LAUSR

The main challenge of foreign objects debris (FOD) monitoring based on millimeter-wave (MMW) radar is the interference of strong ground clutter. The clutter-map constant false alarm rate (CM-CFAR) method is commonly utilized for FOD monitoring, but detection results are usually accompanied by many false alarms in the complex ground clutter environment. To solve this problem, this work proposed a false alarm elimination algorithm. Specifically, the CM-CFAR method is firstly used to separate the suspicious targets (including FOD and false alarms) from the background clutter. Then, the Duffing detection system is constructed to detect the sinusoidal frequencies associated with suspicious targets. Finally, according to the detection results of Duffing system, suspicious targets can be classified as FOD and false alarms. In addition, in order to detect the sinusoidal frequencies efficiently, a quantitative detection method based on Poincare section points analysis is proposed to identify the state transition of Duffing oscillator. The results from both simulation and field case show the excellent false alarm elimination performance of the proposed algorithm.