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.
UAV discrimination from birds using radar track information
Radar Sensor Technology XXVII ; 2023 ; Orlando, Florida, United States
Proc. SPIE ; 12535
2023-06-14
Conference paper
Electronic Resource
English
UAV discrimination from birds using radar track information
British Library Conference Proceedings | 2023
|Engineering Index Backfile | 1969
|A Hypothesis Testing Method for Phantom Track Discrimination in Centralized Radar Network
British Library Online Contents | 2015
|Radar target discrimination using neural networks
IEEE | 2010
|Radar characteristics of birds in flight.
NTRS | 1968
|