CFAR Detection Method in Multi-target Environments for Foreign Object Debris Surveillance Radar

Detection of weak targets in heavy ground clutter is the key issue for Foreign Object Debris (FOD) surveillance radar on airport runways. Since of “target-masking” effect, traditional CFAR detection algorithms cannot detect FOD in multi-target environments effectively. To solve these problems, a trimmed-mean clutter-map CFAR method based on order-statistics is proposed in this paper. First, multi-target echo model of Frequency Modulation Continue Wave (FMCW) radar on airport runways is established. Then, several of the largest samples in reference window are discarded and the remaining ones are averaged as the clutter-level estimation to tolerate interfering targets. In order to obtain a stationary detection threshold to reduce false alarm probability, clutter-map cells are updated scan-by-scan in time domain. At last, simulations verify effectiveness of this proposed method.