Transforming the Deep Space Network into the interplanetary network
Explore the source record for details and available documents.
DSN network communications navigation↗
SEARCH · Search NASA
Results for “DSN network communications navigation”
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.
The Telecommunications and Data Acquisition Report
Archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA) are provided. Activities of the Deep Space Network (DSN) in space communications, radio navigation, radio science, and ground-based radio astronomy are reported. Also included are the plans, supporting research and technology, implementation and operations for the Ground Communications Facility (GCF). In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. In the search for extraterrestrial intelligence (SETI), it reports on implementation and operations for searching the microwave spectrum.
Posner, E. C.↗
NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications
There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.
Telecommunication↗
Telecommunications technology development for the Deep Space Network
The telecommunications technology that is currently being developed for the Deep Space Network (DSN), a system providing communications and navigation support for NASA's deep space missions, is discussed. The major areas of development include Ka-band (32 GHz) technology, beam waveguide antennas, low-noise amplifiers, coding, navigation techniques, high-power transmitters, and optical technology. The expected payoffs of the new technology during the mid-1990's and later are examined.
Yuen, J. H.↗
The Deep Space Network information system in the year 2000
The Deep Space Network (DSN), the largest, most sensitive scientific communications and radio navigation network in the world, is considered. Focus is made on the telemetry processing, monitor and control, and ground data transport architectures of the DSN ground information system envisioned for the year 2000. The telemetry architecture will be unified from the front-end area to the end user. It will provide highly automated monitor and control of the DSN, automated configuration of support activities, and a vastly improved human interface. Automated decision support systems will be in place for DSN resource management, performance analysis, fault diagnosis, and contingency management.
Markley, R. W.↗
Scheduling NASA's Deep Space Network: Priorities, Preferences, and Optimization
NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40\% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process --- oversubsubscription and how to "fairly'" reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.
Johnston, Mark D↗
User Preference Optimization for Oversubscribed Scheduling of NASA’s Deep Space Network
NASA’s Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process — oversubsubscription and how to “fairly” reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.
Johnston, Mark D↗
The Deep Space Network: The challenges of the next 20 years - The 21st century
The Deep Space Network (DSN) has been the radio navigation and communications link between NASA's lunar and deep space missions for 30 years. In this paper, new mission opportunities over the next 20 years are discussed. The system design drivers and the DSN architectural concepts for those challenges are briefly considered.
Dumas, L. N.↗
NASA's Space Communications and Navigation Support to Planetary Probe Missions
No abstract available
navigation↗
Impasse-driven tutoring for reactive skill acquisition
We are interested in developing effective performance-oriented training for the operation of systems that are used for monitor and control purposes. We have focused on one such system, the communications Link Monitor and Control (LMC) system used in NASA's Deep Space Network (DSN), which is a worldwide system for navigating, tracking and communicating with unmanned interplanetary spacecraft. The tasks in this domain are procedural in nature and require reactive, goal-oriented skills; we have previously described a cognitive model for problem solving that accounts for both novice and expert levels of behavior as well as how skill is acquired. Our cognitive modeling work in this task domain led us to make a number of predictions about tutoring that have influenced the design of the system described in this paper.
Hill, Randall W., Jr.↗
Impasse-Driven Tutoring for Reactive Skill Acquisition
We are interested in developing effective performance-oriented training for the operation of systems that are used for monitor and control purposes. We have focused on one such system, the communications Link Monitor and Control (LMC) system used in NASA's Deep Space Network (DSN), which is a worldwide system for navigating, tracking and communicating with unmanned interplanetary spacecraft. The tasks in this domain are procedural in nature and require reactive, goal-oriented skills; we have previously described a cognitive model for problem solving that accounts for both novice and expert levels of behavior as well as how skill is acquired [Hill and Johnson, 1993]. Our cognitive modeling work in this task domain led us to make a number of predictions about tutoring that have influenced the design of the system described in this paper.
Johnson, W. Lewis↗
Traffic Modeling for Deep Space Network in the Human Mars Exploration Era
In this article we describe the analysis and simulation effort of the end-to-end traffic flow for the Deep Space Network (DSN) in the Human Exploration Era, when DSN will provide communication and navigation services for human missions to distant celestial objects like the Moon, asteroids, and Mars. Using the network traffic derived for the 30-day period within July/August 2039 from the Space Communications Mission Model (SCMM), we simulate the bandwidths of the ground links and the buffer profiles of the network nodes. We also use a 2-state Markov scheme that models the store-and-forward mechanism that regulates the ground network traffic. The network traffic modeling and simulation generates ground bandwidth and buffer statistics, which in turn are used to formulate the future DSN ground network bandwidth and storage requirements.
Cheung, Kar-ming↗
Navigation systems
The elements of the measurement and communications network comprising the global deep space navigation system (DSN) for NASA missions are described. Among the measurement systems discussed are: VLBI, two-way Doppler and range measurements, and optical measurements carried out on board the spacecraft. Processing of navigation measurement is carried out using two modules: an N-body numerical integration of the trajectory (and state transition partial derivatives) based on pre-guessed initial conditions; and partial derivatives of simulated observables corresponding to each actual observation. Calculations of velocity correction parameters is performed by precise modelling of all physical phenomena influencing the observational measurements, including: planetary motions; tracking station locations, gravity field structure, and transmission media effects. Some of the contributions to earth-relative orbit estimate errors for the Doppler/range system on board Voyager are discussed in detail. A line drawing of the DSN navigation system is provided.
Jordan, J. F.↗
Proposed upgrade of the Deep Space Network research and development station
Continued exploration of the solar system will require continued evolution of capabilities to support deep space communication and navigation. That evolution will rely, as it has in the past, on the development, demonstration, and field testing of communication and navigation technologies. The existing Deep Space Network (DSN) research and development station, DSS 13, at the Venus site, Goldstone, California was instrumental in those prior developments. However, the present antenna is no longer able to provide the necessary support for technology. The 26 meter antenna has good performance at S-band, fair performance at X-band, but is unusable at the anticipated Ka-band. It is not suitable for conversion to beam waveguides, and is not usable as a test bed for demonstrating high efficiency because of structural pliancy. Additionally, its size and age are increasingly a liability in demonstrations. A 34 meter beam waveguide version of the existing DSN high efficiency (HEF) antennas was proposed for FY-88 Construction of Facilities budget. The antenna is to be built at the Venus site, adjacent to the old antenna, and serve as the DSN research and development antenna through the end of the century.
Smith, Joel G.↗
A Demand Access Paradigm for NASA’s Deep Space Network
NASA’s Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. As part of an investigation into improved efficiency and responsiveness, we have been exploring and prototyping the infusion of a ”demand access” model into the DSN scheduling process. Today, DSN is fully pre-scheduled in advance, and many users rely on a stable schedule to plan their own spacecraft activities, weeks in advance of execution. However, a new class of missions is emerging that may not be scheduled as far in advance, and may be event-driven in coming across science targets at unpredictable times. These users could take advantage of an on-demand mechanism to download data. Simulations have shown that such a mechanism could improve latency (time from data collection to download) by 2x, as well as more efficiently utilize the available DSN antennas. In this paper, we describe a prototype of a demand access process and how it addresses the challenges of co-existing with a staticallyscheduled body of missions, while providing the benefits of lower latency science data return.
Lucena, Girly↗
Recommendations Emerging from an Analysis of NASA's Deep Space Communications Capacity
During 2016-2017, NASA’s Space Communications and Navigation (SCaN) Office chartered a study of Deep Space Network (DSN) communications capacity relative to projected future-mission demand over the next 30 years. In this paper, we briefly describe the methodology used to analyze capacity vs. demand over such a broad timeframe, summarize key findings emerging from the analysis, and discuss the associated recommendations. Performing the analysis entailed: identifying key factors shaping the anticipated future mission set, identifying several alternative future mission set scenarios consistent with these factors, and then analyzing each mission set scenario in terms of required antenna capacity, downlink and uplink capabilities, and spectrum as a function of time. On the basis of these aggregate requirements, DSN loading simulations were then conducted that examined how well each of the postulated mission sets could load up onto the the DSN’s “in-plan” architecture. To the extent that capacity shortfalls emerged during these baseline simulations, architectural solutions to the shortfalls were then postulated and tested via additional simulations. In general, the trend analyses and baseline loading simulations indicated a significant progression in challenges over the next three decades. In the current decade, the DSN appeared to be operating very close to capacity. The first human exploration mission and its secondary payload launch opportunities for cubesats traveling beyond GEO contributed to this loading. As a consequence, the main challenge appeared to be managing peak assetcontention periods. In the next decade, the DSN continued to operate close to capacity but also began transitioning to more frequent human mission support. Upgrading for, and operating, a human-rated system while continuing to meet robotic mission customer requirements emerged as the key challenge. In the 2030’s and beyond, simulations suggested a need for fundamentally new capability and capacity. The high data rates and long link distances characteristic of human Mars exploration drove requirements far beyond what is currently “in plan.” The key challenge then became determining the most cost-effective combination of RF and optical assets for communicating with the postulated human Mars assets while still providing for the needs of all the other missions across the solar system. Various link budget, visibility, and loading analyses ultimately suggested that the human Mars exploration demands of the 2030’s could best be addressed with two cross-linked RF-optical areostationary relays (or an areostationary relay and deep space habitat) providing a dual “trunk link” to an array of 2-to-3 additional 34m beam waveguide antennas and an ~8.5m optical antenna at each DSN Complex. The dual “trunk link” would enable the same amount of total data return to Earth as a single trunk link at twice the data rate, but with only half the required array size on the ground, assuming use of Multiple Spacecraft Per Antenna (MSPA) techniques. MSPA techniques, including a Multiple Uplink Per Antenna (MUPA) technique currently under investigation, also showed promise for reducing asset contention in the decades prior to human Mars exploration.
Lee, Carlyn-Ann↗
NASA’s Deep Space Network: Automation in the Follow-the-Sun Era
The Deep Space Network (DSN) comprises three sites, located in California, Spain, and Australia; each site operates one 70m and multiple 34m antennas that provide communications and navigation services to NASA and international partners. As part of a multiyear upgrade in automation of the network, the DSN has undertaken a series of operations efficiency improvements which has fundamentally changed the operations paradigm of the network. At the start of this effort, each site operated only their local antennas and equipment 24 hours/day, 7 days/week, and each spacecraft activity (link) had a single dedicated Link Control Operator. In its final stage, realized in 2020, each one of the three sites operates the entire network during their local day shift, handing off control to the next site as their day ends, and tracks can be run in a fully automated manner with no operator intervention. This paradigm change has realized significant operations cost savings, but has posed some major challenges along the way. This paper describes the system changes that enabled the operations efficiency improvements, some the challenges, and plans for the future.
Levesque, Michael↗
The Telecommunications and Data Acquisition Report
Developments in space communications, radio navigation, radio science, ground-base radio astronomy, reports on the Deep Space Network (DSN) and its Ground Communications Facility (GCF), and applications of radio interferometry at microwave frequencies are discussed.
Posner, E. C.↗