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NASA NTRS2016

Comparison of Atmospheric Delay Statistics from Deep Space Network Arrays and Nearby Test Interferometers

Several techniques have been explored and demonstrated that allow for greater data return on space-to-ground links. Among these techniques, arraying several smaller diameter dish antennas together is one method used in several arenas. These arrays can achieve larger effective area and gain than are available from a single larger antenna. This technique is routinely used by the NASA Deep Space Network (DSN) at 8.4 GHz where the incoming signals are much weaker than those experienced by the near-Earth satellite community. When considering arraying at much higher frequencies such as 32 GHz deep-space Ka-band, the phase alignment of the individual antenna signals is significantly disrupted by atmospheric turbulence. Since 2012, several downlink array demonstrations have been conducted using 32 GHz carrier signals emitted by the deep space probes Cassini and Kepler. Site test interferometers (STIs) that receive signals from geostationary satellites have been deployed at all three DSN tracking complexes for long-term monitoring of atmospheric delay fluctuations. In a previous DSN array demonstration study involving the Cassini spacecraft, it was shown that statistics of the adjusted STI phase fluctuations matched the statistics of concurrent array demonstration phase fluctuations. These adjustments accounted for differences in antenna separation, elevation angle and spacecraft frequencies. The STI antenna separations were about 200 m and the DSN antenna separations were about 300 m. These adjustments made use of the thick-layer turbulence model that was applicable to the Goldstone desert climate during the summer months for which the data were acquired. In this paper, we report on the results of additional array demonstrations involving the Kepler spacecraft and compare the adjusted STI phase fluctuations with those seen by a nearby two-element array of 34 m diameter antennas tracking Kepler’s 32 GHz signal at the Goldstone, California and Madrid, Spain DSN sites. We also discuss results from a demonstration using an array over a longer 12.5 km baseline. The Cassini and Kepler array demonstrations were found to validate the long term statistics acquired from several years of STI data as well as the models used to adjust the statistics for the conditions of an array. These statistics represent reliable estimates of the phase fluctuations that would be seen by an array tracking a deep space signal after applying appropriate adjustments for a given array configuration, elevation angle profile and observing frequency.

Morabito, David D.↗

NASA NTRS2022

Periodic Solar Wind Structures Observed in Measurements of Elemental and Ionic Composition in situ at L1

Mesoscale periodic structures observed in solar wind plasma serve as an important diagnostic tool for constraining the processes that govern the formation of the solar wind. These structures have been observed in situ and in remote data as fluctuations in proton and electron density. However, only two events of this type have been reported regarding the elemental and ionic composition. Composition measurements are especially important in gaining an understanding of the origin of the solar wind as the composition is frozen into the plasma at the Sun and does not evolve as it advects through the heliosphere. Here, we present the analysis of four events containing mesoscale periodic solar wind structure during which the Iron and Magnesium number density data, measured by the Solar Wind Ion Composition Spectrometer (SWICS)on board the Advanced Composition Explorer spacecraft, are validated at statistically significant count levels. We use a spectral analysis method specifically designed to extract periodic signals from astrophysical time series and apply it to the SWICS 12-minute native resolution dataset. We find variations in the relative abundance of elements with low first ionization potential, mass dependencies, and charge state during time intervals in which mesoscale periodic structures are observed. These variations are linked to temporal or spatial variations in solar source regions and put constraints on the solar wind formation mechanisms that produce them. Techniques presented here are relevant for future, higher-resolution studies of data from new instruments such as Solar Orbiter’s Heavy Ion Sensor.

Irena Gershkovich↗

NASA NTRSDate not supplied

Comparing and Automatically Optimizing the Performance of Systematic Error Correctors for TESS Light Curves

Accurate and precise removal of systematic errors from TESS light curves (lcs) is critical for exoplanet, stellar, and asteroseismology studies•Various approaches exist to correct for systematics while preserving intrinsic stellar variability (Luger et al. 2016, 2018; Hedges et al. 2021; Smith et al. 2012; Stumpe et al. 2014; Aigrain et al. 2017)•However, no comprehensive analyseshave been carried out to properly compare these approaches and determine their validity on different target types in both an individual and statistical manner•Current correctors have been usually demonstrated on their own and on limited sets of hand-picked targets•To apply these corrections more generally, it is important to compare multiple correctors on larger samples•We are particularly interested in the ability to remove scattered light contaminationfrom the Earth and the Moon, which is a key systematic for TESS

David Rapetti↗

NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗

NASA NTRS2013

Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using a common grid sequence and multiple turbulence models for the June 2012 fifth Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for the 4th Drag Prediction Workshop. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

Statistical analysis↗

NASA NTRS1981

Some statistical problems inherent in measuring precipitation

A formula permitting calculation of the mean-square error of the mean value of a random variable due to periodic sampling is derived and applied to estimating the sampling error for satellite observation of the mean rainfall during the GARP Atlantic Tropical Experiment (GATE). The effects of both spatial resolution and frequency of observation on the sampling error are summarized in graphs. It is found that four observations per day are sufficient to determine the monthly mean rainfall over an area of 2.5 deg square (280km x 280km) to within a standard deviation of 5 percent of its mean value; two samples per day would yield an error with a standard deviation slightly less than 10 percent of the mean. A satellite instrument with less frequent sampling may produce significantly greater error in the estimate of monthly mean rainfall.

Flueck, J. A.↗

NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗

NASA NTRS2000

Possible Statistics of Two Coupled Random Fields: Application to Passive Scalar

We use the relativity postulate of scale invariance to derive the similarity transformations between two coupled scale-invariant random elds at different scales. We nd the equations leading to the scaling exponents. This formulation is applied to the case of passive scalars advected i) by a random Gaussian velocity field; and ii) by a turbulent velocity field. In the Gaussian case, we show that the passive scalar increments follow a log-Levy distribution generalizing Kraichnan's solution and, in an appropriate limit, a log-normal distribution. In the turbulent case, we show that when the velocity increments follow a log-Poisson statistics, the passive scalar increments follow a statistics close to log-Poisson. This result explains the experimental observations of Ruiz et al. about the temperature increments.

Dubrulle, B.↗

NASA NTRS1972

Study of optimum methods of optical communication

Optimum methods of optical communication accounting for the effects of the turbulent atmosphere and quantum mechanics, both by the semi-classical method and the full-fledged quantum theoretical model are described. A concerted effort to apply the techniques of communication theory to the novel problems of optical communication by a careful study of realistic models and their statistical descriptions, the finding of appropriate optimum structures and the calculation of their performance and, insofar as possible, comparing them to conventional and other suboptimal systems are discussed. In this unified way the bounds on performance and the structure of optimum communication systems for transmission of information, imaging, tracking, and estimation can be determined for optical channels.

Harger, R. O.↗

NASA NTRS1972

A double-loop tracking system.

A nonlinear analysis which can be used to assess certain statistical characteristics of double-loop tracking systems is presented. It takes into account the mutual coupling effects of the loops in the system. Two approaches are taken to obtain steady-state probability density functions (pdf's) of the system phase errors. From these pdf's, important system performance statistics, e.g., the phase-error variances, can be calculated, thus illustrating the application and usefulness of the analysis. The analysis is applied to a satellite transponder as an example.

Yuen, J. H.↗

NASA NTRS1976

Preliminary compressor design study for an advanced multistage axial flow compressor

An optimum, axial flow, high pressure ratio compressor for a turbofan engine was defined for commercial subsonic transport service starting in the late 1980's. Projected 1985 technologies were used and applied to compressors with an 18:1 pressure ratio having 6 to 12 stages. A matrix of 49 compressors was developed by statistical techniques. The compressors were evaluated by means of computer programs in terms of various airline economic figures of merit such as return on investment and direct-operating cost. The optimum configuration was determined to be a high speed, 8-stage compressor with an average blading aspect ratio of 1.15.

Marman, H. V.↗

NASA NTRS1977

Analysis of a discrete spectrum analyzer for the detection of radio frequency interference

As the radio frequency spectrum becomes increasingly overcrowded, interference with mission-critical DSN operations is rising at an alarming rate. To alleviate this problem the DSN is developing a wideband surveillance system for on-site detection and identification of potential sources of radio frequency interference (RFI), which will complement the existing frequency coordination activities. The RFI monitoring system is based on a wideband, multi-look discrete spectrum analyzer operating on fast Fourier transform principles. An extensive general statistical analysis is presented of such spectrum analyzers and derives threshold detection performance formulas for signals of interest. These results are then applied to the design of the RFI spectrum analyzer under development.

Levitt, B. K.↗

NASA NTRS1985

Implicit dual control for general stochastic systems

A new implicit dual technique is presented for stochastic adaptive control synthesis. In this technique, denoted as the method of utility costs (MOUC), a new control policy is derived from a known starting control policy by using a single iteration in time-varying policy space. An important result is that the new control policy yields a corresponding improvement in adaptive performance relative to the known starting policy. Since the starting policy can be chosen arbitrarily, the new policy has potentially superior performance relative to any existing design. Unlike other implicit dual designs, the MOUC can be applied to systems having constrained inputs, discontinuities, discrete valued disturbances, as well as in situations where the variances of the associated process statistics are large. A numerical example is given in which a controller is synthesized to provide improved performance relative to the Open-Loop Feedback policy of Dreyfus.

Bayard, D. S.↗

NASA NTRS1990

A classification of the galaxy groups

A statistical criterion has been proposed to reveal the random and physical clusterings among stars, galaxies and other objects. This criterion has been applied to the galaxy triples of the list by Karachentseva, Karaschentsev and Scherbanovsky, and the double galaxies of the list by Dahari where the primary components are the Seyfert galaxies. The confident physical, probable physical, probable optical and confident optical groups have been identified. The limit difference of radial velocities of components for the confident physical multiple galaxies has also been estimated.

Anosova, Joanna P.↗

NASA NTRS1991

A consensual neural network

A neural network architecture called a consensual neural network (CNN) is proposed for the classification of data from multiple sources. Its relation to hierarchical and ensemble neural networks is discussed. CNN is based on the statistical consensus theory and uses nonlinearly transformed input data. The input data are transformed several times, and the different transformed data are applied as if they were independent inputs. The independent inputs are classified using stage neural networks and outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote-sensing data and geographic data are given.

Benediktsson, J. A.↗

NASA NTRS1995

Distorted turbulence submitted to frame rotation: RDT and LES results

The objective of this effort is to carry the analysis of Lee et al. (1990) to the case of shear with rotation. We apply the RDT approximation to turbulence submitted to frame rotation for the case of a uniformly sheared flow and compare its mean statistics to results of high resolution DNS of a rotating plane channel flow. In the latter, the mean velocity profile is modified by the Coriolis force, and accordingly, different regions in the channel can be identified. The properties of the plane pure strain turbulence submitted to frame rotation are, in addition, investigated in spectral space, which shows the usefulness of the spectral RDT approach. This latter case is investigated here. Among the general class of quadratic flows, this case does not follow the same stability properties as the others since the related mean vorticity is zero.

Godeferd, Fabien S.↗

NASA NTRS1994

A Compositional Relevance Model for Adaptive Information Retrieval

There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

Mathe, Nathalie↗

NASA NTRS2004

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗