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Technical, administrative, and managerial data documentation by contractors on interfaces between Voyager project and related space programs
Lunar/earth data bank study, with user information requirements and system design concept
The Apollo management of data for postflight engineering evaluation is described. The sources of Apollo telemetry data, the control of data processing by a single data team, the data techniques used to assist in evaluation of the large quantity of data, and the operation of the data team before the mission and during the evaluation phase are described. The techniques used to ensure the output of valid data and to determine areas in which data were of questionable quality are also included.
Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition.
The data management system for the Large Space Telescope (LST) must be capable of meeting requirements of 160 million bits per 95 min orbit with a bit error rate of less than 0.00001 for data. The system will be supported by the Tracking and Data Relay Satellite System of the Space Tracking and Data Network. The on-board system includes a general purpose computer that controls the vehicle as a stable observation platform and the array of instruments used for data collection. The ground-based system comprises a Mission Operations Center (MOC), a Science Institute where instrument data is processed, and a communications service for the space and point-to-point data flow. The allocation of hardware and software between on-board and ground-based components to achieve design objectives of maximum flexibility at minimum cost is discussed.
The requirements, implementation techniques, and mission analysis associated with on-board data management for EOPAP were studied. SEASAT-A was used as a baseline, and the storage requirements, data rates, and information extraction requirements were investigated for each of the following proposed SEASAT sensors: a short pulse 13.9 GHz radar, a long pulse 13.9 GHz radar, a synthetic aperture radar, a multispectral passive microwave radiometer facility, and an infrared/visible very high resolution radiometer (VHRR). Rate distortion theory was applied to determine theoretical minimum data rates and compared with the rates required by practical techniques. It was concluded that practical techniques can be used which approach the theoretically optimum based upon an empirically determined source random process model. The results of the preceding investigations were used to recommend an on-board data management system for (1) data compression through information extraction, optimal noiseless coding, source coding with distortion, data buffering, and data selection under command or as a function of data activity, (2) for command handling, (3) for spacecraft operation and control, and (4) for experiment operation and monitoring.
Onboard checkout and data management system
System logic, data acquisition process, and digital data transmission system of onboard checkout and data management system
Viewgraphs on data management system technology discipline for Space Station Freedom are presented. Topics covered include: systems technology area needs; storage technology area needs; processor technology area needs; communications technology area needs; software system technology area needs; human interface technology area needs; software development and verification; and onboard communications.
Manufacturing engineering represents the crossroads of technical data management in a Computer Integrated Manufacturing (CIM) environment. Process planning, numerical control programming and tool design are the key functions which translate information from as engineered to as assembled. In order to transition data from engineering to manufacturing, it is necessary to introduce a series of product interpretations which contain an interim introduction of technical parameters. The current automation of the product definition and the production process places manufacturing engineering in the center of CAD/CAM with the responsibility of communicating design data to the factory floor via a manufacturing model of the data. A close look at data management requirements for manufacturing engineering is necessary in order to establish the overall specifications for CADD output, CAM input, and CIM integration. The functions and issues associated with the orderly evolution of computer aided engineering and manufacturing are examined.
State, local, and regional agencies involved in natural resources management were investigated as potential users of satellite remotely sensed data. This group's needs are assessed and alternative data management systems serving some of those needs are outlined. It is concluded that an operational earth observation data management system will be of most use to these user agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.
Five typical AMPS experiments were formulated to allow simulation studies to verify data management concepts. Design studies were conducted to analyze these experiments in terms of the applicable procedures, data processing and displaying functions. Design concepts for AMPS data management system are presented which permit both automatic repetitive measurement sequences and experimenter-controlled step-by-step procedures. Extensive use is made of a cathode ray tube display, the experimenters' alphanumeric keyboard, and the computer. The types of computer software required by the system and the possible choices of control and display procedures available to the experimenter are described for several examples. An electromagnetic wave transmission experiment illustrates the methods used to analyze data processing requirements.
The MOODS Data Management System (MDMS) provides access to the Master Oceanographic Observation Data Set (MOODS) which is maintained by the Naval Oceanographic Office (NAVOCEANO). The MDMS incorporates database technology in providing seamless access to parameter (temperature, salinity, soundspeed) vs. depth observational profile data. The MDMS is an interactive software application with a graphical user interface (GUI) that supports user control of MDMS functional capabilities. The purpose of this document is to define and describe the structural framework and logical design of the software components/units which are integrated into the major computer software configuration item (CSCI) identified as MDMS, Version 1.0. The preliminary design is based on functional specifications and requirements identified in the governing Statement of Work prepared by the Naval Oceanographic Office (NAVOCEANO) and distributed as a request for proposal by the National Aeronautics and Space Administration (NASA).
The use of computers in autonomous telerobots is reaching the point where advanced distributed processing concepts and techniques are needed to support the functioning of Space Station era telerobotic systems. Three major issues that have impact on the design of data management functions in a telerobot are covered. It also presents a design concept that incorporates an intelligent systems manager (ISM) running on a spaceborne symbolic processor (SSP), to address these issues. The first issue is the support of a system-wide control architecture or control philosophy. Salient features of two candidates are presented that impose constraints on data management design. The second issue is the role of data management in terms of system integration. This referes to providing shared or coordinated data processing and storage resources to a variety of telerobotic components such as vision, mechanical sensing, real-time coordinated multiple limb and end effector control, and planning and reasoning. The third issue is hardware that supports symbolic processing in conjunction with standard data I/O and numeric processing. A SSP that currently is seen to be technologically feasible and is being developed is described and used as a baseline in the design concept.
Groups associated with the design, operational, and training aspects of the International Space Station make extensive use of modeling and simulation tools. Users of these tools often need to access and manipulate large quantities of data associated with the station, ranging from design documents to wiring diagrams. Retrieving and manipulating this data directly within the simulation and modeling environment can provide substantial benefit to users. An approach for providing these kinds of data management services, including a database schema and class structure, is presented. Implementation details are also provided as a data management system is integrated into the Intelligent Virtual Station, a modeling and simulation tool developed by the NASA Ames Smart Systems Research Laboratory. One use of the Intelligent Virtual Station is generating station-related training procedures in a virtual environment, The data management component allows users to quickly and easily retrieve information related to objects on the station, enhancing their ability to generate accurate procedures. Users can associate new information with objects and have that information stored in a database.
The DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, videlicet knowledge-based expert systems, science visualization, and science data management. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system.
A low risk design methodology to permit the local bus structures to support increased data carrying capacities and to speed messages and data flow between nodes or stations on the Space Station Freedom Data Management System in anticipation of growing requirements was evaluated and recommended. The recommended design employs a collateral fiber optic technique that follows a NATO avionic standard that is developed, tested, and available. Application of this process will permit a potential 25 fold increase in data transfer performance on the local wire bus network with a fiber optic network, maintaining the functionality of the low-speed bus and supporting all of the redundant transmission and fault detection capabilities designed into the existing system. The application of wavelength division multiplexing (WDM) technology to both the local data bus and global data bus segments of the Data Management System to support anticipated additional highspeed data transmission requirements was also examined. Techniques were examined to provide a dual wavelength implementation of the fiber optic collateral networks. This dual wavelength implementation would permit each local bus to support two simultaneous high-speed transfers on the same fiber optic bus structure and operate within the limits of the existing protocol standard. A second WDM study examined the use of spectral sliced technology to provide a fourfold increase in the Fiber Distributed Data Interface (FDDI) global bus networks without requiring modifications to the existing installed cable plant. Computer simulations presented indicated that this data rate improvement can be achieved with commercially available optical components.
NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.