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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Sensor filter designs for large flexible spacecraft

Traditional control methods may excite flexible modes causing degraded performance or instability of large flexible space structures (LFSS). Control techniques developed for control of LFSS requires a numerical model of the structure and some knowledge of model error. This will be increasingly difficult with the complex space structures planned for the future. If filters could be used to condition the sensor output, control design would be less demanding. This paper is presented in viewgraph format.

Nimmo, Nancy A.↗
NASA NTRS1996

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

Ramirez, W. Fred↗
NASA NTRS2011

Data Analysis And Polarization Measurements With GEMS

The Gravity and Extreme Magnetism SMEX (GEMS) mission was selected by NASA for flight in 2014. GEMS will make the first sensitive survey of X-ray polarization across a wide range of source classes including black hole and neutron star binaries, AGN of different types, rotation and accretion-powered pulsars, magnetars, shell supernova remnants and pulsar wind nebulae. GEMS employs grazing-incidence foil mirrors and novel time-projection chamber (TPC) polarimeters leveraging the photoelectric effect. The GEMS detectors image the charge tracks of photoelectrons produced by 2 - 10 keV X-rays. The initial direction of the photoelectron is determined by the linear polarization of the photon. We present an overview of the data analysis challenges and methods for GEMS, including procedures for producing optimally filtered images of the charge tracks and estimating their initial directions. We illustrate our methods using laboratory measurements of polarized and unpolarized X-rays with flight-like detectors as well as from simulated tracks. We also present detailed simulations exploring the statistics of polarization measurements appropriate for GEMS, and make comparisons with previous work.

Stohmayer, Tod↗
NASA NTRS1993

Feasibility of determining surface emissions of trace gases using an inverse method in a three-dimensional chemical transport model

The paper investigates the feasibility of using an inverse method based on a linear Kalman filter in a three-dimensional atmospheric transport model, for the determination of regional surface fluxes with rapid convergence, using data from a finite number of observation sites. It was found that the inverse method used was capable to accurately determine regional surface fluxes using the present ALE/GALE sites, and to converge to the correct solution within a year or two, using initial conditions very different from the final solution.

Hartley, Dana↗
NASA NTRS2013

Tuning and Robustness Analysis for the Orion Absolute Navigation System

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test flight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Holt, Greg N.↗
NASA NTRS1987

Optimal application of Morrison's iterative noise removal for deconvolution. Appendices

Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.

Ioup, George E.↗
NASA NTRS1995

Cleanliness evaluation of rough surfaces with diffuse IR reflectance

Contamination on bonding surfaces has been determined to be a primary cause for degraded bond strength in certain solid rocket motor bondlines. Hydrocarbon and silicone based organic contaminants that are airborne or directly introduced to a surface are a significant source of contamination. Diffuse infrared (IR) reflectance has historically been used as an effective technique for detection of organic contaminants, however, common laboratory methods involving the use of a Fourier transform IR spectrometer (FTIR) are impractical for inspecting the large bonding surface areas found on solid rocket motors. Optical methods involving the use of acousto-optic tunable filters and fixed bandpass optical filters are recommended for increased data acquisition speed. Testing and signal analysis methods are presented which provide for simultaneous measurement of contamination concentration and roughness level on rough metal surfaces contaminated with hydrocarbons.

Pearson, L. H.↗
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 NTRS1984

Instrument failure detection and isolation in a system with variable plant parameters

This paper considers the problem of detecting instrument failures in a system in which there are plant parameter variations. The method described is based on the use of Kalman filters to provide a detection comparison in a manner similar to Clark's dedicated observer method. To improve the sensitivity to sensor variation and reduce the sensitivity to plant parameter variation the Kalman filters are designed to be sub-optimal. A procedure is described to design the sub-optimal filters so as to improve a measure of the ratio of sensor to plant sensitivity.

Alexandro, F. J., Jr.↗
NASA NTRS1989

Performance of FFT methods in local gravity field modelling

Fast Fourier transform (FFT) methods provide a fast and efficient means of processing large amounts of gravity or geoid data in local gravity field modelling. The FFT methods, however, has a number of theoretical and practical limitations, especially the use of flat-earth approximation, and the requirements for gridded data. In spite of this the method often yields excellent results in practice when compared to other more rigorous (and computationally expensive) methods, such as least-squares collocation. The good performance of the FFT methods illustrate that the theoretical approximations are offset by the capability of taking into account more data in larger areas, especially important for geoid predictions. For best results good data gridding algorithms are essential. In practice truncated collocation approaches may be used. For large areas at high latitudes the gridding must be done using suitable map projections such as UTM, to avoid trivial errors caused by the meridian convergence. The FFT methods are compared to ground truth data in New Mexico (xi, eta from delta g), Scandinavia (N from delta g, the geoid fits to 15 cm over 2000 km), and areas of the Atlantic (delta g from satellite altimetry using Wiener filtering). In all cases the FFT methods yields results comparable or superior to other methods.

Forsberg, Rene↗
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 NTRS2019

Cleanroom Contamination Identification Method Development

During fabrication, assembly, and testing of spacecraft and flight hardware it is vital to avoid contaminants that can cause degradation and could result in significant failure. Yet, there is no existing contamination monitoring method that provides the identity of airborne particles in a cleanroom facility. Knowing the particle identities, would allow scientists and engineers to determine the source of the contaminants and prevent setbacks before they occur or cause damage. Current cleanliness monitoring methods include airborne particle counters (APCs), fallout filters, and visual inspections. Particle counts from APCs are the primary metric used to define a cleanroom class and hence its level of cleanliness, but do not provide identification nor can they differentiate between large and small sizes of particles. In addition, using fallout filters is not a proactive, timely, or representative approach to cleanroom contamination monitoring because these samples are only retrieved after 30 days and are placed away from spacecraft processing to avoid interference with operations. In contrast, the forced air sampling method can collect a sample within an hour at any location required and provide results in less than a day. This system uses a cassette and filter sample medium to capture airborne particles which are then taken to a scanning electron microscope with energy dispersive spectroscopy (SEM/EDS) to identify and size the captured particles. Development of forced air sampling into an established laboratory capability will allow for fast sampling and routine identification of unknown contamination sources within the cleanroom. The test method development required market research for an air sampling cassette that increases sample collection efficiency and a filter with low enough background contamination to allow differentiation between a blank (control) and the collected sample. It was determined that a conductive black cassette and a polycarbonate filter were the best options. Conductive black cassettes, in comparison to the standard styrene, are manufactured using polypropylene filled with carbon. This makes the cassette conductive and minimizes the tendency of particles to stick to the wall of the cassette due to electrostatic force. In previous trials a mixed cellulose ester (MCE) filter was used to capture the contaminants, however the rougher surface of the filter contributed to entrapment of the particles within the filter structure and made it harder to identify the particles. In comparison, track etched polycarbonate filters have random cylindrical pores and a smooth surface which contributes to uniform sample distribution on the surface of the filter. Future work includes: testing the system using control samples to determine the efficiency and suitability of the medium, performing sample collection in various environments to establish ideal operating parameters and analyzing contaminant particles using SEM/EDS and assistant characterization techniques. Once fully developed, employing the forced air sampling method will help to prevent damage to spacecraft, avoid schedule delays, and allow for mission success.

Hernandez Melendez, Jailyn M.↗
NASA NTRS1993

Improvements in ERBS attitude determination without gyros

Previous papers have described the modification of the Earth Radiation Budget Satellite (ERBS) Attitude Determination System (ADS) to overcome the impact of on board gyro degradation and failure on attitude ground support of the mission. Two approaches were taken: implementing a Kalman filter in place of the batch-least-squares attitude estimator to account for the propagation error produced by high-noise gyro data, and modeling the ERBS attitude dynamics to restore rate information in the case of gyro failure. Both of these methods had shortcomings. In practice, the filter attitude diverged without complete sensor observability, and accurate dynamics modeling required knowledge of disturbance torque parameters that had to be determined manually. These difficulties have been overcome by improved tuning of the filter and by incorporating dynamics parameter estimation into the ERBS ADS.

Chu, D.↗
NASA NTRS1984

Effect of RF Filtering on the Performance of Uncoded PCM/PM Telemetry Channels

A method for calculating the increase in received telemetry signal power required to compensate for the use of a radio frequency interference (RFI) filter in front of the DSN receiving system low-noise amplifier is described. The telemetry system for which the degradation is calculated is an uncoded PCM/PM system in which the NRZ data directly modulates the carrier at a modulation level which leaves a discrete carrier. A phase-locked loop in the RF receiver tracks the discrete carrier and coherently demodulates the PCM data. The RFI filter may be a series of Butterworth, Tchebychev, or Bessel low-pass, high-pass, band-pass, or band-reject filters, each with arbitrary bandwidth, number of poles, and, for band-pass or band-reject filters, resonant frequency. The only restriction is that the RFI filter must have only simple poles. Numerical results are presented for the RFI filters the DSN plans to place in front of the S-band FET, S-band maser, and X-band maser low noise amplifiers. The main conclusion is that the filters will produce negligible degradation at data rates below 4 Mbps.

Koerner, M. A.↗
NASA NTRS2024

Iterated Sigma-Point Kalman Filtering for Trajectory Reconstruction

Two second-order Kalman filtering methods are added to the New Statistical Trajec-tory Estimation Program (NewSTEP). The two filters are of the class of Sigma-Point Kalman Filters, namely the Unscented Kalman Filter and the Divided Difference Filter. Both filters are implemented with an iterative measurement update step. Results from simulation test case and a flight data test case are provided to show the filter performance. The results indicate that the new second-order filters pro-duce trajectory estimates with reduced uncertainties when compared to the existing first-order filtering method.

Sophia Vedvik↗
NASA NTRS2005

Hubble Space Telescope Angular Velocity Estimation During the Robotic Servicing Mission

In 2004 NASA began investigation of a robotic servicing mission for the Hubble Space Telescope (HST). Such a mission would require estimates of the HST attitude and rates in order to achieve a capture by the proposed Hubble robotic vehicle (HRV). HRV was to be equipped with vision-based sensors, capable of estimating the relative attitude between HST and HRV. The inertial HST attitude is derived from the measured relative attitude and the HRV computed inertial attitude. However, the relative rate between HST and HRV cannot be measured directly. Therefore, the HST rate with respect to inertial space is not known. Two approaches are developed to estimate the HST rates. Both methods utilize the measured relative attitude and the HRV inertial attitude and rates. First, a non-linear estimator is developed. The nonlinear approach estimates the HST rate through an estimation of the inertial angular momentum. Second, a linearized approach is developed. The linearized approach is a pseudo-linear Kalman filter. Simulation test results for both methods are given. Even though the development began as an application for the HST robotic servicing mission, the methods presented are applicable to any rendezvous/capture mission involving a non-cooperative target spacecraft.

Thienel, Julie K.↗
NASA NTRS1981

Optimal interpolation and the Kalman filter

The estimation theory of stochastic-dynamic systems is described and used in a numerical study of optimal interpolation. The general form of data assimilation methods is reviewed. The Kalman-Bucy, KB filter, and optimal interpolation (OI) filters are examined for effectiveness in performance as gain matrices using a one-dimensional form of the shallow-water equations. Control runs in the numerical analyses were performed for a ten-day forecast in concert with the OI method. The effects of optimality, initialization, and assimilation were studied. It was found that correct initialization is necessary in order to localize errors, especially near boundary points. Also, the use of small forecast error growth rates over data-sparse areas was determined to offset inaccurate modeling of correlation functions near boundaries.

Cohn, S.↗
NASA NTRS2004

Adaptive Numerical Dissipative Control in High Order Schemes for Multi-D Non-Ideal MHD

The goal is to extend our adaptive numerical dissipation control in high order filter schemes and our new divergence-free methods for ideal MHD to non-ideal MHD that include viscosity and resistivity. The key idea consists of automatic detection of different flow features as distinct sensors to signal the appropriate type and amount of numerical dissipation/filter where needed and leave the rest of the region free of numerical dissipation contamination. These scheme-independent detectors are capable of distinguishing shocks/shears, flame sheets, turbulent fluctuations and spurious high-frequency oscillations. The detection algorithm is based on an artificial compression method (ACM) (for shocks/shears), and redundant multi-resolution wavelets (WAV) (for the above types of flow feature). These filter approaches also provide a natural and efficient way for the minimization of Div(B) numerical error. The filter scheme consists of spatially sixth order or higher non-dissipative spatial difference operators as the base scheme for the inviscid flux derivatives. If necessary, a small amount of high order linear dissipation is used to remove spurious high frequency oscillations. For example, an eighth-order centered linear dissipation (AD8) might be included in conjunction with a spatially sixth-order base scheme. The inviscid difference operator is applied twice for the viscous flux derivatives. After the completion of a full time step of the base scheme step, the solution is adaptively filtered by the product of a 'flow detector' and the 'nonlinear dissipative portion' of a high-resolution shock-capturing scheme. In addition, the scheme independent wavelet flow detector can be used in conjunction with spatially compact, spectral or spectral element type of base schemes. The ACM and wavelet filter schemes using the dissipative portion of a second-order shock-capturing scheme with sixth-order spatial central base scheme for both the inviscid and viscous MHD flux derivatives and a fourth-order Runge-Kutta method are denoted.

Yee, H. C.↗