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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Determination of Ceres Physical Parameters Using Radiometric and Optical Data

The Dawn spacecraft was launched on September 27th, 2007. Its mission is to rendezvous with and observe the two largest bodies in the main asteroid belt, Vesta and Ceres. It has completed over a year’s worth of direct observations of Vesta from early 2011 through late 2012. In the spring of 2015, the Dawn spacecraft entered orbit around the asteroid Ceres for the start of what is expected to be more than a year of science operations. The science data collected from this encounter consist of infrared (IR) images and spectra, visible images through a number of color filters, gamma ray detections and measurements of the Ceres gravity field. These data will be collected during several science phases: an Approach phase (1500000-4860 km from Ceres), a Survey orbit (4860 km radius), a High Altitude Mapping Orbit (HAMO) (1940 km radius) and a Low Altitude Mapping Orbit (LAMO) (855 km radius). The Approach phase included three Rotational Characterization (RC) opportunities. Designing each science orbit and successfully transferring into that orbit requires a sufficiently accurate estimate of Ceres physical parameters (body fixed frame, GM and harmonics). This paper focuses on work performed to estimate Ceres physical parameters using Deep Space Network (DSN) radiometric tracking data and optical measurements derived from science camera imagery. This paper describes planning for the data acquisition, as well as processing techniques and methodology. The trajectories predicted by the gravity field estimations are also compared with the actual as-flown trajectories. Observations of the gravity at high altitudes are found to be sufficient to design precision orbits at lower altitudes. Follow-up analysis after successfully reaching LAMO is included, as is a discussion of lessons learned.

Kennedy, Brian M.↗
NASA NTRS2022

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗
NASA NTRS1972

Cathodochromic cathode ray tube: An operations manual

A cathodochromic (CC) storage and display system capable of storing full TV resolution images has been built. The images are derived from standard TV signals: composite video, composite sync, composite blanking, horizontal drive, and vertical drive. Image storage takes place in the CC CRT; the fixed image is written for several TV frames for the contrast to be usable. Once stored on the CC CRT, the image can be read out in one of three modes: with the eye, a 35-mm camera, or a TV camera. Incoming information may also be stored in a storage tube similar to the CC CRT but with a phosphor layer behind the CC layer. By exciting the phosphor layer with a standard raster scan it is possible to read out an image stored in the CC layer in one of three modes: direct viewing, photography, or flying-spot readout using a photomultiplier.

Heyman, P. M.↗
NASA NTRS1998

Photometric Study of Uranian Satellites

The best summary of my work at NASA is expressed in the following abstract, submitted the Division for Planetary Science of the American Astronomical Society and to be presented at the annual meeting in Madison in October. We report photometric measurements of Uranian satellites Miranda, Ariel, Umbriel and Titania (10.4 Aug. 1995), and Neptune's satellite Triton (21.2 Sept. 1995) with the infrared camera (IRCAM) and standard J (1.13 - 1.42 microns), H (1.53 - 1.81 microns), and K (2.00 - 2.41 microns) filters at the 3.8-m UKIRT telescope on Mauna Kea. The individual images frames are 256 x 256 pixels with a platescale of .286 arcsec/pixel, resulting in a 1.22 arc min field of view. This summer brought the IR photometry measurements nearly to a close. As indicated by the abstract above, I will present this work at the annual DPS meeting in October. In anticipation of the opening of the new Carl Sagan Laboratory for Cosmochemisty, of which I will be a participating member, I also devoted a considerable fraction of the summer to learning the biochemistry which underlies the experiments to be conducted. To put the end of the summary close to the beginning, it was a most productive summer.

Kesten, Philip R.↗
DOE OSTI2022

High speed ultraviolet digital image correlation (UV-DIC) for dynamic strains at extreme temperatures

Digital Image Correlation (DIC) is a camera-based method of measuring full-field displacements and strains from the surface of a deforming object. It can be applied at any length scale (determined by the lenses) and any time scale (determined by the camera), and because it is non-contacting, it can also be used at temperatures much higher than can be withstood by bonded strain gauges. At extreme temperatures, materials emit light in the form of blackbody radiation, which can saturate the camera sensor. It has previously been shown that the emitted light can be effectively screened by using ultraviolet (UV) cameras, lenses, and filters; however, commercially available UV cameras are relatively slow, which limits the speed of combined UV-DIC measurements. In this study, a UV intensifier was paired with a high-speed camera, and its ability to perform UV-DIC at high temperature and high speed was investigated. The system was compared over three different experiments: (A) a quasi-static thermal expansion test at high temperature, (B) a vibration test at room temperature, and (C) the same vibration test repeated at high temperature. The system successfully performed DIC up to at least 1600 °C at frame rates of 5000 fps, which is more than 100 times faster than other examples of UV-DIC in the literature. In all cases, measurements made using the UV intensifier were much noisier than those made without the intensifier, but the intensifier enabled measurements at temperatures well above those which an unfiltered high-speed camera otherwise saturates.

47 OTHER INSTRUMENTATION↗
NASA NTRS1979

Sealed position sensitive hard X-ray detector having large drift region for all sky camera with high angular resolution

A sealed position sensitive proportional counter filled with two atmospheres of 95% xenon and 5% methane, and containing a drift region of 24 atm cm, has operated in a stable manner for many months. The detector contains G-10 frames to support the anode and cathode wires. The detector was sealed successfully by a combination of vacuum baking the G-10 frames at 150 C for two weeks followed by assembly into the detector in an environment of dry nitrogen, and the use of passive internal getters. The counter is intended for use with a circumferential cylindrical collimator. Together they provide a very broad field of view detection system with the ability to locate cosmic hard X-ray and soft gamma ray sources to an angular precision of a minute of arc. A set of instruments based on this principle have been proposed for satellites to detect and precisely locate cosmic gamma ray bursts.

Gorenstein, P.↗
NASA NTRS1976

Intensified charge coupled devices for ultra low light level imaging

Development of a sensor incorporating a CCD and photocathode for operation in the electron bombarded mode in both a magnetic and an electrostatic focussed, gated configuration is described. Initial format size is 100 x 160 pixels with eventual growth to 400 x 400 pixels. The sensor is part of a digital camera system which includes the low level video conditioning electronics, a camera controller, a high speed buffer memory, and digital recording and display electronics. The memory uses CMOS/SOS and has a capacity of 1.6 Mbits with operating rates of 48 Mbits/sec. Individual frames are co-added to provide wide dynamic range and photometric precision better than 1%. A 4-bit video quantization is used to increase the photon counting detection rate before coincidence losses become serious.

Sobieski, S.↗
NASA NTRS1999

Camera-on-a-Chip

Jet Propulsion Laboratory's research on a second generation, solid-state image sensor technology has resulted in the Complementary Metal- Oxide Semiconductor Active Pixel Sensor (CMOS), establishing an alternative to the Charged Coupled Device (CCD). Photobit Corporation, the leading supplier of CMOS image sensors, has commercialized two products of their own based on this technology: the PB-100 and PB-300. These devices are cameras on a chip, combining all camera functions. CMOS "active-pixel" digital image sensors offer several advantages over CCDs, a technology used in video and still-camera applications for 30 years. The CMOS sensors draw less energy, they use the same manufacturing platform as most microprocessors and memory chips, and they allow on-chip programming of frame size, exposure, and other parameters.

Source record↗
NASA NTRSDate not supplied

VTXO: The Virtual Telescope for X-ray Observations

The Virtual Telescope for X-ray Observations (VTXO) will use lightweight Phase Frensel Lenses (PFLs) in a virtual X-ray telescope with⇠1 km focal length and with⇠50 milli-arc second angular resolution. VTXO is formed by using precision formation flying of two SmallSats: a smaller OpticsSat that houses the PFLs and navigation beacons while a larger DetectorSat contains an X-ray camera, a precision start tracker, and the propulsion for the formation flying. The baseline flight dynamics uses a highly elliptical super synchronous orbit allow the formation to hold in an inertial frame around the 90,000 km apogee for 10 hours of the 32.5 hour orbit with nearly a year mission lifetime. VTXO’s fine angular resolution enables measuring the environments close to the central engines of bright compact X-ray sources. This X-ray imaging capability allows for the study of the effects of dust scattering near to the central objects such as Cyg X-3 and GX 5-1, for the search for jet structure near to the compact object in X-ray novae such as Cyg X-1 and GRS 1915+105, and for the search for structure in the termination shock of in the Crab pulsar wind nebula. The VTXO SmallSat and instrument designs, mission parameters, and science performance are described. VTXO development was supported as one of the selected 2018 NASA Astrophysics SmallSat Study (AS3) missions

John F Krizmanic↗
DOE OSTI2023

Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement

In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.

47 OTHER INSTRUMENTATION↗
NASA NTRS1986

Solid state imagers and their applications; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

Topics treated include the use of semiconductor imagers in high energy particle physics, an X-ray image sensor based on an optical TDI-CCD imager, and an electron-sensitive CCD readout array for a circular-scan streak tube. Papers are presented on the pan-imager, high resolution linear arrays, the reduction of reflection losses in solid-state image sensors, a high resolution CCD imager module with swing operation, large area CCD image sensors for scientific applications, and new readout techniques for frame transfer CCDs. Consideration is given to advanced optoelectronical sensors for autonomous rendezvous/docking and proximity operations in space, the testing and characterization of CCDs for the Rosat star sensors, an advanced radial camera for the Hubble Space Telescope, and scanning or staring infrared imagers.

Declerck, Gilbert J.↗
NASA NTRS1996

Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

Kasturi, Rangachar↗
NASA NTRS2010

Daytime Water Detection Based on Color Variation

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.

reflection coefficient↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRS2000

Leonid Storm Flux Analysis From One Leonid MAC Video AL50R

A detailed meteor flux analysis is presented of a seventeen-minute portion of one videotape, collected on November 18, 1999, during the Leonid Multi-instrument Aircraft Campaign. The data was recorded around the peak of the Leonid meteor storm using an intensified CCD camera pointed towards the low southern horizon. Positions of meteors on the sky were measured. These measured meteor distributions were compared to a Monte Carlo simulation, which is a new approach to parameter estimation for mass ratio and flux. Comparison of simulated flux versus observed flux levels, seen between 1:50:00 and 2:06:41 UT, indicate a magnitude population index of r = 1.8 +/- 0.1 and mass ratio of s = 1.64 +/- 0.06. The average spatial density of the material contributing to the Leonid storm peak is measured at 0.82 +/- 0.19 particles per square kilometer per hour for particles of at least absolute visual magnitude +6.5. Clustering analysis of the arrival times of Leonids impacting the earth's atmosphere over the total observing interval shows no enhancement or clumping down to time scales of the video frame rate. This indicates a uniformly random temporal distribution of particles in the stream encountered during the 1999 epoch. Based on the observed distribution of meteors on the sky and the model distribution, recommendations am made for the optimal pointing directions for video camera meteor counts during future ground and airborne missions.

Gural, Peter S.↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗