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Radar track classification or discrimination is a capability that unlocks the potential of the common radar sensor that typically reports only track information. For example, in counter-UAV analysis there are many more tracks from birds and other moving clutter than from UAVs, so UAV radars can be overwhelmed with uninteresting tracks of birds. Track classification tries to identify the characteristics of UAVs in flight to discriminate UAVs from other tracks and thus to reduce false alarms. We have performed a pilot project on machine learning of the track characteristics to develop this capability, finding better than 90% sensitivity and specificity on recognizing multiple types of target UAVs.
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Dave Tahmoush, "UAV discrimination from birds using radar track information," Proc. SPIE 12535, Radar Sensor Technology XXVII, 125350X (14 June 2023); https://doi.org/10.1117/12.2666281