On the Impact of Drone Airscrews Signature on Passive Radar Detection and Tracking Stages

In this paper, the impact of the drone airscrews signature in passive radars exploiting Digital Video Broadcasting signals is tackled. Beamforming techniques optimized to minimize the variance of the interference using the statistical characterization of real clutter data followed by a CFAR detector are used to detect drones and their associated airscrews signature. An independent bi-dimensional tracker based on the Kalman filter is proposed to tackle the drone and airscrews tracking process, and to extract micro-Doppler signature features. Real radar data acquired by a technological demonstrator developed at the University of Alcalá were used to evaluate the proposed solution. Results proved the suitability of the proposed detection and tracking schemes for airscrews signature feature extraction. Ansys HFSS electromagnetic simulator validated the results.