ARGUS: A UK Citizen Science study in support of the Surveillance of Space
Year: 2019

Space debris poses a collisional risk to satellites that are essential to everyday life here on Earth. This issue is not, however, always appreciated by the wider public outside the space tracking domain. Dstl initiated the Argus experiment (named after the Greek god known as "the all seeing one" with the aim of harnessing the enthusiasm of amateur astronomers within the UK to bring space debris tracking to the masses. Argus was a Citizen Science project, involving scientists at the United Kingdom's (UK) Ministry of Defence's Defence Science and Technology Laboratory (Dstl) working with members of the Basingstoke Astronomical Society (BAS) Argus examined the potential utility of employing a distributed array of amateur grade astronomical imaging systems to inform the development of an indigenous UK Space Situational Awareness (SSA) capability. BAS members used their equipment to take observations of low Earth orbit (LEO) satellites selected from those routinely tracked by the International Laser Ranging Service (ILRS) Dstl extracted satellite positions from the resulting images and used in house software to determine an orbit fit to the data. The results were critically compared to published ILRS measurements. This activity highlighted shortcomings in our existing image processing software and orbital dynamics modelling software, and provided an opportunity to ingest a large dataset from a heterogeneous architecture and test the performance of Dstl's software. This emphasised the criticality of timing accuracy. Comparison by Dstl of initial measurements to ILRS predictions revealed significant timestamp accuracy issues with the commercially available astronomical software used by BAS members in the control of their cameras. BAS developed both hardware and software solutions to significantly increase the timestamp accuracy. These techniques included characterisation of camera timing delays and clock synchronisation, ultimately achieving synchronisation to within approximately 2 milliseconds. The project prompted significant development of Dstl's in house software. Dstl's image processing software automatically detects and measures satellite trails in optical images. The image processing software has been ported from two independent IDL and MATLAB instances into a Python implementation which includes a number of improvements. These include improved rejection of false positives, a lower detection threshold and the automatic association of related trails. The robustness and utility of Dstl's orbit determination software, Mission Planner, was improved by the implementation of timing bias estimation and a Levenberg Marquardt algorithm. Argus has highlighted infrastructure issues which would have to be addressed by any operational SSA system such as automation and remote operation, connectivity, data standardisation, sensor availability and sensor tasking. Additionally, it provided a better appreciation of the benefits and difficulties associated with Citizen Science collaborations. The experiment also determined the capabilities and limitations of using amateur grade equipment for SSA. This experiment marks the first time that Dstl has conducted a citizen science project. The technical expertise and enthusiasm of BAS for the project played a significant role in its success. Argus has demonstrated that amateurgrade equipment is capable of observing a reasonable proportion of the LEO satellite population.