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Vacuum evaporation method for manufacturing neutral density filters with nonlinear density profiles.
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Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll
Telban and Cardullo have developed and successfully implemented the non-linear optimal motion cueing algorithm at the Visual Motion Simulator (VMS) at the NASA Langley Research Center in 2005. The latest version of the non-linear algorithm performed filtering of motion cues in all degrees-of-freedom except for pitch and roll. This manuscript describes the development and implementation of the non-linear optimal motion cueing algorithm for the pitch and roll degrees of freedom. Presented results indicate improved cues in the specified channels as compared to the original design. To further advance motion cueing in general, this manuscript describes modifications to the existing algorithm, which allow for filtering at the location of the pilot's head as opposed to the centroid of the motion platform. The rational for such modification to the cueing algorithms is that the location of the pilot's vestibular system must be taken into account as opposed to the off-set of the centroid of the cockpit relative to the center of rotation alone. Results provided in this report suggest improved performance of the motion cueing algorithm.
Study of the use of a nonlinear, rate limited, filter on pilot control signals
The use of a filter on the pilot's control output could improve the performance of the pilot-aircraft system. What is needed is a filter with a sharp high frequency cut-off, no resonance peak, and a minimum of lag at low frequencies. The present investigation studies the usefulness of a nonlinear, rate limited, filter in performing the needed function. The nonlinear filter is compared with a linear, first order filter, and no filter. An analytical study using pilot models and a simulation study using experienced test pilots was performed. The results showed that the nonlinear filter does promote quick, steady maneuvering. It is shown that the nonlinear filter attenuates the high frequency remnant and adds less phase lag to the low frequency signal than does the linear filter. It is also shown that the rate limit in the nonlinear filter can be set to be too restrictive, causing an unstable pilot-aircraft system response.
Filtering for linear distributed parameter systems
Nonlinear filtering for linear parabolic distributed parameter systems with white noise, considering stochastic boundary value problem
Approximate continuous nonlinear minimal- variance filtering
Valid equations derived for approximate continuous nonlinear minimal variance filtering - mathematical models
Launch and space vehicle control studies. Volume 1 - Digitized non-linear filter for launch vehicle application Final report
Digitized nonlinear filter for Saturn 5 attitude control in S-1C boost phase
2-D nonlinear IIR-filters for image processing - An exploratory analysis
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
Statistical Orbit Determination using the Particle Filter for Incorporating Non-Gaussian Uncertainties
The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.
A 3-D nonlinear recursive digital filter for video image processing
This paper introduces a recursive 3-D nonlinear digital filter, which is capable of performing noise suppression without degrading important image information such as edges in space or time. It also has the property of unnoticeable bandwidth reduction immediately after a scene change, which makes the filter an attractive preprocessor to many interframe compression algorithms. The filter consists of a nonlinear 2-D spatial subfilter and a 1-D temporal filter. In order to achieve the required computational speed and increase the flexibility of the filter, all of the linear shift-variant filter modules are of the IIR type.
Stochastic processes and filtering theory
Book on stochastic processes and filtering theory covering probability theory, Markov processes, linear and nonlinear filters, etc
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.
Linear prediction filters for linear and nonlinear modeled geomagnetic activity
It is shown that the Faraday loop analog model of geomagnetic activity exhibits both the directly driven and loading-unloading magnetospheric responses to solar wind input. It is further shown that the directly driven component is a linear response to loading while the loading-unloading response is nonlinear. Linear prediction filters which relate model input to output are discussed. By either allowing or suppressing the loading-unloading model response filters that relate to nonlinear or linear dynamics, respectively, have been computed. Filters that described the directly driven response are finite ranged; they asymptote to zero with increasing lag on a time scale that is fixed by the dissipation rate of the model. Filters that describe the nonlinear total response are infinite ranged; they asymptote with increasing lag to large amplitude periodic oscillations. Some implications of these infinite ranged filters are discussed.
The power spectral density of digital modulations transmitted over nonlinear channels
This paper examines by analytical methods the power spectral densities of digital modulations (in particular, staggered and unstaggered quadrature modulations) passed through band-limited nonlinear channels. Previously observed (by computer simulation or hardware measurement) behavior of such spectra with regard to the suppression or restoration of its sidelobes after passing through the nonlinearity is verified analytically. Several examples corresponding to specific quadrature modulations and filter-nonlinearity combinations are presented as illustrations of the general results.
Real-time image processing II; Proceedings of the Meeting, Orlando, FL, Apr. 16-18, 1990
The present conference discusses topics in the fields of feature extraction and implementation, filter and correlation algorithms, optical correlators, high-level algorithms, and digital image processing for ranging and remote driving. Attention is given to a nonlinear filter derived from topological image features, IR image segmentation through iterative thresholding, orthogonal subspaces for correlation masking, composite filter trees and image recognition via binary search, and features of matrix-coherent optical image processing. Also discussed are multitarget tracking via hybrid joint transform correlator, binary joint Fourier transform correlator considerations, global image processing operations on parallel architectures, real-time implementation of a differential range finder, and real-time binocular stereo range and motion detection.
Construction of Low Dissipative High Order Well-Balanced Filter Schemes for Non-Equilibrium Flows
The goal of this paper is to generalize the well-balanced approach for non-equilibrium flow studied by Wang et al. [26] to a class of low dissipative high order shock-capturing filter schemes and to explore more advantages of well-balanced schemes in reacting flows. The class of filter schemes developed by Yee et al. [30], Sjoegreen & Yee [24] and Yee & Sjoegreen [35] consist of two steps, a full time step of spatially high order non-dissipative base scheme and an adaptive nonlinear filter containing shock-capturing dissipation. A good property of the filter scheme is that the base scheme and the filter are stand alone modules in designing. Therefore, the idea of designing a well-balanced filter scheme is straightforward, i.e., choosing a well-balanced base scheme with a well-balanced filter (both with high order). A typical class of these schemes shown in this paper is the high order central difference schemes/predictor-corrector (PC) schemes with a high order well-balanced WENO filter. The new filter scheme with the well-balanced property will gather the features of both filter methods and well-balanced properties: it can preserve certain steady state solutions exactly; it is able to capture small perturbations, e.g., turbulence fluctuations; it adaptively controls numerical dissipation. Thus it shows high accuracy, efficiency and stability in shock/turbulence interactions. Numerical examples containing 1D and 2D smooth problems, 1D stationary contact discontinuity problem and 1D turbulence/shock interactions are included to verify the improved accuracy, in addition to the well-balanced behavior.
Real-time filtering and detection of dynamics for compression of HDTV
The preprocessing of video sequences for data compressing is discussed. The end goal associated with this is a compression system for HDTV capable of transmitting perceptually lossless sequences at under one bit per pixel. Two subtopics were emphasized to prepare the video signal for more efficient coding: (1) nonlinear filtering to remove noise and shape the signal spectrum to take advantage of insensitivities of human viewers; and (2) segmentation of each frame into temporally dynamic/static regions for conditional frame replenishment. The latter technique operates best under the assumption that the sequence can be modelled as a superposition of active foreground and static background. The considerations were restricted to monochrome data, since it was expected to use the standard luminance/chrominance decomposition, which concentrates most of the bandwidth requirements in the luminance. Similar methods may be applied to the two chrominance signals.
Filtering Image Records Using Wavelets and the Zakai Equation
Consider the problem of detecting and localizing a faint object moving In an "essentially stationary" background, using a sequence of two-dimensional low-SNR images of the scene. A natural approach consists of "digitizing" each snapshot into a discrete set of observations, sufficiently (perhaps not exactly) matched to the object In question, then tracking the object using an appropriate stochastic filter. The tracking would be expected to make up for the low signal-to-noise ratio, this allowing one to "coherently" process successive images in order to beat down the noise and localize the object. Thus, "tracking" here does not refer to the usual notion of detecting then tracking: rather, we track in order to detect The problem then becomes one of choosing the appropriate image representation as well as the optimal (and necessarily nonlinear filter. We propose exact and approximate solutions using wavelets and the Zakai equation. The smoothness of the wavelets used is required in the derivation of the evolution equation for the conditional density giving the filter, and their orthogonality makes it possible to carry out actual computations of the Ito- and change-of-gauge-terms in the algorithm effectively.