Tracking and data acquisition support for the mariner venus 1962 mission
Spacecraft tracking and data acquisition for Mariner II Venus probe
MARINER II SPACE PROBE↗
SEARCH · Engineering Papers
Results for “Missions Data”
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.
SPICE: a real example of data system re-use to reduce the costs of ground data systems development and mission operations
NASA's SPICE ancillary informaton system is used by engineers and scientists to capture and access a variety of engineering and other ancillary information throughout the mission lifecycle.
observation geometry ancillary data↗
Sensor Data Distribution With Robustness and Reliability: Toward Distributed Components Model
In planetary surface exploration mission, sensor data distribution is required in many aspects, for example, in navigation, scheduling, planning, monitoring, diagnostics, and automation of the field tasks. The challenge is to distribute such data in the robust and reliable way so that we can minimize the errors caused by miscalculations, and misjudgments that based on the error data input in the mission. The ad-hoc wireless network on planetary surface is not constantly connected because of the nature of the rough terrain and lack of permanent establishments on the surface. There are some disconnected moments that the computation nodes will re-associate with different repeaters or access points until connections are reestablished. Such a nature requires our sensor data distribution software robust and reliable with ability to tolerant disconnected moments. This paper presents a distributed components model as a framework to accomplish such tasks. The software is written in Java and utilized the available Java Message Services schema and the Boss implementation. The results of field experimentations show that the model is very effective in completing the tasks.
Alena, Richard L.↗
Tracking and data system support for the Pioneer project. Volume 2 - Pioneer 7. Prelaunch to end of nominal mission
Tracking and data system support for prelaunch and nominal mission of Pioneer 7 space probe
Renzetti, N. A.↗
Parts Quality Management: Direct Part Marking of Data Matrix Symbol for Mission Assurance
A United States Government Accountability Office (GAO) review of twelve NASA programs found widespread parts quality problems contributing to significant cost overruns, schedule delays, and reduced system reliability. Direct part marking with Data Matrix symbols could significantly improve the quality of inventory control and parts lifecycle management. This paper examines the feasibility of using direct part marking technologies for use in future NASA programs. A structural analysis is based on marked material type, operational environment (e.g., ground, suborbital, Low Earth Orbit), durability of marks, ease of operation, reliability, and affordability. A cost-benefits analysis considers marking technology (label printing, data plates, and direct part marking) and marking types (two-dimensional machine-readable, human-readable). Previous NASA parts marking efforts and historical cost data are accounted for, including inhouse vs. outsourced marking. Some marking methods are still under development. While this paper focuses on NASA programs, results may be applicable to a variety of industrial environments.
Moss, Chantrice↗
LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska
Airborne remote sensing data collected from Los Alamos National Laboratory’s (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller Road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDAR System was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, and lidar data and imagery can be found in NGA281 (https://doi.org/10.5440/1671794).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Kougarok 64 Field Site, Seward Peninsula, Alaska
Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 64 along the Kougarok road (Nome-Taylor Highway) between Nome, Alaska and Taylor, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, raw LiDAR data, and RGB imagery can be found in NGA298.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Design, development, performance, and reconditioning of Ni-Cd batteries using polyropylene separators
A performance assessment is made for the Viking Mars Lander Program's sealed, sterilizable, 8-ampere hour Ni-Cd batteries, which use a nonwoven polypropylene separator material. Attention is given to separator wettability, the optimization of electrolyte quantity, and the reduction of plate carbonate, in view of thermal considerations and other environmental design and test requirements generated by mission characteristics. Life data based on mission experience identify, in addition to performance and degradation behavior, a series of shallow discharge reconditioning cycles and an intensive program of deep discharge reconditioning.
Britting, A. O., Jr.↗
Overview of the Astrophysics Data System
The Astrophysics Division of NASA has built a geographically- and logically-distributed heterogeneous information system for the dissemination and coordinated multispectral analysis of data from astrophysics missions. The Astrophysics Data System (ADS) is a truly distributed system in which the data and the required processing are physically distributed. To accommodate the anticipated growth and changes in both requirements and technology, the ADS employs a server/client architecture which allows services and data to be added or replaced without having to change the basic architecture or interfaces. Current datasets accessible through the system include all the tabular astronomical data available at each of six existing astrophysics data centers. Additional data nodes, at both NASA data centers and academic institutions, will be added shortly. The future evolution of the system will be driven in large part by user services mounted both by the ADS project itself and by members of the astrophysics community.
Good, John C.↗
RF/optical interference design for optical intersatellite links
A design approach for the RF/optical link interface for a data relay satellite is described. The flexibility of forward and return links in future data acquisition satellites in handling varying missions and data rates to 1 Gbit/s is considered. Attention is focused on requirements for the NASA Tracking and Data Acquisition System. System components are described including the return link multiplexer, the return link transmultiplexer, the forward link multiplexer, the forward link demultiplexer, and the frontside/backside switch. Ping-pong buffers, which provide rate buffering for each input data stream, are discussed and justification bits, which handle variations due to Doppler shift and local oscillator variation, are considered. The time-division multiplexed streams consist of a unique synchronization word for frame synchronization, and control words associated with each data burst to identify the presence or absence of a justification bit. Redundant data paths are described for both forward and return data streams.
Garlow, Ronald K.↗
Overview of the Astrophysics Data System
The Astrophysics Division of NASA has built a geographically and logically distributed heterogeneous information system for the dissemination and coordinated multispectral analysis of data from astrophysics missions. The Astrophysics Data System (ADS) is a truly distributed system in which the data and the required processing are physically distributed. To accommodate the anticipated growth and changes in both requirements and technology, the ADS employs a server/client architecture which allows services and data to be added or replaced without having to change the basic architecture or interfaces. Current datasets accessible through the system include all the tabular astronomical data available at each of six existing astrophysics data centers. Additional data nodes, at both NASA data centers and academic institutions, will be added shortly. The future evolution of the system will be driven in large part by user services mounted both by the ADS project itself and by members of the astrophysics community.
Good, John C.↗
The relationship between dietary intake, exercise, energy balance and the space craft environment
Space flight is associated with the loss of skeletal muscle, principally from muscles with anti-gravity functions. Examination of data across different missions can permit a distinction to be made between true microgravity responses and what are mission-specific responses. Protein metabolism has been investigated on six missions, four short-term [Shuttle missions Space Life Sciences 1 (1991, SLSI), Space Life Sciences 2 (1993, SLS2), Deutsche-2 (1993, D2) and the Life and Microgravity Sciences (1996, LMS)] and two long-term missions (Skylab 1993 and NASA/MIR, 1996-1998). Measurements made include dietary intake (six missions), nitrogen balance (four missions), whole-body protein kinetics with [15N]glycine as the tracer (four missions) and cortisol excretion (three missions). Also available for comparison are bed rest studies with and without exercise. The purpose of this paper is to see what can be learnt about the muscle loss problem by comparing metabolic results across the six missions for which data are available and against bed rest. The analysis suggests that there is a linkage between the inability to maintain energy balance and exercise, and the connection is the decreased efficiency of removal of the metabolic by-products of exercise (heat, CO2) during space flight.
long duration↗
Data Compression for Deep Space Missions
Explore the source record for details and available documents.
data compression deep space wavelet progressive er↗
Land Remote Sensing Overview
A general overview of the USGS land remote sensing program is presented. The contents include: 1) Brief overview of USGS land remote sensing program; 2) Highlights of JACIE work at USGS; 3) Update on NASA/USGS Landsat Data Continuity Mission; and 4) Notes on alternative data sources.
Byrnes, Ray↗
Parts Quality Management: Direct Part Marking via Data Matrix Symbols for Mission Assurance
A United States Government Accountability Office (GAO) review of twelve NASA programs found widespread parts quality problems contributing to significant cost overruns, schedule delays, and reduced system reliability. Direct part-marking with Data Matrix symbols could significantly improve the quality of inventory control and parts lifecycle management. This paper examines the feasibility of using 15 marking technologies for use in future NASA programs. A structural analysis is based on marked material type, operational environment (e.g., ground, suborbital, orbital), durability of marks, ease of operation, reliability, and affordability. A cost-benefits analysis considers marking technology (data plates, label printing, direct part marking) and marking types (two-dimensional machine-readable, human-readable). Previous NASA parts marking efforts and historical cost data are accounted for, including in-house vs. outsourced marking. Some marking methods are still under development. While this paper focuses on NASA programs, results may be applicable to a variety of industrial environments.
Moss, Chantrice↗
IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]
Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.
K A Shair↗
IMPACTing Medical System Design with a Risk Analysis Tool
Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.
K A Shair↗
Neural-Based Compression Scheme for Solar Image Data
Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them efficiently transferable to the ground station is a twofold decision to make. Stronger compression methods, by distorting the data, can increase data throughput at the cost of accuracy which could affect scientific analysis of the data. On the other hand, preserving subtle details in the compressed data requires a high amount of data to be transferred, reducing the desired gains from compression. In this work, we propose a neural network-based lossy compression method to be used in NASA’s data-intensive imagery missions. We chose NASA’s Solar Dynamics Observatory (SDO) mission which transmits 1.4 terabytes of data each day as a proof of concept for the proposed algorithm. In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs. The RD variational autoencoder used in this work is jointly trained with a channel-dependent entropy model as a shared prior between the analysis and synthesis transforms to make the entropy coding of the latent code more effective. We also studied how optimizing perceptual losses could help our neural compressor to preserve high-frequency details of the data in the reconstructed compressed image. Our neural image compression algorithm outperforms currently-in-use and state-of-the-art codecs such as JPEG and JPEG-2000 in terms of the RD performance when compressing extreme-ultraviolet (EUV) data. As a proof of concept for use of this algorithm in SDO data analysis, we have performed coronal hole (CH) detection using our compressed images, and generated consistent segmentations, even at a compression rate of ∼ 0.1 bits per pixel (compared to 8 bits per pixel on the original data) using EUV data from SDO.
Image coding↗