Editorial: RSN Editorial 2023

Abstract

It is a pleasure to report that the Premium Award for the best paper published in the journal in 2020/21 is made to Samiur Rahman and Duncan Robertson of the University of St Andrews, Scotland, for their paper Classification of drones and birds using convolutional neural networks applied to radar micro-Doppler spectrogram images, which was published in the May 2020 issue, (Vol. 14 No. 5, pp. 653–661). Drones are becoming more and more widespread in both civil and military operations. It is necessary to be able to detect and classify these targets reliably, and radar is one of the most widely used sensors for the purpose. An important part of this involves distinguishing between drones and birds, which is complicated by the fact that birds and drones have comparable radar cross sections and travel at comparable speeds. However, the micro-Doppler modulation due to the flapping of wings of a bird or the rotation of propeller or rotor blades of a drone are significantly different, so provides a means of solving the problem. The paper describes and demonstrates a classification method based on Convolutional Neural Networks (CNNs) to recognise the features of the micro-Doppler signatures. Experimental data was gathered using two FMCW radars, one operating at 24 GHz and one at 94 GHz, at a local falconry. Excellent results were obtained, with classification accuracies better than 94% and in some cases very close to 100%. The paper is judged to be outstanding because it represents a substantial amount of work—both theoretical and experimental, because of its excellent and significant results, and because of the clarity of its writing. We warmly congratulate the authors on this award. The names of the members of the Editorial Board are listed on the journal page of the Wiley Online Library https://ietresearch.onlinelibrary.wiley.com/journal/17518792; the members are distinguished researchers who represent the full scope of the journal, and they come from all over the world. They help with reaching decisions on submitted papers, encouraging authors to submit their work to the journal, and proposing topics for Special Issues and Special Sections. Several have now reached the end of their term of appointment, and we thank them for their service over many years. We have also appointed a number of new members, and we welcome them to their task and look forward to their inputs. Finally, we express our gratitude to the reviewers for their time, expertise and hard work in refereeing papers and maintaining the reputation of the journal, both for quality and for rapid publication. This is an essential part of the publication process, but necessarily the reviewers must remain anonymous. This editorial is one place where we can acknowledge their contribution and record our thanks to them. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.