edunetarchive/nachevsky_deep_satellite_telemetry_tracing

The project help to propagate anomalies in satellite telemetry.

Deep_Satellite_Telemetry_Tracing

The main goal is anomaly propagation in satellite telemetry. There are a several approaches to solve the problem, but the system reflects the case based on tracer implementation. The idea of applying the approach is inspired by the article. The implementation of the tracer is based on the project

Data preprocessing

Unfortunately, the real raw telemetry data cannot be displayed here due to security concerns. However, the data.tar file contains already preprocessed info to implement the tracing pipeline. In this case, the necessary information about the satellite system are angles, estimated and measured wheel velocities. The components form a state vector, and in this vector we can find anomalies by component.

The key steps of the preprocessing are:

1. get LOWESS curve to align raw telemetry
2. get absolute values for quantile barrier application and binarization.
3. create representation of state vector in the tracing problem form.

Results

Such a baseline is used by the telemetry of the on-board ARO system, which provides a solution to the same problem. According to the ROCAUC metrics, the ARO system quality is 54%, while the tracer quality is 82%.