SIDLOC (Spacecraft Identification and Localization) is a new transmission scheme proposed by Libre Space Foundation to enable LEO satellite identification and tracking. The SIDLOC system relies on a reduced size autonomous transmitter that requires minimal integration and area on the carrier spacecraft. The ground segment of the SIDLOC system utilizes the existing SatNOGS network and the UHF band to perform the signal demodulation and identification. The SIDLOC system uses DSSS (Direct Sequence Spread Spectrum) PSK modulated signals with an effective bitrate of ~50 bits/s.

Project HyperClass aimed at accelerating the technology to process spectra received from single pixel images of space objects and:

i) extract the material composition of the object,

ii) classify the object according to a set of predefined features,

iii) estimate the attitude motion from the spectral lightcurve.

Visualisation is the bridge between the quantitative information hidden in the data and the human intuition and understanding; it is a challenge of key importance in the present ?Big Data? era. In all three segments of the Space Safety Programme (S2P) large amounts of data are produced daily. Adequate visualisation can lead to more effective analysis of diverse aspects and increase knowledge about the unfolding of different phenomena. For example, the main current means of visualisation of Space Weather phenomena used by scientists and operators are 2D and in few cases 3D graphs.

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During this Phase 0 maturation study, ASUK, with the support of Thales Alenia Space (TAS), Nammo, MDA and GMV, performed a programmatic, business and technical assessment of a future low-Earth orbit (LEO) refuelling mission. The mission concept proposes developing and demonstrating core technologies in a preliminary service offering to enable a commercial in-orbit refuelling service. Such a service will swiftly redefine how satellites are designed and operated, launching a dynamic and sustainable in-orbit ecosystem with significant potential.

In the frame of an In Orbit Servicing Maturation Phase (IOSMP) contract, this maturation study has been realised on the START-€ solution which is proposed to extend the lifetime of geostationary orbit (GEO) communication satellites. The START-€ servicer spacecraft will first demonstrate on a GEO communication satellite its ability to perform the critical operations related to its mission, before proceeding with several commercial life extension missions by capturing and taking the AOCS control of aged client spacecraft.

The Sun regularly releases considerable amounts of energy resulting in coronal mass ejections (CMEs) and accelerated particles, which can have a variety of adverse space weather effects at Earth and in the near-Earth environment. A useful means of tracking space weather activity is via solar radio bursts (SRBs) associated with CMEs and solar energetic particle events (SEPs); CME-driven shocks can be tracked via Type II SRBs, while energetic electrons escaping into the heliosphere can be tracked via Type III SRBs.

Space weather observations and the prediction of expected disturbances on ground- and space-based infrastructure are critical for the safety and evolution of our modern society. Space weather events, like solar storms, can have a significant impact on navigation, communication, power grids and other electrical conducting infrastructures. Therefore, space weather predictions are very important, but recently lack a reliable estimation of the geo-effectivity as well as detailed information for regions and systems potentially affected.

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.