reset password

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