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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1968

Deep space FM system, a concept

Deep space frequency modulation system permits transmission of data where the signal deviation is greater than 1/2 the predetection bandwidth. It provides satisfactory performance at great distances or with low signal levels.

Doland, G. D.↗
NASA NTRS1979

The Deep Space Network

Progress on the Deep Space Network (DSN) supporting research and technology, advanced development, engineering and implementation, and DSN operations is presented. The functions and facilities of the DSN are described.

Source record↗
NASA NTRS1983

Interference susceptibility of a typical deep space network receiving system

The Deep Space Network (DSN), operated by the Jet Propulsion Laboratory for NASA, is used primarily for communication with interplanetary spacecraft. The high sensitivity required to achieve communication with distant spacecraft makes the DSN very susceptible to radio frequency interference (RFI). In this article a comprehensive description of the interference susceptibility of a typical DSN receiving system is given. Specifically, the effects of interference on the carrier tracking loop, the telemetry receiving subsystem, and the saturation effect on the maser, are presented.

Sue, M. K.↗
NASA NTRS1987

Navigation of spacecraft on deep space missions

The control of deep mission spacecraft by computing and signaling to the spacecraft a series of propulsive, velocity correction commands which maneuver the craft to its desired course is examined. The technical elements of the global navigation system (measurement, communications, computation, and propulsion) are described. The ground-computing facilities used to navigate spacecraft on deep space missions consist of computer and software systems used to compute orbits from radio tracking and on-board optical image data (radio, Doppler, and VLBI measurements). The accuracy of these measurements is evaluated, and the modeling of the data is discussed. Examples concerned with the navigation of Voyager and Galileo are presented.

Jordan, James F.↗
NASA NTRS2001

Trends in instrument systems for Deep Space Exploration

Instrument systems for deep space exploration have undergone dramatic changes in the last few years. They are smaller, lighter and less poer hungry. The line between science instruments and spacecraft sensors is blurring.

instruments sensors FIDO surface explorer↗
NASA NTRS1996

Extreme Deep Space Communications

Recent work in deep space telecommunication systems has been performed in support of NASA's Mission to the Solar System planning activity. The results show that high bandwidth communications (higher thatn 1 Mbps) are feasible with communication infrastructure investments at targets of high exploration activity. These targets include Mars, Jupiter, and Neptune. Infrastructure improvements must also be made at Earth.

space telecommunications Mission to the Solar Syst↗
NASA NTRS2003

The Deep Space Network large array

The Deep Space Network (DSN) is primarily used for telecommunications with scientific spacecraft engaged in solar system exploration.

DSN↗
NASA NTRS2006

Implementing Distributed Operations: A Comparison of Two Deep Space Missions

Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.

Cassini Mission↗
NASA NTRS2004

The Development of Large Inflatable Antenna for Deep-Space Communications

NASA/JPL's deep-space exploration program has been placing emphasis on reducing the mass and stowage volume of its spacecraft's high-gain and large-aperture antennas. To achieve these goals, the concept of deployable flat reflectarray antenna using an inflatable/thin-membrane structure was introduced at JPL several years ago. A reflectarray is a flat array antenna space-fed by a low-gain feed located at its focal point in a fashion similar to that of a parabolic reflector. The ref1ectarray's elements, using microstrip technology, can be printed onto a flat thin-membrane surface and are each uniquely designed to compensate for the different phase delays due to different path lengths from the feed. Although the reflectarray suffers from limited bandwidth (typically < 10%), it offers a more reliably deployed and maintained flat "natural" surface. A recent hardware development at JPL has demonstrated that a 0.2mm rms surface tolerance (l/50th of a wavelength) was achieved on a 3-meter Ka-band inflatable reflectarray. Another recent development, to combat the reflectarray's narrow band characteristic, demonstrated that dual-band performance, such as X- and Ka-bands, with an aperture efficiency of above 50 percent is achievable by the reflectarray antenna. To mechanically deploy the antenna, the reflectarray's thin membrane aperture surface is supported, tensioned and deployed by an inflatable tubular structure. There are several critical elements and challenging issues associated with the inflatable tube structure. First, the inflatable tube must be made rigidizable so that, once the tube is fully deployed in space, it rigidizes itself and the inflation system is no longer needed. In addition, if the tube is penetrated by small space debris, the tube will maintain its rigidity and not cause deformation to the antenna structure. To support large apertures (e.g. 10m or beyond) without causing any buckling to the small-diameter inflatable tube during vibration, the tube, in addition to rigidization, is also reinforced by circumferential thin blades, as well as axial blades. Second, a controlled deployment mechanism, such as by using Velcro strips, must also be implemented into the system so that, for very large structures, the long inflatable tubes can be deployed in a time-controlled fashion and not get tangled with each other. Third, the thermal analysis is another critical element and must be performed for the tube design in order to assure that the inflated tube, under extreme space thermal conditions, will not deform significantly. Finally, the dynamic vibration analysis must also be performed on the inflatable structure. This will investigate the response of the structure due to excitation introduced by the spacecraft maneuvering and thus determine any necessary damping. Several reflectarray antennas have been developed at JPL to demonstrate the technology. These include an earlier 1-meter X-band inflatable reflectarray, a 3-meter Ka-band inflatable reflectarray, a half-meter dual-band (X and Ka) reflectarray, and the current on-going 10-meter inflatable structure development. The detailed RF and mechanical descriptions of these antennas, as well as their performances, will be presented during the conference.

inflatable antenna↗
NASA NTRS2011

EPIC Radiance Simulator for Deep Space Climate ObserVatoRy (DSCOVR)

The Deep Space Climate ObserVatoRy (DSCOVR) is a planned space weather mission for the Sun and Earth observations from the Lagrangian L1 point. Onboard of DSCOVR is a multispectral imager EPIC designed for unique observations of the full illuminated disk of the Earth with high temporal and 10 km spatial resolution. Depending on latitude, EPIC will observe the same Earth surface area during the course of the day in a wide range of solar and view zenith angles in the backscattering view geometry with the scattering angle of 164-172 . To understand the information content of EPIC data for analysis of the Earth clouds, aerosols and surface properties, an EPIC radiance Simulator was developed covering the UV -VIS-NIR range including the oxygen A and B-bands (A=340, 388, 443, 555, 680, 779.5, 687.7, 763.3 nm). The Simulator uses ancillary data (surface pressure/height, NCEP wind speed) as well as MODIS-based geophysical fields such as spectral surface bidirectional reflectance, column water vapor, and properties of aerosols and clouds including optical depth, effective radius, phase and cloud top height. The original simulations are conducted at 1 km resolution using the look-up table approach and then are averaged to 10 km EPIC radiances. This talk will give an overview of the EPIC Simulator with analysis of results over the continental USA and northern Atlantic.

Lyapustin, Alexei↗
NASA NTRS2011

An Analysis of Database Replication Technologies with Regard to Deep Space Network Application Requirements

The Deep Space Network (DSN) has three communication facilities which handle telemetry, commands, and other data relating to spacecraft missions. The network requires these three sites to share data with each other and with the Jet Propulsion Laboratory for processing and distribution. Many database management systems have replication capabilities built in, which means that data updates made at one location will be automatically propagated to other locations. This project examines multiple replication solutions, looking for stability, automation, flexibility, performance, and cost. After comparing these features, Oracle Streams is chosen for closer analysis. Two Streams environments are configured - one with a Master/Slave architecture, in which a single server is the source for all data updates, and the second with a Multi-Master architecture, in which updates originating from any of the servers will be propagated to all of the others. These environments are tested for data type support, conflict resolution, performance, changes to the data structure, and behavior during and after network or server outages. Through this experimentation, it is determined which requirements of the DSN can be met by Oracle Streams and which cannot.

Oracle Database File System↗
NASA NTRS2006

Implementing distributed operations : a comparison of two Deep Space Missions

Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.

Larsen, Barbara↗
NASA NTRS2017

AI and Autonomy Initiatives for NASA’s Deep Space Network (DSN)

NASA’s Deep Space Network (DSN) consists of thirteen large (34- and 70-meter) antennas that are used to communicate with approximately 40 NASA and partner spacecraft, all at great distance from the earth (generally at Lunar distances and beyond). The DSN has a long history — over 50 years — and has evolved with cutting edge, often custom, telecommunications equipment and associated software systems. In recent years, and in preparation for an increasing future demand, there has been an effort to invest in initiatives that will result in significant cost savings in the future. These efforts are building on, or augmenting, the recent deployment of “Follow-the-Sun” operations (day shift remote operational control of the entire network from each of the three antenna complexes in turn) — which is being deployed in 2017. This paper focuses on Adaptive Demand Access: in a paradigm shift from completely pre-planned operations, this concept calls for spacecraft to signal their intent (or not) for near-future contacts, in case they have science results of interest, or have experienced an anomaly. This would take advantage of a beacon tone transmission, which can be detected using smaller antennas. When a connection request is received, the DSN ground systems would adaptively accommodate the request, inserting the contact into the plan as soon as possible, subject to constraints and priorities. The demand access concept incorporates onboard data analysis and science data processing, so that beacon tones can be generated with maximum information. This area is representative of several where infusing AI technologies can lead to improved effectiveness of the DSN as the network readies for support of expanded Mars exploration efforts in the 2020’s and beyond.

Wyatt, E. Jay↗