A New Deep Space Network for the Next Century
NASA's Deep Space Network (DSN) is responsible for providing communications, tracking, and
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The Deep Space Network, volume 17
The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.
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The deep space network, volume 18
The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.
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Understanding and Verifying Deep Neural Networks
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Deep Neural Networks↗
Maintenance of time and frequency in the Jet Propulsion Laboratory's Deep Space Network using the Global Positioning System
The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. Various methods are used to coordinate the clocks among the three tracking complexes. These methods include Loran-C, TV Line 10, Very Long Baseline Interferometry (VLBI), and the Global Positioning System (GPS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN Frequency and Timing System (DFT). Areas of discussion are: (1) a brief history of the GPS timing receivers in the DSN, (2) a description of the data and information flow, (3) data on the performance of the DSN master clocks and GPS measurement system, and (4) a description of hydrogen maser frequency steering using these data.
Clements, P. A.↗
Space Programs Summary no. 37-43, volume III for the period November 1 to December 31, 1966. The deep space network
Advanced communications techniques and control capability studies for Deep Space Network
INTERPLANETARY FLIGHT↗
Complexity-Based Link Assignment for NASA’s Deep Space Network for Follow-the-Sun Operations
NASA’s Deep Space Network (DSN) recently underwent a paradigm shift in its operations approach called Follow the Sun Operations (FtSO) in an effort to increase efficiency for forthcoming expansion of the network. This change requires each Deep Space Communications Complex (DSCC) to remotely control the other two complexes’ antennas during their local day shift, in contrast to locally controlling only their own antennas 24x7. Remote operations increases the workload of each complex during their day shift, specifically that of the Link Control Operators (LCOs), and presents a new challenge for planning and managing the distribution of responsibility for each link. A new DSN software assembly, the Link Complexity and Maintenance (LCM) software, was developed to support workload management for LCOs, as well as for planning site-local maintenance activities. The LCM deployment was a vital part of the transition to FtSO in November 2017. This paper discusses the architecture of LCM, its feature set, and lessons learned during its development and rollout.
Lee, Carlyn↗
(abstract) Spacecraft Doppler Tracking with the Deep Space Network in the Search for Gravitational Waves
The Deep Space Network generates accurate radio science data observables for investigators who use radio links between spacecraft and the Earth to examine small changes in the phase and/or amplitude of the signal to study a wide variety of structures and phenomena in space. Several such studies are directed at aspects of the theory of general relativity such as gravitational redshift and gravitational waves. A gravitational wave is a propagating, polarized gravitational field, a ripple in the curvature of space-time. In Einstein's theory of general relativity, the waves are propagating solutions of the Einstein field equations. Their amplitudes are dimensionless strain amplitudes that change the fractional difference in distance between test masses and the rates at which separated clocks keep time. Predicted by all relativistic theories of gravity, they are extremely weak (the ratio of gravitational forces to electrical forces is about 10(sup -40)) and are generated at detectable levels only by astrophysical sources - very massive sources under violent dynamical conditions. The waves have never been detected but searches in the low-frequency band using Doppler tracking of many spacecraft have been conducted and others are being planned. Upper limits have been placed on the gravitational wave strength with the best sensitivities to date are for periodic waves being 7 x 10(sup -15).
gravitational waves theory of general relativity D↗
Proposed Array-based Deep Space Network for NASA
The current assets of the Deep Space Network (DSN) of the National Aeronautics and Space Administration (NASA), especially the 70-m antennas, are aging and becoming less reliable. Furthermore, they are expensive to operate and difficult to upgrade for operation at Ka-band (321 GHz). Replacing them with comparable monolithic large antennas would be expensive. On the other hand, implementation of similar high-sensitivity assets can be achieved economically using an array-based architecture, where sensitivity is measured by G/T, the ratio of antenna gain to system temperature. An array-based architecture would also provide flexibility in operations and allow for easy addition of more G/T whenever required. Therefore, an array-based plan of the next-generation DSN for NASA has been proposed. The DSN array would provide more flexible downlink capability compared to the current DSN for robust telemetry, tracking and command services to the space missions of NASA and its international partners in a cost effective way. Instead of using the array as an element of the DSN and relying on the existing concept of operation, we explore a broader departure in establishing a more modern concept of operations to reduce the operations costs. This paper presents the array-based architecture for the next generation DSN. It includes system block diagram, operations philosophy, user's view of operations, operations management, and logistics like maintenance philosophy and anomaly analysis and reporting. To develop the various required technologies and understand the logistics of building the array-based lowcost system, a breadboard array of three antennas has been built. This paper briefly describes the breadboard array system and its performance.
telemetry↗
The deep space network, volume 2 Progress report, Jan. - Feb. 1971
Deep Space Network, Ground Communications Facility, Space Flight Operations Facility, and Deep Space Instrumentation Facility research and development - Vol. 2
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The deep space network, volume 7
The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Space Flight Operations Facility are described.
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Deep space network support of the Manned space flight network for Apollo, 1962 - 1968, volume 1
Deep Space Network support of Manned Space Flight Network for Apollo project
Flanagan, F. M.↗
Deep space network
Background, current status, and sites of Deep Space Network stations are briefly discussed.
Flanagan, F. M.↗
The Deep Space Network
The functions and facilities of the Deep Space Network, its supporting research and technology and network operations are discussed.
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The deep space network
A report is given of the Deep Space Networks progress in (1) flight project support, (2) tracking and data acquisition research and technology, (3) network engineering, (4) hardware and software implementation, and (5) operations.
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The deep space network
The functions and facilities of the Deep Space Network are considered. Progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations is reported.
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Ka-band (32-GHz) performance of 70-meter antennas in the Deep Space Network
Two models are provided of the Deep Space Network (DSN) 70 m antenna performance at Ka-band (32 GHz) and, for comparison purposes, one at X-band (8.4 GHz). The baseline 70 m model represents expected X-band and Ka-band performance at the end of the currently ongoing 64 m to 70 m mechanical upgrade. The improved 70 m model represents two sets of Ka-band performance estimates (the X-band performance will not change) based on two separately developed improvement schemes: the first scheme, a mechanical approach, reduces tolerances of the panels and their settings, the reflector structure and subreflector, and the pointing and tracking system. The second, an electronic/mechanical approach, uses an array feed scheme to compensate fo lack of antenna stiffness, and improves panel settings using microwave holographic measuring techniques. Results are preliminary, due to remaining technical and cost uncertainties. However, there do not appear to be any serious difficulties in upgrading the baseline DSN 70 m antenna network to operate efficiently in an improved configuration at 32 GHz (Ka-band). This upgrade can be achieved by a conventional mechanical upgrade or by a mechanical/electronic combination. An electronically compensated array feed system is technically feasible, although it needs to be modeled and demonstrated. Similarly, the mechanical upgrade requires the development and demonstration of panel actuators, sensors, and an optical surveying system.
Imbriale, W. A.↗
Operator assistant to support deep space network link monitor and control
Preparing the Deep Space Network (DSN) stations to support spacecraft missions (referred to as pre-cal, for pre-calibration) is currently an operator and time intensive activity. Operators are responsible for sending and monitoring several hundred operator directivities, messages, and warnings. Operator directives are used to configure and calibrate the various subsystems (antenna, receiver, etc.) necessary to establish a spacecraft link. Messages and warnings are issued by the subsystems upon completion of an operation, changes of status, or an anomalous condition. Some points of pre-cal are logically parallel. Significant time savings could be realized if the existing Link Monitor and Control system (LMC) could support the operator in exploiting the parallelism inherent in pre-cal activities. Currently, operators may work on the individual subsystems in parallel, however, the burden of monitoring these parallel operations resides solely with the operator. Messages, warnings, and directives are all presented as they are received; without being correlated to the event that triggered them. Pre-cal is essentially an overhead activity. During pre-cal, no mission is supported, and no other activity can be performed using the equipment in the link. Therefore, it is highly desirable to reduce pre-cal time as much as possible. One approach to do this, as well as to increase efficiency and reduce errors, is the LMC Operator Assistant (OA). The LMC OA prototype demonstrates an architecture which can be used in concert with the existing LMC to exploit parallelism in pre-cal operations while providing the operators with a true monitoring capability, situational awareness and positive control. This paper presents an overview of the LMC OA architecture and the results from initial prototyping and test activities.
Cooper, Lynne P.↗