An adaptive censoring CFAR detector in non-homogeneous environments
杂乱
恒虚警率
计算机科学
同种类的
探测器
人工智能
算法
物理
雷达
电信
统计物理学
作者
Lulin Wang,Xingyu Mao,Guiru Liu,Jian Sun
标识
DOI:10.1117/12.3029371
摘要
Because variability index CFAR (VI-CFAR) and switching variability index CFAR (SVI-CFAR) detectors are affected by the number and location of interference targets and the number of clutter reference cells, a nonhomogeneous environment cannot be recognized accurately, resulting in a detection performance decline in a nonhomogeneous environment. This paper proposes an adaptive censoring CFAR detector (AC-CFAR), which first calculates the position of the transition and then identifies whether the subreference window starting from the transition is in a homogeneous environment. Then, based on the position of the transition and whether the subreference window is in a homogeneous environment, an appropriate method was selected from CA-CFAR, GO-CFAR and OS-CFAR to calculate the detection threshold. Monte Carlo simulation results show that the detection performance of AC-CFAR is consistent with that of VI-CFAR and SVI-CFAR, and near that of CA-CFAR in a homogeneous environment, but its performance is better than that of VI-CFAR and SVI-CFAR in a multitarget environment with a large number of interference targets. In particular, the number of interference targets is uneven on both sides of the cell being tested. In a clutter edge environment with less clutter, the false alarm rate of AC-CFAR is marginally lower than that of VI-CFAR and SVI-CFAR.