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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Knowledge-based network operations

An expert system for enhancing the operability of the ground communication element of the Jet Propulsion Laboratory's Deep Space Network is described. The system performs network fault management, configuration management, and performance management in real time. Extracted management information serves as input to the expert system and is used to update a management information data base. The monitor and control activities involve dividing software for each processor into layers which are each modeled as a finite state machine.

Wu, Chuan-Lin↗
NASA NTRS2022

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗
NASA NTRS2005

Multi-Agent Modeling and Simulation Approach for Design and Analysis of MER Mission Operations

A space mission operations system is a complex network of human organizations, information and deep-space network systems and spacecraft hardware. As in other organizations, one of the problems in mission operations is managing the relationship of the mission information systems related to how people actually work (practices). Brahms, a multi-agent modeling and simulation tool, was used to model and simulate NASA's Mars Exploration Rover (MER) mission work practice. The objective was to investigate the value of work practice modeling for mission operations design. From spring 2002 until winter 2003, a Brahms modeler participated in mission systems design sessions and operations testing for the MER mission held at Jet Propulsion Laboratory (JPL). He observed how designers interacted with the Brahms tool. This paper discussed mission system designers' reactions to the simulation output during model validation and the presentation of generated work procedures. This project spurred JPL's interest in the Brahms model, but it was never included as part of the formal mission design process. We discuss why this occurred. Subsequently, we used the MER model to develop a future mission operations concept. Team members were reluctant to use the MER model, even though it appeared to be highly relevant to their effort. We describe some of the tool issues we encountered.

Seah, Chin↗
NASA NTRS1973

Demonstration of intercontinental DSN clock synchronization by VLBI

The prototype system for Deep Space Network clock synchronization by VLBI has been demonstrated to operate successfully over intercontinental baselines in a series of experiments between Deep Space Stations at Madrid, Spain, and Goldstone, California. As predicted by analysis and short baseline demonstration, the system achieves reliable synchronization between 26m and 64m antenna stations with 17 and 37K nominal system temperatures using under one million bits of data from each station. Semi-real-time operation is feasible since this small amount of data can be transmitted to JPL and processed within minutes. The system resolution is 50 to 400ns, depending on the amount of data processed and the source intensity. The accuracy is believed to be comparable to the resolution, although it could be independently confirmed to only about 5 microseconds using LORAN C.

Hurd, W. J.↗
NASA NTRS1979

DSN command system Mark 3-78

The Deep Space Network Command System Mark III-78 implementation and functional operation are described. Software upgrade enables expanded storage capacity in the Deep Space Station Command Processor Assembly. Store-and-forward command data handling is operational for Voyager and Helios. Near-real-time command data handling was retained for Viking and Pioneer.

Thorman, H. C.↗
NASA NTRS1976

A history of the deep space network

The Deep Space Network (DSN) has been managed and operated by the Jet Propulsion Laboratory (JPL) under NASA contract ever since NASA was formed in late 1958. The Tracking and data acquisition tasks of the DSN are markedly different from those of the other NASA network, STDN. STDN, which is an amalgamation of the satellite tracking network (STADAN) and the Manned Space Flight Network (MSFN), is primarily concerned with supporting manned and unmanned earth satellites. In contrast, the DSN deals with spacecraft that are thousands to hundreds of millions of miles away. The radio signals from these distant craft are many orders of magnitude weaker than those from nearby satellites. Distance also makes precise radio location more difficult; and accurate trajectory data are vital to deep space navigation in the vicinities of the other planets of the solar system. In addition to tracking spacecraft and acquiring data from them, the DSN is required to transmit many thousands of commands to control the sophisticated planetary probes and interplanetary monitoring stations. To meet these demanding requirements, the DSN has been compelled to be in the forefront of technology.

Corliss, W. R.↗
NASA NTRS1994

Development of a Prototype Real-Time Automated Filter for Operational Deep Space Navigation

Operational deep space navigation has in the past, and is currently, performed using systems whose architecture was designed to accommodate tape data transfers and computing environments with a tiny fraction of the current capability. Additionally, this architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational flow has been developed. This system will allow for more rapid response as well as much reduced staffing to support mission navigation operations.

deep↗
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 NTRS1981

DSN scheduling system

The Deep Space Network (DSN) Scheduling Group provides the operationally oriented administrative support necessary for the effective scheduling of the DSN. The scheduling system plus the levels of schedules are explained.

Dorham, R.↗
NASA NTRS1981

Radio astronomy

The activities of the Deep Space Network in support of radio astronomy operations during the first quarter of 1981 are reported. Results of the use of a low noise maser are presented, as well as updates in DSN support of experiments sanctioned by the Radio Astronomy Experiment Selection Panel.

Shaffer, R. D.↗
NASA NTRS1981

Radio astronomy

The activities of the Deep Space Network in support of Radio Astronomy Operations during April and May 1981 are reported. Work in progres in support of an experiment selected for use of the DSN by the Radio Astronomy Experiment Selection Panel, Twin Quasi-Stellar Object VLBI, is reported.

Wolken, P. R.↗
NASA NTRS1981

Pioneers 6 through 12 mission support

The continuing efforts of the Deep Space Network in support of Pioneer Mission Operations during the cruise phases of the Pioneers 6 through 11 spacecraft and Pioneer Venus orbital operations are discussed.

Nevarez, R. E.↗
NASA NTRS1984

Telecommunications and data acquisition support for the Pioneer Venus Project: Pioneers 12 and 13, prelaunch through March 1984

The support provided by the Telecommunications and Data Acquisition organization of the Jet Propulsion Laboratory (JPL) to the Pioneer Venus missions is described. The missions were the responsibility of the Ames Research Center (ARC). The Pioneer 13 mission and its spacecraft design presented one of the greatest challenges to the Deep Space Network (DSN) in the implementation and operation of new capabilities. The four probes that were to enter the atmosphere of Venus were turned on shortly before arrival at Venus, and the DSN had to acquire each of these probes in order to recover the telemetry being transmitted. Furthermore, a science experiment involving these probes descending through the atmosphere required a completed new data type to be generated at the ground stations. This new data type is known as the differential very long baseline interferometry. Discussions between ARC and JPL of the implementation requirements involved trade-offs in spacecraft design and led to a very successful return of science data. Specific implementation and operational techniques are discussed, not only for the prime mission, but also for the extended support to the Pioneer 12 spacecraft (in orbit around Venus) with its science instruments including that for radar observations of the planet.

Miller, R. B.↗
NASA NTRS1988

Heat exchanger expert system logic

The reduction is described of the operation and fault diagnostics of a Deep Space Network heat exchanger to a rule base by the application of propositional calculus to a set of logic statements. The value of this approach lies in the ease of converting the logic and subsequently implementing it on a computer as an expert system. The rule base was written in Process Intelligent Control software.

Cormier, R.↗
NASA NTRS2008

Architecture Study on Telemetry Coverage for Immediate Post-Separation Phase

This document is the viewgraphs that accompanies a paper that presents the preliminary results of an architecture study that provides continuous telemetry coverage for NASA missions for immediate post-separation phase. After launch when the spacecraft separated from the upper stage, the spacecraft typically executes a number of mission-critical operations prior to the deployment of solar panels and the activation of the primary communication subsystem. JPL, GSFC, and APL have similar design principle statements that require continuous coverage of mission-critical telemetry during the immediate post-separation phase. To conform to these design principles, an architecture that consists of a separate spacecraft transmitter and a robust communication network capable of tracking the spacecraft signals is needed. The main results of this study are as follows: 1) At low altitude (< 10000 km) when most post-separation critical operations are executed, Earth-based network (e.g. Deep Space Network (DSN)) can only provide limited coverage, whereas space-based network (e.g. Space Network (SN)) can provide continuous coverage. 2) Commercial-off-the-shelf SN compatible transmitters are available for small satellite applications. In this paper we present the detailed coverage analysis of Earth-based and Space-based networks. We identify the key functional and performance requirements of the architecture, and describe the proposed selection criteria of the spacecraft transmitter. We conclude the paper with a proposed forward plan.

architecture↗
NASA NTRS2008

Architecture Study on Telemetry Coverage for Immediate Post-Separation Phase

This paper presents the preliminary results of an architecture study that provides continuous telemetry coverage for NASA missions for immediate post-separation phase. This study is a collaboration effort between Jet Propulsion Laboratory (JPL), Goddard Space Flight Center (GSFC), and Applied Physics Laboratory (APL). After launch when the spacecraft separated from the upper stage, the spacecraft typically executes a number of mission-critical operations prior to the deployment of solar panels and the activation of the primary communication subsystem. JPL, GSFC, and APL have similar design principle statements that require continuous coverage of mission-critical telemetry during the immediate post-separation phase. To conform to these design principles, an architecture that consists of a separate spacecraft transmitter and a robust communication network capable of tracking the spacecraft signals is needed.This paper presents the preliminary results of an architecture study that provides continuous telemetry coverage for NASA missions for immediate post-separation phase. This study is a collaboration effort between Jet Propulsion Laboratory (JPL), Goddard Space Flight Center (GSFC), and Applied Physics Laboratory (APL). After launch when the spacecraft separated from the upper stage, the spacecraft typically executes a number of mission-critical operations prior to the deployment of solar panels and the activation of the primary communication subsystem. JPL, GSFC, and APL have similar design principle statements that require continuous coverage of mission-critical telemetry during the immediate post-separation phase. To conform to these design principles, an architecture that consists of a separate spacecraft transmitter and a robust communication network capable of tracking the spacecraft signals is needed. The main results of this study are as follows: 1) At low altitude (< 10000 km) when most post-separation critical operations are executed, Earth-based network (e.g. Deep Space Network (DSN)) can only provide limited coverage, whereas space-based network (e.g. Space Network (SN)) can provide continuous coverage. 2) Commercial-off-the-shelf SN compatible transmitters are available for small satellite applications. In this paper we present the detailed coverage analysis of Earth-based and Space-based networks. We identify the key functional and performance requirements of the architecture, and describe the proposed selection criteria of the spacecraft transmitter. We conclude the paper with a proposed forward plan.

architecture↗