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At least 55 records · Page 3

Technique for Extension of Small Antenna Array Mutual-Coupling Data to Larger Antenna Arrays

A technique is presented whereby the mutual interaction between a small number of elements in a planar array can be interpolated and extrapolated to accurately predict the combined interactions in a much larger array of many elements. An approximate series expression is developed, based upon knowledge of the analytical characteristic behavior of the mutual admittance between small aperture antenna elements in a conducting ground plane. This expression is utilized to analytically extend known values for a few spacings and orientations to other element configurations, thus eliminating the need to numerically integrate a large number of highly oscillating and slowly converging functions. This paper shows that the technique can predict very accurately the mutual coupling between elements in a very large planar array with a knowledge of the self-admittance of an isolated element and the coupling between only two-elements arranged in eight different pair combinations. These eight pair combinations do not necessarily have to correspond to pairs in the large array, although all of the individual elements must be identical.

Bailey, M. C.↗

Wireless Telemetry and Command (T and C) Program

The Wireless Telemetry and Command (T&C) program is to investigate methods of using commercial telecommunications service providers to support command and telemetry services between a remote user and a base station. While the initial development is based on ground networks, the development is being done with an eye towards future space communications needs. Both NASA and the Air Force have indicated a plan to consider the use of commercial telecommunications providers to support their space missions. To do this, there will need to be an understanding of the requirements and limitations of interfacing with the commercial providers. The eventual payoff will be the reduced operations cost and the ability to tap into commercial services being developed by the commercial networks. This should enable easier realization of EP services to the end points, commercial routing of data, and quicker integration of new services into the space mission operations. Therefore, the ultimate goal of this program is not just to provide wireless radio communications for T&C services but to enhance those services through wireless networking and provider enhancements that come with the networks. In the following chapters, the detailed technical procedure will be showed step by step. Chapter 2 will talk about the general idea of simulation as well as the implementation of data acquisition including sensor array data and GPS data. Chapter 3 will talk about how to use LabVEEW and Component Works to do wireless communication simulation and how to distribute the real-time information over the Internet by using Visual Basic and ActiveX controls. Also talk about the test configuration and validation. Chapter 4 will show the test results both from In-Lab test and Networking Test. Chapter 5 will summarize the whole procedure and give the perspective for the future consideration.

Jiang, Hui↗

Tracking and Characterization of Aircraft Wakes Using Acoustic and Lidar Measurements

Data from the 2003 Denver International Airport Wake Acoustics Test are further examined to discern spectral content of aircraft wake signatures, and to compare three dimensional wake tracking from acoustic data to wake tracking data obtained through use of continuous wave and pulsed lidar. Wake tracking data derived from acoustic array data agree well with both continuous wave and pulsed lidar in the horizontal plane, but less well with pulsed lidar in the vertical direction. Results from this study show that the spectral distribution of acoustic energy in a wake signature varies greatly with aircraft type.

Booth, Earl R., Jr.↗

Performance of the real-time array signal combiner during the Voyager mission

During the Voyager Mission each Deep Space Station used its 64 meter antenna together with a 34 meter antenna to form an array. Data were selected from the Saturn encounter period from November 2 to November 13, 1980, to analyze the signal combiner performance. A statistical analysis of the residual gain data from all of the arrayed Deep Space Stations indicates that the Real Time Combiner is operating within the designed accuracy range of 0.2 + or - 0.05 dB around the theoretical gain. A decrease in the residual gain value appears to correlate with an increase in antenna elevation, which may be directly related to the changing antenna gain with elevation. Overall, the combined signal to noise ratio is improved by an average of 0.62 + or - 0.15 dB over the 64 meter signal to noise ratio alone.

Bartok, C. D.↗

Enhancing Discovery, Search, and Access of NASA Hydrological Data by Leveraging GEOSS

An ongoing NASA-funded project has removed a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other EOSDIS (Earth Observing System Data Information System) data sets (e.g., precipitation, soil moisture). These time series (data rods) are pre-generated. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. The Global Earth Observation System of Systems (GEOSS) is a logical mechanism for providing access to the data rods. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. The ongoing data rods project has demonstrated the feasibility of leveraging the GEOSS infrastructure to help provide access to time series of model grid information or grids of information over a geographical domain for a particular time interval. A recently-begun, related NASA-funded ACCESS-GEOSS project expands on these prior efforts. Current work is focused on both improving the performance of the generation of on-the-fly (OTF) data rods and the Web interfaces from which users can easily discover, search, and access NASA data.

GEOSS↗

Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

water cycle extreme events↗

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗

Enhancement of Mutual Discovery, Search, and Access of Data for Users of NASA and GEOSS-Cataloged Data Systems

An ongoing NASA-funded Data Rods (time series) project has demonstrated the removal of a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other NASA data sets. Data rods are pre-generated or generated on-the-fly (OTF), leveraging the NASA Simple Subset Wizard (SSW), a gateway to NASA data centers. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. Preliminary work has shown GEOSS can be leveraged to help provide access to data rods. A new NASA-funded project is extending this early work.

data access↗

A cluster analysis method for identification of subpopulations of cells in flow cytometric list-mode arrays

A specialized program was developed for flow cytometric list-mode data using an heirarchical tree method for identifying and enumerating individual subpopulations, the method of principal components for a two-dimensional display of 6-parameter data array, and a standard sorting algorithm for characterizing subpopulations. The program was tested against a published data set subjected to cluster analysis and experimental data sets from controlled flow cytometry experiments using a Coulter Electronics EPICS V Cell Sorter. A version of the program in compiled BASIC is usable on a 16-bit microcomputer with the MS-DOS operating system. It is specialized for 6 parameters and up to 20,000 cells. Its two-dimensional display of Euclidean distances reveals clusters clearly, as does its 1-dimensional display. The identified subpopulations can, in suitable experiments, be related to functional subpopulations of cells.

Li, Z. K.↗

Subspace-based Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

A subspace-based form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique is based on an eigenvalue decomposition of the background noise cross-spectral matrix. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels, and when background data do not match between measurements. Experimental results show limited success in recovering signal behavior for data in which conventional background subtraction fails. The results also demonstrate the subspace subtraction technique's ability to maintain a physical coherence relationship in the modified cross-spectral matrix. Deconvolution results from microphone phased array data indicate that array integration methods are largely insensitive to subtraction type, and that background subtraction with appropriate background data is an effective alternative to diagonal removal.

deconvolution↗

Lightning and Radar Measures of Mixed Phase Updraft Variability in Tracked Storms During the TRACER Field Campaign in Houston, Texas

Properties of 7488 thunderstorms are summarized for June-September 2022 during the TRACER field campaign Houston, Texas using polarimetric weather radar and VHF 3D lightning mapping array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day, and cells with lightning had stronger polarimetric columns. Track-level correlation of lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

TRACER field campaign↗

Exploring New Methods of Displaying Bit-Level Quality and Other Flags for MODIS Data

The NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC) archives and distributes snow and sea ice products derived from the MODerate resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra and Aqua satellites. All MODIS standard products are in the Earth Observing System version of the Hierarchal Data Format (HDF-EOS). The MODIS science team has packed a wealth of information into each HDF-EOS file. In addition to the science data arrays containing the geophysical product, there are often pixel-level Quality Assurance arrays which are important for understanding and interpreting the science data. Currently, researchers are limited in their ability to access and decode information stored as individual bits in many of the MODIS science products. Commercial and public domain utilities give users access, in varying degrees, to the elements inside MODIS HDF-EOS files. However, when attempting to visualize the data, users are confronted with the fact that many of the elements actually represent eight different 1-bit arrays packed into a single byte array. This project addressed the need for researchers to access bit-level information inside MODIS data files. In an previous NASA-funded project (ESDIS Prototype ID 50.0) we developed a visualization tool tailored to polar gridded HDF-EOS data set. This tool,called the Polar researchers to access, geolocate, visualize, and subset data that originate from different sources and have different spatial resolutions but which are placed on a common polar grid. The bit-level visualization function developed under this project was added to PHDIS, resulting in a versatile tool that serves a variety of needs. We call this the EOS Imaging Tool.

Khalsa, Siri Jodha Singh↗

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

A maximum correlation method for image construction of IRAS survey data

An algorithm is presented for the construction of images using linear array data with nonuniform scan coverage of object space and nonuniform detector responses. The algorithm achieves the maximum correlation between adjacent pixels, i.e., the smoothest image, consistent with the data and data uncertainties. For high spatial data density and signal-to-noise ratio, the achievable spatial resolution can exceed the diffraction limit of the optics. The capability of the algorithm is illustrated using 60-micron data from the region centered on the galaxy M101, obtained during the all-sky survey performed by the Infrared Astronomical Satellite. The 60-micron map produced has a resolution of about 36 arcsec and allows the identification of many H II regions by position and aperture photometry for the brighter ones. The achieved resolution is discussed in terms of the a priori estimate of the mean correlation length of the data, the directly measured FWHM in the final image, and the results of aperture photometry of M101 H II regions NGC 5447, 5455, 5461, 5462 and 5471.

Aumann, H. H.↗

Wavespace-Based Coherent Deconvolution

Array deconvolution is commonly used in aeroacoustic analysis to remove the influence of a microphone array's point spread function from a conventional beamforming map. Unfortunately, the majority of deconvolution algorithms assume that the acoustic sources in a measurement are incoherent, which can be problematic for some aeroacoustic phenomena with coherent, spatially-distributed characteristics. While several algorithms have been proposed to handle coherent sources, some are computationally intractable for many problems while others require restrictive assumptions about the source field. Newer generalized inverse techniques hold promise, but are still under investigation for general use. An alternate coherent deconvolution method is proposed based on a wavespace transformation of the array data. Wavespace analysis offers advantages over curved-wave array processing, such as providing an explicit shift-invariance in the convolution of the array sampling function with the acoustic wave field. However, usage of the wavespace transformation assumes the acoustic wave field is accurately approximated as a superposition of plane wave fields, regardless of true wavefront curvature. The wavespace technique leverages Fourier transforms to quickly evaluate a shift-invariant convolution. The method is derived for and applied to ideal incoherent and coherent plane wave fields to demonstrate its ability to determine magnitude and relative phase of multiple coherent sources. Multi-scale processing is explored as a means of accelerating solution convergence. A case with a spherical wave front is evaluated. Finally, a trailing edge noise experiment case is considered. Results show the method successfully deconvolves incoherent, partially-coherent, and coherent plane wave fields to a degree necessary for quantitative evaluation. Curved wave front cases warrant further investigation. A potential extension to nearfield beamforming is proposed.

Bahr, Christopher J.↗

A plasma-based non-intrusive point source for acoustic beamforming applications

A laser-generated plasma acoustic point source is used to directly measure the point spread function (PSF) of a microphone phased array. In beamforming analysis of microphone phased array data, the true acoustic field is convolved with the array's PSF. By directly measuring the PSF, corrections to the array analysis can be computed and applied. The acoustic source is measured in an open-jet aeroacoustic facility to evaluate the effects of sampling rate, microphone installation, source shift, reflections, shear layer refraction and model presence. Results show that measurements exhibit behavior consistent with theory with regard to source shift and shear layer refraction. Application of a measured PSF in beamforming analysis shows the process provides an effective in-situ method for array calibration both with and without flow and allows for corrections to incorporate reflections and scattering. The technique improves the agreement of beamforming results with the true spectrum of a known source, especially in the presence of reflections.

phased array↗