Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network parameter error”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Calibrated Ancillary System (CAS) user's guide, volume 6

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of CAS. Volume 6 describes ancillary products procedures, enhancement menu and processing task procedures for SDT/TDT (shuttle data tape/telemetry descriptor tape), database errors and network data driver (NDD) product menu procedures, and utility menu procedures.

Source record↗

Performance evaluation of antenna arrays with noisy carrier reference

The performance evaluation of coherent receivers with noisy carrier references and multiple antennas is presented. The received signal is assumed to be residual carrier BPSK, with a PLL used for extracting the carrier. Explicit relationships between the error probabilities and the various system parameters are given. Specific results are given for the performance gain of combined carrier referencing over baseband only combining when the channel alignment process is ideal. A simple asymptotic expression for the performance gain is determined when the number of antennas used is increased without bound. Examples using Deep Space Network receivers illustrate the performance of each arraying structure.

Yan, T. Y.↗

Orbit determination of highly elliptical Earth orbiters using improved Doppler data-processing modes

A navigation error covariance analysis of four highly elliptical Earth orbits is described, with apogee heights ranging from 20,000 to 76,800 km and perigee heights ranging from 1,000 to 5,000 km. This analysis differs from earlier studies in that improved navigation data-processing modes were used to reduce the radio metric data. For this study, X-band (8.4-GHz) Doppler data were assumed to be acquired from two Deep Space Network radio antennas and reconstructed orbit errors propagated over a single day. Doppler measurements were formulated as total-count phase measurements and compared to the traditional formulation of differenced-count frequency measurements. In addition, an enhanced data-filtering strategy was used, which treated the principal ground system calibration errors affecting the data as filter parameters. Results suggest that a 40- to 60-percent accuracy improvement may be achievable over traditional data-processing modes in reconstructed orbit errors, with a substantial reduction in reconstructed velocity errors at perigee. Historically, this has been a regime in which stringent navigation requirements have been difficult to meet by conventional methods.

Estefan, J. A.↗

A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos

A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.

Hill, R. E.↗

A microwave holography methodology for diagnostics and performance improvement for large reflector antennas

This microwave holography technique utilizes the Fourier transform relation between the complex far field radiation pattern of an antenna and the complex aperture field distribution. Resulting aperture phase and amplitude distribution data can be used to precisely characterize various crucial performance parameters, including panel alignment, panel shaping, subreflector position, antenna aperture illumination, directivity at various frequencies, and gravity deformation effects. The methodology of data processing presented here was successfully applied to the Deep Space Network (DSN) 34-m beam waveguide antennas. The antenna performance was improved at all operating frequencies by reducing the main reflector mechanical surface rms error to 0.43 mm. At Ka-band (32 GHz), the estimated improvement is 4.1 dB, resulting in an aperture efficiency of 52 percent. The performance improvement was verified by efficiency measurements and additional holographic measurements.

Rochblatt, D. J.↗

Microwave antenna holography

This microwave holography technique utilizes the Fourier transform relation between the complex far field radiation pattern of an antenna and the complex aperture field distribution. Resulting aperture phase and amplitude distribution data can be used to precisely characterize various crucial performance parameters, including panel alignment, panel shaping, subreflector position, antenna aperture illumination, directivity at various frequencies, and gravity deformation effects. The methodology of data processing presented here was successfully applied to the Deep Space Network (DSN) 34-m beam waveguide antennas. The antenna performance was improved at all operating frequencies by reducing the main reflector mechanical surface rms error to 0.43 mm. At Ka-band (32 GHz), the estimated improvement is 4.1 dB, resulting in an aperture efficiency of 52 percent. The performance improvement was verified by efficiency measurements and additional holographic measurements.

Rochblatt, David J.↗

Effective Uncertainty Quantification for Multi-Angle Polarimetric Aerosol Remote Sensing Over Ocean

Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and the nonlinear dependence of the forward model on the retrieved parameters near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on efficient neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the uncertainty evaluation technique in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, as well as guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.

PACE↗

Three-Dimensional Stereoscopic Tracking Velocimetry and Experimental/Numerical Comparison of Directional Solidification

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in both ground and space experiments for understanding materials processing and fluid physics. The experiments in these fields most likely inhibit the application of conventional planar probes for observing 3-D phenomena. Here, we present the investigation results of stereoscopic tracking velocimetry (STV) for measuring 3-D velocity fields, which include diagnostic technology development, experimental velocity measurement, and comparison with analytical and numerical computation. STV is advantageous in system simplicity for building compact hardware and in software efficiency for continual near-real-time monitoring. It has great freedom in illuminating and observing volumetric fields from arbitrary directions. STV is based on stereoscopic observation of particles-Seeded in a flow by CCD sensors. In the approach, part of the individual particle images that provide data points is likely to be lost or cause errors when their images overlap and crisscross each other especially under a high particle density. In order to maximize the valid recovery of data points, neural networks are implemented for these two important processes. For the step of particle overlap decomposition, the back propagation neural network is utilized because of its ability in pattern recognition with pertinent particle image feature parameters. For the step of particle tracking, the Hopfield neural network is employed to find appropriate particle tracks based on global optimization. Our investigation indicates that the neural networks are very efficient and useful for stereoscopically tracking particles. As an initial assessment of the diagnostic technology performance, laminar water jets with and without pulsation are measured. The jet tip velocity profiles are in good agreement with analytical predictions. Finally, for testing in material processing applications, a simple directional solidification apparatus is built for experimenting with a metal analog of succinonitrile. Its 3-D velocity field at the liquid phase is then measured to be compared with those from numerical computation. Our theoretical, numerical, and experimental investigations have proven STV to be a viable candidate for reliably measuring 3-D flow velocities. With current activities are focused on further improving the processing efficiency, overall accuracy, and automation, the eventual efforts of broad experimental applications and concurrent numerical modeling validation will be vital to many areas in fluid flow and materials processing.

Lee, David↗

An efficient technique for the performance evaluation of antenna arrays with noisy carrier reference

An efficient computational technique is developed to evaluate the performance of coherent receivers with noisy carrier reference and multiple antennas. The received signal is assumed to be uncoded residual carrier BPSK (binary phase shift keying), with a PLL (phase locked loop) used for extracting the carrier. Explicit relationships between the error probabilities and the various system parameters are given. Specific results are given for the performance gain of combined carrier referencing over baseband only combining when the channel alignment process is ideal. A simple asymptotic expression for the performance gain is determined when the number of antennas used is increased without bound. An example using a Block 3 Deep Space Network PLL illustrates the performance of each arraying structure. The technique used is applicable to the performance evaluation for other receivers having similar decision statistics.

Yan, T. Y.↗

Climate Change and Sounder Radiometric Stability

Satellite instrument radiometric stability is critical for climate studies. The Atmospheric Infrared Sounder (AIRS) radiances are of sufficient stability and accuracy to serve as a climate data record as evidenced by comparisons with the global network of buoys. In this paper we examine the sensitivity of derived geophysical products to potential instrument radiometric stability issues due to diurnal, orbital and seasonal variations. Our method is to perturb the AIRS radiances and examine the impact to retrieved parameters. Results show that instability in retrieved temperature products will be on the same order of the brightness temperature error in the radiances and follow the same time dependences. AIRS excellent stability makes it ideal for examining impacts of instabilities of future systems on geophysical parameter performance.

Sounding↗

Modeling the Swift BAT Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. (2014) is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of approximately greater than 97% (approximately less than 3% error), which is a significant improvement on a cut in GRB flux which has an accuracy of 89:6% (10:4% error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of eta(sub 0) approximately 0.48(+0.41/-0.23) Gpc(exp -3) yr(exp -1) with power-law indices of eta(sub 1) approximately 1.7(+0.6/-0.5) and eta(sub 2) approximately -5.9(+5.7/-0.1) for GRBs above and below a break point of z(sub 1) approximately 6.8(+2.8/-3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting. The code used in this is analysis is publicly available online.

gamma rays: general↗

An analysis of mesoscale VAS retrievals using statistical structure functions

Mesoscale sounding data from a truth rawinsonde network and a VAS from March 6-7, 1982 are statistically studied. The parameters of temperature, geopotential height, and mixing ratio at 850, 700, 500, 300, and 200 mb levels, and thickness and precipitable water are examined. The VAS retrieval gradients derived from a physical algorithm and from a regression technique are analyzed; the analysis reveals that both techniques have similar error characteristics and capabilities for calculating gradients of mesoscale temperature and geopotential height. Ground-truth rawinsonde data and VAS retrievals are compared; it is observed that VAS data describes weaker gradients than rawinsonde data.

Fuelberg, H. E.↗

Measuring earth orientation with the Global Positioning System

A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level earth orientation information to aid both spacecraft navigation and the study of high-frequency earth orientation-related processes.

Freedman, Adam P.↗

Optimal Feedback Control of Thermal Networks

An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.

Papalexandris, Miltiadis↗

Galileo Earth approach navigation using connected-element interferometer phase-delay tracking

The application of a Connected-Element Interferometer (CEI) to the navigation of the Galileo spacecraft during its encounter with Earth in December 1990 is investigated. A CEI tracking demonstration is planned for the week of November 11 through 18, 1990, from 27 days to 20 days prior to Earth encounter on December 8. During this period, the spacecraft will be tracked daily with Deep Space Network Stations 13 and 15 at Goldstone. The purpose of this work is twofold: first, to establish and define the navigation performance expected during the tracking demonstration and, second, to study, in a more general sense, the sensitivity of orbit demonstration results obtained with CEI to the data density within CEI tracking passes and to important system parameters, such as baseline orientation errors and the phase-delay measurement accuracy. Computer simulation results indicate that the use of CEI data, coupled with conventional range and Doppler data, may reduce the uncertainty in the declination of the spacecraft's incoming trajectory by 15 to 66 percent compared with the operational solution using range and Doppler data only. The level of improvement depends upon the quantity and quality of the CEI data.

Thurman, S. W.↗

Evaluation of the Land Surface Reflectance Fundamental Climate Data Record

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. In this presentation, we present the validation of the Land surface reflectance used for MODIS, VIIRS, Landsat 8 and Sentinel 2 data. This methodology uses the 6SV Code and data from the AERONET network. The overall accuracy clearly reaches the satellite specifications. To understand how to improve the validation, we developed an exhaustive error budget. Results show an impact of the absorption of aerosol and of the fine mode volume concentration.

Atmospheric correction↗

Modeling the Swift Bat Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift / BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of greater than or equal to 97 percent (less than or equal to 3 percent error), which is a significant improvement on a cut in GRB flux, which has an accuracy of 89.6 percent (10.4 percent error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of n (sub 0) approaching 0.48 (sup plus 0.41) (sub minus 0.23) per cubic gigaparsecs per year with power-law indices of n (sub 1) approaching 1.7 (sup plus 0.6) (sub minus 0.5) and n (sub 2) approaching minus 5.9 (sup plus 5.7) (sub minus 0.1) for GRBs above and below a break point of z (redshift) (sub 1) approaching 6.8 (sup plus 2.8) (sub minus 3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting.

gamma-ray burst: general – gamma-rays: general â↗

Inversion of Multiangular Polarimetric Measurements Over Open and Coastal Ocean Waters: A Joint Retrieval Algorithm for Aerosol and Water-Leaving Radiance Properties

Ocean color remote sensing is a challenging task over coastal waters due to the complex optical properties of aerosols and hydrosols. In order to conduct accurate atmospheric correction, we previously implemented a joint retrieval algorithm, hereafter referred to as the Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm, to obtain the aerosol and water-leaving signal simultaneously. The MAPOL algorithm has been validated with synthetic data generated by a vector radiative transfer model, and good retrieval performance has been demonstrated in terms of both aerosol and ocean water optical properties (Gao et al., 2018). In this work we applied the algorithm to airborne polarimetric measurements from the Research Scanning Polarimeter (RSP) over both open and coastal ocean waters acquired in two field campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in 2014 and the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) in 2015 and 2016. Two different yet related bio-optical models are designed for ocean water properties. One model aligns with traditional open ocean water bio-optical models that parameterize the ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that includes seven free parameters to describe the absorption and scattering by phytoplankton, colored dissolved organic matter, and nonalgal particles. The retrieval errors of both aerosol optical depth and the water-leaving radiance are evaluated. Through the comparisons with ocean color data products from both in situ measurements and the Moderate Resolution Imaging Spectroradiometer (MODIS), and the aerosol product from both the High Spectral Resolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), the MAPOL algorithm demonstrates both flexibility and accuracy in retrieving aerosol and water-leaving radiance properties under various aerosol and ocean water conditions.

Gao, Meng↗