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NASA NTRS2004

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↗

NASA NTRS2011

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↗

NASA NTRS2003

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.↗

NASA NTRS2012

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↗

NASA NTRS2013

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.↗

NASA NTRS2013

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↗

NASA NTRS2015

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.↗

NASA NTRS2016

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↗

NASA NTRS2016

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↗

NASA NTRS2016

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↗

NASA NTRS2015

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.↗

NASA NTRS1973

A Comparison of Near Simultaneous Lidar Returns and Particulate Collections on Filters Flown at Six Stratospheric Altitudes

Collections of particulates on both Los Alamos Scientific Laboratory (LASL) and National Center for Atmospheric Research (NCAR) filter systems were made from an RB 57F aircraft flown at one tropospheric and six stratospheric altitudes over the Boulder, Colorado, area. This daytime flight was spanned by lidar returns on evenings before and after the flight. Scanning electron microscope examination of the LASL filters showed no evidence of solid particulates greater than 2 micrometers (the instrumental resolving power). Quantitative analysis of the NCAR filters yielded chemical composition and mass. The mass values were normalized to the total air flow through the filters to yield mass mixing ratios at the various altitudes. The lidar returns, normalized to molecular densities obtained from sonde data, were put in the form of particulate scattering divided by molecular scattering, i. e., an optical mixing ratio. A plot of the optical mixing ratio versus mass mixing ratio, in the stratosphere, yielded linear relationship, for five of the six data points, going through the origin.

Schuster, Burton G.↗

NASA NTRS2017

Comparison of Factorization-Based Filtering for Landing Navigation

This paper develops and analyzes methods for fusing inertial navigation data with external data, such as data obtained from an altimeter and a star camera. The particular filtering techniques are based upon factorized forms of the Kalman filter, specifically the UDU and Cholesky factorizations. The factorized Kalman filters are utilized to ensure numerical stability of the navigation solution. Simulations are carried out to compare the performance of the different approaches along a lunar descent trajectory using inertial and external data sources. It is found that the factorized forms improve upon conventional filtering techniques in terms of ensuring numerical stability for the investigated landing navigation scenario.

McCabe, James S.↗

NASA NTRS2011

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Calhoun, Philip C.↗

NASA NTRS2018

System and Apparatus for Filtering Particles

Agui, Juan H.↗

NASA NTRS2019

Characterization of Low Frequency Auditory Filters

The purpose of this study is to characterize auditory filters at low frequencies, defined as below about 100 Hz. Three experiments were designed and executed. They were conducted in the Exterior Effects Room at the NASA Langley Research Center, a psychoacoustic facility designed for presentation of aircraft flyover sounds to groups of test subjects. The first experiment measured 36 subjects’ hearing threshold for pure tones (at 25, 31.5, 40, 50, 63 and 80 Hz) in “quiet” conditions. The subjects, male and female, had a wide age range. This experiment allowed the performance of the test facility to be assessed and also provided screened test subjects for participation in subsequent experiments. The second and third experiments used 20 and 10 test subjects, respectively, and measured psychophysical tuning curves (PTCs) that describe auditory filters with center frequencies of approximately 63 and 50 Hz. The latter is assumed to be the lowest (bottom) auditory filter; thus, sounds at frequencies below about 50 Hz are perceived via the lower skirt of this lowest filter. All experiments used an adaptive, three-alternative forced-choice test procedure using either variable level tones or variable level, narrowband noise maskers. Measured PTCs were found to be very similar to other recently published data, both in terms of mean values and intersubject variation, despite different experimental protocols, different test facilities, and a wide range in subjects’ age.

Rafaelof, Menachem↗

NASA NTRS2019

Testbed for Characterizing the Adsorptive Capacities of Pleated Panel Filters

Pleated panel filters offer a new commercial form factor for controlling VOCs in spacecraft cabin air. They differ from conventional commercial granular activated carbons because they have a lower pressure drop across the filter. A testbed was developed for evaluating the removal capacities of commercial pleated panel filters for NH3. The adsorptive capacity of a commercial cation-exchange pleated filter was compared versus the adsorptive capacities of two acid- impregnated activated carbons used for controlling ammonia in spacecraft cabin air.

Monje Mejia, Oscar A.↗

NASA NTRS2019

A Scroll Filter System for In-Situ Resource Utilization CO2 Acquisition of the Martian Atmosphere

The Martian atmosphere, consisting mainly of gaseous CO2, is regarded as one of the main planetary resources capable of providing a significant portion of the oxygen that will be needed for human missions to the planet's surface. NASA's In-Situ Re-source Utilization (ISRU) project supports the development of oxygen generation technologies that can convert the Martian atmosphere into usable oxygen. The thin CO2 based Martian atmosphere, however, carries certain levels of dust stirred up by the Martian winds that must be filtered out at the front end of any CO2 acquisition system. Thus, the ISRU project is developing particulate filters as part of a Mars CO2 acquisition sys-tem. A prototype filter system, known as the Scroll Filter, is being tested under simulated Martian atmospheric conditions in the Mar Atmospheric Flow Loop at the NASA GRC. The measurement techniques as well as the preliminary results from a series of performance tests will be discussed.

Agui, Juan H.↗