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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 NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRS2006

Development of a Thermo-Electric Cooler Simulation Routine for the Wide Field Camera 3 Thermal Model

A SINDA subroutine has been developed to predict the power generated by a Thermo-Electric Cooler (TEC). A TEC can be described analytically by relations between four parameters: cold side temperature, hot side temperature, parasitic heat load, and electrical power. The subroutine requires the user to input the hot side and cold side temperatures, the corresponding parasitic heat load, and coefficients describing the vendor performance curves. The subroutine then utilizes an iterative solution scheme and vendor TEC performance curves for specific hardware to determine the current (and consequently the TEC power) that satisfies these requirements. This paper provides an in-depth discussion of the algorithm employed in the subroutine, implementation of the subroutine in the HST Wide Field Camera 3 thermal model, and the evaluation of the subroutine performance against actual test/correlation data.

Peabody, Hume↗
NASA NTRS2008

Measuring Positions of Objects using Two or More Cameras

An improved method of computing positions of objects from digitized images acquired by two or more cameras (see figure) has been developed for use in tracking debris shed by a spacecraft during and shortly after launch. The method is also readily adaptable to such applications as (1) tracking moving and possibly interacting objects in other settings in order to determine causes of accidents and (2) measuring positions of stationary objects, as in surveying. Images acquired by cameras fixed to the ground and/or cameras mounted on tracking telescopes can be used in this method. In this method, processing of image data starts with creation of detailed computer- aided design (CAD) models of the objects to be tracked. By rotating, translating, resizing, and overlaying the models with digitized camera images, parameters that characterize the position and orientation of the camera can be determined. The final position error depends on how well the centroids of the objects in the images are measured; how accurately the centroids are interpolated for synchronization of cameras; and how effectively matches are made to determine rotation, scaling, and translation parameters. The method involves use of the perspective camera model (also denoted the point camera model), which is one of several mathematical models developed over the years to represent the relationships between external coordinates of objects and the coordinates of the objects as they appear on the image plane in a camera. The method also involves extensive use of the affine camera model, in which the distance from the camera to an object (or to a small feature on an object) is assumed to be much greater than the size of the object (or feature), resulting in a truly two-dimensional image. The affine camera model does not require advance knowledge of the positions and orientations of the cameras. This is because ultimately, positions and orientations of the cameras and of all objects are computed in a coordinate system attached to one object as defined in its CAD model.

Klinko, Steve↗
NASA NTRS1991

Analysis of a multiple reception model for processing images from the solid-state imaging camera

A detection model to identify the presence of Galileo optical communications from an Earth-based Transmitter (GOPEX) signal by processing multiple signal receptions extracted from the camera images is described. The model decomposes a multi-signal reception camera image into a set of images so that the location of the pixel being illuminated is known a priori and the laser can illuminate only one pixel at each reception instance. Numerical results show that if effects on the pointing error due to atmospheric refraction can be controlled to between 20 to 30 microrad, the beam divergence of the GOPEX laser should be adjusted to be between 30 to 40 microrad when the spacecraft is 30 million km away from Earth. Furthermore, increasing beyond 5 the number of receptions for processing will not produce a significant detection probability advantage.

Yan, T.-Y.↗
NASA NTRS1976

Development of a drive system for a sequential space camera

Breadboard models of single and dual motor drives for the shutter, claw and magazine of a space camera system were designed and tested. The single motor technique utilizes a single electronically commutated motor to drive the claw and shutter without resorting to a solenoid actuated clutch for pulse operation. Shutter speed is established by a combination of the cinemode speed and the opening of the conventional DAC two piece shutter. Pulse mode operation is obtained by applying power at a fixed clock rate and removing power at an appropriate point in the mechanical cycle such that the motor comes to rest by system friction. The dual motor approach utilizes a stepper motor to drive the shutter and an electronically commutated dc motor to drive the claw and magazine functions. The motors are synchronized electronically.

Sharpsteen, J. T.↗
NASA NTRS1971

A math model for high velocity sensoring with a focal plane shuttered camera.

A new mathematical model is presented which describes the image produced by a focal plane shutter-equipped camera. The model is based upon the well-known collinearity condition equations and incorporates both the translational and rotational motion of the camera during the exposure interval. The first differentials of the model with respect to exposure interval, delta t, yield the general matrix expressions for image velocities which may be simplified to known cases. The exposure interval, delta t, may be replaced under certain circumstances with a function incorporating blind velocity and image position if desired. The model is tested using simulated Lunar Orbiter data and found to be computationally stable as well as providing excellent results, provided that some external information is available on the velocity parameters.

Morgan, P.↗
NASA NTRS1975

Satellite thermal modeling using the illuminographic camera

The application is discussed of illuminographic camera techniques to the measurement of radiative form factors for satellite modeling applications. The equation for the illuminographic mirror is derived, and the advantages of the method are discussed. Proximity error for the illuminographic mirror is defined, and estimates of this error as a function of the scale factor of the model are given, together with a method for halving this error. Designs for illuminographic mirrors are presented: the first provides a further threefold reduction in proximity error; the second permits the estimation of thermal radiation transfer coefficients to interior regions of otherwise inaccessible volumes. Finally, reflex Polaroid camera techniques appropriate to the relatively small size of the illuminographic mirror are described.

Wiesner, S. J.↗
DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS2011

The Dawn Gravity Investigation at Vesta and Ceres

The objective of the Dawn gravity investigation is to use high precision X-band Doppler tracking and landmark tracking from optical images to measure the gravity fields of Vesta and Ceres to a half-wavelength surface resolution better than 90-km and 300-km, respectively. Depending on the Doppler tracking assumptions, the gravity field will be determined to somewhere between harmonic degrees 15 and 25 for Vesta and about degree 10 for Ceres. The gravity fields together with shape models determined from Dawn's framing camera constrain models of the interior from the core to the crust. The gravity field is determined jointly with the spin pole location. The second degree harmonics together with assumptions on obliquity or hydrostatic equilibrium may determine the moments of inertia.

Vesta↗
NASA NTRS1979

Diagnosis of separated flow regions on wind-tunnel models using an infrared camera

A novel technique utilizing an infrared-sensitive imaging camera has been used to determine the location of three-dimensional (3-D) separated flow regions on an inclined 5 deg semiangle fiberglass cone. The results illustrate that there is a change in the contrast of the infrared (IR) signature on the cone surface corresponding with the location where the skin-friction lines merge toward lines of 3-D separation. This technique should offer a convenient means for locating separated flow regions on wind-tunnel models while obtaining simultaneous force, skin-friction, and pressure data.

Bandettini, A.↗
NASA NTRS1961

Investigations of the Deterioration of 22 Refractory Materials in a Mach Number 2 Jet at a Stagnation Temperature of 3,800 F

A limited investigation of the deterioration characteristics of 22 refractory materials was conducted by exposing them to a stagnation temperature of 3,800 F in a Mach number 2 ceramic-heated jet at the Langley Research Center. The materials tested were six materials whose major constituent was silicon carbide, five cermets whose major constituent was titanium carbide, six materials whose major constituents were metal borides, four cermets containing alumina, and one silicon nitride model. Tests consisted of obtaining weight change and appearance changes for 1/2-inch-diameter hemispherical-nose cylindrical models exposed to the air jet for 30 seconds at a time for a total of four runs or 2 minutes exposure. Curves of weight changes plotted against the number of 30-second tests in the jet were obtained. Estimates of average surface temperature near the stagnation point of the model were obtained by use of a special temperature-measuring camera. The models were examined before and after the completion of the tests for possible changes in microstructure; no significant changes were found. The data obtained were analyzed with the view that the oxidation characteristics of the materials were the main factor in deterioration of the materials under the conditions of the tests. It was concluded that only those materials which changed in weight the least could be recommended for further extensive application-oriented evaluations. The following materials fell in this category: silicon carbide - silicon, chromium - 28-percent alumina cermet, titanium boride - 5-percent boron carbide. The remainder of the materials tested had oxidation characteristics which appeared to be too severely limiting of their general applications to flight vehicles.

Lewis, B. W.↗
NASA NTRS2020

A ROS-based Simulator for Testing the Enhanced Autonomous Navigation of the Mars 2020 Rover

In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover’s stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides roverterrain settling, realistic slip modelling, and camera rendering capability based on the rover’s NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statisticallymeaningful way. This paper provides an overview of the ROSbased simulator used for testing the M2020 ENav algorithms.

Toupet, Olivier↗
NASA NTRSDate not supplied

Velocity and Temperature Measurements in High-speed Flows with Naturally Present Dust Particles Using Rayleigh and Mie Scattering

Dust particles and occasional moisture condensations are unavoidable reality of all wind tunnels. On the path to pursue a goal of velocity and temperature measurements in high-speed wind tunnels we have created a tabletop, spectrally resolved, Rayleigh-Mie scattering setup around a small jet fed by ambient and air with different particle concentration to determine the accuracy of the technique. The other reality of a wind tunnel setup is the spurious reflection and scattering of the incident laser beam by solid surfaces (flare light), which contaminates the Rayleigh-Mie scattered light. This is simulated by backgrounds with different reflectivity towards the collection optics. Light from a CW laser is delivered via an optical fiber and the scattered light from a point on the laser path is spectrally resolved using a stabilized Fabry-Perot interferometer, followed by imaging on an EMCCD camera. A model of the combined background glare, Mie scattering, and the Rayleigh spectrum was fitted to the camera image using maximum likelihood estimation. It was observed that the present modeling approach can extract velocity and temperature with reasonable accuracy when the intensity of the Mie scattered light is less than or comparable to that of the Rayleigh scattered light; beyond that error in velocity measurement remains reasonable ±12m/s but the temperature measurement becomes progressively more inaccurate. Increasingly the flare light is found to cause a bias error in velocity. Similar trend is observed in the presence of both the flare light and the Mie scattered light. The setup has provided a set of data for the future improvement of the modeling procedure, and demonstrated that even in the case of large amount of dust particles and large flare light the present technique can provide measurement of velocity with reasonable accuracy.

Rayleigh scattering↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗