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At least 1,117 records · Page 62

Trajectory specification for high capacity air traffic control

Method and system for analyzing and processing information on one or more aircraft flight paths, using a four-dimensional coordinate system including three Cartesian or equivalent coordinates (x, y, z) and a fourth coordinate .delta. that corresponds to a distance estimated along a reference flight path to a nearest reference path location corresponding to a present location of the aircraft. Use of the coordinate .delta., rather than elapsed time t, avoids coupling of along-track error into aircraft altitude and reduces effects of errors on an aircraft landing site. Along-track, cross-track and/or altitude errors are estimated and compared with a permitted error bounding space surrounding the reference flight path.

Paielli, Russell A.↗

Automating Surface Attitude Positioning and Pointing Operations for Mars 2020

The Surface Attitude Positioning and Pointing (SAPP) subsystem of the Mars Perseverance rover keeps track of the rover’s position and attitude on the surface of Mars. The SAPP Downlink Engineering Operations team members receive data from the rover on a daily basis. They must interpret the data to make sure the rover is staying safe and to support uplink planning. The SAPP team keeps track of the error growth in the rover’s attitude estimate due to noise in the Rover Inertial Measurement Unit’s (RIMU) gyroscopes used to propagate that attitude estimate whenever the rover is moving. Whenever this error grows to a particular threshold, SAPP is responsible for updating the onboard attitude knowledge using the RIMU’s accelerometers to estimate rover roll and pitch and sun imaging to estimate rover yaw, thereby reducing this attitude estimation error. Accurate attitude estimation is required so that the rover can successfully point its High Gain Antenna (HGA) to receive information from Earth and as a backup to the Mars orbiters used for sending data from the rover to Earth, point instruments on its Remote Sensing Mast (RSM), and support safe movement and placement of instruments by the rover’s ARM relative to the Martian surface. The Mars 2020 Engineering Operations team has been working to increase the operational efficiency of the mission and eventually move to a five-hour timeline for daily operations. In pursuit of this goal, the SAPP Engineering Operations team has automated their downlink process by developing a centralized Jupyter notebook to analyze the data received daily from the rover. The SAPP downlink Jupyter notebook automatically collects the data relevant to the SAPP subsystem and visualizes this information in plots and tables that can be easily read by downlink operators to aid them in assessing the status of the subsystem. Various Application Programming Interfaces (APIs) have been incorporated into the downlink daily notebook to automate the collection and posting of data, such as gathering and posting data products to the cloud. The SAPP team has also developed a SAPP downlink software library that includes functions to aid the notebook in processing data. In addition to assessing the SAPP subsystem on a daily basis, operators need to assess the long-term trending behavior of the subsystem over time. An automated trending process has been developed to collect information from the daily notebooks in order to plot and analyze that data in a centralized place. These daily and trending processes have expedited the SAPP downlink assessment and laid the groundwork to completely automate the SAPP downlink process so that SAPP operators are unnecessary unless something unexpected occurs. This paper will provide an overview of the functions that the SAPP subsystem carries out on a daily basis, and will then dive into the automations that have been developed for daily and trending downlink assessment. An assessment of the downlink efficiency will be provided, along with a summary of lessons learned and work to go. Finally, the authors will discuss how these types of automated spacecraft health assessments could be more broadly used within mission operations.

Zarifian, Anais↗

Structure Errors in System Identification

An approach to system identification is presented which explicitly takes structure errors into account and hence provides a systematic way for answering questions concerning the magnitude of estimated parameter errors resulting from structural errors. It is indicated that, from this point of view, it is possible to define near equivalence between process and model and to obtain meaningful theoretical results on solution error system identification. It remains to apply these results to large realistic problems such as those involving models of complex man machine systems.

Bekey, G. A.↗

Estimation of Non-Seasonal Oceanic Mass Redistribution and its Geodynamic Effects from the Topex/Poseidon Observation

Mass redistribution in terms of angular momentum will change the Earth's rotation under the conservation of angular momentum. It also changes the external gravitational field according to Newton's gravitational law. These small geodynamic variations can be measured very accurately by modem space geodetic techniques. We report on new estimates of the oceanic tidal angular momentum and hence the tidal variations in the Earth's rotation rate and polar motion. These are deduced from the new tidal solutions GOT99 and TPXO.3, plus M2 and Mf estimates (with error bars) from TPXO.4a. Comparisons with observed diurnal/semidiurnal tidal variations are generally similar to previous model estimates. Comparisons of models and observations of Mf polar motion are confused, with neither models nor observations agreeing among themselves or with each other. Part of this is caused by differences in Mf currents; model TPXO.4 shows current-intensive Rossby modes along western boundaries of major basins, which are indeed expected on theoretical grounds. Unfortunately, there are no reliable in situ observations of Mf currents useful for comparing models. On non-tidal oceanic mass redistribution we compute the principal components of the multi-year T/P sea surface height (SSH) field using EOF (empirical orthogonal functions) taking into consideration of the latitude-dependent area weighting. Emphasis is placed upon non-seasonal and interannual oscillations on regional scales, including ENSO and the North Atlantic Oscillation. Steric corrections to the observed SSH due to sea surface temperature changes (which has no geodynamic effects) is now under study using POCM ocean model output.

Chao, Benjamin F.↗

Turbulent Output-Based Anisotropic Adaptation

Controlling discretization error is a remaining challenge for computational fluid dynamics simulation. Grid adaptation is applied to reduce estimated discretization error in drag or pressure integral output functions. To enable application to high O(10(exp 7)) Reynolds number turbulent flows, a hybrid approach is utilized that freezes the near-wall boundary layer grids and adapts the grid away from the no slip boundaries. The hybrid approach is not applicable to problems with under resolved initial boundary layer grids, but is a powerful technique for problems with important off-body anisotropic features. Supersonic nozzle plume, turbulent flat plate, and shock-boundary layer interaction examples are presented with comparisons to experimental measurements of pressure and velocity. Adapted grids are produced that resolve off-body features in locations that are not known a priori.

Park, Michael A.↗

Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals

Satellite soil moisture and vegetation optical depth (VOD; related to the total vegetation water mass per unit area) are increasingly being used to study water relations in the soil-plant continuum across the globe. However, soil moisture and VOD are typically jointly estimated, where errors in the optimization approach can cause compensation between both variables and confound such studies. It is thus critical to quantify how satellite microwave measurement errors propagate into soil moisture and VOD. Such a study is especially important for VOD given limited investigations of whether VOD reflects in-situ plant physiology. Furthermore, despite new approaches that constrain (or regularize) VOD dynamics to reduce soil moisture errors, there is limited study of whether regularization reduces VOD errors without obscuring true vegetation temporal dynamics. Here, we find that, across the globe, VOD is less robust to measurement error (more difficult for optimization methods to find the true solution) than soil moisture in their joint estimation. However, a moderate degree of regularization (via time-constrained VOD) reduces errors in VOD to a greater degree than soil moisture and reduces spurious soil moisture-VOD coupling. Furthermore, despite constraining VOD time dynamics, regularized VOD variations on sub-weekly scales are both closer to simulated true VOD time series and have global VOD post-rainfall responses with reduced error signatures compared to VOD retrievals without regularization. Ultimately, we recommend moderately regularized VOD for use in large scale studies of soil-plant water relations because it suppresses noise and spurious soil moisture-VOD coupling without removing the physical signal.

Vegetation optical depth↗

A study of examiner accuracy in cartridge case comparisons. Part 2: Examiner use of the AFTE range of conclusions

Here, this report describes an analysis of how examiners used the Association of Firearm and Toolmark Examiners (AFTE) Range of Conclusions in a controlled study undertaken to estimate examiner error rates in comparing cartridge cases. Results of the error rate analysis are reported in [1]; this paper focuses on a broader analysis of how the entire collection of classification categories, especially those in the Inconclusive range, were used by the participating examiners. Volunteer active examiners with AFTE membership or working in laboratories that participate in Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false-negatives was estimated as 0.367 % from comparisons known to be from the same firearm but reported as eliminations. The overall rate of false-positives was estimated as 1.01 % from comparisons known to be from different firearms but reported as identifications. In the case of true different-source examinations, it is clear that the three Inconclusive categories and the Elimination category are not used consistently by all examiners. We identify five different apparent patterns of use of the AFTE Range of Conclusions scale, and discuss possible reasons for and implications of these differences.

99 GENERAL AND MISCELLANEOUS↗

Estimation of clear-sky insolation using satellite and ground meteorological data

Ground based pyranometer measurements were combined with meteorological data from the Tiros N satellite in order to estimate clear-sky insolations at five U.S. sites for five weeks during the spring of 1979. The estimates were used to develop a semi-empirical model of clear-sky insolation for the interpretation of input data from the Tiros Operational Vertical Sounder (TOVS). Using only satellite data, the estimated standard errors in the model were about 2 percent. The introduction of ground based data reduced errors to around 1 percent. It is shown that although the errors in the model were reduced by only 1 percent, TOVS data products are still adequate for estimating clear-sky insolation.

Staylor, W. F.↗

Interpolation Method Needed for Numerical Uncertainty

Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact problem and uncertainties exist. There is a method to approximate the errors in CFD via Richardson's Extrapolation. This method is based off of progressive grid refinement. To estimate the errors, the analyst must interpolate between at least three grids. This paper describes a study to find an appropriate interpolation scheme that can be used in Richardson's extrapolation or other uncertainty method to approximate errors.

Groves, Curtis E.↗

Interpolation Method Needed for Numerical Uncertainty Analysis of Computational Fluid Dynamics

Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact problem and uncertainties exist. There is a method to approximate the errors in CFD via Richardson's Extrapolation. This method is based off of progressive grid refinement. To estimate the errors in an unstructured grid, the analyst must interpolate between at least three grids. This paper describes a study to find an appropriate interpolation scheme that can be used in Richardson's extrapolation or other uncertainty method to approximate errors. Nomenclature

CFD↗

Pressure Analysis for LAVA-OVEN

The Lunar Advanced Volatiles Analysis (LAVA) and the Oxygen Volatiles Extraction Node (OVEN) are subsystems included in the Regolith Environment Science, and Oxygen Lunar Volatiles Extraction (RESOLVE) payload bound for the Moon in 2019. This Resource Prospector Mission (RPM) has the objective of landing on a shadowed region of the Moons South Pole to collect data and determine whether the resources could be effectively used for space exploration systems. The quantification of the resources will help understand if it can adequately minimize materials carried from Earth by: providing life support, propellants, construction materials or energy supply to the payload or crew. This paper outlines the procedures done for the pressure analysis of the LAVA-OVEN (LOVEN) Integration Testing. The pressure analysis quantifies how much gases and water are present in the sample tested during the Engineering Testing Unit (ETU) phase of instrument development. Ultimately the purpose of these tests is to improve the estimate of the amount of water in each Lunar sample and reduce the time necessary for this estimate. The governing principle that was used for the analysis is the Ideal Gas Law, PV=nRT where P stands for pressure, V for volume, n for number of moles, R being the gas constant and T for temperature. We also estimate the errors involved in these measured and derived quantities since a key objective of the mission is to estimate the quantity of volatiles present in the lunar samples introduced into OVEN.

Lunar↗

The effects of random accelerations on estimation accuracy with applications to the Mariner 1969 relativity experiment

A simple point of view is presented for establishing the relationship between a general modeling error and estimation accuracy. Tentative models are given for the random, nongravitational forces thought likely to affect the Mariner 6 and 7 spacecraft. The navigation data from these spacecraft were used to determine the relativity parameter Gamma. The effect that random accelerations have on the classical least squares filter, which assumes the accelerations do not exist, is calculated, and it is demonstrated that their presence seriously affects the estimates, particularly when an extended data arc is employed. Finally, some preliminary exploration using sequential-type filters, which attempt to model and thus ameliorate the effects of these same accelerations, is reported.

Curkendall, D. W.↗

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Markus, Thorsten↗

Dynamic Modeling from Flight Data with Unknown Time Skews

A method for estimating dynamic model parameters from flight data with unknown time skews is described and demonstrated. The method combines data reconstruction, nonlinear optimization, and equation-error parameter estimation in the frequency domain to accurately estimate both dynamic model parameters and the relative time skews in the data. Data from a nonlinear F-16 aircraft simulation with realistic noise, instrumentation errors, and arbitrary time skews were used to demonstrate the approach. The approach was further evaluated using flight data from a subscale jet transport aircraft, where the measured data were known to have relative time skews. Comparison of modeling results obtained from time-skewed and time-synchronized data showed that the method accurately estimates both dynamic model parameters and relative time skew parameters from flight data with unknown time skews.

Morelli, Eugene A.↗

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗

A new calibration method for time delay standard and its application

A method which is used to measure time delay accurately by using a Type 900-LB slotted line is described. The accuracy for calibrating time delay of a precision coaxial air line Type 900-L is about + or - (0.4 to 0.6)ps, and for coaxial cables with VSWR less than 1.5 and time delay t less than 50ns is about + or - (3 to 5)ps. Theoretical analysis and mathematical derivation of microwave networks in cascade are given. Methods to eliminate the errors which are caused by the discontinuities and the error analysis of the measuring system are presented. Skin effect analysis of the transient characteristic of coaxial transmission line are discussed in detail. Methods to eliminate the errors which result from using the calibrated time delay standard to calibrate time interval measurement instruments are presented. The estimation of errors and formulae for correction of those errors are described.

Su, B. W.↗

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

microwave observations↗

A preliminary estimate of geoid-induced variations in repeat orbit satellite altimeter observations

Altimeter satellites are often maintained in a repeating orbit to facilitate the separation of sea-height variations from the geoid. However, atmospheric drag and solar radiation pressure cause a satellite orbit to drift. For Geosat this drift causes the ground track to vary by + or - 1 km about the nominal repeat path. This misalignment leads to an error in the estimates of sea surface height variations because of the local slope in the geoid. This error has been estimated globally for the Geosat Exact Repeat Mission using a mean sea surface constructed from Geos 3 and Seasat altimeter data. Over most of the ocean the geoid gradient is small, and the repeat-track misalignment leads to errors of only 1 to 2 cm. However, in the vicinity of trenches, continental shelves, islands, and seamounts, errors can exceed 20 cm. The estimated error is compared with direct estimates from Geosat altimetry, and a strong correlation is found in the vicinity of the Tonga and Aleutian trenches. This correlation increases as the orbit error is reduced because of the increased signal-to-noise ratio.

Brenner, Anita C.↗