Telemetry data processing plan for the OGO-A MISSION
Telemetry data processing plan for OGO-A MISSION - pulse code modulation digital and analog data techniques - ground data acquisition system
SEARCH · Engineering Papers
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.
Telemetry data processing plan for OGO-A MISSION - pulse code modulation digital and analog data techniques - ground data acquisition system
The objective of the Fourth Technical Meeting on Fusion Data Processing, Validation and Analysis was to provide a platform during which a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolating needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics and synthetic diagnostics data analysis (including image processing, regression analysis, inverse problems, deep learning, machine learning, big data and physics-based models for control) reported at the meeting. The progress in these areas highlight trends observed in current major fusion confinement devices. A special focus is dedicated on data analysis requirements for ITER and DEMO with a particular attention paid to artificial intelligence for automatization and improving reliability of control processes.
A software system was developed which processes digitized scatterometer data from the 13.3 GHz, 1.6 GHz and 400 MHz scatterometer systems. In addition to this, the hardware capability has been developed to recover the raw analog radar signals and the aircraft parameters from an ADAS data stream in a digital format for processing by the software package. Software for the preparation of data reports and chart presentation of scattering coefficients time histories has also been developed. This report documents the development of the software, describes key components of the processing system and presents examples of the processed data and procedure for software operation.
Fast 3D data analysis and steering of a tomographic experiment by changing environmental conditions or acquisition parameters require fast, close to real-time, 3D reconstruction of large data volumes. Here a performance-optimized TomocuPy package is presented as a GPU alternative to the commonly used central processing unit (CPU) based TomoPy package for tomographic reconstruction. TomocuPy utilizes modern hardware capabilities to organize a 3D asynchronous reconstruction involving parallel read/write operations with storage drives, CPU–GPU data transfers, and GPU computations. In the asynchronous reconstruction, all the operations are timely overlapped to almost fully hide all data management time. Since most cameras work with less than 16-bit digital output, the memory usage and processing speed are furthermore optimized by using 16-bit floating-point arithmetic. As a result, 3D reconstruction with TomocuPy became 20–30 times faster than its multi-threaded CPU equivalent. Full reconstruction (including read/write operations and methods initialization) of a 2048 3 tomographic volume takes less than 7 s on a single Nvidia Tesla A100 and PCIe 4.0 NVMe SSD, and scales almost linearly increasing the data size. To simplify operation at synchrotron beamlines, TomocuPy provides an easy-to-use command-line interface. Efficacy of the package was demonstrated during a tomographic experiment on gas-hydrate formation in porous samples, where a steering option was implemented as a lens-changing mechanism for zooming to regions of interest.
Digital filters for non-real time data processing
The AMPX nuclear data processing code reads evaluated nuclear data files and prepares libraries in continuous energy (CE) and multigroup (MG) formats. These libraries are used by the transport and depletion codes in the SCALE code system.
The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been under development at JPL for the past four years. During this time, a dedicated ground data-processing system has been designed and implemented to store and process the large amounts of data expected. This paper reviews the objectives of this ground data-processing system and describes the hardware. An outline of the data flow through the system is given, and the software and incorporated algorithms developed specifically for the systematic processing of AVIRIS data are described.
The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been under development at JPL for the past four years. During this time, a dedicated ground data-processing system has been designed and implemented to store and process the large amounts of data expected. This paper reviews the objectives of this ground data-processing system and describes the hardware. An outline of the data flow through the system is given, and the software and incorporated algorithms developed specifically for the systematic processing of AVIRIS data are described.
We present the Local Volume Complete Cluster Survey (LoVoCCS; we pronounce it as "low-vox" or "law-vox," with stress on the second syllable), an NSF's National Optical-Infrared Astronomy Research Laboratory survey program that uses the Dark Energy Camera to map the dark matter distribution and galaxy population in 107 nearby (0.03 < z < 0.12) X-ray luminous ([0.1–2.4 keV] L X500 > 10 44 erg s –1 ) galaxy clusters that are not obscured by the Milky Way. The survey will reach Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Year 1–2 depth (for galaxies r = 24.5, i = 24.0, signal-to-noise ratio (S/N) > 20; u = 24.7, g = 25.3, z = 23.8, S/N > 10) and conclude in ~2023 (coincident with the beginning of LSST science operations), and will serve as a zeroth-year template for LSST transient studies. We process the data using the LSST Science Pipelines that include state-of-the-art algorithms and analyze the results using our own pipelines, and therefore the catalogs and analysis tools will be compatible with the LSST. We demonstrate the use and performance of our pipeline using three X-ray luminous and observation-time complete LoVoCCS clusters: A3911, A3921, and A85. A3911 and A3921 have not been well studied previously by weak lensing, and we obtain similar lensing analysis results for A85 to previous studies.
A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.
The most important aspects of the processing of MST radar data are discussed. The important points of on-line data processing for MST radar are reviewed. The goals of the on-line and now almost exclusively digital processing, procedures are to achieve good altitude resolution and coverage, good frequency (Doppler shift) resolution, and good time resolution, while avoiding, the problems of range and frequency ambiguity (aliasing), ground clutter, and interference. Achieving optimum results requires pulse compression and some coherent integration. The first allows full utilization of the average power capability of the transmitter and the second reduces the computing requirements.
A "smart" hand for remote manipulator not only senses forces acting on it and detects presence of objects in immediate vicinity but also processes sensory data and controls its gripping claws. Hand reduces computational load on control computer of manipulator system. Includes wrist body and two opposing jaws with sets of claws that mesh with each other. Jaws of hand open as wide as 8.8 cm. Brushless dc motor operates claws through bevel-gear drive train and pair of ball screws. Maximum grip force 540 N, or about 120 lb.
We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.
NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.
Radar technology is used extensively by NASA for remote sensing of the Earth and other Planetary bodies. In this case study, we learn about different computational concepts for processing radar data. In particular, we learn how to correct a slanted radar image by projecting it on the surface that was sensed by a radar instrument.
The software specifications for the MAGSAT data processing system (MDPS) are presented. The MDPS is divided functionally into preprocessing of primary input data, data management, chronicle processing, and postprocessing. Data organization and validity, and checks of spacecraft and instrumentation are dicussed. Output products of the MDPS, including various plots and data tapes, are described. Formats for important tapes are presented. Dicussions and mathematical formulations for coordinate transformations and field model coefficients are included.
The Mars Pathfinder mission required new capabilities and adaptation of existing capabilities in order to support science analysis and flight operations requirements imposed by the in-situ nature of the mission.
Data processing plan for eccentric orbiting geophysical observatory