Space Situational awareness refers to keeping track of objects in orbit and predicting where they will be at any given time, which requires an accurate estimation of the state of objects orbiting around the Earth. These estimates are derived from networks of ground-based and space-based optical, radar, and laser sensors that operate worldwide to monitor the near-Earth environment continuously. This surveillance action, however, currently covers just a tiny portion of the resident space objects population whose size is continuously growing due to the unrelenting launch activity, coupled with in-orbit object generation events, such as collisions, fragmentations and explosions. Within Te Pūnaha Ātea, Space Institute (TPA-SI), we are devising new tools enabled by high-order techniques to obtain initial estimates of objects' states (initial orbit determination), determine whether multiple observations pertain to the same object (data association), refine such estimates (orbit determination), and finally recover the objects custody by estimating unknown manoeuvres performed. The goal is to create a fast and accurate suite of methods to build and maintain the ever growing catalogue of space objects

Short bio:

Laura Pirovano is a Research Fellow at Te Pūnaha Ātea - Space Institute, focussing on Space Situational Awareness. She received her BSc in Mathematical Engineering from Politecnico di Milano (Italy) in 2013 and her MSc in Aerospace Engineering - with a focus on Space Exploration - from TU Delft (Netherlands) in 2015. During her master's, she did an internship under the Erasmus+ scheme at FH Aachen (Germany) in collaboration with DLR on the coupling between elasticity of flexible structures and the 6 degrees-of-freedom orbital dynamics. She obtained her PhD in Aerospace engineering in 2020 from the University of Surrey on “Cataloguing space debris: Methods for optical data association", after spending 1.5 years at La Universidad de La Rioja (Spain). During her PhD, she carried out a research visit at the Space Debris Office (ESA-ESOC) to test her algorithms with real data and benchmark them with the approaches developed so far, thus gaining more insight into the operational side of the project.

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27.07.2023