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RadLab: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data
Sensors on multiple spacecraft in and beyond low Earth orbit continuously monitor and collect space radiation data and transmit it back to Earth. These data are of vast importance to space biology research, as ionizing radiation affects living organisms—astronauts and non-human experiment subjects alike—placing them at higher risk of carcinogenesis, degenerative diseases, and radiation sickness. Therefore, knowledge of the biological effects of space radiation is essential for planning future crewed missions beyond low Earth orbit. The RadLab project, initiated by GeneLab and ALSDA (the Open Science Data Repository; OSDR) and sponsored by the NASA Human Research Program, is a new effort aimed at connecting dosimetry data from radiation detectors located on the International Space Station (ISS), as well as other spacecraft. To date, access to these data has been fragmented across space agencies and databases; to address this issue, we have developed an application programming interface (API) and an associated graphical user interface (GUI) designed to provide a single point of access to the data. As of now, OSDR has focused on the detectors located on the ISS, with the long-term goal to establish a self-sustained portal receiving continuous updates through APIs connecting to multiple radiation databases of varying scope, as well as individual investigator contributions. The RadLab API implements a request syntax enabling users to query data by craft, sensor type, timespan, etc, allowing for arbitrary combinations of original source data, thus providing programmatic access for use in computational pipelines, while the GUI facilitates data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.
Automated Monitoring of Nuclear Weapon or Space Vehicle Health using Telemetry Data and Principle Component Analysis (PCA).
Abstract not provided.
Mariner Mars 1964 flight dynamic data
Telemetry data in and around Mars spacecraft area analyzed for Mariner III and IV space probes by data from vibration transducers on payload and microphones on umbilical tower
High resolution data processing for PFM TELEMETRY.
Data processing of PFM telemetry whereby resolution of frequency measurements is dependent upon SNR, for application to satellite parameters
Community threat intelligence and visibility for operational technology networks
Techniques are provided for community threat intelligence for operational technology networks. For a plurality of OT networks, at least one monitoring device processes OT network traffic and collects telemetry data, and a telemetry sanitization system applies a sanitization process to the telemetry data to generate sanitized telemetry data that does not include sensitive data. A computer system receives sanitized telemetry data from the telemetry sanitization systems provided for the plurality of OT networks, maintains threat intelligence data generated based on the sanitized telemetry data, and provides access to at least one of the threat intelligence data and the sanitized telemetry data to a plurality of users.
DSN telemetry system data records
The DSN telemetry system now includes the capability to provide a complete magnetic tape record, within 24 hours of reception, of all telemetry data received from a spacecraft. This record, the intermediate data record, is processed and generated almost entirely automatically, and provides a detailed accounting of any missing data.
Real time telemetry and data compression
The generation of telemetry and data compression by the flight program was verified. The adequacy of flight program telemetry control and timing is proven by the analysis of simulation laboratory runs of past programs through the use of telemetry. The telemetry data are correctly issued using specific tags called process input/output (P10) tags. Verification is accomplished by ensuring that a specific P10 tag and mode register setting identifies the correct parameter and that the data are properly scaled for subsequent ground station reduction. It was checked that the LVDC telemetry correctly adheres to the general requirements specified by the EDD. Data compression specifications are verified using compressed data from nominal flight simulations and from a series of perturbations designed to test data table overflows, data dump rates, and compression of data for occurrence events.
Data compression with error-control coding for space telemetry
Data compression with error-control coding for space telemetry
Satellite Telemetry and Data Recovery Systems
Satellite telemetry and data recovery systems
Low data rate telemetry RF system development
Low data rate telemetry radio frequency solid state transmitter for telecommunication system capable of surviving high impact on lunar or planetary surface
Pilot Heavy-Duty Electric Vehicle Deployment for Anchorage, Alaska, Municipal Solid Waste Collection
Through a grant awarded by the U.S. Department of Energy, the Municipality of Anchorage initiated a pilot program in their Solid Waste Services (SWS) department to add heavy-duty electric trucks to its vehicle fleet. The project involves the purchase and deployment of a Peterbilt 220EV electric box truck and two Peterbilt 520EV heavy-duty electric refuse trucks. The Alaska Center for Energy and Power at the University of Alaska Fairbanks performed data analysis. Data collected include telemetry data from both types of electric trucks, charging data from the 520EV telemetry data and a Level 2 charger, and facility-level electric use data.
Pilot Heavy-Duty Electric Vehicle Deployment for Anchorage, Alaska, Municipal Solid Waste Collection
Through a grant awarded by the U.S. Department of Energy, the Municipality of Anchorage initiated a pilot program in their Solid Waste Services (SWS) department to add heavy-duty electric trucks to its vehicle fleet. The project involves the purchase and deployment of a Peterbilt 220EV electric box truck and two Peterbilt 520EV heavy-duty electric refuse trucks. The Alaska Center for Energy and Power at the University of Alaska Fairbanks performed data analysis. Data collected include telemetry data from both types of electric trucks, charging data from the 520EV telemetry data and a Level 2 charger, and facility-level electric use data.
LANDSAT-D flight segment operations manual. Appendix A: Coefficients/calibration data
Telemetry calibration curves for the LANDSAT-4 subsystems are defined by nth order polynomial equations which convert telemetry counts to engineering units. The calibration curve coefficients for each telemetry point are controlled in the data base and are listed along with the unit section number where the sensor is located. Tables showing the coefficients may be obtained from the data base administrator. The tables show telemetry counts versus engineering units.
Telemetry and data processing systems for scientific satellites
Telemetry and data processing systems for scientific satellites
Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation
National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.
Telemetry and data relay for manned space programs
Previously and currently planned methods of transferring or relaying telemetered information from a remote receiving station to the Mission Control Center, at the National Aeronautics and Space Administration Lyndon B. Johnson Space Center, are discussed. The data flow techniques of the Apollo Program (fixed formats), the Skylab Program (data compression), and the Space Shuttle Program (data throughput) are defined and analyzed according to their advantages and deficiencies from an operations viewpoint. Excluded from the data flow technique discussions are command data, tracking data, television data, and Teletype and Datafax messages. Voice transmissions are addressed in the Space Shuttle Program discussion because they form a part of the telemetry data stream. The tradeoffs between actual data flow requirements and existing communications limitations are addressed for each of these programs. Finally, a short discussion of current problem areas in the planned ground data transmission system for the Space Shuttle Program is presented.