An adaptive hierarchal CFAR for optimal target detection in mixed clutter environments

In this paper a hierarchal adaptive switching (AS) CFAR procedure is presented that optimizes CFAR detection performance in the presence of mixed clutter environments. The algorithm selects a CA-CFAR scheme when detection is identified as being in a homogeneous environment and switches to OS-CFAR if the detection environment is non-homogeneous. In non-homogeneous areas, the reference window shape and size are also adapted to the local environment to optimize the probability of detection and to suppress the false alarm breakthrough due to clutter. Experimental results are presented that demonstrate the performance improvement of the hierarchal CFAR.