A Fuzzy CFAR Detection Method for Range-extended Targets with Enhanced Anti-jamming Capability

In order to improve the ability of the high resolution sonar to resist multi-target interferences in automatic detection, a CFAR detection scheme for range-extended targets based on automatic censoring cell averaging CFAR (ACCA-CFAR) method was proposed, which was suitable for Gauss reverberation background. It transformed the value of the target distance unit into the value of the fuzzy membership function mapped to the false alarm space by fuzzy ACCA-CFAR, and then used the fuzzy accumulation criterions to produce the detection statistic. The fuzzy arithmetic sum integrator, the fuzzy algebraic sum integrator and the fuzzy algebraic product integrator were considered. The fuzzy arithmetic sum integrator was first analyzed and the analytical expression of false alarm rate was derived. The simulation results show that the fuzzy algebraic product integrator has better performance in the fluctuating target model while the other two integrators have better performance in the non-fluctuating target model. The fuzzy ACCA-CFAR method has better anti-jamming performance than the existing fuzzy OS-CFAR method, especially when the number of jamming targets exceeds the theoretical upper limit.