluminum cover were unchanged, while narrow-band filters exposed directly to the space environment tended to show a shift in center frequency and increased bandwidth. A pair of infrared-reflecting mirrors exhibited reduced transmittance in the visible, with a mirror under an aluminum cover less degraded than a mirror exposed to space. The bandpass was unchanged for both of these mirrors. Neutral density filters showed a slight increase in transmittance for an uncovered filter; essentially no change for the filter under the aluminum cover.

Blue, M. D.↗

Wavelength tunable liquid crystal imaging filters for remote sensing from geosynchronous platforms

Recent advances in liquid crystal technology have enabled us to construct tunable birefringent filters with bandwidths between approximately 0.1 nm and 50 nm. The center wavelength of these filters can be selected electronically, in a few tens of milliseconds, with no moving parts. These liquid crystal tunable filters (LCTF's), together with existing CCD detectors, make possible a new generation of lightweight, rugged, high-resolution imaging spectrophotometers. Such instruments would be particularly interesting for remote sensing applications from geosynchronous platforms. Important advantages exist in the aperture, absence of image shift, power consumption, size, weight, and absence of high drive frequencies, compared to current instruments used or considered for multispectral scene analysis. In the present work, we have reviewed spectral requirements of planned NASA geosynchronous remote sensing missions and identified several applications of the liquid crystal tunable filter technology. We have modeled the LCTF performance in the visible and near-infrared, and carried out a literature study on space-hardening of the filter components, to evaluate the suitability of LCTF's for geosynchronous missions. We have also compared the power consumption, weight, size, reliability, and optical performance of an imaging spectrophotometer using a LCTF monochromator, to other instruments that have been put forward for remote sensing from geosynchronous platforms. We put forward some conceptual designs for LCTF's that seem to offer important reliability, over the mechanical filter wheels presently baselined for the HEPI and ALM experiments. The extremely wide acceptance angle achievable with LCTF's could also avoid the present need for large-aperture interference filters in the ALM (and LIS) experiments. Thermal vacuum testing and radiation damage analysis is required to investigate the space hardening of these new filters for geosynchronous flight.

Foukal, Peter↗

Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions. Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz model as well as more realistic models of the means and atmosphere. A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter situations to allow for correct update of the ensemble members. The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to be quite puzzling in that results state estimates are worse than for their filter analogue. In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use the Lorenz model to test and compare the behavior of a variety of implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqui↗

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqiu↗

Optical Metrology for the Filter Set for the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS)

The Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) will employ a wide variety of spectral filtration components including narrow band, medium band, wide band, and far ultraviolet (FUV) long pass filters, spatially- variable filters (ramp filters), VIS/IR polarizers, NUV polarizers, FUV prisms, and a grism. These components are spread across ACS's Wide Field, High Resolution, and Solar Blind channels which provide diffraction-limited imaging of astronomical targets using aberration-correcting optics which remove most aberrations from HST's Optical Telescope Assembly (OTA). In order for ACS to be truly advanced, these filters must push the state-of-the-art in performance in a number of key areas at the same time. Important requirements which these filters must meet include outstanding transmitted wavefront, high transmittance, uniform transmittance across each filter, spectrally structure-free bandpasses, exceptionally high out of band rejection, and a high degree of parfocality. These constitute a very stringent set of requirements indeed, especially for filters which are up to 90 mm in diameter. The development of optical metrology stations used to demonstrate that each ACS filter will meet its design specifications is discussed. Of particular note are specially-designed spectral transmissometers and interferometers.

Leviton, Douglas B.↗

A K-band Frequency Agile Microstrip Bandpass Filter using a Thin Film HTS/Ferroelectric/dielectric Multilayer Configuration

We report on YBa2Cu3O(7-delta) (YBCO) thin film/SrTiO3 (STO) thin film K-band tunable bandpass filters on LaAlO3 (LAO) dielectric substrates. The 2 pole filter has a center frequency of 19 GHz and a 4% bandwidth. Tunability is achieved through the non-linear dc electric field dependence of the relative dielectric constant of STO(epsilon(sub rSTO). A large tunability ((Delta)f/f(sub 0) = (f(sub Vmax) - f(sub 0)/f(sub 0), where f(sub 0) is the center frequency of the filter at no bias and f(sub Vmax) is the center frequency of the filter at the maximum applied bias) of greater than 10% was obtained in YBCO/STO/LAO microstrip bandpass filters operating below 77 K. A center frequency shift of 2.3 GHz (i.e., a tunability factor of approximately 15%) was obtained at a 400 V bipolar dc bias, and 30 K, with minimal degradation in the insertion loss of the filter. This paper addresses design, fabrication and testing of tunable filters based on STO ferroelectric thin films. The performance of the YBCO/STO/LAO filters is compared to that of gold/STO/LAO counterparts.

Subramanyam, Guru↗

Technical Report Series on Global Modeling and Data Assimilation: Filtering Techniques on a Stretched Grid General Circulation Model - Volume 16

This report documents the techniques used to filter quantities on a stretched grid general circulation model. Standard high-latitude filtering techniques (e.g., using an FFT (Fast Fourier Transformations) to decompose and filter unstable harmonics at selected latitudes) applied on a stretched grid are shown to produce significant distortions of the prognostic state when used to control instabilities near the pole. A new filtering technique is developed which accurately accounts for the non-uniform grid by computing the eigenvectors and eigenfrequencies associated with the stretching. A filter function, constructed to selectively damp those modes whose associated eigenfrequencies exceed some critical value, is used to construct a set of grid-spaced weights which are shown to effectively filter without distortion. Both offline and GCM (General Circulation Model) experiments are shown using the new filtering technique. Finally, a brief examination is also made on the impact of applying the Shapiro filter on the stretched grid.

Takacs, Lawrence L.↗

Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Simon, Dan↗

The Filtered Abel Transform and Its Application in Combustion Diagnostics

Many non-intrusive combustion diagnosis methods generate line-of-sight projections of a flame field. To reconstruct the spatial field of the measured properties, these projections need to be deconvoluted. When the spatial field is axisymmetric, commonly used deconvolution method include the Abel transforms, the onion peeling method and the two-dimensional Fourier transform method and its derivatives such as the filtered back projection methods. This paper proposes a new approach for performing the Abel transform method is developed, which possesses the exactness of the Abel transform and the flexibility of incorporating various filters in the reconstruction process. The Abel transform is an exact method and the simplest among these commonly used methods. It is evinced in this paper that all the exact reconstruction methods for axisymmetric distributions must be equivalent to the Abel transform because of its uniqueness and exactness. Detailed proof is presented to show that the two dimensional Fourier methods when applied to axisymmetric cases is identical to the Abel transform. Discrepancies among various reconstruction method stem from the different approximations made to perform numerical calculations. An equation relating the spectrum of a set of projection date to that of the corresponding spatial distribution is obtained, which shows that the spectrum of the projection is equal to the Abel transform of the spectrum of the corresponding spatial distribution. From the equation, if either the projection or the distribution is bandwidth limited, the other is also bandwidth limited, and both have the same bandwidth. If the two are not bandwidth limited, the Abel transform has a bias against low wave number components in most practical cases. This explains why the Abel transform and all exact deconvolution methods are sensitive to high wave number noises. The filtered Abel transform is based on the fact that the Abel transform of filtered projection data is equal to an integral transform of the original projection data with the kernel function being the Abel transform of the filtering function. The kernel function is independent of the projection data and can be obtained separately when the filtering function is selected. Users can select the best filtering function for a particular set of experimental data. When the kernal function is obtained, it can be used repeatedly to a number of projection data sets (rovs) from the same experiment. When an entire flame image that contains a large number of projection lines needs to be processed, the new approach significantly reduces computational effort in comparison with the conventional approach in which each projection data set is deconvoluted separately. Computer codes have been developed to perform the filter Abel transform for an entire flame field. Measured soot volume fraction data of a jet diffusion flame are processed as an example.

Simons, Stephen N.↗

Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Simon, Dan↗

Magnetic Bearing Amplifier Output Power Filters for Flywheel Systems

Five power filters and two types of power amplifiers were tested for use with active magnetic bearings for flywheel applications. Filter topologies included low pass filters and low pass filters combined with trap filters at the PWM switching frequency. Two state and three state PWM amplifiers were compared. Each system was evaluated based on current magnitude at the switching frequency, voltage magnitude at 500 kHz, and power consumption. The base line system was a two state amplifier without a power filter. The recommended system is a three state power amplifier with a 50 kHz low pass filter and a 27 kHz trap filter. This system uses 5.57 W. It reduces the switching current by an order of magnitude and the 500 kHz voltage by two orders of magnitude. The relative power consumption varied depending on the test condition between 60 to 130 percent of the baseline.

Lebron-Velilla, Ramon C.↗