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NASA NTRS2019

Scroll Filter System Development for Crewed Deep Space Missions

On board the International Space Station, particulate HEPA filters known as Bacterial Filter Elements (BFE's) are used as the main ventilation filters on the US modules. They consist of two stages of filtration, a static screen filter and a HEPA filter element. Historically, these filters have performed well during the life of the ISS. However, as NASA sets its sights towards mission beyond low earth orbit, or deep space, more capable filters requiring minimal maintenance will be essential because of the nature of these remote and of long duration missions. Therefore NASA is currently developing new filter systems for these mission. One of the filter designs being considered is a new filter system, coined the Scroll BFE. This filter provides two stages of filtration. The first stage is a pre-filter stage using a roll of screen media on a motorized spooling, or scrolling, mechanism to automate the change-out of the screen media in the flow. The second and finishing stage is a static HEPA filter element similar to the ones used on the ISS BFE's. The volume and dimensional format of the filter matches that of the ISS BFE which facilitates is deployment as potential future flight technology demonstration on board the ISS. Ground tests are underway to assess the filter system's performance under industrial standard test protocols applied in a custom designed filtration test stand. In addition, a method of generating relevant particulate matter loads, such as loose fibrous matter, is also being devised to challenge the filter in testing. The latter test challenge will help determine the pre-filter's capacity for handling layers of lint, or fibrous, particulate matter. Early results confirm HEPA efficiency performance of the HEPA stage. This paper will present the results of ground testing of the Scroll Filter System prototype.

Agui, Juan H.↗

NASA NTRS2018

Development of a Multi-Stage Filter System for Cabin Ventilation Systems on the ISS and Future Deep Space Missions

The National Aeronautics and Space Administration's (NASA's) deep space exploration missions will be of significant duration requiring long-life and reliably performing spacecraft cabin ventilation filters. A particulate filter system is being developed at NASA Glenn Research Center (GRC) to meet the challenges of these remote and long duration missions. The capabilities and features of the filter system are expected to expand the life and reduce the maintenance requirements over that of the current ISS (International Space Station) filter by providing pre-filtration stages with novel self-cleaning and regenerable techniques. The filter provides two regenerable pre-filtration stages using a screen mesh media and an impactor collection system, and also provides intermediate stage filtration employing self-replacing filter media. The filter system is also designed to be compatible with the interfaces and performance requirements of the ISS distributed ventilation architecture in the US modules to facilitate testing on ISS type test or mock up platforms. Currently, a prototype of the filter system is undergoing tests in a custom configured filter test stand at the NASA GRC. The test stand provides the same range of flow rates produced on the ISS distributed architecture, and is equipped and instrumented to perform filter tests based on industrial test standards. The test stand has been used successfully to perform filter and flow performance test on returned ISS Bacterial Filter Elements. Similar test protocols were used to characterize the performance of the current filter system. Different performing grades of filter media will be installed and tested on the filter system, and different test particle standards will be used to simulate the range of particulate matter particles and debris the filter will see during a mission. This paper will present results and analysis of the test data to guide and provide input to the next generation filter system.

ISS↗

NASA NTRS2005

Generic Kalman Filter Software

The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on the basis of the aforementioned templates. The GKF software can be used to develop many different types of unfactorized Kalman filters. A developer can choose to implement either a linearized or an extended Kalman filter algorithm, without having to modify the GKF software. Control dynamics can be taken into account or neglected in the filter-dynamics model. Filter programs developed by use of the GKF software can be made to propagate equations of motion for linear or nonlinear dynamical systems that are deterministic or stochastic. In addition, filter programs can be made to operate in user-selectable "covariance analysis" and "propagation-only" modes that are useful in design and development stages.

Lisano, Michael E., II↗

NASA NTRS1995

Experiments with explicit filtering for LES using a finite-difference method

The equations for large-eddy simulation (LES) are derived formally by applying a spatial filter to the Navier-Stokes equations. The filter width as well as the details of the filter shape are free parameters in LES, and these can be used both to control the effective resolution of the simulation and to establish the relative importance of different portions of the resolved spectrum. An analogous, but less well justified, approach to filtering is more or less universally used in conjunction with LES using finite-difference methods. In this approach, the finite support provided by the computational mesh as well as the wavenumber-dependent truncation errors associated with the finite-difference operators are assumed to define the filter operation. This approach has the advantage that it is also 'automatic' in the sense that no explicit filtering: operations need to be performed. While it is certainly convenient to avoid the explicit filtering operation, there are some practical considerations associated with finite-difference methods that favor the use of an explicit filter. Foremost among these considerations is the issue of truncation error. All finite-difference approximations have an associated truncation error that increases with increasing wavenumber. These errors can be quite severe for the smallest resolved scales, and these errors will interfere with the dynamics of the small eddies if no corrective action is taken. Years of experience at CTR with a second-order finite-difference scheme for high Reynolds number LES has repeatedly indicated that truncation errors must be minimized in order to obtain acceptable simulation results. While the potential advantages of explicit filtering are rather clear, there is a significant cost associated with its implementation. In particular, explicit filtering reduces the effective resolution of the simulation compared with that afforded by the mesh. The resolution requirements for LES are usually set by the need to capture most of the energy-containing eddies, and if explicit filtering is used, the mesh must be enlarged so that these motions are passed by the filter. Given the high cost of explicit filtering, the following interesting question arises. Since the mesh must be expanded in order to perform the explicit filter, might it be better to take advantage of the increased resolution and simply perform an unfiltered simulation on the larger mesh? The cost of the two approaches is roughly the same, but the philosophy is rather different. In the filtered simulation, resolution is sacrificed in order to minimize the various forms of numerical error. In the unfiltered simulation, the errors are left intact, but they are concentrated at very small scales that could be dynamically unimportant from a LES perspective. Very little is known about this tradeoff and the objective of this work is to study this relationship in high Reynolds number channel flow simulations using a second-order finite-difference method.

Lund, T. S.↗

NASA NTRS2008

Comparison of Nonlinear Filtering Techniques for Lunar Surface Roving Navigation

Leading up to the Apollo missions the Extended Kalman Filter, a modified version of the Kalman Filter, was developed to estimate the state of a nonlinear system. Throughout the Apollo missions, Potter's Square Root Filter was used for lunar navigation. Now that NASA is returning to the Moon, the filters used during the Apollo missions must be compared to the filters that have been developed since that time, the Bierman-Thornton Filter (UD) and the Unscented Kalman Filter (UKF). The UD Filter involves factoring the covariance matrix into UDUT and has similar accuracy to the Square Root Filter; however it requires less computation time. Conversely, the UKF, which uses sigma points, is much more computationally intensive than any of the filters; however it produces the most accurate results. The Extended Kalman Filter, Potter's Square Root Filter, the Bierman-Thornton UD Filter, and the Unscented Kalman Filter each prove to be the most accurate filter depending on the specific conditions of the navigation system.

Kimber, Lemon↗

NASA NTRSDate not supplied

Testing of the ISS’s Charcoal HEPA Integrated Particle Scrubber (CHIPS) Filters to Ascertain an Efficiency Curve and Most Penetrating Particle Size

High air quality is a top priority in hermetically sealed environments, such as the International Space Station (ISS). Aerosol particulate filtration on the ISS is achieved via 21 HEPA filters. Traditional HEPA filters have an efficiency of 99.97%, but HEPA filters aboard the ISS have been found to achieve 99.99% efficiency. This may be due to the flight-grade HEPA filters chosen or, less likely, that they are combined with activated charcoal filters for siloxane removal in a combination referred to as Charcoal HEPA Integrated Particle Scrubbers (CHIPS) filters. All filters have a Most Penetrating Particle Size (MPPS), but, until now, the MPPS and efficiency curve of the CHIPS filters was not known. The efficiency curve of the CHIPS filters was ascertained at NASA Glenn Research Center through standard salt crystal aerosolization. This method was selected over aerosolized oil droplets due to a desire to preserve the filter’s function for further testing. The CHIPS filters were tested as they are oriented on the ISS (activated charcoal filter followed by a flight-grade HEPA filter), with the HEPA portion alone, and with the activated charcoal portion alone. The results of this experiment are generally useful but can be especially useful for the microbiology and Environmental Control and Life Support Systems (ECLSS). This is due to microbial contamination being a potential concern in the air revitalization systems on the ISS. Knowing the MMPS of the CHIPS filters, in conjunction with levels of airborne microbes, is useful for predicting which and how many microbes are likely to get through the HEPA filters that sit in the beginning of the ISS airstream. It may also be useful to other groups at NASA to know how many particulates are able to pass through high-efficiency filtration, and even for healthcare cleanrooms and other air purification pursuits.

A Nicolas Whitlock↗

NASA NTRS1994

Design of a composite filter realizable on practical spatial light modulators

Hybrid optical correlator systems use two spatial light modulators (SLM's), one at the input plane and the other at the filter plane. Currently available SLM's such as the deformable mirror device (DMD) and liquid crystal television (LCTV) SLM's exhibit arbitrarily constrained operating characteristics. The pattern recognition filters designed with the assumption that the SLM's have ideal operating characteristic may not behave as expected when implemented on the DMD or LCTV SLM's. Therefore it is necessary to incorporate the SLM constraints in the design of the filters. In this report, an iterative method is developed for the design of an unconstrained minimum average correlation energy (MACE) filter. Then using this algorithm a new approach for the design of a SLM constrained distortion invariant filter in the presence of input SLM is developed. Two different optimization algorithms are used to maximize the objective function during filter synthesis, one based on the simplex method and the other based on the Hooke and Jeeves method. Also, the simulated annealing based filter design algorithm proposed by Khan and Rajan is refined and improved. The performance of the filter is evaluated in terms of its recognition/discrimination capabilities using computer simulations and the results are compared with a simulated annealing optimization based MACE filter. The filters are designed for different LCTV SLM's operating characteristics and the correlation responses are compared. The distortion tolerance and the false class image discrimination qualities of the filter are comparable to those of the simulated annealing based filter but the new filter design takes about 1/6 of the computer time taken by the simulated annealing filter design.

Rajan, P. K.↗

NASA NTRS2009

Economical Implementation of a Filter Engine in an FPGA

A logic design has been conceived for a field-programmable gate array (FPGA) that would implement a complex system of multiple digital state-space filters. The main innovative aspect of this design lies in providing for reuse of parts of the FPGA hardware to perform different parts of the filter computations at different times, in such a manner as to enable the timely performance of all required computations in the face of limitations on available FPGA hardware resources. The implementation of the digital state-space filter involves matrix vector multiplications, which, in the absence of the present innovation, would ordinarily necessitate some multiplexing of vector elements and/or routing of data flows along multiple paths. The design concept calls for implementing vector registers as shift registers to simplify operand access to multipliers and accumulators, obviating both multiplexing and routing of data along multiple paths. Each vector register would be reused for different parts of a calculation. Outputs would always be drawn from the same register, and inputs would always be loaded into the same register. A simple state machine would control each filter. The output of a given filter would be passed to the next filter, accompanied by a "valid" signal, which would start the state machine of the next filter. Multiple filter modules would share a multiplication/accumulation arithmetic unit. The filter computations would be timed by use of a clock having a frequency high enough, relative to the input and output data rate, to provide enough cycles for matrix and vector arithmetic operations. This design concept could prove beneficial in numerous applications in which digital filters are used and/or vectors are multiplied by coefficient matrices. Examples of such applications include general signal processing, filtering of signals in control systems, processing of geophysical measurements, and medical imaging. For these and other applications, it could be advantageous to combine compact FPGA digital filter implementations with other application-specific logic implementations on single integrated-circuit chips. An FPGA could readily be tailored to implement a variety of filters because the filter coefficients would be loaded into memory at startup.

Kowalski, James E.↗

NASA NTRS1993

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Kher, A.↗

NASA NTRS1998

Design and Specification of Optical Bandpass Filters for Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS)

Advanced optical bandpass filters for the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) have been developed on a filter-by-filter basis through detailed studies which take into account the instrument's science goals, available optical filter fabrication technology, and developments in ACS's charge-coupled-device (CCD) detector technology. These filters include a subset of filters for the Sloan Digital Sky Survey (SDSS) which are optimized for astronomical photometry using today's charge-coupled-devices (CCD's). 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 for these filters include outstanding transmitted wavefront, high transmittance, uniform transmittance across each filter, spectrally structure-free bandpasses, exceptionally high out of band rejection, a high degree of parfocality, and immunity to environmental degradation. These constitute a very stringent set of requirements indeed, especially for filters which are up to 90 mm in diameter. The highly successful paradigm in which final specifications for flight filters were derived through interaction amongst the ACS Science Team, the instrument designer, the lead optical engineer, and the filter designer and vendor is described. Examples of iterative design trade studies carried out in the context of science needs and budgetary and schedule constraints are presented. An overview of the final design specifications for the ACS bandpass and ramp filters is also presented.

Leviton, Douglas B.↗

NASA NTRS2009

Solar Rejection Filter for Large Telescopes

To reject solar radiation photons at the front aperture for large telescopes, a mosaic of large transmission mode filters is placed in front of the telescope or at the aperture of the dome. Filtering options for effective rejection of sunlight include a smaller filter down-path near the focus of the telescope, and a large-diameter filter located in the front of the main aperture. Two types of large filters are viable: reflectance mode and transmittance mode. In the case of reflectance mode, a dielectric coating on a suitable substrate (e.g. a low-thermal-expansion glass) is arranged to reflect only a single, narrow wavelength and to efficiently transmit all other wavelengths. These coatings are commonly referred to as notch filter. In this case, the large mirror located in front of the telescope aperture reflects the received (signal and background) light into the telescope. In the case of transmittance mode, a dielectric coating on a suitable substrate (glass, sapphire, clear plastic, membrane, and the like) is arranged to transmit only a single wavelength and to reject all other wavelengths (visible and near IR) of light. The substrate of the large filter will determine its mass. At first glance, a large optical filter with a diameter of up to 10 m, located in front of the main aperture, would require a significant thickness to avoid sagging. However, a segmented filter supported by a structurally rugged grid can support smaller filters. The obscuration introduced by the grid is minimal because the total area can be made insignificant. This configuration can be detrimental to a diffraction- limited telescope due to diffraction effects at the edges of each sub-panel. However, no discernable degradation would result for a 20 diffraction-limit telescope (a photon bucket). Even the small amount of sagging in each subpanel should have minimal effect in the performance of a non-diffraction limited telescope because the part has no appreciable optical power. If the front aperture filter is integrated with the telescope dome, it will reject heat from the dome and will significantly reduce dome temperature regulation requirements and costs. Also, the filter will protect the telescope optics from dust and other contaminants in the atmosphere. It will be simpler to clean or replace this filter than the telescope primary mirror. It may be necessary to paint the support grid with a highly reflective material to avoid overheating.

Hemmati, Hamid↗

NASA NTRS2005

Removing Pathogens Using Nano-Ceramic-Fiber Filters

A nano-aluminum-oxide fiber of only 2 nanometers in diameter was used to develop a ceramic-fiber filter. The fibers are electropositive and, when formulated into a filter material (NanoCeram(TradeMark)), would attract electro-negative particles such as bacteria and viruses. The ability to detect and then remove viruses as well as bacteria is of concern in space cabins since they may be carried onboard by space crews. Moreover, an improved filter was desired that would polish the effluent from condensed moisture and wastewater, producing potable drinking water. A laboratory- size filter was developed that was capable of removing greater than 99.9999 percent of bacteria and virus. Such a removal was achieved at flow rates hundreds of times greater than those through ultraporous membranes that remove particles by sieving. Because the pore size of the new filter was rather large as compared to ultraporous membranes, it was found to be more resistant to clogging. Additionally, a full-size cartridge is being developed that is capable of serving a full space crew. During this ongoing effort, research demonstrated that the filter media was a very efficient adsorbent for DNA (deoxyribonucleic acid), RNA (ribonucleic acid), and endotoxins. Since the adsorption is based on the charge of the macromolecules, there is also a potential for separating proteins and other particulates on the basis of their charge differences. The separation of specific proteins is a major new thrust of biotechnology. The principal application of NanoCeram filters is based on their ability to remove viruses from water. The removal of more than 99.9999 percent of viruses was achieved by a NanoCeram polishing filter added to the effluent of an existing filtration device. NanoCeram is commercially available in laboratory-size filter discs and in the form of a syringe filter. The unique characteristic of the filter can be demonstrated by its ability to remove particulate dyes such as Metanyl yellow. Its particle size is only 2 nanometers, about the size of a DNA molecule, yet the NanoCeram syringe filter is capable of retaining the dyes as the fluid is passed through the syringe, without much back-pressure. Endotoxins, which are contaminants that are part of the residue of destroyed bacteria, can cause toxic shock and are therefore of major concern in pharmaceutical products. The NanoCeram syringe filter is capable of removing greater than 99.96 percent of the endotoxins.

Tepper, Frederick↗

NASA NTRS2015

Characterization of a Regenerable Impactor Filter for Spacecraft Cabin Applications

Regenerable filters will play an important role in human exploration beyond low-Earth orbit. Life Support Systems aboard crewed spacecrafts will have to operate reliably and with little maintenance over periods of more than a year, even multiple years. Air filters are a key component of spacecraft life support systems, but they often require frequent routine maintenance. Bacterial filters aboard the International Space Station require almost weekly cleaning of the pre-filter screen to remove large lint debris captured in the microgravity environment. The source of the airborne matter which is collected on the filter screen is typically from clothing fibers, biological matter (hair, skin, nails, etc.) and material wear. Clearly a need for low maintenance filters requiring little to no crew intervention will be vital to the success of the mission. An impactor filter is being developed and tested to address this need. This filter captures large particle matter through inertial separation and impaction methods on collection surfaces, which can be automatically cleaned after they become heavily loaded. The impactor filter can serve as a pre-filter to augment the life of higher efficiency filters that capture fine and ultrafine particles. A prototype of the filter is being tested at the Particulate Filtration Laboratory at NASA Glenn Research Center to determine performance characteristics, including particle cut size and overall efficiency. Model results are presented for the flow characteristics near the orifice plate through which the particle-laden flow is accelerated as well as around the collection bands.

air filters↗

NASA NTRS1993

Design of coupled mace filters for optical pattern recognition using practical spatial light modulators

Spatial light modulators (SLMs) are being used in correlation-based optical pattern recognition systems to implement the Fourier domain filters. Currently available SLMs have certain limitations with respect to the realizability of these filters. Therefore, it is necessary to incorporate the SLM constraints in the design of the filters. The design of a SLM-constrained minimum average correlation energy (SLM-MACE) filter using the simulated annealing-based optimization technique was investigated. The SLM-MACE filter was synthesized for three different types of constraints. The performance of the filter was evaluated in terms of its recognition (discrimination) capabilities using computer simulations. The correlation plane characteristics of the SLM-MACE filter were found to be reasonably good. The SLM-MACE filter yielded far better results than the analytical MACE filter implemented on practical SLMs using the constrained magnitude technique. Further, the filter performance was evaluated in the presence of noise in the input test images. This work demonstrated the need to include the SLM constraints in the filter design. Finally, a method is suggested to reduce the computation time required for the synthesis of the SLM-MACE filter.

Rajan, P. K.↗

NASA NTRS2005

Nonlinear Attitude Filtering Methods

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

F Landis Markley↗

NASA NTRS2012

Hybrid Filter Membrane

Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of dust particles on the filter surface and to facilitate dust removal with pulse or back airflow.

Laicer, Castro↗

NASA NTRS2019

Tunable mid-wave infrared spectral filters based on GexSbyTez for multispectral imaging

The mid-wave infrared (MWIR) spectrum contains a wealth of invaluable information including the spectral ‘fingerprint’ of many chemical species and has applications in remote sensing and astronomical imaging. Traditionally, filtering for the MWIR is achieved by means of passive multilayer interference (dichroic) filters, Fabry-Perot-based micro-electro-mechanical system (MEMS) filters, liquid crystal tunable filters, and focal plane array (FPA) filters. For accurate multispectral imaging applications, these approaches suffer from various limitations such as: having moving parts; exhibiting slow response times, and; having limited spectral bandwidth / resolution. Recently, there has been significant interest toward ‘active’ spectral imaging technologies, whereby the ability to provide electrically tunable narrowband filtering—spanning the entire MWIR—is highly desirable. In this work we introduce a new spectral imaging technology, namely actively tunable optical transmission filters using the phase-change material (PCM) GexSbyTez (GST). The GST exhibits a large, reversible change in its refractive index across the MWIR upon a phase transition (from amorphous to crystalline). This refractive index modulation governs the filter’s optical characteristics. Through an optical stimulus or applied voltage—which changes the GST state from amorphous to crystalline—one can actively tune the filter with MHz speed. We incorporate GST into optimized guided mode resonance (GMR) and plasmonic nanohole array (PNA) device architectures, enabling <10nm spectral resolution and tunable operation across 3~5µm. Our proposed PCM-MWIR filter will be able to extract the maximum amount of ‘useful’ information within the atmosphere for remote Earth sensing measurements at operational speeds orders of magnitude faster than current airborne-based sensors. Moreover, it may enable affordable SmallSat-based MWIR instrumentation which is complimentary to other observation systems. The MISSE (Materials International Space Station Experiment-Flight Facility) experiment has been proposed as a testbed for a PCM-based tunable MWIR filter module to allow exposure of the module to the low Earth orbit space environment. This will provide valuable data regarding the robustness of the filter to withstand the radiation and atomic oxygen environment and allow assessment of the technology for use in space applications.

Kim, Hyun Jung↗

NASA NTRS1989

Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear

An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.

Keel, Byron M.↗