Throwing-mine detection based on azimuth coherence

Throwing-mine detection is a typical problem of low RCS (radar cross section) targets detection in heavy clutter, in which the high false alarm rate is a difficult problem. Classical CFAR (Constant False Alarm Rate) detection algorithm only utilizes the image contrast characteristics, in the case of low SNR (Signal to Noise Ratio), a large number of false alarms generates. In order to further reduce false alarm rate, CFAR-IHP (Constant False Alarm Rate-Internal Hermitian Product) detection algorithm is proposed in this paper. CFAR-IHP is based on CFAR and target azimuth coherence characteristic, therefore, we first get the sub-aperture image sequence to extract target azimuth information by the sub-aperture processing algorithm for SAR image. Lastly, based on Ku-band SAR data, we use CFAR-IHP (Constant False Alarm Rate-Internal Hermitian Product) algorithm to detect the targets, experimental results show that the method further eliminate the clutter and the azimuth coherence helpfully reduces the false alarms.