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NASA NTRS1994

Testing and Performance Analysis of a 650 Mbps QPPM Modem for Free-space Laser Communications

The testing and performance of a prototype modem developed at NASA Lewis Research Center for high-speed free-space direct detection optical communications is described. The testing was performed under laboratory conditions using computer control with specially developed test equipment that simulates free-space link conditions. The modem employs quaternary pulse position modulation (QPPM) at 325 Megabits per second (Mbps) on two optical channels, which are multiplexed to transmit a single 650 Mbps data stream. The measured results indicate that the receiver's automatic gain control (AGC), phased-locked-loop slot clock recovery, digital symbol clock recovery, matched filtering, and maximum likelihood data recovery circuits were found to have only 1.5 dB combined implementation loss during bit-error-rate (BER) performance measurements. Pseudo random bit sequences and real-time high quality video sources were used to supply 650 Mbps and 325 Mbps data streams to the modem. Additional testing revealed that Doppler frequency shifting can be easily tracked by the receiver, that simulated pointing errors are readily compensated for by the AGC circuits, and that channel timing skew affects the BER performance in an expected manner. Overall, the needed technologies for a high-speed laser communications modem were demonstrated.

Mortensen, Dale J.↗

NASA NTRS2013

VLBI2010 Receiver Back End Comparison

VLBI2010 requires a receiver back-end to convert analog RF signals from the receiver front end into channelized digital data streams to be recorded or transmitted electronically. The back end functions are typically performed in two steps: conversion of analog RF inputs into IF bands (see Table 2), and conversion of IF bands into channelized digital data streams (see Tables 1a, 1b and 1c). The latter IF systems are now completely digital and generically referred to as digital back ends (DBEs). In Table 2 two RF conversion systems are compared, and in Tables 1a, 1b, and 1c nine DBE systems are compared. Since DBE designs are advancing rapidly, the data in these tables are only guaranteed to be current near the update date of this document.

Petrachenko, Bill↗

DOE OSTI2020

The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT

IoT devices and sensor networks present new opportunities for measuring, monitoring, and guiding scientific experiments. Sensors, cameras, and instruments can be combined to provide previously unachievable insights into the state of ongoing experiments. However, IoT devices can vary greatly in the type, volume, and velocity of data they generate, making it challenging to fully realize this potential. Indeed, synergizing diverse IoT data streams in near-real time can require the use of machine learning (ML). In addition, new tools and technologies are required to facilitate the collection, aggregation, and manipulation of sensor data in order to simplify the application of ML models and in turn, fully realize the utility of IoT devices in laboratories. Here we will demonstrate how the use of the Argonne-developed Manufacturing Data and Machine Learning (MDML) platform can analyze and use IoT devices in a manufacturing experiment. MDML is designed to standardize the research and operational environment for advanced data analytics and AI-enabled automated process optimization by providing the infrastructure to integrate AI in cyber-physical systems for in situ analysis. We will show that MDML is capable of processing diverse IoT data streams, using multiple computing resources, and integrating ML models to guide an experiment.

Machine Learning↗

DOE OSTI2011

KAZRARSCL-Cloud Boundaries subset

The KAZR-ARSCL VAP provides cloud boundaries and best-estimate time-height fields of radar moments. The VAP merges corrected KAZR moments from all active radar modes with cloud base and cloud mask observations from the micropulse lidar (MPL), cloud base from the ceilometer, as well information from soundings, rain gauge, and microwave radiometer instruments to produce two data streams, one with best-estimate cloud base and cloud layer boundaries, and another which also includes best-estimate time-height fields of radar moments. This DOI is for the data stream that contain cloud layer boundaries only.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

KAZRARSCL-c0-Cloud Boundaries subset

The KAZR-ARSCL VAP provides cloud boundaries and best-estimate time-height fields of radar moments. The VAP merges corrected, but uncalibrated, KAZR moments from all active radar modes with cloud base and cloud mask observations from the micropulse lidar (MPL), cloud base from the ceilometer, as well information from soundings, rain gauge, and microwave radiometer instruments to produce two data streams, one with best-estimate cloud base and cloud layer boundaries, and another which also includes best-estimate time-height fields of radar moments. This DOI is for the data stream that contain cloud layer boundaries only. Please note that the reflectivity used in this level c0 product is uncalibrated.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Multi-Sensor Integration of Vegetation Index Products for Long-Term Monitoring of Vegetation Dynamics: A Case Study from MODIS to VIIRS

Spectral vegetation index (VI) time series data from moderate resolution sensors, such as Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), have widely been used to identify "hot spot" areas of vegetation changes and to characterize long-term trends of vegetation changes. The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor series of the Joint Polar Satellite System (JPSS) program is slated to continue the highly calibrated data stream initiated with MODIS. The first VIIRS sensor has operationally been acquiring Earth-reflected radiation since March 2012. The second VIIRS sensor (NOAA-20) was launched in November 2017, which is to continue the measurements made by the first VIIRS sensor. In this study, we examined an integrated use of MODIS and VIIRS VI time series data on capturing vegetation dynamics in the Asia-Pacific region using their overlapped period of observations (2013-2017). Three VIs, the "top-of-canopy (TOC)" normalized difference vegetation index (NDVI), TOC enhanced vegetation index (EVI), and TOC two-band enhanced vegetation index (EVI2), were investigated. For all the three VIs, VIIRS VIs were systematically higher than the MODIS counterparts due mainly to their spectral bandpass differences. However, both VIIRS and MODIS VIs showed the comparable spatial patterns in their temporal variations. Empirical spectral corrections allowed to merge the two data streams, which slightly improved the temporal resolution of the VI temporal profiles. These results suggest the suitability of VIIRS data to extend and merge into the MODIS VI record for long-term vegetation dynamics studies.

MODIS↗

DOE OSTI2016

Development of Cloud and Precipitation Property Retrieval Algorithms and Measurement Simulators from ASR Data

What has made the ASR program unique is the amount of information that is available. The suite of recently deployed instruments significantly expands the scope of the program (Mather and Voyles, 2013). The breadth of this information allows us to pose sophisticated process-level questions. Our ASR project, now entering its third year, has been about developing algorithms that use this information in ways that fully exploit the new capacity of the ARM data streams. Using optimal estimation (OE) and Markov Chain Monte Carlo (MCMC) inversion techniques, we have developed methodologies that allow us to use multiple radar frequency Doppler spectra along with lidar and passive constraints where data streams can be added or subtracted efficiently and algorithms can be reformulated for various combinations of hydrometeors by exchanging sets of empirical coefficients. These methodologies have been applied to boundary layer clouds, mixed phase snow cloud systems, and cirrus.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Real-time Social Internet Data to Guide Forecasting Models

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

A framework for collaborative review of candidate events in high data rate streams: The V-FASTR experiment as a case study

“Fast radio transients” are defined here as bright millisecond pulses of radio-frequency energy. These short-duration pulses can be produced by known objects such as pulsars or potentially by more exotic objects such as evaporating black holes. The identification and verification of such an event would be of great scientific value. This is one major goal of the Very Long Baseline Array (VLBA) Fast Transient Experiment (V-FASTR), a software-based detection system installed at the VLBA. V-FASTR uses a “commensal” (piggy-back) approach, analyzing all array data continually during routine VLBA observations and identifying candidate fast transient events. Raw data can be stored from a buffer memory, which enables a comprehensive off-line analysis. This is invaluable for validating the astrophysical origin of any detection. Candidates discovered by the automatic system must be reviewed each day by analysts to identify any promising signals that warrant a more in-depth investigation. To support the timely analysis of fast transient detection candidates by V-FASTR scientists, we have developed a metadata-driven, collaborative candidate review framework. The framework consists of a software pipeline for metadata processing composed of both open source software components and project-specific code written expressly to extract and catalog metadata from the incoming V-FASTR data products, and a web-based data portal that facilitates browsing and inspection of the available metadata for candidate events extracted from the VLBA radio data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2011

An Autonomous System for Grouping Events in a Developing Aftershock Sequence

We describe a prototype detection framework that automatically clusters events in real time from a rapidly unfolding aftershock sequence. We use the fact that many aftershocks are repetitive, producing similar waveforms. By clustering events based on correlation measures of waveform similarity, the number of independent event instances that must be examined in detail by analysts may be reduced. Our system processes array data and acquires waveform templates with a short-term average (STA)/long-term average (LTA) detector operating on a beam directed at the P phases of the aftershock sequence. The templates are used to create correlation-type (subspace) detectors that sweep the subsequent data stream for occurrences of the same waveform pattern. Events are clustered by association with a particular detector. Hundreds of subspace detectors can run in this framework a hundred times faster than in real time. Nonetheless, to check the growth in the number of detectors, the framework pauses periodically and reclusters detections to reduce the number of event groups. These groups define new subspace detectors that replace the older generation of detectors. Because low-magnitude occurrences of a particular signal template may be missed by the STA/LTA detector, we advocate restarting the framework from the beginning of the sequence periodically to reprocess the entire data stream with the existing detectors. We tested the framework on 10 days of data from the Nevada Seismic Array (NVAR) covering the 2003 San Simeon earthquake. One hundred eighty-four automatically generated detectors produced 676 detections resulting in a potential reduction in analyst workload of up to 73%.

58 GEOSCIENCES↗

DOE OSTI2026

WHONDRS 2016 Sediment Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon

This dataset supports a broader synoptic effort to map morphological, hydrological, chemical, and biological conditions across a fifth-order mountain stream network. Samples were generated through a collaborative synoptic sampling effort in 2016. The dataset provides sediment Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) from 60 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Related data were collected as part of the event and were published separately in collaboration with other team members. The data are available at http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1567-2019 (Ward et al., 2019). The hydroshare data package contains processed FTICR-MS data from the samples included in this data package. The data were processed via Formultitude (previously called Formularity; https://github.com/PNNL-Comp-Mass-Spec/Formultitude). However, we have re-processed the data using Core-MS and included it in this data package. Additional related data collected in 2025 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3023310 and http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of sample data; (2) data dictionary; (3) file-level metadata; (4); (5) coordinates; and (6) readme. The sample data subfolder contains 12 Tesla (12T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, or .json.

Biogeochemistry↗

NASA NTRS1977

Double quadriphase modulation/demodulation technique for three-channel communication link

A modulation technique for a three-channel communication link is introduced. The structure of the modulator is such as to form an unbalanced quadriphase signal wherein the high rate data stream is bi-phase modulated on the in-phase carrier component, while the sum of the two lower rate signals is bi-phase modulated on the quadrature component of the same carrier. The sum of the two lower signals is, in turn, formed by modulating with the respective data streams the in-phase and the quadrature components of a square wave subcarrier. At the demodulator, the tracking of the carrier and the subcarrier is performed by two independent Costas loops. The demodulation of the high data rate signal is carried out after establishing the carrier reference signal, while the lower rate signals are demodulated after the subcarrier loop recovers the subcarrier. In this paper, the performance of the two loops is analyzed and the expressions for the tracking errors are derived. Finally, a numerical example pertaining to the Space Shuttle-to-TDRS Ku-band link is presented for illustration.

Alem, W. K.↗

NASA NTRS2008

Visualization Component of Vehicle Health Decision Support System

The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a tool for NASA's flight controllers to monitor the International Space Station and a future Crew Exploration Vehicle.

Jacob, Joseph↗

DOE OSTI2023

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO 2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO 2 data relates to the correction of the soil carbon imbalance.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Live Aircraft Encounter Visualization at FutureFlight Central

Researchers at the National Aeronautics and Space Administration (NASA) have developed an aircraft data streaming capability that can be used to visualize live aircraft in near real-time. During a joint Federal Aviation Administration (FAA)/NASA Airborne Collision Avoidance System flight series, test sorties between unmanned aircraft and manned intruder aircraft were shown in real-time at NASA Ames' FutureFlight Central tower facility as a virtual representation of the encounter. This capability leveraged existing live surveillance, video, and audio data streams distributed through a Live, Virtual, Constructive test environment, then depicted the encounter from the point of view of any aircraft in the system showing the proximity of the other aircraft. For the demonstration, position report data were sent to the ground from on-board sensors on the unmanned aircraft. The point of view can be change dynamically, allowing encounters from all angles to be observed. Visualizing the encounters in real-time provides a safe and effective method for observation of live flight testing and a strong alternative to travel to the remote test range.

Video Streaming↗

NASA NTRS1982

High density bit transition requirements versus the effects on BCH error correcting code

The design to achieve the required bit transition density for the Space Shuttle high rate multiplexes (HRM) data stream of the Space Laboratory Vehicle is reviewed. It contained a recommended circuit approach, specified the pseudo random (PN) sequence to be used and detailed the properties of the sequence. Calculations showing the probability of failing to meet the required transition density were included. A computer simulation of the data stream and PN cover sequence was provided. All worst case situations were simulated and the bit transition density exceeded that required. The Preliminary Design Review and the critical Design Review are documented. The Cover Sequence Generator (CSG) Encoder/Decoder design was constructed and demonstrated. The demonstrations were successful. All HRM and HRDM units incorporate the CSG encoder or CSG decoder as appropriate.

Ingels, F. M.↗

NASA NTRS2003

LISA Optics Model: Early Results

The Laser Interferometer Space Antenna (LISA) optics model is used to generate a synthetic data stream in the absence of gravitational waves. The simulation has the spacecraft in moving in their respective Keplerian orbits. The pointing of the spacecraft and station keeping about the proof masses is accomplished using a control scheme, which minimizes the disturbance on the proof masses in the sensitive direction. The resulting data stream gives an indication of the magnitude of instrumental noise due to pointing jitter and motions of the spacecraft with respect to the proof masses. Computational details are presented and the results discussed.

Waluschka, Eugene↗

NASA NTRS2013

Detection of Moving Targets Using Soliton Resonance Effect

The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

Kulikov, Igor K.↗