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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

DSN Wide Area Network Architecture, Capacity and Performance

This paper discusses the architecture of the wide area network that connects key communications facilities within the National Aeronautic and Space Administration (NASA) Deep Space Network (DSN). Several considerations are given to the design of this wide area network to ensure a timely, reliable, and secure data delivery between the mission users and their spacecraft. The network star configuration simplifies data delivery to users and minimizes operational cost. The dual-path connections maximize the system reliability, with geographical diversity in data routing to avoid single point of failure. Data encryption enhances the protection of mission users’ data. The system bandwidth is determined by balancing the needs to minimize the operating bandwidth cost and to have sufficient bandwidth to be able to deliver data to all users within the required. The DSN uses a class base weighted fair queuing (CBWFQ) method in its data delivery. This scheme guarantees a minimum bandwidth to each class of users and allows users to also access any unused bandwidth by other groups. The paper will also show performance of system reliability and bandwidth margin.

Liao, Jason↗
NASA NTRS2021

An evaluation of the CAN bus for use on the Europa Lander motor controller

This paper will present the application of the Controller Area Network (CAN) for communication between the Motor Control Processor and the Europa Lander Motor Control Cards. The Europa Lander preproject team is concerned about lowering the estimated mass, volume, and power of the mission concept so that it could maximize its science return. The motor controller uses multiple Motor Control Cards to control the 24 motors that will be operating in the extremes of the Europa environment. The CAN bus was considered because of its multi-drop nature, low power interface, and simple communication protocol.

Lias, Malcolm↗
NASA NTRS2021

Draft LunaNet Interoperability Specification

Under the guidance of NASA’s Space Communication and Navigation (SCaN) program, this document, along with its companion documents, LunaNet Services Requirements Document (TBD) and the LunaNet Concept of Operations and Architecture (TBD), provides the basis for a comprehensive set of requirements for operation of a lunar communications and navigation network capable of interoperating with other networks compliant with the Lunar Network (LunaNet) for services to the human exploration, lunar science, and space technology missions. LunaNet will start with a simple architecture of a few nodes to meet the needs of the early missions and evolve to meet the growing needs of a sustained lunar presence. All relay network services are not expected to be met by a single spacecraft platform, or node. The expectation is that the needs of NASA, its partners and other users will be met through a combination of interoperable systems provided by NASA, international partners, and commercial providers. Interoperability across this network-of-networks can be achieved through negotiation of mutually-agreed-upon standards that will be reflected in this document and in the specifications defined by other participants in the combined, cooperative lunar network.

LunaNet↗
NASA NTRS2021

An Evaluation of the CAN bus for Use on the Europa Lander Motor Controller

This paper will present the application of the Controller Area Network (CAN) for communication between the Motor Control Processor and the Europa Lander Motor Control Cards. The Europa Lander mission is concerned about lowering the mass, volume, and power so that it can maximize its science return. The motor controller uses multiple Motor Control Cards to control the 24 motors that will be operating in the extremes of the Europa environment. The CAN bus was considered because of its multi-drop nature, low power interface, and simple communication protocol. Beyond communication with the motor controller cards we also use the CAN bus interface to gather telemetry from the Power Conversion Card. Our system requires the collection of telemetry at a rate of 64Hz from the Power Conversion Card and all active motor controllers along with the sending of control packets and the receipt of control parameters at 512 Hz. In the paper we will address the ability of the CAN bus to meet these requirements along with our Arduino based test system used to learn about the CAN bus standard and verify our analysis.

Lias, Malcolm↗
NASA NTRS2022

Draft LunaNet Interoperability Specification

This document, along with its companion documents, provides the basis for a comprehensive set of requirements for operation of a lunar communications and navigation network capable of interoperating with other networks compliant with the Lunar Network (LunaNet). LunaNet will include Earth ground stations and orbiting spacecraft and will provide services to human exploration, lunar science, and space technology missions. LunaNet will start with a simple architecture of a few nodes to meet the needs of the early missions and evolve to meet the growing needs of a sustained lunar presence. All relay network services are not expected to be met by a single spacecraft, or node. The expectation is that the needs of users will be met through a combination of interoperable systems provided by NASA, international partners, and commercial providers. Interoperability across this network-of-networks can be achieved through negotiation of mutually-agreed-upon standards that will be reflected in this document and in the specifications defined by other participants in the cooperative lunar network. This document was written and reviewed by NASA and the European Space Agency (ESA).

LunaNet↗
NASA NTRSDate not supplied

GeneLab for High Schools – Bioinformatic Training For Students And Educators

Modern biological sciences are increasingly based on high-throughput molecular techniques, including genomics, transcriptomics, and proteomics. NASA’s GeneLab program has collected extensive data from ‘omics’ studies, curated them into an accessible platform and provided data analysis/visualization tools to facilitate the generation of new hypotheses and research directions. GeneLab for High Schools (GL4HS), launched in 2017, has endeavored to utilize this database and provide tools for students to understand and analyze omics datasets whilst also learning about spaceflight research. The GL4HS program ran in person at Ames from 2017-2019 and has run virtually since 2020. Each year fifteen high school students are trained to analyze and interpret GeneLab transcriptomic data. Additionally, in the last several years we have expanded our “teacher training program” to include 10 teachers total in an effort to enable this program to be utilized in classrooms across the USA. Teachers also join the NASA GeneLab Education Working Group (EWG) enabling support as they implement custom GL4HS modules into their classrooms. The GL4HS program consists of three main components – (1) core learning modules, (2) networking and teamwork, and (3) an independent learning project. Students are also taught critical networking and science communication skills facilitating their ability to ‘sell their science’ in innovative and creative ways. This program has enabled students to learn about biology in space and to have a glimpse into the world of research for the first time. Many of the students in this program shared that the course was transformative to their perception about biological sciences and how it linked to other areas of STEM. The ultimate and long-term goal of GL4HS is to expand the program to multiple locations thereby facilitating the reach of NASA Space Biology beyond NASA-centric regions.

GeneLab↗
NASA NTRS2022

Draft LunaNet Interoperability Specification

This document, along with its companion documents, provides the basis for a comprehensive set of requirements for operation of a lunar communications and navigation network capable of interoperating with other networks compliant with the Lunar Network (LunaNet). LunaNet will include Earth ground stations and orbiting spacecraft and will provide services to human exploration, lunar science, and space technology missions. LunaNet will start with a simple architecture of a few nodes to meet the needs of the early missions and evolve to meet the growing needs of a sustained lunar presence. All relay network services are not expected to be met by a single spacecraft, or node. The expectation is that the needs of users will be met through a combination of interoperable systems provided by NASA, international partners, and commercial providers. Interoperability across this network-of-networks can be achieved through negotiation of mutually-agreed-upon standards that will be reflected in this document and in the specifications defined by other participants in the cooperative lunar network. This document was written and reviewed by NASA and the European Space Agency (ESA).

LunaNet↗
NASA NTRSDate not supplied

Machine Learning for the Validation of Expert-Elicited Causal Risk Diagrams

Exposure to spaceflight poses risk to human health in complex ways. To help manage this risk, the Human Systems Risk Board (HSRB) at the National Aeronautics and Space Administration (NASA) maintains a set of causal diagrams that attempt to explain how spaceflight hazards generate health risks and lead to adverse outcomes both in-mission, immediately post-mission, and over the long term. These causal risk diagrams are formulated as directed acyclic graphs (DAGs) and can function as knowledge graphs of connected risks and outcomes. These DAGs have proven useful for communication, and, through network analysis, have allowed for the identification of structurally important factors in the risk network. However, the utility these DAGs provide is directly proportional to their verisimilitude, making assessment of this trait using empirical data – whether from actual human spaceflight or various spaceflight analogue exposures and model organisms – a high priority. In this research we explore the use of machine learning algorithms to learn DAG structure from empirical data as a means of evaluating human-elicited DAG structures. To do so, we test several different graph structure-learning algorithms on data concerning changes in the bones of rats and mice after exposure to either spaceflight or a spaceflight analogue. We explore potential methods for indexing the similarity between each algorithm’s output DAG with all the others and with that of the expert-elicited DAG. We discuss next steps in this ongoing line of research and open science initiatives underway to complete them.

directed acyclic graphs↗
NASA NTRS2023

Expanding the Deep Space Network to Support the Heliophysics System Observatory

Difficulties associated with receiving telemetry from satellites severely limit the volume of scientific data that can be downlinked to the ground. Current missions employ techniques such as compressing and pruning datasets to reduce the data volume they transmit. While existing mission designs are already restricted by limited telemetry budgets, future Heliophysics System Observatory missions will produce ever larger data volumes with higher resolution and cadence observations from constellations of satellites spread throughout the heliosphere1. In addition, heliophysics missions often produce data for the operational Space Weather community that requires a low latency between observation and downlink. In light of current limitations, the infrastructure to receive NASA satellite telemetry must be expanded and modernized to support the science needs of future data-rich heliophysics missions.

deep space network (DSN)↗
NASA NTRS2024

NASA’s Lunar Communications and Navigation Architecture: Human Lunar Return

NASA’s Artemis missions will return humanity to the Moon, establishing a long-term presence there and opening more of the lunar surface to exploration than ever before. This rapid growth of lunar activity requires robust and resilient communications, navigation, and networking capabilities for crew safety, command and control of spacecraft, return of science data, and precise maneuvering of assets in space and on the lunar surface.

Michael J Zemba↗
NASA NTRSDate not supplied

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul D Mckee↗
NASA NTRSDate not supplied

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul McKee↗
DOE OSTI2020

Data Driven Online Learning of Power System Dynamics

With the advancement of sensing and communication in power networks, high-frequency real-time data from a power network can be used as a resource to develop better monitoring capabilities. In this work, a systematic approach based on data-driven operator theoretic methods involving Koopman operator is proposed for the online identification of power system dynamics. In particular, a new algorithm is provided, which unlike any previously existing algorithms, updates the Koopman operator iteratively as new data points are acquired. The proposed algorithm has three advantages: a) allows for real-time monitoring of the power system dynamics b) linear power system dynamics (this linear system is usually in a higher dimensional feature space and is not same as linearization of the underlying nonlinear dynamics) and c) computationally fast and less intensive when compared to the popular Extended Dynamic Mode Decomposition (EDMD) algorithm. The efficiency of the proposed algorithm is illustrated on an IEEE 9 bus system using synthetic data from the nonlinear model and on IEEE 39 bus system using synthetic data from the linearized model.

Sinha, Subhrajit↗
NASA NTRS1978

Network functions and facilities

The network is designed for two-way communications with unmanned spacecraft traveling approximately 16,000 km (10,000 miles) from earth to the farthest planets and to the edge of our solar system. The objectives, functions, and organization of the Deep Space Network are summarized. Deep space station, ground communication, and network operations control capabilities are described.

Renzetti, N. A.↗
NASA NTRS1973

The deep space network, volume 16

The objectives, functions, and organization of the DSN are summarized, and the instrumentation facility, ground communication facility, and the network control system are described. The requirements for supporting planetary flight projects are discussed along with the research and technology for tracking, navigation, network control, and data processing.

Source record↗
NASA NTRS2018

Next Generation Relay Services at Mars via an International Relay Network

Nearly all data acquired by vehicles on the surface of Mars are returned to Earth via Mars orbiters – more than 1.7 terabits so far. Successful communication between the various spacecraft is achieved via the careful implementation of internationally recognized CCSDS telecommunications protocols and the use of planning and coordination services provided by NASA’s Mars Program Office and the Multimission Ground Systems and Services (MGSS) Program at the Jet Propulsion Laboratory in Pasadena, CA. This modern Mars relay network has evolved since its inception in 2004 with the addition and loss of several missions, but it has fundamentally remained unchanged. Ground interfaces between the various spacecrafts’ mission operations centers on Earth remain largely unique for each participant, each mission maintains its own interfaces with deep space communications networks (e.g. DSN, ESTRACK), which are similar but still unique; and relay sessions at Mars require careful ground planning, coordination, and implementation. This paper will discuss the existing architecture and consider how several technologies may be applied to the next generation of relay services at Mars. Ultimately, these are expected to lead to the implementation of a delay and disruption tolerant network at Mars, a precursor to becoming a major element in an emerging Solar System Internet.

Edwards, Charles D. Jr↗
NASA NTRS2018

Assessing C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration's (NASA) Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude UAS operations. Currently there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. The UTM technical challenge will develop comprehensive and validated airspace operations and integration requirements to safely enable large-scale persistent access to visual line of sight and autonomous beyond visual line of sight small UAS in low-altitude airspace. Within the UTM project, a number of communications technologies to support UTM command and control (C2) are under investigation. In particular, commercial networked cellular systems are being tested and assessed for their ability to meet the reliability, scalability, cybersecurity and redundancy required. NASA Glenn Research Center is studying some of the aspects of employing such networks for UTM C2 communications. This includes the development of a test platform for sensing and characterizing the airborne C2 communications environment at various altitudes and in various terrains and topologies, measuring such aspects as received signal strength and interference. System performance aspects such as latency in the link, handover performance, packet error loss rate, drop outs, coverage gaps and other aspects impacting UTM operation will also be assessed. In this paper we explore some of the C2 approaches being proposed and demonstrated in the UTM project, the reliability, availability and other general C2 performance requirements, and approaches to evaluating and analyzing UTM C2 links based on commercial cellular networks.

air traffic control↗
NASA NTRS2014

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

ground stations↗