DUG Insight: A software package for big-data analysis and visualisation, and its demonstration for passive radar space situational awareness using radio telescopes
Dylan Grigg, Steven Tingay, Marcin Sokolowski, Randall Wayth

TL;DR
This paper demonstrates DUG Insight, a flexible software for large-scale radio astronomy data analysis, applied to passive radar detection of space objects and aircraft, enhancing space situational awareness capabilities.
Contribution
It introduces DUG Insight's capabilities for processing massive radio datasets and demonstrates its application in passive detection of space objects and aircraft.
Findings
Detected 19 unique RSOs within 1,500 km range
Processed nearly 68,000 sky images over three days
Showcased DUG Insight's scalability and flexibility
Abstract
As the demand for software to support the processing and analysis of massive radio astronomy datasets increases in the era of the SKA, we demonstrate the interactive workflow building, data mining, processing, and visualisation capabilities of DUG Insight. We test the performance and flexibility of DUG Insight by processing almost 68,000 full sky radio images produced from the Engineering Development Array (EDA2) over the course of a three day period. The goal of the processing was to passively detect and identify known Resident Space Objects (RSOs: satellites and debris in orbit) and investigate how radio interferometry could be used to passively monitor aircraft traffic. These signals are observable due to both terrestrial FM radio signals reflected back to Earth and out-of-band transmission from RSOs. This surveillance of the low Earth orbit and airspace environment is useful as a…
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Taxonomy
TopicsRadio Astronomy Observations and Technology · Antenna Design and Optimization · Spacecraft Design and Technology
