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NASA NTRS1993

Deep Space Network (DSN), Network Operations Control Center (NOCC) computer-human interfaces

The Network Operations Control Center (NOCC) of the DSN is responsible for scheduling the resources of DSN, and monitoring all multi-mission spacecraft tracking activities in real-time. Operations performs this job with computer systems at JPL connected to over 100 computers at Goldstone, Australia and Spain. The old computer system became obsolete, and the first version of the new system was installed in 1991. Significant improvements for the computer-human interfaces became the dominant theme for the replacement project. Major issues required innovating problem solving. Among these issues were: How to present several thousand data elements on displays without overloading the operator? What is the best graphical representation of DSN end-to-end data flow? How to operate the system without memorizing mnemonics of hundreds of operator directives? Which computing environment will meet the competing performance requirements? This paper presents the technical challenges, engineering solutions, and results of the NOCC computer-human interface design.

Ellman, Alvin↗

NASA NTRS1994

DSN co-observing operations to support space VLBI missions

Reliable radio astronomy support of space very long baseline interferometry (VLBI) missions by ground radio telescopes is mandatory in order to achieve a high scientific return from the missions. The 70 m DSN antennas along with other ground radio telescopes will perform as the ground segment of the earth-space interferometer. Improvements of radio astronomy VLBI operations at the DSN to achieve higher reliability, efficiency, flexibility, and lower operations costs is a major goal in preparing for radio astronomy support of SVLBI. To help realize this goal, a remote control and monitoring mode for radio astronomy operations at the DSN has been developed.

Altunin, Valery I.↗

NASA NTRS1999

Propagation Effects of Importance to the NASA/JPL Deep Space Network (DSN)

This paper presents Propagation Effects of Importance To The NASA/JPL Deep Space Network (DSN). The topics include: 1) DSN Antennas; 2) Deep Space Telecom Link Basics; 3) DSN Propagation Region of Interest; 4) Ka-Band Weather Effects Models and Examples; 5) Existing Goldstone Ka-Band Atmosphere Attenuation Model; 6) Existing Goldstone Atmosphere Noise Temperature Model; and 7) Ka-Band delta (G/T) Relative to Vacuum Condition. This paper summarizes the topics above.

Slobin, Steve↗

NASA NTRS2006

The NASA Deep Space Network (DSN) Array

The DSN Array Project is currently working with Senior Management at both JPL and NASA to develop strategies towards starting a major implementation project. Several studies within NASA are concluding, all of which recommend that any future DSN capability include arraying of antennas to increase performance. Support of Deep Space, Lunar, and CEV (crewed exploration vehicle) missions is possible. High data rate and TDRSS formatting is being investigated. Any future DSN capacity must include Uplink. Current studies ongoing to investigate and develop technologies for uplink arraying; provides advantages in three ways: 1) N2 effect. EIRP grows as N2(-vs-N for a downlink array); 2) Improved architectural options (can separate uplink and downlink); and 3) Potential for more cost effective transmitters for fixed EIRP.

communications↗

NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

NASA NTRSDate not supplied

Near Rectilinear Halo Orbit Determination with Simulated DSN Observations

This paper presents the results of a high-fidelity simulation of spacecraft orbit determination in a near rectilinear halo orbit (NRHO). Others in the literature have examined this problem with linear covariance analysis, but the highly-nonlinear dynamics of this orbit challenge the assumptions underlying such analyses. The present work builds on similar analysis performed by other authors to contribute a fuller understanding of the operational requirements for NRHO navigation. The present work serves as a check to the assumptions of previous studies and an independent verification of those results. The results from the literature are extended by quantifying the space of orbital states from which a spacecraft with given control authority can safely return to the nominal path. Spacecraft state uncertainty estimates are evaluated as a function of time. Simulated range and range-rate measurements with the Deep Space Network (DSN) ground stations are used to model orbit determination accuracy. Orbit maintenance maneuvers are performed using both short-horizon and long-horizon stationkeeping targeting. Monte Carlo analysis of orbit determination and stationkeeping is performed. This paper quantifies the achievable state uncertainty with deep space network (DSN)-only range and range-rate observations. This paper also addresses requirements on the frequency of DSN observation periods and correlates ground contact frequency with navigation accuracy. The results of several related studies are presented and discussed: the effect of missing ground station passes, the effect of missing stationkeeping maneuvers, the sensitivity of the spacecraft state estimate to realistic error sources, and stationkeeping propellant budget.

Nathan L Parrish↗

NASA NTRS1994

DSN Co-Observing Operations to Support Space VLBI Missions

Reliable radio astronomy support of Space Very-Long-Baseline- Interferometry missions by ground radio telescopes is mandatory in order to achieve high scientific return from missions, The 70m DSN antennas along with other ground radio telescopes will perform as the ground segment of the Earth-space interferometer. Improvements of radio astronomy VLBI operations at the DSN to achieve higher reliability, efficiency, flexibility, and lower operations costs is a major goal in preparing for radio astronomy support of SVLBI. To help realize this goal, a remote control and monitoring mode for radio astronomy operations at the DSN is being developed.

radio↗

NASA NTRS1996

Space VLBI Co-Observing Developments in the DSN

The JPL/NASA Deep Space Network (DSN) plans to participate in the upcoming Space VLBI missions by using its 70m antenna time to co-observe with space-based radio telescopes. To enhance this support, the DSN is upgrading its radio astronomy equipment at L- and K-band, its VLBI recorders, and its computers and software for co-observing operations.

telescopes radio astronomy Jet Propulsion Laborato↗

NASA NTRS1995

Earth Rotation Parameters From DSN VLBI: 1995

A description of the DSN VLBI data set and of last year's analysis can be found in last year's report. Other than including another year's data, the main changes in this year's analysis from last year's are in the use of meteorological data for determining tropospheric parameters and in the weighting of the data to account for the uncertainty in the observables caused by tropospheric effects and source structure. A priori dry zenith tropospheric delays were determined from barometric pressure measurements at the DSN sites, corrected for height differences between the pressure sensor and the antennas. A priori wet zenith tropospheric delays were derived from tables of monthly average wet zenith delays for each station, which are based on historical radiosonde data. The Lanyi function was used for mapping zenith tropospheric delays to observed elevations. the temperature at the top of the boundary layer, a parameter in the Lanyi function, was taken to be the 24-hour average of the surface temperature at the station. Adjustments to the wet troposphere zenith delays were estimated every two to three hours.

Earth rotation, DSN, VLBI↗

NASA NTRS2005

Interference estimate around Canberra DSN Station at 2.04 GHz during Huygens release phase from Cassini

During the descent phase of the Huygens Probe released from the Cassini spacecraft and inserted at Titan, the Deep Space Network (DSN) Canberra Deep Space Station (DSS) 43 (with its 70-m antenna) is being considered as a backup station to directly receive the Huygens Probe data being transmitted at 2.04 GHz. This study provides an assessment on the interference level from the major nearby transmitters operating in this frequency band. The minimum trans-horizon attenuations are calculated using terrain topographic data and the Trans-Horizon Interference Propagation Loss (THIPL) Computing Program recently developed based on ITU-R P.452, and the calculations take into account all propagation modes under a 0.1% of time exceeded. We find that there are five terrestrial transmitters within 100 km of DSS 43. Transmitter 1 is the closest to DSS 43, and needs to be coordinated to avoid interference. The rest of the four transmitters will not interfere with DSS 43. The interference levels from these transmitters are all below the DSN protection criteria of 99.9% of time.

Deep Space Network (DSN)↗

NASA NTRS2007

DSN Antenna Array Architectures Based on Future NASA Mission Needs

A flexible method of parametric, full life-cycle cost analysis has been combined with data on NASA's future communication needs to estimate the required number and operational dates of new antennas for the Deep Space Network (DSN). The requirements were derived from a subset of missions in the Integrated Mission Set database of NASA's Space Communications Architecture Working Group. Assuming that no new antennas are 'constructed', the simulation shows that the DSN is unlikely to meet more than 20% of mission requirements by 2030. Minimum full life-cycle costs result when antennas in the diameter range, 18m-34m, are constructed. Architectures using a mixture of antenna diameters produce a slightly lower full life-cycle cost.

array↗

NASA NTRS2009

Estimating Accurate Relative Spacecraft Angular Position from DSN VLBI Phases Using X-Band Telemetry or DOR Tones

At present spacecraft angular position with Deep Space Network (DSN) is determined using group delay estimates from very long baseline interferometer (VLBI) phase measurements employing differential one way ranging (DOR) tones. As an alternative to this approach, we propose estimating position of a spacecraft to half a fringe cycle accuracy using time variations between measured and calculated phases as the Earth rotates using DSN VLBI baseline(s). Combining fringe location of the target with the phase allows high accuracy for spacecraft angular position estimate. This can be achieved using telemetry signals of at least 4-8 MSamples/sec data rate or DOR tones.

x-band telemetry↗

NASA NTRS1975

DSN telemetry system performance with convolutionally code data

The results obtained to date and the plans for future experiments for the DSN telemetry system were presented. The performance of the DSN telemetry system in decoding convolutionally coded data by both sequential and maximum likelihood techniques is being determined by testing at various deep space stations. The evaluation of performance models is also an objective of this activity.

Mulhall, B. D. L.↗

NASA NTRS1976

DSN ground communications facility

The Ground Communications Facility (GCF) is one of the three functional elements of the Deep Space Network (DSN) and provides the capability required for the transmission, reception, and monitoring of voice and data communications between the various locations of the DSN. The GCF uses common carrier circuits interconnected to specialized switching, terminal, and monitor equipment, integrated into a world-wide system, and operated in support of space flight missions. The five subsystems of GCF (Teletype, Voice, High-Speed, Wideband, and Monitor) are described. The Office of Tracking and Data Acquisition of the Jet Propulsion Laboratory provides the technical direction and systems management of the GCF and acts as the representative of NASCOM for communications switching functions on the west coast.

Glenn, M. S.↗

NASA NTRS1976

DSN research and technology support

Continuing remote controlled pulsar observations are noted, along with routine observations of 22 pulsars. Preliminary installation of equipment for planned unattended operation of the Venus Station is reported, along with extensive measurements and performance evaluation of the 26-m antenna. Support of the X-band radar at the Mars Station (DSS 14), and stability and reliability testing of the DSS 13 receiving system is reported. Klystron testing and other DSN support activities of the DSN High-Power Transmitter Maintenance Facility are noted, along with energy conservation modifications to two buildings at DSS 13. Radio Science experiment support included Planetary Radio Astronomy, Pulsar Rotation Constancy, Interstellar Microwave Spectroscopy, and Very Long Baseline Interferometry observations. An increased schedule of clock synchronization transmissions, planned on five-day centers, is noted, as 39 transmissions were made to Australia, DSS 43, and Spain, DSS 63.

Jackson, E. B.↗

NASA NTRS1977

DSN test and training system, Mark III-77

The Mark III-77 system is configured to support DSN testing and training in preparation for the Mariner-Jupiter-Saturn 1977 and Pioneer-Venus 1978 missions, in addition to the on-going in-flight missions. DSN Test and Trailing System capabilities include functions performed in the Deep Space Stations, Ground Communications Facility, and Network Operations Control Center.

Thornman, H. C.↗

NASA NTRS1977

Maintenance and operations cost model for DSN subsystems

A procedure is described which partitions the recurring costs of the Deep Space Network (DSN) over the individual DSN subsystems. The procedure results in a table showing the maintenance, operations, sustaining engineering and supportive costs for each subsystems.

Burt, R. W.↗