SEARCH · Engineering Papers

Results for “measurement errors”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances

Motivated by the needs of Mars data assimilation. particularly quantification of measurement errors and generation of averaging kernels. we have evaluated atmospheric temperature retrievals from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances. Multiple sets of retrievals have been considered in this study; (1) retrievals available from the Planetary Data System (PDS), (2) retrievals based on variants of the retrieval algorithm used to generate the PDS retrievals, and (3) retrievals produced using the Mars 1-Dimensional Retrieval (M1R) algorithm based on the Optimal Spectral Sampling (OSS ) forward model. The retrieved temperature profiles are compared to the MGS Radio Science (RS) temperature profiles. For the samples tested, the M1R temperature profiles can be made to agree within 2 K with the RS temperature profiles, but only after tuning the prior and error statistics. Use of a global prior that does not take into account the seasonal dependence leads errors of up 6 K. In polar samples. errors relative to the RS temperature profiles are even larger. In these samples, the PDS temperature profiles also exhibit a poor fit with RS temperatures. This fit is worse than reported in previous studies, indicating that the lack of fit is due to a bias correction to TES radiances implemented after 2004. To explain the differences between the PDS and Ml R temperatures, the algorithms are compared directly, with the OSS forward model inserted into the PDS algorithm. Factors such as the filtering parameter, the use of linear versus nonlinear constrained inversion, and the choice of the forward model, are found to contribute heavily to the differences in the temperature profiles retrieved in the polar regions, resulting in uncertainties of up to 6 K. Even outside the poles, changes in the a priori statistics result in different profile shapes which all fit the radiances within the specified error. The importance of the a priori statistics prevents reliable global retrievals based a single a priori and strongly implies that a robust science analysis must instead rely on retrievals employing localized a priori information, for example from an ensemble based data assimilation system such as the Local Ensemble Transform Kalman Filter (LETKF).

Hoffman, Matthew J.↗

NASA NTRS2012

Hydrocarbons on Phoebe, Iapetus, and Hyperion: Quantitative Analysis

We present a quantitative analysis of the hydrocarbon spectral bands measured on three of Saturn's satellites, Phoebe, Iaperus, and Hyperion. These bands, measured with the Cassini Visible-Infrared Mapping Spectrometer on close fly-by's of these satellites, are the C-H stretching modes of aromatic hydrocarbons at approximately 3.28 micrometers (approximately 3050 per centimeter), and the are four blended bands of aliphatic -CH2- and -CH3 in the range approximately 3.36-3.52 micrometers (approximately 2980- 2840 per centimeter) bably indicating the presence of polycyclic aromatic hydrocarbons (PAH), is unusually strong in comparison to the aliphatic bands, resulting in a unique signarure among Solar System bodies measured so far, and as such offers a means of comparison among the three satellites. The ratio of the C-H bands in aromatic molecules to those in aliphatic molecules in the surface materials of Phoebe, NAro:NAliph approximately 24; for Hyperion the value is approximately 12, while laperus shows an intermediate value. In view of the trend of the evolution (dehydrogenation by heat and radiation) of aliphatic complexes toward more compact molecules and eventually to aromatics, the relative abundances of aliphatic -CH2- and -CH3- is an indication of the lengths of the molecular chain structures, hence the degree of modification of the original material. We derive CH2:CH3 approximately 2.2 in the spectrum of low-albedo material on laperus; this value is the same within measurement errors to the ratio in the diffuse interstellar medium. The similarity in the spectral signatures of the three satellites, plus the apparent weak trend of aromatic/aliphatic abundance from Phoebe to Hyperion, is consistent with, and effectively confirms that the source of the hydrocarbon-bearing material is Phoebe, and that the appearance of that material on the other two satellites arises from the deposition of the inward-spiraling dust that populates the Phoebe ring.

Cruikshank, Dale P.↗

NASA NTRS2013

Motor Qualification for Long-Duration Mars Missions

Qualification of motors for deep space under extreme thermal environments to be encountered during the Mars Science Laboratory (MSL) mission is required to verify the reliability and validate mission assurance requirements. The motor assembly must survive all ground operations, plus the nominal 670 Martian-day (or sol) mission that includes summer and winter seasons of the Mars environment. The motor assembly was tested and characterized under extreme temperature conditions with reference to hardware requirements. The motor assembly has been proved to be remarkably robust and displayed no sign of degradation due to the 3 X (three times per JPL design principles) thermal environmental exposure to the punishing Mars surface operations cycles. The motor characteristics obtained before, during, and post-test comparisons for the surface operations cycles are within measurement error of one another. The motors withstood/survived 2,010 extreme temperature cycles with a Delta T of 190 C deep temperature cycles, representing three times the expected thermal cycling exposure during the MSL surface operations. The qualification test hardware elements (A200 motor assembly, encoders, and resolver) have not shown any signs of degradation due to the PQV (Package Qualification and Verification) testing. The test hardware has demonstrated sufficient life to survive the deep thermal cycles associated with MSL mission surface operations for three lives.

Ramesham, Rajeshuni↗

NASA NTRS2013

RF Reference Switch for Spaceflight Radiometer Calibration

The goal of this technology is to provide improved calibration and measurement sensitivity to the Soil Moisture Active Passive Mission (SMAP) radiometer. While RF switches have been used in the past to calibrate microwave radiometers, the switch used on SMAP employs several techniques uniquely tailored to the instrument requirements and passive remote-sensing in general to improve radiometer performance. Measurement error and sensitivity are improved by employing techniques to reduce thermal gradients within the device, reduce insertion loss during antenna observations, increase insertion loss temporal stability, and increase rejection of radar and RFI (radio-frequency interference) signals during calibration. The two legs of the single-pole double-throw reference switch employ three PIN diodes per leg in a parallel-shunt configuration to minimize insertion loss and increase stability while exceeding rejection requirements at 1,413 MHz. The high-speed packaged diodes are selected to minimize junction capacitance and resistance while ensuring the parallel devices have very similar I-V curves. Switch rejection is improved by adding high-impedance quarter-wave tapers before and after the diodes, along with replacing the ground via of one diode per leg with an open circuit stub. Errors due to thermal gradients in the switch are reduced by embedding the 50-ohm reference load within the switch, along with using a 0.25-in. (approximately equal to 0.6-cm) aluminum prebacked substrate. Previous spaceflight microwave radiometers did not embed the reference load and thermocouple directly within the calibration switch. In doing so, the SMAP switch reduces error caused by thermal gradients between the load and switch. Thermal issues are further reduced by moving the custom, highspeed regulated driver circuit to a physically separate PWB (printed wiring board). Regarding RF performance, previous spaceflight reference switches have not employed high-impedance tapers to improve rejection. The use of open-circuit stubs instead of a via to provide an improved RF short is unique to this design. The stubs are easily tunable to provide high rejection at specific frequencies while maintaining very low insertion loss in-band.

Knuble, Joseph↗

NASA NTRS2013

Evaluating Light Rain Drop Size Estimates from Multiwavelength Micropulse Lidar Network Profiling

This paper investigates multiwavelength retrievals of median equivolumetric drop diameter D(sub 0) suitable for drizzle and light rain, through collocated 355-/527-nm Micropulse Lidar Network (MPLNET) observations collected during precipitation occurring 9 May 2012 at the Goddard Space Flight Center (GSFC) project site. By applying a previously developed retrieval technique for infrared bands, the method exploits the differential backscatter by liquid water at 355 and 527 nm for water drops larger than approximately 50 micrometers. In the absence of molecular and aerosol scattering and neglecting any transmission losses, the ratio of the backscattering profiles at the two wavelengths (355 and 527 nm), measured from light rain below the cloud melting layer, can be described as a color ratio, which is directly related to D(sub 0). The uncertainty associated with this method is related to the unknown shape of the drop size spectrum and to the measurement error. Molecular and aerosol scattering contributions and relative transmission losses due to the various atmospheric constituents should be evaluated to derive D(sub 0) from the observed color ratio profiles. This process is responsible for increasing the uncertainty in the retrieval. Multiple scattering, especially for UV lidar, is another source of error, but it exhibits lower overall uncertainty with respect to other identified error sources. It is found that the total error upper limit on D(sub 0) approaches 50%. The impact of this retrieval for long-term MPLNET monitoring and its global data archive is discussed.

light-rain drop size estimates↗

NASA NTRS2011

Reduced Kalman Filters for Clock Ensembles

This paper summarizes the author's work ontimescales based on Kalman filters that act upon the clock comparisons. The natural Kalman timescale algorithm tends to optimize long-term timescale stability at the expense of short-term stability. By subjecting each post-measurement error covariance matrix to a non-transparent reduction operation, one obtains corrected clocks with improved short-term stability and little sacrifice of long-term stability.

Kalman filter↗

NASA NTRS2011

Space-Time Data Fusion

Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.

Greenhouse Gases Observing Satellite (GOSAT)↗

NASA NTRS2015

Sulfur and Oxygen Isotopic Analysis of a Cosmic Symplectite from a Comet Wild 2 Stardust Terminal Particle

Introduction: Analyses of comet 81P/Wild 2 samples re-turned from the Stardust mission have uncovered surprising simi-larities to meteoritic material, including the identification of inner solar system grains [1-3]. The TEM characterization of terminal particle (TP) 4 from Stardust track #147 revealed an assemblage consisting of symplectically intergrown pentlandite and nanocrys-talline maghemite coexisting with high-Ca pyroxene [4]. Mineral-ogically similar cosmic symplectites (COS) containing pentlandite and magnetite in the primitive Acfer 094 meteorite are highly de-pleted in 16O (17O, 18O ~ 180 per mille) [5-7]. This isotopic signature is proposed to record alteration with primordial solar nebula water. Conversely, the normal O isotopic composition of the Stardust COS indicates alteration by a different aqueous reservoir, perhaps on the comet [8]. In this study, we analyzed the Wild 2 COS for S isotopes to further constrain its origin. Experimental: Thin sections of TP4 (12 m) were produced and their mineralogy was thoroughly characterized by TEM. Two of the sections were analyzed for O isotopes by isotopic imaging in the JSC NanoSIMS 50L. The sample in one of the slices was completely consumed. The remaining material in the adjacent slice was analyzed simultaneously for 16O, 32S, 33S, 34S, and 56Fe16O in electron multipliers using a Cs+ primary ion beam. Quasi-simulta-neous arrival (QSA) can have a significant effect on S isotopic ra-tios when using electron multipliers, resulting in undercounting of 32S [9]. Canyon Diablo troilite (CDT) was measured numerous times to deduce a correction factor for QSA and ensure measure-ment reproducibility. Isotopic ratios are reported relative to CDT. Results and Discussion: The Wild 2 COS is enriched in the heavy S isotopes relative to CDT (33S = 6.5 +/- 1.6 per mille; 34S = 5.1 +/- 0.7 per mille; 1). The degree of 33S enrichment indicates mass-inde-pendent fractionation (MIF) with 33S = 3.9 +/- 1.7 per mille. MIF of S has been observed in some chondrules (33S up to 0.11per mille) [10], but this effect has not been identified in sulfides from carbonaceous chondrites [11] or IDPs [12]. S isotopic analysis of Stardust impact craters also did not reveal MIF or anomalies, save for one potential 32S-rich presolar sulfide [13]. Measurement errors on these impact craters were much larger than those in this study, however. MIF of S has been proposed to result from heterogeneities in the solar neb-ula from nucleosynthetic components [14] or photochemical irra-diation of solar nebula gas [10]. Presolar SiC grains are observed to have 32S enrichments [15, 16] contrary to the S isotopic compo-sition of the cometary COS. The S isotopic composition more likely reflects irradiation of nebular gas.

Nguyen, A. N.↗

NASA NTRS2015

Dealing with Uncertainties in Initial Orbit Determination

A method to deal with uncertainties in initial orbit determination (IOD) is presented. This is based on the use of Taylor differential algebra (DA) to nonlinearly map the observation uncertainties from the observation space to the state space. When a minimum set of observations is available DA is used to expand the solution of the IOD problem in Taylor series with respect to measurement errors. When more observations are available high order inversion tools are exploited to obtain full state pseudo-observations at a common epoch. The mean and covariance of these pseudo-observations are nonlinearly computed by evaluating the expectation of high order Taylor polynomials. Finally, a linear scheme is employed to update the current knowledge of the orbit. Angles-only observations are considered and simplified Keplerian dynamics adopted to ease the explanation. Three test cases of orbit determination of artificial satellites in different orbital regimes are presented to discuss the feature and performances of the proposed methodology.

Armellin, Roberto↗

NASA NTRS2015

A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

EnBS↗

NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗

NASA NTRS2015

Trend Estimates of AERONET-Observed and Model-Simulated AOTs Between 1993 and 2013

Recently, temporal changes in Aerosol Optical Thickness (AOT) have been investigated based on model simulations, satellite and ground-based observations. Most AOT trend studies used monthly or annual arithmetic means that discard details of the generally right-skewed AOT distributions. Potentially, such results can be biased by extreme values (including outliers). This study additionally uses percentiles (i.e., the lowest 5%, 25%, 50%, 75% and 95% of the monthly cumulative distributions fitted to Aerosol Robotic Network (AERONET)-observed and ECHAM/MESSy Atmospheric Chemistry (EMAC)-model simulated AOTs) that are less affected by outliers caused by measurement error, cloud contamination and occasional extreme aerosol events. Since the limited statistical representativeness of monthly percentiles and means can lead to bias, this study adopts the number of observations as a weighting factor, which improves the statistical robustness of trend estimates. By analyzing the aerosol composition of AERONET-observed and EMAC-simulated AOTs in selected regions of interest, we distinguish the dominant aerosol types and investigate the causes of regional AOT trends. The simulated and observed trends are generally consistent with a high correlation coefficient (R = 0.89) and small bias (slope+/-2(sigma) = 0.75 +/- 0.19). A significant decrease in EMAC-decomposed AOTs by water-soluble compounds and black carbon is found over the USA and the EU due to environmental regulation. In particular, a clear reversal in the AERONET AOT trend percentiles is found over the USA, probably related to the AOT diurnal cycle and the frequency of wildfires. In most of the selected regions of interest, EMAC-simulated trends are mainly attributed to the significant changes of the dominant aerosols; e.g., significant decrease in sea salt and water soluble compounds over Central America, increase in dust over Northern Africa and Middle East, and decrease in black carbon and organic carbon over Australia.

AERONET↗

NASA NTRS2016

Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach

This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.

Warner, James E.↗

NASA NTRS2016

Wavelength Locking to CO2 Absorption Line-Center for 2-Micron Pulsed IPDA Lidar Application

An airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar is currently under development at NASA Langley Research Center (LaRC). This IPDA lidar system targets both atmospheric carbon dioxide (CO2) and water vapor (H2O) column measurements. Independent wavelength control of each of the transmitted laser pulses is a key feature for the success of this instrument. The wavelength control unit provides switching, tuning and locking for each pulse in reference to a 2-micron CW (Continuous Wave) laser source locked to CO2 line-center. Targeting the CO2 R30 line center, at 2050.967 nanometers, a wavelength locking unit has been integrated using semiconductor laser diode. The CO2 center-line locking unit includes a laser diode current driver, temperature controller, center-line locking controller and CO2 absorption cell. This paper presents the CO2 center-line locking unit architecture, characterization procedure and results. Assessment of wavelength jitter on the IPDA measurement error will also be addressed by comparison to the system design.

Refaat, Tamer F.↗

NASA NTRS2017

Filter Tuning Using the Chi-Squared Statistic

This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The goal of the process is to characterize the filter performance in the metric of covariance realism. The Chi-squared statistic is the value calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance. The process of tuning an Extended Kalman Filter (EKF) for Aqua and Aura support is described, including examination of the measurement errors of available observation types, and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-squared statistic, calculated from EKF solutions, are assessed.

Filter Tuning↗

NASA NTRS2017

Interval Predictor Models for Data with Measurement Uncertainty

An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations.

Lacerda, Marcio J.↗

NASA NTRS2017

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

A new horizontal time metric, Time to Protected Zone, is proposed for use in the Detect and Avoid (DAA) Systems equipped by unmanned aircraft systems (UAS). This time metric has three advantages over the currently adopted time metric, modified tau: it corresponds to a physical event, it is linear with time, and it can be directly used to prioritize intruding aircraft. The protected zone defines an area around the UAS that can be a function of each intruding aircraft's surveillance measurement errors. Even with its advantages, the Time to Protected Zone depends explicitly on encounter geometry and may be more sensitive to surveillance sensor errors than modified tau. To quantify its sensitivity, simulation of 972 encounters using realistic sensor models and a proprietary fusion tracker is performed. Two sensitivity metrics, the probability of time reversal and the average absolute time error, are computed for both the Time to Protected Zone and modified tau. Results show that the sensitivity of the Time to Protected Zone is comparable to that of modified tau if the dimensions of the protected zone are adequately defined.

alert↗

NASA NTRS2017

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

UAS↗