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NASA NTRSDate not supplied

Wavelength Calibration of the Full-sun Ultraviolet Rocket SpecTrograph (FURST)

The Sun has a well-known periodicity in sunspot number and magnetic field variation. The underlying cause of this 11-year cycle is not fully understood and has yet to be connected with those processes in other stellar objects. The Full-sun Ultraviolet Rocket SpecTrograph (FURST) is a sounding rocket payload being developed by Montana State University (MSU) alongside the Marshall Space Flight Center(MSFC) solar physics group. Scheduled to launch from White Sands Missile Range (WSMR) in 2022, this instrument is unique in that it will provide the connection between stellar observatories with measurements of our Sun. It will achieve this through measuring high-resolution full-disk spectral irradiance. We aim to obtain a wavelength resolution R>10,000 in the 120 - 181 nm UltraViolet (UV) range, on par with that of the Hubble (HST) Space Telescope Imaging Spectrograph (STIS). This resolution goal will allow us to study the relatively low-temperature plasma in the chromosphere and lower corona with spectral accuracy down to 0.1 Å (a Doppler-shift of about±30 km/s). In addition, the Lyman Alpha(121 nm) line is known to saturate most CCD electronics. These factors illustrate the particular challenge of precise wavelength calibration for this spectral range. We are building a collimator in order to calibrate the FURST instrument under these strict spectral requirements. This paper will present the results of our simulation of the diagnostic lamp signal to be used for wavelength calibration. The simulation allows us to begin to account for photon noise, electronic readout noise, and statistical error. These in turn lead to the development of our pre- and post-launch calibration plans. Future work includes absolute radiometric and wavelength calibration with this new collimator. In addition, the ability of FURST to measure small Doppler-shifts will provide capabilities for planetary atmospheric scientists. This impact is coupled with the diverse international partnership created by the closely-knit Sounding Rocket teams around the globe. Sounding Rockets like FURST have an even broader impact, as they encourage future satellite missions under the prospect of long-term observations

FURST↗
NASA NTRSDate not supplied

Wavelength Calibration of the Full-sun Ultraviolet Rocket SpecTrograph: (FURST)

The Sun has a well-known periodicity in sunspot number and magnetic field variation. The underlying cause of this 11-year cycle is not fully understood and has yet to be connected with those processes in other stellar objects. The Full-sun Ultraviolet Rocket SpecTrograph (FURST) is a sounding rocket payload being developed by Montana State University (MSU) alongside the Marshall Space Flight Center (MSFC) solar physics group. Scheduled to launch from White Sands Missile Range (WSMR) in 2022, this instrument is unique in that it will provide the connection between stellar observatories with measurements of our Sun. It will achieve this through extremely high-resolution full-disk spectroscopy in EUV. We aim to obtain a wavelength resolution R > 10,000 in the 115 - 181 nm range, on par with that of the Hubble (HST) Space Telescope Imaging Spectrograph (STIS). The Lyman Alpha line (121 nm) is known to oversaturate most CCD electronics and is of particular challenge for this spectral range. In addition, this resolution goal will allow us to study the 3 km/s motion (a Doppler-shift of about 0.01 Angstroms) of the relatively low-temperature plasma in the chromosphere and lower corona. This paper will present the results of our simulation of the diagnostic lamp signal to be used in this wavelength calibration. To test the viability of this precise of a device, we are building a collimator capable of calibrating the FURST instrument under these strict radiometric requirements. By way of a diagnostic lamp simulation, we will account for photon noise, CCD electronic readout noise, and statistical error. These will lead to the development of our pre- and post-launch calibration plan. Future work includes absolute radiometric and wavelength calibration with this new collimator. In addition, the ability of FURST to measure extremely small Doppler-shifts will provide capabilities for planetary atmospheric scientists. This impact is coupled with the diverse international partnership created by the closely-knit Sounding Rocket teams across the globe. These Sounding Rockets have an even broader impact, as they encourage future satellite missions under the prospect of long-term observations.

FURST↗
NASA NTRS2022

Merging of the Case 2 Regional Coast Colour and Maximum‑Peak Height Chlorophyll‑a Algorithms: Validation and Demonstration of Satellite‑derived Retrievals Across US Lakes

Water quality monitoring is relevant for protecting the designated, or beneficial uses, of water such as drinking, aquatic life, recreation, irrigation, and food supply that support the economy, human well-being, and aquatic ecosystem health. Managing finite water resources to support these designated uses requires information on water quality so that managers can make sustainable decisions. Chlorophyll-a (chl-a, µg L−1) concentration can serve as a proxy for phytoplankton biomass and may be used as an indicator of increased anthropogenic nutrient stress. Satellite remote sensing may present a complement to in situ measures for assessments of water quality through the retrieval of chl-a with in-water algorithms. Validation of chl-a algorithms across US lakes improves algorithm maturity relevant for monitoring applications. This study compares performance of the Case 2 Regional Coast Colour (C2RCC) chl-a retrieval algorithm, a revised version of the Maximum-Peak Height (MPH(P)) algorithm, and three scenarios merging these two approaches. Satellite data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS) and the Ocean and Land Colour Instrument (OLCI), while field observations were obtained from 181 lakes matched with U.S. Water Quality Portal chl-a data. The best performance based on mean absolute multiplicative error (MAEmult) was demonstrated by the merged algorithm referred to as C15−M10 (MAEmult = 1.8, biasmult = 0.97, n = 836). In the C15−M10 algorithm, the MPH(P) chl-a value was retained if it was > 10 µg L−1; if the MPH(P) value was ≤ 10 µg L−1, the C2RCC value was selected, as long as that value was < 15 µg L−1. Time-series and lake-wide gradients compared against independent assessments from Lake Champlain and long-term ecological research stations in Wisconsin were used as complementary examples supporting water quality reporting requirements. Trophic state assessments for Wisconsin lakes provided examples in support of inland water quality monitoring applications. This study presents and assesses merged adaptations of chl-a algorithms previously reported independently. Additionally, it contributes to the transition of chl-a algorithm maturity by quantifying error statistics for a number of locations and times.

Satellite↗
NASA NTRS2022

Deep Interacting Multiple Model Filtering

In this paper, a deep learning-based multiple model estimation framework is presented for the state estimation of hybrid dynamical systems from high dimensional observations such as camera images. A low dimensional vector which represents the measurement of the latent dynamical system and its corresponding variance are learned using a deep encoder neural network. An Interacting Multiple Model (IMM) filter is used to generate the latent state estimates and covariances using multiple dynamical models, which can be learned using backpropagation through time. The state estimates of the dynamical system and the corresponding covariance matrix are generated from the latent state estimates and covariance using a deep decoder neural network. The whole network is trained in an end-to-end manner using a loss function which minimizes the negative log-likelihood of the neural network parameters. Simulation results are presented using a 2D bouncing ball example and estimation error statistics are computed which demonstrates the accuracy and consistency of the estimation.

Ghananeel Rotithor↗
NASA NTRS2023

Compressible Turbulence in the Near-Sun Solar Wind Parker Solar Probe's First Eight Perihelia

Many questions remain about the compressibility of solar wind turbulence with respect to its origins and properties. Low plasma beta (ratio of thermal to magnetic pressure) environments allow for the easier generation of compressible turbulence, enabling study of the relationship between density fluctuations and turbulent Mach number. Utilizing Parker Solar Probe plasma data, we examine the normalized proton density fluctuations as a function of turbulent Mach number M t conditioned on plasma beta and cross helicity. With consideration of statistical error in the parameters computed from in situ data, we find a general result consistent with both linear-wave theory and nearly incompressible turbulence in an inhomogeneous background field. We compare observational results conditioned on plasma beta and cross helicity with 3D magnetohydrodynamic simulations and observe rather significant similarities with respect to how those parameters affect the proportionality between density fluctuations and turbulent Mach number. This study further investigates the complexity of compressible turbulence as viewed by the density scaling relationship and may help better understand the compressible environment of the near-Sun solar wind.

Manuel Enrique Cuesta↗
NASA NTRS1990

Statistical analysis of modeling error in structural dynamic systems

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Hasselman, T. K.↗
NASA NTRS1976

The statistical significance of error probability as determined from decoding simulations for long codes

The very low error probability obtained with long error-correcting codes results in a very small number of observed errors in simulation studies of practical size and renders the usual confidence interval techniques inapplicable to the observed error probability. A natural extension of the notion of a 'confidence interval' is made and applied to such determinations of error probability by simulation. An example is included to show the surprisingly great significance of as few as two decoding errors in a very large number of decoding trials.

Massey, J. L.↗
NASA NTRS1999

Adaptive Error Estimation in Linearized Ocean General Circulation Models

Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large representation error, i.e. the dominance of the mesoscale eddies in the T/P signal, which are not part of the 21 by 1" GCM. Therefore, the impact of the observations on the assimilation is very small even after the adjustment of the error statistics. This work demonstrates that simult&neous estimation of the model and measurement error statistics for data assimilation with global ocean data sets and linearized GCMs is possible. However, the error covariance estimation problem is in general highly underdetermined, much more so than the state estimation problem. In other words there exist a very large number of statistical models that can be made consistent with the available data. Therefore, methods for obtaining quantitative error estimates, powerful though they may be, cannot replace physical insight. Used in the right context, as a tool for guiding the choice of a small number of model error parameters, covariance matching can be a useful addition to the repertory of tools available to oceanographers.

Chechelnitsky, Michael Y.↗
NASA NTRS1999

Model Error Estimation for the CPTEC Eta Model

Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.

Tippett, Michael K.↗
NASA NTRS1972

Synchronization using pulsed edge tracking in optical PPM communication system

A pulse position modulated (PPM) optical communication system using narrow pulses of light for data transmission requires accurate time synchronization between transmitter and receiver. The presence of signal energy in the form of optical pulses suggests the use of a pulse edge tracking method of maintaining the necessary timing. The edge tracking operation in a binary PPM system is examined, taking into account the quantum nature of the optical transmissions. Consideration is given first to pure synchronization using a periodic pulsed intensity, then extended to the case where position modulation is present and auxiliary bit decisioning is needed to aid the tracking operation. Performance analysis is made in terms of timing error and its associated statistics. Timing error variances are shown as a function of system signal to noise ratio.

Gagliardi, R.↗
NASA NTRS1992

Persistence and predictability in a perfect model

A realistic two-level GCM is used to examine the relationship between predictability and persistence. Predictability is measured by the average divergence of ensembles of solutions starting from perturbed initial conditions, and persistence is defined in terms of the autocorrelation function based on a single long-term model integration. The average skill of the dynamical forecasts is compared with the skill of simple persistence-based statistical forecasts. For initial errors comparable in magnitude to present-day analysis errors, the statistical forecast loses all skill after about one week, reflecting the lifetime of the lowest frequency fluctuations in the model. Large ensemble mean dynamical forecasts would be expected to remain skillful for about 3 wk. The disparity between the skill of the statistical and dynamical forecasts is greater for the higher frequency modes, which have little memory beyond 1 d, yet remain predictable for about 2 wk. The results are analyzed in terms of two characteristic time scales.

Schubert, Siegfried D.↗
NASA NTRS1981

An analytic technique for statistically modeling random atomic clock errors in estimation

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Fell, P. J.↗
NASA NTRS1981

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Alston, D. W.↗
NASA NTRS2006

Statistical Characterization of Environmental Error Sources Affecting Electronically Scanned Pressure Transducers

Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure (ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.

Green, Del L.↗
NASA NTRS2006

Statistical Characterization of Environmental Error Sources Affecting Electronically Scanned Pressure Transducers

Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure [ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.

Green, Del L.↗
NASA NTRS2010

Solar Array Disturbances to Spacecraft Pointing During the Lunar Reconnaissance Orbiter (LRO) Mission

The Lunar Reconnaissance Orbiter (LRO), the first spacecraft to support NASA s return to the Moon, launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle. It was initially inserted into a direct trans-lunar trajectory to the Moon. After a five day transit to the Moon, LRO was inserted into the Lunar orbit and successfully lowered to a low altitude elliptical polar orbit for spacecraft commissioning. Successful commissioning was completed in October 2009 when LRO was placed in its near circular mission orbit with an approximate altitude of 50km. LRO will spend at least one year orbiting the Moon, collecting lunar environment science and mapping data, utilizing a suite of seven instruments to enable future human exploration. The objective is to provide key science data necessary to facilitate human return to the Moon as well as identification of opportunities for future science missions. LRO's instrument suite will provide the high resolution imaging data with sub-meter accuracy, highly accurate lunar cartographic maps, mineralogy mapping, amongst other science data of interest. LRO employs a 3-axis stabilized attitude control system (ACS) whose primary control mode, the "Observing Mode", provides Lunar nadir, off-nadir, and inertial fine pointing for the science data collection and instrument calibration. This controller combines the capability of fine pointing with on-demand large angle full-sky attitude reorientation. It provides simplicity of spacecraft operation as well as additional flexibility for science data collection. A conventional suite of ACS components is employed in the Observing Mode to meet the pointing and control objectives. Actuation is provided by a set of four reaction wheels developed in-house at NASA Goddard Space Flight Center (GSFC). Attitude feedback is provided by a six state Kalman filter which utilizes two SELEX Galileo Star Trackers for attitude updates, and a single Honeywell Miniature Inertial Measurement Unit (MIMU) to provide body rates for attitude propagation. Rate is computed by differentiating accumulated angle provided by the MIMU. The Observing Mode controller is required to maintain fine pointing while a large fully-articulated solar array (SA) maintains its panel normal to the solar incidence. This paper describes the disturbances to the attitude control resulting from the SA articulation. Observing Mode performance in the presence of this disturbance was assessed while the spacecraft was in an initial elliptical low altitude orbit during the commissioning phase, which started about two weeks after launch and lasted for 90 days. LRO demonstrated excellent pointing performance during Observing Mode nadir and inertial attitude target operations during this phase. Transient LRO attitude errors observed during commissioning resulted primarily from three sources, Diviner instrument calibrations, RW zero crossings, and SA articulation. Even during times of considerable disturbance from SA articulation, the attitude errors were maintained below the statistical attitude error requirement level of 15 arc-sec (3 sigma).

Calhoun, Philip↗