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At least 37 records · Page 2

Creating an Interface to view Multi-Spacecraft Swarm Telemetry

Distributed Spacecraft Systems are a type of multi-spacecraft mission architecture that can not only provide improved resolution, coverage, and availability of existing missions, but also enable missions that would be previously infeasible using traditional approaches. Distributed Spacecraft Autonomy (DSA) is a project developed by the National Aeronautics and Space Administration that enables distributed spacecraft systems. In previous science swarm missions, the spacecraft involved have not been able to communicate with each other without utilizing a ground station. Now that the spacecraft can perform inter-satellite communication, the spacecraft can be treated as a collective. Swarm autonomy is critical for a growing number of satellites which means novel ways of displaying swarm data needs to be implemented. Such systems introduce unique challenges to traditional approaches for command and control of these spacecraft, due to the large number of spacecraft and the complexity of the interactions between them. The ground data system for DSA addresses these challenges through the creation of a custom user interface that allows a single operator to orchestrate a multi-spacecraft swarm in a scalable way. This plenary describes the details of the autonomy demonstration being performed, the requirements of those using the interface to analyze the spacecraft telemetry to assess demonstration success, and the approach taken by the ground systems team to create an interface that satisfies these requirements. This approach involves the creation of several distinct components that correspond to the level of detail presented to the user. These components are based on conventional user roles in human-robot interaction, including supervisor, operator, and mechanic, extended to accommodate the additional overhead of coordinating actions between agents. One main feature of the interface is the listenability matrix component which will represent inter-satellite communications in a heat mapped matrix. The above work described will enable users to command and interact with the spacecraft as a collective.

human-swarm interaction↗

Trends in Space Station telemetry applications

Spacecraft telemetry systems have evolved from simple hardware devices to complex computer applications performing data acquisition and formatting tasks. This paper reviews the role of spacecraft computers in performing telemetry functions and examines computer-based telemetry systems being considered for use on the NASA Space Station.

Muratore, John F.↗

Ulysses spacecraft control and monitoring system

The baseline Ulysses spacecraft control and monitoring system (SCMS) concepts and the converted SCMS, residing on a DEC/VAX 8350 hardware, are considered. The main functions of the system include monitoring and displaying spacecraft telemetry, preparing spacecraft commands, producing hard copies of experimental data, and archiving spacecraft telemetry. The SCMS system comprises over 20 subsystems ranging from low-level utility routines to the major monitoring and control software. These in total consist of approximately 55,000 lines of FORTRAN source code and 100 VMS command files. The SCMS major software facilities are described, including database files, telemetry processing, telecommanding, archiving of data, and display of telemetry.

Hamer, P. A.↗

Telemetry Metrics: Monitoring Data Quality in the Spacecraft Ground Data System

During the launch of Mars Odyssey, ground data system (GDS) engineers experienced a glitch in the ground data system that caused us to re-evaluate how we looked at spacecraft telemetry, particularly during the spacecraft development period and for critical spacecraft events in flight. Spacecraft telemetry told the subsystem and instrument engineers about the health and status of the spacecraft, but there was surprisingly little information about how well the ground data system was doing in getting information from the spacecraft to the engineers.The problem for the Mars Odyssey launch was with a single channel not updating as often as expected. Spacecraft engineers considered calling off the Launch but eventually decided that this particular channel did not provide information that was crucial for launch. It was only after the post launch acquisition of the Odyssey signal that ground data system engineers heard there had been a concern about the channel....

Mars↗

Process and methodology of developing Cassini G and C Telemetry Dictionary

While the Cassini spacecraft telemetry design had taken on the new approach of 'packetized telemetry', the AACS (Attitude and Articulation Subsystem) had further extended into the design of 'mini-packets' in its telemetry system. Such telemetry packet and mini-packet design produced the AACS Telemetry Dictionary; iterations of the latter in turn provided changes to the former. The ultimate goals were to achieve maximum telemetry packing density, optimize the 'freshness' of more time-critical data, and to effect flexibility, i.e., multiple AACS data collection schemes, without needing to change the overall spacecraft telemetry mode. This paper describes such a systematic process and methodology, evidenced by various design products related to, or as part of, the AACS Telemetry Dictionary.

Kan, Edwin P.↗

Estimating Torque Imparted on Spacecraft Using Telemetry

There have been a number of missions with spacecraft flying by planetary moons with atmospheres; there will be future missions with similar flybys. When a spacecraft such as Cassini flies by a moon with an atmosphere, the spacecraft will experience an atmospheric torque. This torque could be used to determine the density of the atmosphere. This is because the relation between the atmospheric torque vector and the atmosphere density could be established analytically using the mass properties of the spacecraft, known drag coefficient of objects in free-molecular flow, and the spacecraft velocity relative to the moon. The density estimated in this way could be used to check results measured by science instruments. Since the proposed methodology could estimate disturbance torque as small as 0.02 N-m, it could also be used to estimate disturbance torque imparted on the spacecraft during high-altitude flybys.

Lee, Allan Y.↗

GlastCam: A Telemetry-Driven Spacecraft Visualization Tool

Developed for the GLAST project, which is now the Fermi Gamma-ray Space Telescope, GlastCam software ingests telemetry from the Integrated Test and Operations System (ITOS) and generates four graphical displays of geometric properties in real time, allowing visual assessment of the attitude, configuration, position, and various cross-checks. Four windows are displayed: a "cam" window shows a 3D view of the satellite; a second window shows the standard position plot of the satellite on a Mercator map of the Earth; a third window displays star tracker fields of view, showing which stars are visible from the spacecraft in order to verify star tracking; and the fourth window depicts

Stoneking, Eric T.↗

Navigation Algorithms for the SeaWiFS Mission

The navigation algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were designed to meet the requirement of 1-pixel accuracy-a standard deviation (sigma) of 2. The objective has been to extract the best possible accuracy from the spacecraft telemetry and avoid the need for costly manual renavigation or geometric rectification. The requirement is addressed by postprocessing of both the Global Positioning System (GPS) receiver and Attitude Control System (ACS) data in the spacecraft telemetry stream. The navigation algorithms described are separated into four areas: orbit processing, attitude sensor processing, attitude determination, and final navigation processing. There has been substantial modification during the mission of the attitude determination and attitude sensor processing algorithms. For the former, the basic approach was completely changed during the first year of the mission, from a single-frame deterministic method to a Kalman smoother. This was done for several reasons: a) to improve the overall accuracy of the attitude determination, particularly near the sub-solar point; b) to reduce discontinuities; c) to support the single-ACS-string spacecraft operation that was started after the first mission year, which causes gaps in attitude sensor coverage; and d) to handle data quality problems (which became evident after launch) in the direct-broadcast data. The changes to the attitude sensor processing algorithms primarily involved the development of a model for the Earth horizon height, also needed for single-string operation; the incorporation of improved sensor calibration data; and improved data quality checking and smoothing to handle the data quality issues. The attitude sensor alignments have also been revised multiple times, generally in conjunction with the other changes. The orbit and final navigation processing algorithms have remained largely unchanged during the mission, aside from refinements to data quality checking. Although further improvements are certainly possible, future evolution of the algorithms is expected to be limited to refinements of the methods presented here, and no substantial changes are anticipated.

Hooker, Stanford B.↗

Template Matching Approach to Signal Prediction

A new approach to signal prediction and prognostic assessment of spacecraft health resolves an inherent difficulty in fusing sensor data with simulated data. This technique builds upon previous work that demonstrated the importance of physics-based transient models to accurate prediction of signal dynamics and system performance. While models can greatly improve predictive accuracy, they are difficult to apply in general because of variations in model type, accuracy, or intended purpose. However, virtually any flight project will have at least some modeling capability at its disposal, whether a full-blown simulation, partial physics models, dynamic look-up tables, a brassboard analogue system, or simple hand-driven calculation by a team of experts. Many models can be used to develop a predict, or an estimate of the next day s or next cycle s behavior, which is typically used for planning purposes. The fidelity of a predict varies from one project to another, depending on the complexity of the simulation (i.e. linearized or full differential equations) and the level of detail in anticipated system operation, but typically any predict cannot be adapted to changing conditions or adjusted spacecraft command execution. Applying a predict blindly, without adapting the predict to current conditions, produces mixed results at best, primarily due to mismatches between assumed execution of spacecraft activities and actual times of execution. This results in the predict becoming useless during periods of complicated behavior, exactly when the predict would be most valuable. Each spacecraft operation tends to show up as a transient in the data, and if the transients are misaligned, using the predict can actually harm forecasting performance. To address this problem, the approach here expresses the predict in terms of a baseline function superposed with one or more transient functions. These transients serve as signal templates, which can be relocated in time and space against the signal background. One then has the ability to reconstruct a signal regardless of the precise timing of the transients. During operation, one applies the actual start times of spacecraft activities as they occur, and produces a reconstructed, accurate predict in real-time. This general approach is valid under two important conditions. First, the transients themselves must be time-invariant. Second, the transients must be reasonably consistent with respect to different operating points. Both of these assumptions are generally valid, but in the case of a complicated system with numerous types of overlapping transients, this approach may not be effective. Fortunately, there tend to be few transients in spacecraft telemetry of sensor quantities or low-level health and status information because these signals rarely reflect multiple different types of operation. Furthermore, if the predict is at least reasonably close to actual operation, the shift either in time, or in the operating point when the transient occurs - is likely to be small. The proposed approach considers three ways to recognize a transient. The first and most reliable is to use a different signal that identifies operating mode - often the transient will be correlated to a change in operating mode, and this change can usually be detected positively from discrete signals in spacecraft telemetry. If there is no useful mode signal, the second option is to identify the transient template by hand, and detect the onset of the transient using a curve-fitting approach. Finally, if one elects not to choose by hand, there is an option for automatic selection. This technique has been applied to sensor data from several JPL missions and industrial applications, demonstrating an improvement in accurate prediction of future behavior and early detection of system problems. This technique is applicable to practically any time-varying, quantitative sensor measurement.

Mackey, Ryan↗

Telemetry communications guidelines

Data transmission capabilities of spacecraft telemetry communications systems, and guidelines for planning 1975-1980 missions

SPACECRAFT COMMUNICATIONS SYSTEM↗

Command and telemetry in autonomous spacecraft design

Some major steps are summarized in the evolution of autonomous design features for planetary exploration spacecraft. The control and data architectures for the Viking, Voyager, and Galileo spacecraft are considered. Telemetry and command capabilities are fundamental features of spacecraft design that have been successfully used for autonomous control. Also discussed is the Autonomous Redundancy and Maintenance Management Subsystem (ARMMS) concept. The software approach to autonomous control provides for modifications to the control process or the addition of new operating features during flight operations.

Turner, P. R.↗