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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.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

pattern identification↗
NASA NTRS1982

NASA deep space network operations planning and preparation

The responsibilities and structural organization of the Operations Planning Group of NASA Deep Space Network (DSN) Operations are outlined. The Operations Planning group establishes an early interface with a user's planning organization to educate the user on DSN capabilities and limitations for deep space tracking support. A team of one or two individuals works through all phases of the spacecraft launch and also provides planning and preparation for specific events such as planetary encounters. Coordinating interface is also provided for nonflight projects such as radio astronomy and VLBI experiments. The group is divided into a Long Range Support Planning element and a Near Term Operations Coordination element.

Jensen, W. N.↗
NASA NTRS2001

Deep Space Network turbo decoder implementation

A new decoder is being developed by the Jet Propulsion Laboratory for NASA's Deep Space Network. This unit will decode the new turbo codes, which have recently been approved by the Consultative Committee for Space Data Systems (CCSDS). Turbo codes provide up to 0.8 dB improvement in Eb/No over the current best codes used by deep space missions.

turbo codes↗
NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗
NASA NTRS2011

Experimental Evaluation of Optically Polished Aluminum Panels on the Deep Space Network's 34 Meter Antenna

The potential development of large aperture ground?based "photon bucket" optical receivers for deep space communications has received considerable attention recently. One approach currently under investigation is to polish the aluminum reflector panels of 34?meter microwave antennas to high reflectance, and accept the relatively large spotsize generated by state of?the?art polished aluminum panels. Theoretical analyses of receiving antenna pointing, temporal synchronization and data detection have been addressed in previous papers. Here we describe the experimental effort currently underway at the Deep Space Network (DSN) Goldstone Communications Complex in California, to test and verify these concepts in a realistic operational environment. Two polished aluminum panels (a standard DSN panel polished to high reflectance, and a custom designed aluminum panel with much better surface quality) have been mounted on the 34 meter research antenna at Deep?Space Station 13 (DSS?13), and a remotely controlled CCD camera with a large CCD sensor in a weather?proof container has been installed next to the subreflector, pointed directly at the custom polished panel. The point?spread function (PSF) generated by the Vertex polished panel has been determined to be smaller than the sensor of the CCD camera, hence a detailed picture of the PSF can be obtained every few seconds, and the sensor array data processed to determine the center of the intensity distribution. In addition to estimating the center coordinates, expected communications performance can also been evaluated with the recorded data. The results of preliminary pointing experiments with the Vertex polished panel receiver using the planet Jupiter to simulate the PSF generated by a deep?space optical transmitter are presented and discussed in this paper.

optical receiver↗
NASA NTRS1979

Forecasting of loading on the Deep Space Network for proposed future NASA mission sets

The paper describes a computer program, DSNLOAD, which provides the Deep Space Network (DSN) loading information given a proposed future NASA mission set. The DSNLOAD model includes required pre- and post-calibration periods, and station 'overhead' such as maintenance or 'down' time. The analysis is presented which transforms station view period data for the mission set into loading matrices used to assess loading requirement. Assessment of future loading on the DSN for a set of NASA missions by estimating the tracking situation and presenting the DSN loading data, and a flowchart for selecting a possible future mission, determining a heliocentric orbit for the mission, generating view period schedules, and converting these schedules into basic loading data for each mission for each station are given. The tracking schedule model which considers the tracking schedule to be represented by passes of maximum required length and centered within the view period of available tracking time for each mission is described, and, finally, an example of typical loading study is provided.

Webb, W. A.↗
NASA NTRS1981

Deep space network software cost estimation model

A parametric software cost estimation model prepared for Jet PRopulsion Laboratory (JPL) Deep Space Network (DSN) Data System implementation tasks is described. The resource estimation mdel modifies and combines a number of existing models. The model calibrates the task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software life-cycle statistics.

Tausworthe, R. C.↗
NASA NTRS2001

Uplink-Downlink: A History of the Deep Space Network, 1957-1997

In these pages, the informed reader will discover a simple description of what the Deep Space Network (DSN) is about, and how it works an aspect of NASA's spectacular planetary program that seldom found its way into the popular media coverage of those major events. Future historical researchers will find a complete record of the origin and birth of the DSN, its subsequent development and expansion over the ensuing four decades, and a description of the way in which the DSN was used to fulfill the purpose for which it was created. At the same time, the specialist reader is provided with an abundant source of technical references that address every aspect of the advanced telecommunications technology on which the success of the DSN depended. And finally, archivists, educators, outreach managers, and article writers will have ready recourse to the inner workings of the DSN and how they related to the more publicly visible events of the planetary space program.

Mudgway, Douglas J.↗
NASA NTRS2012

Experimental Evaluation of the "Polished Panel Optical Receiver" Concept on the Deep Space Network's 34 Meter Antenna

The potential development of large aperture ground-based "photon bucket" optical receivers for deep space communications has received considerable attention recently. One approach currently under investigation proposes to polish the aluminum reflector panels of 34-meter microwave antennas to high reflectance, and accept the relatively large spotsize generated by even state-of-the-art polished aluminum panels. Here we describe the experimental effort currently underway at the Deep Space Network (DSN) Goldstone Communications Complex in California, to test and verify these concepts in a realistic operational environment. A custom designed aluminum panel has been mounted on the 34 meter research antenna at Deep-Space Station 13 (DSS-13), and a remotely controlled CCD camera with a large CCD sensor in a weather-proof container has been installed next to the subreflector, pointed directly at the custom polished panel. Using the planet Jupiter as the optical point-source, the point-spread function (PSF) generated by the polished panel has been characterized, the array data processed to determine the center of the intensity distribution, and expected communications performance of the proposed polished panel optical receiver has been evaluated.

photon counting detection↗
NASA NTRS1978

The deep space network

Progress in flight support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations at the Deep Space Network is reported.

Source record↗
NASA NTRS1992

Deep Space Network Antennas

Explore the source record for details and available documents.

antenna deep space network dsn telemetry planetary↗
NASA NTRS1975

The Deep Space Network

This report presents DSN progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations. Each issue presents material in some, but not all, of the following categories in the order indicated. - Description of the DSN - Mission Support Ongoing Planetary/Interplanetary Flight Projects Advanced Flight Projects - Radio Science - Special Projects - Supporting Research and Technology Tracking and Ground-Based Navigation Communications--Spacecraft/Ground Station Control and Operations Technology Network Control and Data Processing - Network and Facility Engineering and Implementation Network Network Operations Control Center Ground Communications Deep Space Stations - Operations Network Operations Network Operations Control Center Ground Communications Deep Space Stations - Program Planning TDA Planning Quality Assurance In each issue, the part entitled "Description of the DSN" describes the functions and facilities of the DSN and may report the current configuration of one of the five DSN systems (Tracking, Telemetry, Command, Monitor & Control, and Test & Training). The work described in this report series is either performed or managed by the Tracking and Data Acquisition organization of JPL for NASA.

Tracking and Data Acquisition organization↗
NASA NTRS1993

NASA's next generation all-digital deep space network breadboard receiver

This paper describes the breadboard advanced receiver (ARX) that is currently being built for future use in NASA's deep space network (DSN). This receiver has unique requirements in having to operate with very weak signals from deep space probes and provide high quality telemetry and tracking data. The hybrid analog/digital receiver performs multiple functions including carrier, subcarrier and symbol synchronization. Tracking can be achieved for either residual, suppressed or hybrid carriers and for both sinusoidal and square wave subcarriers. System requirements are specified and a functional description of the ARX is presented. The various digital signal processing algorithms used are also discussed and illustrated with block diagrams. Other functions such as time tagged Doppler extraction and monitor/control are also discussed including acquisition algorithms and lock detection schemes.

Hinedi, Sami↗
NASA NTRS1976

LS-44: An improved deep space network station location set for Viking navigation

Improved estimates for the spin axis and longitude components of the Deep Space Network station locations were obtained from post-flight processing of radio metric data received from various Mariner planetary missions. The use of an upgraded set of ionospheric calibrations and the incorporation of near-Venus and near-Mercury radio metric data from the Mariner 10 spacecraft are the principal contributing effects to the improvement. These new estimates, designated Location Set (LS) 44, have supported Viking navigation activities in the vicinity of Mars. As such, the station locations were determined relative to the planetary positions inherent in JPL Development Ephemeris (DE) 84, which was used throughout the Viking mission. The article also presents and discusses a version of LS 44 based upon the latest planetary ephemeris, DE 96.

Koble, H. M.↗
NASA NTRS1984

Effects of CW interference on the carrier tracking loop of the deep space network

A radio-frequency interference (RFI) environment can cause serious problems for communications systems, such as the Deep Space Network (DSN). For this reason, it is necessary to determine first the RFI susceptibility characteristics for DSN receiving systgms. The present investigation is concerned with CW RFI's which are close in frequency to the carrier frequency. The carrier tracking loop is highly sensitive, and this type of RFI will degrade the carrier loop performance before saturation effects become noticeable. The investigation has the objective to develop an analytical model which will make it possible to predict the tracking performance of the Block IV receiver when operated in the presence of a CW RFI in the receiver passband. The Block IV receiver represents one of the DSN receivers. Attention is given to the effects of a CW RFI on a phase-locked loop, the effects of a bandpass limiter, numerical results, experimental verification, and aspects of computer simulation.

Sue, M. K.↗
NASA NTRS2004

Amplitude Scintillation due to Atmospheric Turbulence for the Deep Space Network Ka-Band Downlink

Fast amplitude variations due to atmospheric scintillation are the main concerns for the Deep Space Network (DSN) Ka-band downlink under clear weather conditions. A theoretical study of the amplitude scintillation variances for a finite aperture antenna is presented. Amplitude variances for weak scattering scenarios are examined using turbulence theory to describe atmospheric irregularities. We first apply the Kolmogorov turbulent spectrum to a point receiver for three different turbulent profile models, especially for an exponential model varying with altitude. These analytic solutions then are extended to a receiver with a finite aperture antenna for the three profile models. Smoothing effects of antenna aperture are expressed by gain factors. A group of scaling factor relations is derived to show the dependences of amplitude variances on signal wavelength, antenna size, and elevation angle. Finally, we use these analytic solutions to estimate the scintillation intensity for a DSN Goldstone 34-m receiving station. We find that the (rms) amplitude fluctuation is 0.13 dB at 20-deg elevation angle for an exponential model, while the fluctuation is 0.05 dB at 90 deg. These results will aid us in telecommunication system design and signal-fading prediction. They also provide a theoretical basis for further comparison with other measurements at Ka-band.

Ho, C.↗
NASA NTRS2000

Deep Space Network turbo decoder implementation

A new decoder is being developed by the Jet Propulsion Laboratory for NASA's Deep Space Network. This unit will decode the new turbo codes, which have recently been approved by the Consultative Committee for Space Data Systems (CCSDS).

turbo decoder turbo code↗