Satellite Anomaly Injection & Detection (SAID) Testbed
Satellites perform a host of vital functions including communications, weather prediction, geolocation, defense, and many others. In these complicated systems, it is extremely important that accurate data flows freely between the ground and the satellite via uplinks and downlinks. When strange behaviors or anomalies occur, it is vital that the errors be identified and corrected before a disaster occurs. Sometimes these anomalies are the result of errors in the hardware or software, issues introduced by the environment, or an attack by a hacker. Effective anomaly detection techniques can help identify problems on the vehicle before they happen, which can help improve mission success.
The operation of satellites in long-term term operation is affected by many uncertain factors. Anomaly detection based on telemetry data is a critical satellite health monitoring task that is important for identifying unusual or unexpected events. The use of simulation tools allows users to configure and deploy platforms to be used in real-time environments as well as simulate any anomalies that can take place. Machine learning can be used to detect these anomalies by comparing actual observed values with the predicted intervals of telemetry data. Simulation tools can be utilized by students to develop a way to solve these complex problems using applications already being used in the industry.
For this project, we have developed software components to integrate with and utilize existing industry open-source software components to perform the tasks outlined below to:
- Generate satellite simulation data
- Inject anomalous scenarios into the flight system
- Apply techniques for detecting the anomalies onboard and on the ground
Outcomes from the project:
- Software source to developed anomaly injection and detection capabilities
- Detailed documentation on design, implementation, tests, and results from each of the anomaly scenarios
- User manual to set up, configure, and run the OSK with the anomaly injection and detection capabilities
- Monthly review meetings with Aerospace liaisons and final outbrief to Aerospace engineers
Team Meetings with Advisor: Friday 2pm (with liaisons every 3 weeks)
Zoom Link: https://calstatela.zoom.us/j/88631222180
Student Led Meetings: Monday 6pm on Discord
Roles (details of Project Organization in Resources) |
Name | |
---|---|---|
Project Leads |
- Dearo Yam - Diana Degiacomo |
dearoyam.edu@gmail.com degiacomodiana@gmail.com |
Documentation Leads |
Diana Degiacomo Gabe Kutasi |
degiacomodiana@gmail.com fisherman_nab@yahoo.com |
Documentation Team |
Martha Caldera Rafael Zaragoza |
mcaldera2@yahoo.com raf.zaragoza@gmail.com |
Code Development Leads |
Dearo Yam Gustavo Torres |
dearoyam.edu@gmail.com gtorres9912@gmail.com |
Code Development Team |
Michael Morris Tomas Velarde Jae Lee |
michaeldmorris009@gmail.com tomasplaceholder@gmail.com Leejoe0368@gmail.com |
- Martha Caldera
- Diana Degiacomo
- Gabriel Kutasi
- Jae Lee
- Michael Morris
- Gustavo Torres
- Tomas Velarde
- Dearo Yam
- Rafael Zaragoza