Open Source Paper Award Winners at RADAR 2024

Congratulations to Nathan Misaghi, Michael Parker, and Brian Ng for winning the Best Open Source Paper Award for the paper entitled "Target Localisation in Real Time for Non-Coherent Multistatic Passive Radar" at the 2024 International Radar Conference in Rennes, France.

Running radar research projects at universities has often proven to be difficult due to the amount of technical resources to build a radar from scratch, or the financial cost to purchase one off the shelf. Even more difficult can be the transfer of radar data from research labs and/or private companies to the university students, due to intellectual property concerns. To address this issue, a simple real-time and open-source radar software system has been developed, providing a low barrier to entry into collecting radar data and algorithm development.

The radar is designed to operate as a passive radar, utilising broadcast transmissions of opportunity. A number of software defined radios are supported including the SDRplay RspDuo, Ettus USRP devices and 2 HackRF’s with a common clock source. The signal processing consists of simple textbook algorithms for ambiguity processing, clutter filtering and detection.

A presentation was delivered at the International Radar Conference 2024 in Rennes, France which ran 3 passive radar nodes for multistatic target localisation. Each radar node was running the open-source software and reporting aircraft detections in real-time over the internet. Each node also associated its detections to an aircraft using ADS-B. A processing node ingested all the associated detections and used ellipse and ellipsoid intersections to plot the target position on a map.

Development of radar algorithms requires exposure to real data and lots of time spent looking at outputs to understand patterns (eyes on delay-Doppler maps). Although the radar is limited by 2-channel operation (reference and surveillance with no beamforming), it can serve as an entry level tool for radar algorithm development.

The real-time radar is available on GitHub at http://github.com/30hours/blah2 with setup instructions on the page. The multistatic target localisation code used in the paper can be found on the GitHub page of the author.

Written by Nathan Misaghi