Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system
Riccardo Palamà, Francesco Fioranelli, Matthew Ritchie, Michael Inggs, Simon Lewis, Hugh Griffiths
Abstract
Abstract This article presents the results of a series of measurements of multistatic radar signatures of small UAVs at L‐ and X‐bands. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter‐receiver and two bistatic receivers. NeXtRAD is capable of recording simultaneous bistatic and monostatic data with baselines and two‐way bistatic range of the order of a few kilometres. The paper presents an empirical analysis with range‐time plots and micro‐Doppler signatures of UAVs and birds of opportunity recorded at several hundred metres of distance. A quantitative analysis of the overall signal‐to‐noise ratio is presented along with a comparison between the power of the signal scattered from the drone body and blades. A simple study with empirically obtained features and four supervised‐learning classifiers for binary drone versus non‐drone separation is also presented. The results are encouraging with classification accuracy consistently above 90% using very simple features and classification algorithms.