NEU4SST - Neuromorphic Processing for Space Surveillance and Tracking
Programme
Discovery
Programme Reference
EISI_I-2022-00363
Contractor
UNIVERSITY OF STRATHCLYDE
Start Date
End Date
Status
Closed
Country
United Kingdom
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Description
In this project the authors looked at event-based sensing and processing for space situational awareness (SSA). Many advantages exist with the new paradigm of neuromorphic engineering, the authors investigate whether event-based optical data is suitable for the task and if processing with Spiking Neural Networks (SNN) provides advantages in terms of efficiency and efficacy. With the implementation of a novel heterogeneous LIF SNN, authors claim to surpass the state of the art in event-based SSA with a 15% increase in accuracy.
Technology Domain
1 - On-board Data Subsystems
11 - Space Debris
16 - Optics
Competence Domain
3-Avionic Systems
5-Radiofrequency & Optical Systems and Products
10-Astrodynamics, Space Debris and Space Environment
Keywords
SSA
SST
Spiking Neural Networks
Executive summary