Abstract
This paper addresses the problem of automatically allocating Collision Avoidance Manoeuvres under uncertainty by a robust Bayesian framework. This framework allows propagating the objects' uncertainty, predicting collisions, allocating manoeuvres, updating the state estimation with Bayesian inference, and redefining the manoeuvres, accounting at all steps for aleatory and epistemic uncertainty.
The Bayesian framework combines a robust particle filter for state estimation and uncertainty propagation, an intelligent agent for automatically classifying risk events and allocating avoidance manoeuvres, and a Collision Avoidance Manoeuvre optimiser for obtaining the optimal manoeuvre.
A test case is included to show the operation of the system. Two scenarios are presented: a collision and a near-miss conjunction.
The Bayesian framework combines a robust particle filter for state estimation and uncertainty propagation, an intelligent agent for automatically classifying risk events and allocating avoidance manoeuvres, and a Collision Avoidance Manoeuvre optimiser for obtaining the optimal manoeuvre.
A test case is included to show the operation of the system. Two scenarios are presented: a collision and a near-miss conjunction.
| Original language | English |
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| Number of pages | 11 |
| Publication status | Published - 23 Apr 2021 |
| Event | 8th European Conference on Space Debris - ESA/ESOC, Darmstadt, Germany Duration: 20 Apr 2021 → 23 Apr 2021 https://space-debris-conference.sdo.esoc.esa.int/ |
Conference
| Conference | 8th European Conference on Space Debris |
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| Country/Territory | Germany |
| City | Darmstadt |
| Period | 20/04/21 → 23/04/21 |
| Internet address |
Keywords
- robust Bayesian estimation
- intelligent agent
- collision avoidance optimisation
- epistemic uncertainty