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At least 559 records · Page 31

Electronic filters, signal conversion apparatus, hearing aids and methods

An electronic filter for filtering an electrical signal. Signal processing circuitry therein includes a logarithmic filter having a series of filter stages with inputs and outputs in cascade and respective circuits as GOVERNMENT SUPPORT This invention was made with U.S. Government support under Veterans Administration Contract VA KV 674P857 and National Aeronautics and Space Administration (NASA) Research Grant No. NAG10-0040. The U.S. Government has certain rights in this invention.

Morley, Jr., Robert E.↗

Devices based on surface plasmon interference filters

Devices based on surface plasmon filters having at least one metal-dielectric interface to support surface plasmon waves. A multi-layer-coupled surface plasmon notch filter is provided to have more than two symmetric metal-dielectric interfaces coupled with one another to produce a transmission spectral window with desired spectral profile and bandwidth. Such notch filters can form various color filtering devices for color flat panel displays.

Wang, Yu↗

Kalman Filter for Spinning Spacecraft Attitude Estimation

This paper presents a Kalman filter using a seven-component attitude state vector comprising the angular momentum components in an inertial reference frame, the angular momentum components in the body frame, and a rotation angle. The relatively slow variation of these parameters makes this parameterization advantageous for spinning spacecraft attitude estimation. The filter accounts for the constraint that the magnitude of the angular momentum vector is the same in the inertial and body frames by employing a reduced six-component error state. Four variants of the filter, defined by different choices for the reduced error state, are tested against a quaternion-based filter using simulated data for the THEMIS mission. Three of these variants choose three of the components of the error state to be the infinitesimal attitude error angles, facilitating the computation of measurement sensitivity matrices and causing the usual 3x3 attitude covariance matrix to be a submatrix of the 6x6 covariance of the error state. These variants differ in their choice for the other three components of the error state. The variant employing the infinitesimal attitude error angles and the angular momentum components in an inertial reference frame as the error state shows the best combination of robustness and efficiency in the simulations. Attitude estimation results using THEMIS flight data are also presented.

Markley, F. Landis↗

Nanofiber Filters Eliminate Contaminants

With support from Phase I and II SBIR funding from Johnson Space Center, Argonide Corporation of Sanford, Florida tested and developed its proprietary nanofiber water filter media. Capable of removing more than 99.99 percent of dangerous particles like bacteria, viruses, and parasites, the media was incorporated into the company's commercial NanoCeram water filter, an inductee into the Space Foundation's Space Technology Hall of Fame. In addition to its drinking water filters, Argonide now produces large-scale nanofiber filters used as part of the reverse osmosis process for industrial water purification.

Source record↗

Enhancing Spin Filters by Use of Bulk Inversion Asymmetry

Theoretical calculations have shown that the degrees of spin polarization in proposed nonmagnetic semiconductor resonant tunneling spin filters could be increased through exploitation of bulk inversion asymmetry (BIA). These enhancements would be effected through suitable orientation of spin collectors (or spin-polarization- inducing lateral electric fields), as described below. Spin filters -- more precisely, sources of spin-polarized electron currents -- have been sought for research on, and development of, the emerging technological discipline of spintronics (spin-transport electronics). The proposed spin filters were to be based on the Rashba effect, which is an energy splitting of what would otherwise be degenerate quantum states, caused by a spinorbit interaction in conjunction with a structural-inversion asymmetry (SIA) in the presence of interfacial electric fields in a semiconductor heterostructure. The magnitude of the energy split is proportional to the electron wave number. In a spin filter, the spin-polarized currents produced by the Rashba effect would be extracted by quantum-mechanical resonant tunneling.

Ting, David↗

Compact Micromachined Bandpass Filters for Infrared Planetary Spectroscopy

The thermal instrument strawman payload of the Jupiter Europa Orbiter on the Europa Jupiter Science Mission will map out thermal anomalies, the structure, and atmospheric conditions of Europa and Jupiter within the 7-100 micron spectral range. One key requirement for the payload is that the mass cannot exceed 3.7 kg. Consequently, a new generation of light-weight miniaturized spectrometers needs to be developed. On the path toward developing these spectrometers is development of ancillary miniaturized spectroscopic components. In this paper, we present a strategy for making radiation hard and low mass FIR band pass metal mesh filters. Our strategy involves using MEMS-based fabrication techniques, which will permit the quasi-optical filter structures to be made with micron-scale precision. This will enable us to achieve tight control over both the pass band of the filter and the micromachined silicon support structure architecture, which will facilitate integration of the filters for a variety of applications.

Brown, Ari D.↗

Model Adaptation for Prognostics in a Particle Filtering Framework

One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

Saha, Bhaskar↗

Coronagraphic Notch Filter for Raman Spectroscopy

A modified coronagraph has been proposed as a prototype of improved notch filters in Raman spectrometers. Coronagraphic notch filters could offer alternatives to both (1) the large and expensive double or triple monochromators in older Raman spectrometers and (2) holographic notch filters, which are less expensive but are subject to environmental degradation as well as to limitations of geometry and spectral range. Measurement of a Raman spectrum is an exercise in measuring and resolving faint spectral lines close to a bright peak: In Raman spectroscopy, a monochromatic beam of light (the pump beam) excites a sample of material that one seeks to analyze. The pump beam generates a small flux of scattered light at wavelengths slightly greater than that of the pump beam. The shift in wavelength of the scattered light from the pump wavelength is known in the art as the Stokes shift. Typically, the flux of scattered light is of the order of 10 7 that of the pump beam and the Stokes shift lies in the wave-number range of 100 to 3,000 cm 1. A notch filter can be used to suppress the pump-beam spectral peak while passing the nearby faint Raman spectral lines. The basic principles of design and operation of a coronagraph offer an opportunity for engineering the spectral transmittance of the optics in a Raman spectrometer. A classical coronagraph may be understood as two imaging systems placed end to end, such that the first system forms an intermediate real image of a nominally infinitely distant object and the second system forms a final real image of the intermediate real image. If the light incident on the first telescope is collimated, then the intermediate image is a point-spread function (PSF). If an appropriately tailored occulting spot (e.g., a Gaussian-apodized spot with maximum absorption on axis) is placed on the intermediate image plane, then the instrument inhibits transmission of light from an on-axis source. However, the PSFs of off-axis light sources are formed off axis - that is, away from the occulting spot - so that they become refocused onto the final image plane.

Cohen, David↗

Compact Micromachined Infrared Bandpass Filters for Planetary Spectroscopy

The future needs of space based observational planetary and astronomy missions include low mass and small volume radiometric instruments that can operate in high radiation and low temperature environments. Here we focus on a central spectroscopic component, the bandpass filter. We model the bandpass response of the filters to target the wavelength of the resonance peaks at 20, 40, and 60 micrometers and report good agreement between the modeled and measured response. We present a technique of using common micromachining processes for semiconductor fabrication to make compact, free standing resonant metal mesh filter arrays with silicon support frames. The process can accommodate multiple detector array architectures and the silicon frame provides lightweight mechanical support with low form factor. We also present a conceptual hybridization of the filters with a detector array.

Merrell, Willie C., II↗

Parallel Subconvolution Filtering Architectures

These architectures are based on methods of vector processing and the discrete-Fourier-transform/inverse-discrete- Fourier-transform (DFT-IDFT) overlap-and-save method, combined with time-block separation of digital filters into frequency-domain subfilters implemented by use of sub-convolutions. The parallel-processing method implemented in these architectures enables the use of relatively small DFT-IDFT pairs, while filter tap lengths are theoretically unlimited. The size of a DFT-IDFT pair is determined by the desired reduction in processing rate, rather than on the order of the filter that one seeks to implement. The emphasis in this report is on those aspects of the underlying theory and design rules that promote computational efficiency, parallel processing at reduced data rates, and simplification of the designs of very-large-scale integrated (VLSI) circuits needed to implement high-order filters and correlators.

Gray, Andrew A.↗

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.

Mashiku, Alinda↗

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Thompson, David R.↗

Automatic Data Filter Customization Using a Genetic Algorithm

This work predicts whether a retrieval algorithm will usefully determine CO2 concentration from an input spectrum of GOSAT (Greenhouse Gases Observing Satellite). This was done to eliminate needless runtime on atmospheric soundings that would never yield useful results. A space of 50 dimensions was examined for predictive power on the final CO2 results. Retrieval algorithms are frequently expensive to run, and wasted effort defeats requirements and expends needless resources. This algorithm could be used to help predict and filter unneeded runs in any computationally expensive regime. Traditional methods such as the Fischer discriminant analysis and decision trees can attempt to predict whether a sounding will be properly processed. However, this work sought to detect a subsection of the dimensional space that can be simply filtered out to eliminate unwanted runs. LDAs (linear discriminant analyses) and other systems examine the entire data and judge a "best fit," giving equal weight to complex and problematic regions as well as simple, clear-cut regions. In this implementation, a genetic space of "left" and "right" thresholds outside of which all data are rejected was defined. These left/right pairs are created for each of the 50 input dimensions. A genetic algorithm then runs through countless potential filter settings using a JPL computer cluster, optimizing the tossed-out data s yield (proper vs. improper run removal) and number of points tossed. This solution is robust to an arbitrary decision boundary within the data and avoids the global optimization problem of whole-dataset fitting using LDA or decision trees. It filters out runs that would not have produced useful CO2 values to save needless computation. This would be an algorithmic preprocessing improvement to any computationally expensive system.

Mandrake, Lukas↗

System and Apparatus for Filtering Particles

A modular pre-filtration apparatus may be beneficial to extend the life of a filter. The apparatus may include an impactor that can collect a first set of particles in the air, and a scroll filter that can collect a second set of particles in the air. A filter may follow the pre-filtration apparatus, thus causing the life of the filter to be increased.

Agui, Juan H.↗

Model-Based Engine Control Architecture with an Extended Kalman Filter

This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

engine control↗

Model-Based Engine Control Architecture with an Extended Kalman Filter

This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The non-linear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

engine control↗

Filter Media Tests Under Simulated Martian Atmospheric Conditions

Human exploration of Mars will require the optimal utilization of planetary resources. One of its abundant resources is the Martian atmosphere that can be harvested through filtration and chemical processes that purify and separate it into its gaseous and elemental constituents. Effective filtration needs to be part of the suite of resource utilization technologies. A unique testing platform is being used which provides the relevant operational and instrumental capabilities to test articles under the proper simulated Martian conditions. A series of tests were conducted to assess the performance of filter media. Light sheet imaging of the particle flow provided a means of detecting and quantifying particle concentrations to determine capturing efficiencies. The media's efficiency was also evaluated by gravimetric means through a by-layer filter media configuration. These tests will help to establish techniques and methods for measuring capturing efficiency and arrestance of conventional fibrous filter media. This paper will describe initial test results on different filter media.

Martian Atmosphere↗

Desensitized Optimal Filtering and Sensor Fusion Toolkit

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Karlgaard, Christopher D.↗