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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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NASA NTRS1979

CCD sensors for spacecraft optical navigation

The optical navigation process uses spaceborne measurements of the apparent direction vector from the spacecraft to a target body, (planet, satellite, star, etc.) to improve estimates of the spacecraft trajectory. Ground-based controllers assimilate the optical measurements, together with spacecraft radio-tracking data and target ephemeris data, to generate a best estimate of the trajectory relative to the target. The present paper deals with a development program supporting the use of (solid state) CCD (Charged Coupled Device) imagers for spacecraft navigation. It is shown that stars can be detected that are two to three magnitudes fainter than with an equivalent vidicon based instrument, that effects of global response nonuniformity and dark current spikes can be essentially eliminated from the data as a result of the reproducibility of both effects, and that charge trailing during readout of star image data can lead to position measurement errors.

Eisenman, A. R.↗

NASA NTRS1994

A simple suboptimal least-squares algorithm for attitude determination with multiple sensors

Three-axis attitude determination is equivalent to finding a coordinate transformation matrix which transforms a set of reference vectors fixed in inertial space to a set of measurement vectors fixed in the spacecraft. The attitude determination problem can be expressed as a constrained optimization problem. The constraint is that a coordinate transformation matrix must be proper, real, and orthogonal. A transformation matrix can be thought of as optimal in the least-squares sense if it maps the measurement vectors to the reference vectors with minimal 2-norm errors and meets the above constraint. This constrained optimization problem is known as Wahba's problem. Several algorithms which solve Wahba's problem exactly have been developed and used. These algorithms, while steadily improving, are all rather complicated. Furthermore, they involve such numerically unstable or sensitive operations as matrix determinant, matrix adjoint, and Newton-Raphson iterations. This paper describes an algorithm which minimizes Wahba's loss function, but without the constraint. When the constraint is ignored, the problem can be solved by a straightforward, numerically stable least-squares algorithm such as QR decomposition. Even though the algorithm does not explicitly take the constraint into account, it still yields a nearly orthogonal matrix for most practical cases; orthogonality only becomes corrupted when the sensor measurements are very noisy, on the same order of magnitude as the attitude rotations. The algorithm can be simplified if the attitude rotations are small enough so that the approximation sin(theta) approximately equals theta holds. We then compare the computational requirements for several well-known algorithms. For the general large-angle case, the QR least-squares algorithm is competitive with all other know algorithms and faster than most. If attitude rotations are small, the least-squares algorithm can be modified to run faster, and this modified algorithm is faster than all but a similarly specialized version of the QUEST algorithm. We also introduce a novel measurement averaging technique which reduces the n-measurement case to the two measurement case for our particular application, a star tracker and earth sensor mounted on an earth-pointed geosynchronous communications satellite. Using this technique, many n-measurement problems reduce to less than or equal to 3 measurements; this reduces the amount of required calculation without significant degradation in accuracy. Finally, we present the results of some tests which compare the least-squares algorithm with the QUEST and FOAM algorithms in the two-measurement case. For our example case, all three algorithms performed with similar accuracy.

Brozenec, Thomas F.↗

NASA NTRS2004

Application of Polarization to the MODIS Aerosol Retrieval Over Land

Reflectance measurements in the visible and infrared wavelengths, from the Moderate Resolution Imaging Spectroradiometer (MODIS), are used to derive aerosol optical thicknesses (AOT) and aerosol properties over land surfaces. The measured spectral reflectance is compared with lookup tables, containing theoretical reflectance calculated by radiative transfer (RT) code. Specifically, this RT code calculates top of the atmosphere (TOA) intensities based on a scalar treatment of radiation, neglecting the effects of polarization. In the red and near infrared (NIR) wavelengths the use of the scalar RT code is of sufficient accuracy to model TOA reflectance. However, in the blue, molecular and aerosol scattering dominate the TOA signal. Here, polarization effects can be large, and should be included in the lookup table derivation. Using a RT code that allows for both vector and scalar calculations, we examine the reflectance differences at the TOA, with and without polarization. We find that the differences in blue channel TOA reflectance (vector - scalar) may reach values of 0.01 or greater, depending on the sun/surface/sensor scattering geometry. Reflectance errors of this magnitude translate to AOT differences of 0.1, which is a very large error, especially when the actual AOT is low. As a result of this study, the next version of aerosol retrieval from MODIS over land will include polarization.

Levy, Robert C.↗

NASA NTRSDate not supplied

Wide Bandgap Semiconductor Devices & Systems for Communications in Extreme Environment

The feasibility of Ka-band gallium nitride (GaN) based high power amplifier (HPA) for signal amplification in extreme planetary environment is investigated and its measured performance is presented. The data includes Pout, PAE, EVM for several waveforms and data rates, output spectrum, IMD, Noise Figure, and Gain. The data indicates excellent overall performance. Potential application of this HPA includes communication systems required to operate in the extreme hot environment of Mercury and Venus, extreme cold and high radiation environment of Jupiter’s icy moons, and Artemis missions that involve human/robotic exploration and long-term presence on the Moon.

Gallium Nitride↗

DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2001

Twenty Years of Radiation Measurements in Low-Earth Orbit - What Have We Learned Space Radiation Environment?

The advent of the Space Shuttle program has made possible space radiation environment measurements spanning a wide range of altitudes and orbital inclinations over multiple solar cycles. These measurements range from routine integral dose measurements with thermoluminescent dosimeters to particle energy spectra measurements made with a charged particle telescope. This paper will review the new understanding about the space radiation environment gained from this diverse data set. Major findings from these measurements include: estimations of the westward drift rate of the South Atlantic Anomaly (SAA) of 0.28-0.49/y; evidence for a northward component to the SAA drift of 0.08-0.12/y; observation of the formation and decay of the pseudo-stable additional radiation belt following the Mar 1991 SPE and geomagnetic storm with an estimated decay e-folding time of 9-10 months; observation of a local geomagnetic east-west trapped proton exposure anisotropy with an estimated magnitude of 1.6-3.3; demonstration that the trapped proton exposure in low-Earth orbit (LEO) can be reasonably modeled as a power law function of atmospheric density in the SAA region, with best correlations obtained when the exospheric temperature saturates at 938-975 K; the actual solar cycle modulation of trapped proton exposure in LEO is less than predicted by the AP8 model; and the testing and validation of GCR flux models, radiation transport codes, and dynamic geomagnetic cutoff models. Long-term, time-resolved proportional counter measurements made aboard the Mir during the same period provides further demonstration of the solar cycle modulation of the trapped protons at low altitudes - the observed modulation is also well described as power law function of atmospheric density. These data and findings have helped to improve the overall accuracy of pre-mission crew exposure projections using various semi-empirical space environment models, radiation transport codes, and spacecraft radiation shielding models. During the rise phase of solar cycle 22 (1987-1991), the RMS error between preflight exposure projections and measured crew exposure was 73%. For the rise phase of cycle 23 (1997-2001), the preflight exposure projection RMS error has decreased to 23%. The launch and assembly of the Space Station has begun a new era of long-term LEO space environment monitoring. The radiation environment at the Space Station will be monitored with three external charged particle telescopes oriented in the velocity vector, anti-velocity vector, and zenith directions. Data from the telescopes will provide charge, mass, energy, and arrival direction for incident particles with energy to mass ratios of 13- 450 MeV/amu and Z of 1-24. The external environment data will be complimented by measurements from a portable charged particle telescope and proportional counter located inside the vehicle.

Golightly, Michael J.↗