Adaptive CFAR detector based on CA/GO/OS three-dimensional fusion

A new adaptive CFAR (Constant False Alarm Rate) detector based on CA/GO/OS three-dimensional fusion is proposed in this paper. The detector integrates the best detection performance of CA-CFAR, GO-CFAR and OS-CFAR in homogeneous environment, clutter edge environment and multi-target environment respectively, and uses the convex hull learning algorithm to use the decision convex hull for target detection in three-dimensional space. Through detailed simulation analysis in homogeneous environment, multi-target environment, clutter edge environment, multi-target and clutter edge simultaneous environment, it is proved that the detection performance of the CFAR detector in different environments has maintained a very high level and has a good ability to adapt to clutter environment.