An Adaptive CFAR Detector for Range-Spread Target in Various Environments

In range-spread target detection, the background may be nonhomogeneous for part of target energy spreading into contiguous cells or adjacent targets existing in the reference window. Estimation deviation of clutter results in target masking effect. To deal with the problem, an adaptive constant false alarm ratio (CFAR) algorithm based on Variability Index (VI) and Ordered Data Variability (ODV) for range-spread target detection in various environments is proposed. The detector dynamically tailors background estimation and CFAR algorithm based on these statistics of the clutter reference samples. Performance of the proposed detector is evaluated in various backgrounds. Simulation results show that VI-ODV detector acts like CA-CFAR in a homogeneous background. Compared with CA, SO, Order statistics (OS) and VI-CFAR, VI-ODV has a better performance in nonhomogeneous environments and multiple targets background, meanwhile, the algorithm greatly reduces computational load in contrast with ODV-CFAR. The detector is showed to be of strong applicability for actual environments.