From BEXUS to HEMERA: The application of lessons learned on the development and manufacturing of stratospheric payloads at S5Lab

In the last years the S5Lab (Sapienza Space Systems and Space Surveillance Laboratory) from Sapienza University of Rome has given to the students the opportunity to gather knowledge on stratospheric payloads by supporting the design and development of two experiments selected for the participation in the REXUS/BEXUS educational Programme, managed by three european space institutions. The insights and lessons learned gathered during the participations in the REXUS/BEXUS educational programme gave the possibility to the student to take part in the development of a third experiment in the frame of the professional research programme HEMERA and complete it successfully. STRATONAV (STRATOspheric NAVigation experiment) was a stratospheric experiment based on Software Defined Radios (SDRs) technology whose aim was the testing of the VOR (VHF Omnidirectional Range) navigation system, evaluating its performance above the standard service volume, which was launched on BEXUS 22 in October 2016. TARDIS (Tracking and Attitude Radio-based Determination In Stratosphere) was developed as a follow up of STRATONAV between 2018 and 2019. Similarly to its predecessor TARDIS was a stratospheric experiment aimed at exploiting the VOR signal, with the aid of SDRs, to perform in-flight attitude and position determination, and was launched on BEXUS 28 in October 2019. After the launch of TARDIS, a team composed both by former STRATONAV and TARDIS students was formed for the development of a third stratospheric experiment going by the name of STRAINS (Stratospheric Tracking Innovative Systems), conceived by Sapienza University of Rome and ALTEC and supported by ASI. STRAINS main objective was the proof of concept of the possibility of achieving the Time Difference of Arrival (TDOA) and the Frequency Difference of Arrival (FDOA) for navigation purposes with the aid of SDRs. The experiment was developed between 2020 and 2021 exploiting the lessons learned from the former team members of the tw