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ESA Operational Collision Avoidance UNOOSA – Promoting Space Sustainability 25th February 2021

Francesca Letizia ESA Office

ESA UNCLASSIFIED - Releasable to the Public 1 Collision avoidance service: why

Statistics Local perspective on space Collisions with objects debris at larger than 1 cm have the potential of prematurely ending a mission

Global perspective Collisions can significantly contribute to the Cosmos-Iridium collision evolution of the debris 3294 new objects environment

Accidental break-ups caused by collisions covered by standards (ISO 24113) and guidelines (UN LTS B.4) 2 Collision avoidance service: the missions

Sentinel 2A/B Institutional Cryosat-2 missions Sentinel 3A/B Third-party Cheops missions Proba 2

Sentinel 1A/B SAOCOM-1A/B Additional support to non-LEO missions B (, XMM, Integral) Swarm A, C and during LEOPs (MSG, Galileo, MetopC, Aelous Sentinel 6)

3 Our process at a glance DISCOS Space object Read more about our properties models process at SSA data CDMs Automated providers retrieval

Trajectories & Propagation MiniCat CRASS CORAM manoeuvre data

Flight Interface dynamics monitoring SCARF Trajectories & covariance data visualisation Flight control Debris team analysts 4 Data sharing – Operational products DISCOS Space B1.1 object weather properties models SSA data CDMs Automated providers retrieval Provide contact information (e.g. through space-track.org) B1.2 Regularly update own ’ information (orbit & manoeuvre plan) Adopt standard formats when exchanging information: Trajectories & Propagation• CDMs issuedMiniCat by SSA data providersCRASS CORAM manoeuvre data • OEMs for orbit information B2.3 • OPMs for manoeuvre data Flight Interface dynamics monitoring SCARF Trajectories & covariance data visualisation

5 Data sharing – information on objects DISCOS Space B1.5 object weather properties models SSA data CDMs Automated providers retrieval Data curation for objects in space Assess provided worldwide • normal users: web-based interface Trajectories & Propagation MiniCat CRASS CORAM manoeuvre data• operational users: API available

Backbone for several analysis activities such as compliance monitoring Flight Interface dynamics monitoring SCARF Trajectories & covariance data visualisation

6 Conjunction assessment DISCOS Space object weather properties models SSA data CDMs Automated Pool of chaser Check for Collision risk providers retrieval orbits and conjunctions computation covariance not in CDMs

Trajectories & Propagation MiniCat CRASS CORAM B4 manoeuvre data + (if needed) design of the Flight Interface avoidance dynamics monitoring manoeuvre SCARF Trajectories & covariance data visualisation

7 Conjunction assessment DISCOS Space object weather properties models SSA data CDMs Automated Pool of chaser Check for Collision risk providers retrieval orbits and conjunctions computation covariance not in CDMs

Trajectories & Propagation MiniCat CRASS CORAM B4 manoeuvre data C2 + (if needed) design of the We makeFlight available tools Interface(DRAMA) avoidance anddynamics methodologies to analysemonitoring the collision risk and reduction manoeuvre SCARF strategies duringTrajectories the design & of a missioncovariance data visualisation

8 Alerts & manoeuvres

Escalated events = alert to missions collision probability near pre-defined threshold & conjunction closer than 3 days Manoeuvre collision probability above pre-defined threshold & conjunction closer than ~ 1 day

For a Sentinel-like mission: • 1 alert/month • 1 manoeuvre/3 months For each manoeuvre • Negligible fuel consumption • ~8 hours of data outage 9 Alerts & manoeuvres

Escalated events = alert to missions C4 collision probability near pre-defined threshold & conjunction closer than 3 days Manoeuvre collision probability above pre-defined threshold & conjunction closer than ~ 1 day

For a Sentinel-like mission: • 1 alert/month • 1 manoeuvre/3 months For each manoeuvre • Negligible fuel consumption • ~8 hours of data outage 10 Conjunction statistics Data for events with collision probability > 10-6

11 Conjunction statistics Data for events with collision probability > 10-6

Payload-related debris Satellites

Rocket-related debris 12 Emerging trends: towards more automated systems

Current approach Research directions & future approaches

Assessment of historical conjunctions and model training

Approaches for automated (and explainable) decisions

Advanced manoeuvre design

Coordination of operators and Flight control Debris catalogue providers team analysts

13 Emerging trends: towards more automated systems

Current approach Research directions & future approaches

Assessment of historical conjunctions and model training

Approaches for automated Open competition in 2019(and explainable)for researchers decisions to test machine learning approaches D1 Distribution of anonymised operational CDMs to support research inAdvanced conjunction manoeuvre evaluation design

Coordination of operators and Flight control Debris catalogue providers team analysts

14 Emerging trends: small satellites & trackability

15 Conclusions

UN LTS Collision avoidance an operational reality for actors in space: B1 convergence of self-interest and long-term sustainability of operations as captured in the UN LTS Guidelines

B2 ESA process based on standardised products, curated object data, automated workflow + contribution in tools and B4 knowledge dissemination

The changes in the use of space call for C2 • Increased data quality and sharing • Improved coordination methods C4 • Increased automation

Developments in collisions avoidance activities are an important D1 pillar in ESA Space Safety Programme 16 Produced by

Follow @esaoperations for the latest graphics and podcasts on collision avoidance activity & sustainable operations realised in collaboration with UNOOSA 17 Dr. Francesca Letizia ESA/ESOC Space Debris Office (OPS-SD) Robert-Bosch-Str. 5, 64293 , T +496151902079 [email protected] http://www.esa.int/debris

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