Temporal Characterization of the Remote Sensors Response to Radiation Damage in L2

TL;DR

This paper presents TECSEL2, a big data system for analyzing radiation damage effects on spacecraft remote sensors at L2, with applications to Gaia and generic large time series datasets.

Contribution

Introduces TECSEL2, a novel big data-based system for characterizing sensor response to radiation damage and detecting anomalies in large time series data from space missions.

Findings

Effective detection of radiation-induced sensor anomalies.

Correlation between solar events and sensor malfunctions.

Applicable to Gaia and other large-scale time series datasets.

Abstract

Remote sensors on spacecrafts acquire huge volumes of data that can be processed for other purposes in addition to those they were designed for. The project TECSEL2 was born for the usage of the Gaia AIM/AVU daily pipeline output and solar events data to characterize the response of detectors subjected to strong radiation damage within an environment not protected by the terrestrial magnetic field, the Lagrangian point L2, where Gaia operates. The project also aims at identifying anomalies in the scientific output parameters and relate them to detectors malfunctioning due to radiation damage issues correlating with solar events occurred in the same time range. TECSEL2 actually designs and implements a system based on big data technologies which are the state of art in the fields of data processing and data storage. The final goal of TECSEL2 is not only related to the Gaia project, because it provides useful analysis techniques for generic and potentially huge time series datasets.