Automatic Censoring CFAR Detector Based on Ordered. Data Difference with Noncoherent Integration

Nonhomogeneous clutter environments such as multiple target situation and clutter edge environment can dramatically affect the radar signal detection performance. In order to solve the problem, this paper proposes an automatic censored CFAR detector based on ordered data difference with non-coherent integration. The proposed CFAR detector does not require any prior information about the background enviromnent and uses the hypothesis test of first-order difference (FOD) result of ordered data to reject the unwanted samples in the reference window. After censoring the unwanted ranked cells, the remaining samples are combined to fonn an estimate of the background power level, thus getting better radar signal detection performance. The simulation results show that the CFAR detector provides low loss CFAR performance in a homogeneous enviromnent and also performs robustly in nonhomogeneous environments.