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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 NTRS1977

Minimax decoding of cyclic block codes

A minimax decoding algorithm utilizing soft bit detection of an (n,k) cyclic block code is described which will permit the correction of up to n-k bit errors interspersed at random locations throughout the block. The decoding solution consists of: (1) identifying the ordered soft bit set and, (2) finding the minimum order solution to the resulting syndrome equations where the nonzero error vector components are constrained to be a subset of the soft bit set. An efficient implementation of the decoding operation is described. In essence, this algorithm focuses the correction capability of the code on those bit positions which have the lowest a posteriori probabilities of correct detection.

Greene, E. P.↗
NASA NTRS1978

Quasi-optimal decoding of linear block codes using soft decision detection

A simple but effective decoding procedure, applicable to any (n,k) linear block code with symbols from GF(q), is described. The technique involves a transformation of the parity check equations which focuses the code's correction power on the soft symbol set while still retaining the capability to correct one symbol error from outside this set. The soft symbol set is defined to be the n-k least reliably detected code symbol positions whose parity check row-spaces are linearly independent. The process generates a number of error vector screening candidates, each a solution to the parity check equations, and the maximum-likelihood candidate is accepted.

Greene, E. P.↗
NASA NTRS1980

Navigation accuracy analysis for the Halley flyby phase of a dual comet mission using ion drive

A dual comet (Halley Flyby/Tempel 2 Rendezvous) mission, making use of the solar electric propulsion system, is under consideration for a 1985 launch. This paper presents navigation accuracy analysis results for the Halley flyby phase of this mission. Orbit determination and guidance accuracies are presented for the baseline navigation strategy, along with the results of a number of sensitivity studies involving parameters such as data frequencies, data accuracies, ion drive thrust vector errors, comet ephemeris uncertainties, time lags associated with data processing and command sequence generation, probe release time, and navigation coast arc duration.

Wood, L. J.↗
NASA NTRS1980

Navigation accuracy analyses for two comet rendezvous missions using ion drive

Two cometary missions, making use of the solar electric propulsion system, have recently been considered for launches in the mid to late 1980's. This paper presents navigation accuracy analysis results for the rendezvous portions of these missions, the target bodies being Comet Tempel 2 and Comet Tuttle-Giacobini-Kresak. Orbit determination and guidance accuracies are presented for the baseline navigation strategies, along with the results of a number of sensitivity studies involving parameters such as data frequencies, data accuracies, ion drive thrust vector errors, comet emphemeris uncertainties, time lags associated with data processing and command sequence generation, and certain guidance law parameters. The accuracies obtained are, in some respects, significantly better than the results of previous solar electric propulsion comet rendezvous studies.

Wood, L. J.↗
NASA NTRS1982

The Magsat mission

The cesium-vapor scalar and fluxgate vector magnetometers aboard the Magsat spacecraft, which has a twilight, sun-synchronous orbit with a 96.76-deg inclination, have together measured the earth's magnetic field magnitude to accuracies better than 2 nT, and the magnitude of each field component to better than 6 nT. The magnetometers are located at the end of a boom to isolate them from the effects of spacecraft fields, and an optical system was used to measure the attitude of the vector magnetometer and sun sensor at the boom relative to the two star cameras of the main spacecraft structure. The data gathered is available from the National Space Science Data Center in several formats and is currently undergoing analysis. Scalar and vector error budget values are given for the spacecraft's five error sources, which include the instrument, position and time errors, digitization noise, attitude errors, and spacecraft fields.

Langel, R.↗
NASA NTRS1982

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 3

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 3 of the four major tasks included in the study. Task 3 compares flight plans developed on the Suitland forecast with actual data observed by the aircraft (and averaged over 10 degree segments). The results show that the average difference between the forecast and observed wind speed is 9 kts. without considering direction, and the average difference in the component of the forecast wind parallel to the direction of the observed wind is 13 kts. - both indicating that the Suitland forecast underestimates the wind speeds. The Root Mean Square (RMS) vector error is 30.1 kts. The average absolute difference in direction between the forecast and observed wind is 26 degrees and the temperature difference is 3 degree Centigrade. These results indicate that the forecast model as well as the verifying analysis used to develop comparison flight plans in Tasks 1 and 2 is a limiting factor and that the average potential fuel savings or penalty are up to 3.6 percent depending on the direction of flight.

Keitz, J. F.↗
NASA NTRS1986

Analysis and forecast experiments incorporating satellite soundings and cloud and water vapor drift wind information

A system for assimilating conventional meteorological data and satellite-derived data in order to produce four-dimensional gridded data sets of the primary atmospheric variables used for updating limited area forecast models is described. The basic principles of a data assimilation scheme as proposed by Lorenc (1984) are discussed. The design of the system and its incremental assimilation cycles are schematically presented. The assimilation system was tested using radiosonde, buoy, VAS temperature, dew point, gradient wind data, cloud drift, and water vapor motion data. The rms vector errors for the data are analyzed.

Goodman, Brian M.↗
NASA NTRSDate not supplied

Design of a Thermal Testbed for Metrology of Active Antennas

NASA mission requirements have driven an increased interest in active phased array antennas (APAA) for space-based user communication terminals. Recent advancements in 5G technology have driven down the cost of APAA development and manufacturing all while providing a technology solution that covers many existing Ka-Band satellite communication spectrum bands. While these developments have provided ample opportunities to leverage new chips and arrays for use in space, there is also a need to evaluate these antennas in a relevant environment. Active arrays, as designed for use in 5G, require thermal management to avoid damage to the device as well as to maintain performance. Measured performance under various thermal conditions is essential both for understanding overall APAA performance and ensuring operation is within required tolerances. To address these measurement needs, the SmallSat Ka-band Operations User Terminal (SKOUT) project at the NASA Glenn Research Center (GRC) developed a test environment that combines traditional antenna and communication system metrology with a conduction cooling/heating thermal control system to simulate the space thermal environment. This paper will address the metrologysystem design and performance specifications as well as test article setup and operation. Tests that are typically performed at ambient temperature can now be performed over the typical temperature range of a Low Earth Orbit (LEO) mission. These tests include error vector magnitude (EVM), gain to noise temperature (G/T), antenna patterns, and non-linear characterization. The paper will cover the configuration for each test and provide results from a recent test campaign. Results illustrate the importance of higher fidelity environmental testing when evaluating the performance of an APAA.

active phased array↗
NASA NTRS2020

SNPP and N20 VIIRS Solar Vector Orientation Knowledge Error Detected by SDSM Sun Views

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a passive scanning Earth observing satellite radiometer. The VIIRS has 22 spectral bands with design center wavelengths from 0.41 to 12.01 μm, providing data to generate more than 20 Earth’s biogeophysical parameters. Fourteen of the 22 VIIRS bands are the reflective solar bands (RSBs), detecting Earth reflected sunlight. To ensure data quality, regular on-orbit radiometric calibrations of the RSBs are performed, mainly through observations of an onboard solar diffuser (SD). The spectral radiance provided by the sunlit SD depends on the SD screen transmittance which is a function of the solar vector orientation. Additionally, on orbit the SD’s bidirectional reflectance distribution function (BRDF) changes its value due to solar bombardment. The BRDF change is derived from the SD stability monitor (SDSM) measurements. The SDSM views the Sun through a screen with through holes (the SDSM screen) and the SD at almost the same time. The time series of the ratio of the signal strengths is a measure of the SD BRDF on-orbit change. Hence the measurements of the on-orbit SD BRDF change depends on the SDSM screen relative transmittance which is also solar vector orientation dependent. In this paper for both the SNPP and the NOAA-20 VIIRS instruments we examine the solar vector orientation knowledge error through matching the SDSM screen relative effective transmittances derived from the calibration data collected on the yaw maneuver and the regular orbits.

SNPP↗
NASA NTRS1983

Simplified Syndrome Decoding of (n, 1) Convolutional Codes

A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

I. S. Reed↗
NASA NTRS1983

New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

Reed, I. S.↗
NASA NTRS1983

New syndrome decoder for (n, 1) convolutional codes

The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

Reed, I. S.↗
NASA NTRS1984

New syndrome decoding techniques for the (n, k) convolutional codes

This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

Reed, I. S.↗
NASA NTRS1990

Effects of error sources on the parallelism of an optical matrix-vector processor

The error sources in a high accuracy optical matrix-vector processor are analyzed by numerical simulation in terms of their effects on the parallelism and speed of the processor. These effects are detailed for radices -2, -4 and -8. Radix -4 is shown to provide maximum parallel processing capabilities under the effects of the system's error sources. Processing speed is shown to be a function of matrix partitioning and the number of parallel processing channels. Consequently, radix -4 operation provides a higher processing speed than radix -2 and -8 for most matrix-vector multiplications when error source effects are considered.

Perlee, Caroline J.↗
NASA NTRS2008

Effect of GOES-R Image Navigation and Registration Errors on Atmospheric Motion Vectors

High temporal frequency imagery from geostationary satellites allows for the continuous monitoring of rapidly changing atmospheric constituents such as smoke, dust, water vapor and clouds. The image sequences are often used to quantify the displacement of image features such as water vapor and clouds to produce atmospheric motion vectors (AMVs) which are used as diagnostic tools and also assimilated into numerical weather forecast models. The basic principle behind the determination of AMVs is the calculation of the physical displacement of features from one image (time) to the next. This process assumes that the features being tracked do not change as a function of time, usually requiring the use of short time interval imagery to minimize substantial change in size and shape of the features being tracked. High spatial resolution imagery also is required for reliable feature identification. While these image resolution and temporal sampling requirements often provide major drivers for space-based instrument design requirements, accurate image navigation and registration, INn (between a sequence of images), is also critical to the derivation of useful AMVs. In this paper and poster to be presented at the conference, the image navigation and registration (INR) accuracy expected for the Advanced Baseline Imager (ABI) on the GOES-R series of satellites will be discussed in light of its impact on AMV accuracy. Significant satellite platform and modeling enhancements are planned which should significantly improve INn performance of the GOES-R instruments. Some of these improvements have been demonstrated for the GOES-13 satellite which was launched in summer of 2006. An analysis of GOES-13 INR data, from the special satellite check out period, will be used in the assessment.

Jedlovec, Gary↗
NASA NTRS1991

Effects of atmospheric modeling errors on determinations of baseline vectors from very long baseline interferometry

An investigation is conducted in order to expose errors in the formula for the elevation angle dependence of the hydrostatic atmospheric propagation delay, called the mapping function. A series of special VLBI experiments that involve a large fraction of group delay data from very low elevation angles are performed. Twenty-two experiments, each 26 hours in duration, were performed using VLBI antennas at Goldstone, California and at Westford, Massachusetts. Elevation angle cutoff tests were used to examine the contribution of these errors to the estimates of the vertical coordinate of site position. This contribution is determined to be about 19 mm. It is also found that, for the spacing of 1-2 months between experiments, the mapping function errors do not exhibit a coherent annual signature, but appear to be random in the long term.

Davis, J. L.↗