Imagine trying to listen to a whisper from the beginning of time, but a loud radio is playing right next to you. This work creates a high-tech 'noise-canceling' system to filter out the static from our own galaxy. By cleaning up this cosmic interference, we can finally hear the faint echoes of the Big Bang.
High-precision sensors are often blinded by 'foreground noise' from the environment. This makes it impossible to detect weak, critical signals without advanced filtering and separation techniques.
The project is building high-level data products, including updated radio catalogues and component-separated maps, along with simulation tools for future experiments.
If you are a satellite sensor manufacturer dealing with signal interference from galactic noise — this project developed advanced data analysis techniques and templates that improve the precision of signal separation. This allows for cleaner data acquisition in high-frequency bands.
If you are a machine learning software provider dealing with complex pattern recognition in noisy datasets — this project developed machine learning tools to isolate specific signals from overlapping contaminants. This enhances the accuracy of automated signal classification.
If you are an RF equipment developer dealing with the characterization of wide-spectrum radio emissions — this project developed updated catalogues of radio sources and magnetic field studies. This provides a better baseline for understanding background radio noise.
Based on available project data, no pricing or cost information is provided as the project is funded by a HORIZON-RIA grant.
The project focuses on high-level data products and models for the scientific community, but the underlying signal separation techniques are applicable to any high-noise RF environment.
Based on available project data, the results are intended to be made available through widely-used platforms for the scientific community, suggesting an open-access or academic licensing model.
The project period is from 2024-01-01 to 2026-12-31.
It integrates data from the Planck satellite with ground-based experiments like QUIJOTE, C-BASS, and S-PASS to support future missions like LiteBIRD.
The consortium is purely academic and research-driven, consisting of 6 partners from 4 countries (ES, FR, IT, UK). With 3 universities and 3 research organizations and 0% industry participation, the project is currently in a deep-tech discovery phase, focusing on fundamental physics and data modeling rather than immediate commercialization.
Contact the AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS in Spain.
Contact us to find partners for translating these signal-processing algorithms into commercial RF software.
