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

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

An automatic editing algorithm for GPS data

An algorithm has been developed to edit automatically Global Positioning System data such that outlier deletion, cycle slip identification, and correction are independent of clock instability, selective availability, receiver-satellite kinematics, and tropospheric conditions. This algorithm, called TurboEdit, operates on undifferenced, dual frequency carrier phase data, and requires the use of P code pseudorange data and a smoothly varying ionospheric electron content. TurboEdit was tested on the large data set from the CASA Uno experiment, which contained over 2500 cycle slips.Analyst intervention was required on 1 percent of the station-satellite passes, almost all of these problems being due to difficulties in extrapolating variations in the ionospheric delay. The algorithm is presently being adapted for real time data editing in the Rogue receiver for continuous monitoring applications.

Blewitt, Geoffrey↗
NASA NTRS2004

Karhunen-Loeve Analysis of SCIGN GPS Data

During the final year of this project, we made substantial progress on the proposed work. Specifically, we have continued the horizontal and vertical Karhunen-Loeve (KL) analysis of SCIGN data and implemented the study of a number of particular modes. In particular, we studied the spatial and temporal interactions of these modes in an effort to better understand and model the source of each signal.

Rundle, John B.↗
NASA NTRS1993

Global Positions and Velocities from One Year of GPS Data

A generalized no-fiducial approach has been developed to obtain global positions and velocities without fixing any individual position or velocity components. The method used can be applied to any global geodetic technique and proceeds in three general steps. First, daily solutions derived with weak constraints are combined to yield one global set of positions and velocities. Second, 14 minimal constraints are applied to remove uncertainties due to the loosely defined reference frame. Third, transformation from one reference frame to another is accomplished with a 14 parameter transformation. One year of daily FLINN solutions, each made with data from about 40 sites, have been combined to yield our best fit global model...

Heflin, M. B.↗
DOE OSTI2026

Scalable GPS Data Logging To Support Advanced Fleet Analysis

This highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. National Laboratory of the Rockies researchers developed and demonstrated low-cost, open-source Arduino data loggers with 3D-printed cases that are compatible with global navigational systems and built with components available ubiquitously worldwide, enabling cost-effective collection and analysis of fleet operational data. Validated on an overseas transit bus fleet, NLR analysis showed that, with sufficient charging opportunities, 90% of observed duty cycles could be accomplished by electric buses with no modifications to operations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Driver Identification Dataset

The ORNL Driver Identification Dataset was created to collect and analyze driving behavior data from 50 different drivers. Each driver operated a 2014 Kenworth T270 Class 6 truck around Fort Collins, Colorado while various data sources recorded their driving behavior and vehicle performance. The dataset includes CANbus (Controller Area Network) data, GPS data, inertial measurement data, and biometric data from a heart rate monitor. A cyberattack was executed during each drive, which caused multiple dashboard warning lights to illuminate and set the tachometer and speedometer to zero, regardless of actual speed. The attack was stopped either after one minute or if the driver pulled over. By downloading the dataset, you agree to the following: 1) I will not use or disclose the data for any purpose other than Research as that term is defined in 10 CFR 745.102. 2) I will not, under any circumstances, request or accept private or linking identifiers for the data used. 3) I will not attempt to determine the identity of the individuals associated with the data. 4) I will use appropriate safeguards to prevent the use or disclose of the data for any purpose other than Research.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1999

Calibrating Spaceborne Microwave Radiometers with GPS

Data from terrestrial GPS receivers are being used in growing numbers of applications requiring precise tropospheric sensing. One emerging application is the calibration of water vapor measurements from spaceborne microwave radiometers.

GPS Water Vapor Radiometers↗
DOE OSTI2023

Outer Radiation Belt Flux and Phase Space Density Response to Sheath Regions: Van Allen Probes and GPS Observations

Turbulent and compressed sheath regions preceding interplanetary coronal mass ejections strongly impact electron dynamics in the outer radiation belt. Changes in electron flux can occur on timescales of tens of minutes, which are unlikely to be captured by a two-satellite mission. The recently released Global Positioning System (GPS) data set generally has shorter revisit times (at L ~ 4–8) owing to the large number of satellites in the constellation equipped with energetic particle detectors. Investigating electron fluxes at energies from 140 keV to 4 MeV and sheaths observed in 2012–2018, we show that the flux response to sheaths on a timescale of 6 hr, previously reported from Van Allen Probes (RBSP) data, is reproduced by GPS measurements. Furthermore, GPS data enables derivation of the response on a timescale of 30 min, which further confirms that the energy and L-shell dependent changes in electron flux are associated with the impact of the sheath. Sheath-driven loss is underestimated over longer timescales as the electrons recover during the ejecta. We additionally show the response of electron phase space density (PSD), which is a key quantity in identifying non-adiabatic loss from the system and electron energization through wave-particle interactions. The PSD response is calculated from both RBSP and GPS data for the 6 hr timescale, as well as from GPS data for the 30 min timescale. The response is divided based on the geoeffectiveness of the sheaths revealing that electrons are effectively accelerated only during geoeffective sheaths, while loss commonly occurs during all sheaths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Medium- and Heavy-Duty Truck Duty Cycles

This dataset provides second-by-second duty cycle data for Class 6 and Class 8 diesel trucks in Texas, including key vehicle metrics, engine-related data, and GPS data (excluding GPS latitude and longitude to ensure confidentiality). The data were collected via tablets installed on the trucks and organized into daily datasets, each associated with a unique vehicle ID and date. There are 12 daily datasets for Class 6 diesel trucks (three unique vehicle IDs) and 43 daily datasets for Class 8 diesel trucks (six unique vehicle IDs). The units associated with each column are included in the name. The engine performance data include columns such as engine speed, engine percent torque, and engine fuel rate. Road grade (%/100) was estimated using the GPS altitude and wheel-based vehicle speed, which is used as an input for FASTSim. Cumulative distance was also calculated using the wheel-based vehicle speed. Additional columns include: - Engine Speed (RPM): Removed inaccurate readings and used to calculate angular velocity (radians/second). - Torque (N·m): Calculated using engine percent torque, nominal friction percent torque, and engine reference torque values (those columns were removed from dataset), then normalized to express as torque (%). - Flywheel Power (%): Calculated using the angular velocity and torque (in kW), then normalized as a percentage of the maximum value. - Engine Fuel Rate (%) and Torque (%): Both metrics were normalized by dividing by their respective maximum values within each dataset to express them as percentages. The datasets were analyzed to assess the energy impact of various driving behaviors, simulate energy efficiency, and recommend optimal routes for diesel trucks using NLR’s tool called RouteE. For driver coaching, factors like speed and acceleration limits were considered, and idle periods were reduced (assuming the engine was off during idling) to adjust each drive cycle. These adjusted drive cycles were then simulated in FASTSim to evaluate their effect on fleet energy consumption and estimate potential energy savings. The original cycles are available for download on this page ![image](CoVaR_Image_for_Data_Page_Kenworth_Truck.jpg)

1Hz↗
NASA NTRS1986

Total ionospheric electron content calibration using SERIES GPS satellite data

The current status of the Deep Space Network advanced systems research into ionospheric calibration techniques, based on Global Positioning System (GPS) data is described. A GPS-based calibration system is planned to replace the currently used Faraday rotation method by 1989. The SERIES receiver system determines the differential group delay of signals transmitted at two different carrier frequencies. This differential delay includes an ionospheric component and a GPS transmitter offset. The transmitter offsets are different for each GPS satellite. Tests were conducted to assess the effect of the offsets on the ionospheric calibration accuracy. From the obtained data, the total electron content and GPS transmitter offsets are calculated by a least squares estimation method employing a local model of total ionospheric electron content. The end product is an estimation of the total ionospheric content for an arbitrary line-of-sight direction. For the presented polynomial fitting technique, the systematic error due to mismodeling is estimated to be approximately 6 x 10 to the 16th power el/sq m, while the formal error is approximately 2 x 10 to the 16th power el/sq m. The final goal is an error of 3 x 10 to the 16th power el/sq m (approximately 0.7 ns at 2.3 GHz).

Lanyi, G.↗
NASA NTRS2005

Processing GPS Occultation Data To Characterize Atmosphere

GOAS [Global Positioning System (GPS) Occultation Analysis System] is a computer program that accepts signal-occultation data from GPS receivers aboard low-Earth-orbiting satellites and processes the data to characterize the terrestrial atmosphere and, in somewhat less comprehensive fashion, the ionosphere. GOAS is very robust and can be run in an unattended semi-operational processing mode. It features sophisticated retrieval algorithms that utilize the amplitudes and phases of the GPS signals. It incorporates a module that, using an assumed atmospheric refractivity profile, simulates the effects of the retrieval processing system, including the GPS receiver. GOAS utilizes the GIPSY software for precise determination of orbits as needed for calibration. The GOAS output for the Earth s troposphere and mid-to-lower stratosphere consists of high-resolution (<1 km) profiles of density, temperature, pressure, atmospheric refractivity, bending angles of signals, and water-vapor content versus altitude from the Earth s surface to an altitude of 30 km. The GOAS output for the ionosphere consists of electron-density profiles from an altitude of about 50 km to the altitude of a satellite, plus parameters related to the rapidly varying structure of the electron density, particularly in the E layer of the ionosphere.

Hajj, George↗