Preserving dark skies with neuromorphic camera technology

Satellite streak contamination is becoming increasingly prevalent in wide-field astronomical imaging, as constellations of satellites are beginning to take shape in low Earth orbit (LEO). The problem looks set to worsen, with tens of thousands of satellites due to launch over the coming decade. The typically large uncertainties in satellite trajectories, coupled with their fast angular motion across the sky, make it challenging to reliably predict if/when they will pass within the field of view of a telescope. With the constellations here to stay, astronomers are urgently in need of preventative measures.

Neuromorphic (event-based) camera technology holds great promise for this area. Event-based cameras seek to replicate the functionality of the biological retina, efficiently registering only the meaningful information in a scene. They are capable of providing a near-continuous stream of information with much lower data rates than frame-based alternatives, both favourable characteristics for a rapid-response system.

We aim to develop a dual-purpose instrument to benefit both the astronomy and space domain awareness (SDA) communities, utilising neuromorphic technology to:

Detect satellites and supplement catalogues by refining existing (often out-of-date) orbital state information.
Provide early warning of satellites on course to contaminate an astronomical field of interest.
Capability (1) has significant commercial potential within the rapidly growing SDA market, highlighted in the National Space Strategy as an area in which the UK government has ambitions to establish global leadership. Existing surveillance networks are under immense strain due to the soaring population in LEO and there is a drive to develop new sovereign SDA sensors.

The proposed project will explore the capabilities of neuromorphic cameras when applied to space surveillance. Specifically, we identify the following key objectives:

Commissioning of a prototype instrument comprising a latest-generation neuromorphic camera and existing Warwick instrumentation at our campus observatory, and subsequently at our facilities in La Palma, Canary Islands.
Development of software for data reduction, calibrations for brightness and position, satellite detection, and trajectory refinement, building from existing algorithms developed during the Project Lead's STFC-funded PhD studentship.
Simulation of different sensor architectures to establish an optimal observational strategy for the early warning system, taking both the satellite contamination problem and requirements for SDA into consideration.
Proof-of-concept study to validate the findings from the sensor architecture simulation with the prototype instrument, making use of catalogued information to assess the instrument's performance when faced with a variety of scenarios.