The next generation Python API for STK
An ontology of space situational awareness.
Data Driven Thermospheric Density Modeling with Machine Learning
The Orbital Debris Ontology (ODO) is an ontology of the orbital debris domain, containing classes for orbital entities and concepts, such as the types of orbital debris.
This repository includes all the necessary routines to run the CAM optimization with the method described in Pavanello et al. 2024.
Proyecto del Máster en Ingeniería de Telecomunicaciones (UAM) sobre clasificación de satélites y debris orbital usando datos TLE y Machine Learning (SVM, RF, XGBoost) en Python.
Space-Situational-Awareness-Operationsplattform mit FastAPI-Backend, Redis-Mission-Bus, Docker-Microservices, Security-Monitoring und Chaos-Injection.
Verteiltes Testbed für Space Situational Awareness (SSA): Docker-basierte FastAPI-/Worker-Architektur zur Analyse von orbitalen Konjunktionsereignissen mit PostgreSQL-Backend und optionalem QEMU-Sensor-Node.
The OSEO (or OSO-Orbital Space Ontology) is conceived as an alternative to the SSAO. The latter was originally described as the overall domain, but by demarcating the domain more precisely the OSEO/OSO name may better capture the overall domain. Name change is TBD, pending further researcher and domain demarcation.
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