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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Four-dimensional guidance algorithms for aircraft in an air traffic control environment

Theoretical development and computer implementation of three guidance algorithms are presented. From a small set of input parameters the algorithms generate the ground track, altitude profile, and speed profile required to implement an experimental 4-D guidance system. Given a sequence of waypoints that define a nominal flight path, the first algorithm generates a realistic, flyable ground track consisting of a sequence of straight line segments and circular arcs. Each circular turn is constrained by the minimum turning radius of the aircraft. The ground track and the specified waypoint altitudes are used as inputs to the second algorithm which generates the altitude profile. The altitude profile consists of piecewise constant flight path angle segments, each segment lying within specified upper and lower bounds. The third algorithm generates a feasible speed profile subject to constraints on the rate of change in speed, permissible speed ranges, and effects of wind. Flight path parameters are then combined into a chronological sequence to form the 4-D guidance vectors. These vectors can be used to drive the autopilot/autothrottle of the aircraft so that a 4-D flight path could be tracked completely automatically; or these vectors may be used to drive the flight director and other cockpit displays, thereby enabling the pilot to track a 4-D flight path manually.

Pecsvaradi, T.↗
NASA NTRS1987

Optoelectronic Proximity Sensor Finds Edges

Seams tracked for automatic control of welding. Optoelectronic system based on relatively simple array of optical proximity sensors locates edge of plate. Used to control automatic production machinery. System follows curved seams as well as straight ones, and neither special control programming nor precise initial positioning workpiece necessary for accurate tracking of seam.

Bejczy, Antal K.↗
NASA NTRS2007

Hierarchically Structured Non-Intrusive Sign Language Recognition

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Zieren, Jorg↗
NASA NTRS1988

High-dynamic GPS tracking

The results of comparing four different frequency estimation schemes in the presence of high dynamics and low carrier-to-noise ratios are given. The comparison is based on measured data from a hardware demonstration. The tested algorithms include a digital phase-locked loop, a cross-product automatic frequency tracking loop, and extended Kalman filter, and finally, a fast Fourier transformation-aided cross-product frequency tracking loop. The tracking algorithms are compared on their frequency error performance and their ability to maintain lock during severe maneuvers at various carrier-to-noise ratios. The measured results are shown to agree with simulation results carried out and reported previously.

Hinedi, S.↗
NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗
NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.

David M. Giles↗
NASA NTRS1998

Automated Track Recognition and Event Reconstruction in Nuclear Emulsion

The major advantages of nuclear emulsion for detecting charged particles are its submicron position resolution and sensitivity to minimum ionizing particles. These must be balanced, however, against the difficult manual microscope measurement by skilled observers required for the analysis. We have developed an automated system to acquire and analyze the microscope images from emulsion chambers. Each emulsion plate is analyzed independently, allowing coincidence techniques to be used in order to reject back- ground and estimate error rates. The system has been used to analyze a sample of high-multiplicity Pb-Pb interactions (charged particle multiplicities approx. 1100) produced by the 158 GeV/c per nucleon Pb-208 beam at CERN. Automatically reconstructed track lists agree with our best manual measurements to 3%. We describe the image analysis and track reconstruction techniques, and discuss the measurement and reconstruction uncertainties.

Deines-Jones, P.↗
NASA NTRS2010

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

ASV (AUTONOMOUS SEA SURFACE VEHICLE)↗
NASA NTRS1975

Miniature sonar fish tag

Self-powered sonar device may be implanted in body of fish. It transmits signal that can be detected with portable tracking gear or by automatic detection-and-tracking system. Operating life of over 4000 hours may be expected. Device itself may be used almost indefinitely.

Lovelady, R. W.↗
NASA NTRS1982

Oculometer focus and mirror control

An automatic focusing system designed around an ultrasonic range measurement is described. Besides maintaining the focus, subject distance is a by-product which could lighten the NOVA computational effort. An automatic head tracking unit is also discussed. It is intended to reduce the search time required when track is lost. An X-Y ultrasonic measurement is also made in this design to control the deflection mirrors.

Guy, W. J.↗
NASA NTRS1982

Space Shuttle Orbiter onboard rendezvous navigation

Much of the work that the Space Shuttle will perform requires a capability to rendezvous with other orbiting objects. The formulation and design philosophy behind the Space Shuttle Orbiter rendezvous navigation system are the subjects of this paper. The current rendezvous navigation design incorporates a Kalman filter to estimate the relative position and velocity. The filter is augmented with state elements for the estimation of colored measurement noise and acceleration modeling errors. Several measurement types are available to the filter: a manual optical sighting device, an automatic optical tracking instrument, and a rendezvous radar which provides range and range rate measurements as well as the line of sight direction. The filter also includes a technique for detecting highly improbable measurements and excluding them from Kalman processing.

Little, M. J.↗
NASA NTRS1987

Challenges in modeling the X-29 flight test performance

Presented are methods, instrumentation, and difficulties associated with drag measurement of the X-29A aircraft. The initial performance objective of the X-29A program emphasized drag polar shapes rather than absolute drag levels. Priorities during the flight envelope expansion restricted the evaluation of aircraft performance. Changes in aircraft configuration, uncertainties in angle-of-attack calibration, and limitations in instrumentation complicated the analysis. Limited engine instrumentation with uncertainties in overall in-flight thrust accuracy made it difficult to obtain reliable values of coefficient of parasite drag. The aircraft was incapable of tracking the automatic camber control trim schedule for optimum wing flaperon deflection during typical dynamic performance maneuvers; this has also complicated the drag polar shape modeling. The X-29A was far enough off the schedule that the developed trim drag correction procedure has proven inadequate. However, good drag polar shapes have been developed throughout the flight envelope. Preliminary flight results have compared well with wind tunnel predictions. A more comprehensive analysis must be done to complete performance models. The detailed flight performance program with a calibrated engine will benefit from the experience gained during this preliminary performance phase.

John W Hicks↗
NASA NTRS1987

Challenges in modeling the X-29A flight test performance

The paper presents the methods, instrumentation, and difficulties associated with drag measurement of the X-29A aircraft. The initial performance objective of the X-29A program emphasized drag polar shapes rather than absolute drag levels. Priorities during the flight envelope expansion restricted the evaluation of aircraft performance. Changes in aircraft configuration, uncertainties in angle-of-attack calibration, and limitations in instrumentation complicated the analysis. Limited engine instrumentation with uncertainties in overall in-flight thrust accuracy made it difficult to obtain reliable values of coefficient of parasite drag. The aircraft was incapable of tracking the automatic camber control trim schedule for optimum wing flaperon deflection during typical dynamic performance maneuvers; this has also complicated the drag polar shape modeling. The X-29A was far enough off the schedule that the developed trim drag correction procedure has proven inadequate. Despite these obstacles, good drag polar shapes have been developed throughout the flight envelope. Preliminary flight results have compared well with wind tunnel predictions. A more comprehensive analysis must be done to complete the performance models. The detailed flight performance program with a calibrated engine will benefit from the experience gained during this preliminary performance phase.

Hicks, John W.↗
NASA NTRS1988

Infrared measurements in the spring 1987 ozone hole

Solar spectra were recorded from Arrival Heights (McMurdo), Antartica, with a FTIR system during the austral spring of 1987. Spectra were recorded on 22 days from September 13 through October 28. The instrument was setup with 2 detectors for simultaneous operation in 2 wavelength regions. Several stratospheric gases have measurable absorptions in these regions including HCl, HNO3, O3, ClONO2, and NO2. The system is equipped with an automatic solar tracking system and records data on tape cartridges. A portable personal computer allows Fourier transforming and initial processing of some of the data. The HNO3 gas column amount shows large variations, but no apparent correlation with stratospheric temperature. The HCl column shows a steady increase from 0.9 x 10 to the 15th power molecules/sq.cm. on September 13 to 1.5 x 10 to the 15th power on October 6. McMurdo moved out of the polar vortex for a few days, and the HCl column jumped to 2.9 x 10 to the 15th power by October 11. Although McMurdo moved back under the vortex, the HCl continued to increase, reaching 3.4 x 10 to the 15th power at the end of the period.

Murcray, F. J.↗
NASA NTRS1990

Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given.

Zwally, H. Jay↗