针对如何减小干扰环境下各传感器状态的不确定性对融合检测性能的影响,文中提出一种自适应神经网络-模糊推理融合检测系统。该系统通过自适应地综合处理传感器状态和传感器检测性能信息得到可靠的融合检测结果。仿真结果表明,在干扰环境下新的融合检测系统要明显优于其它几种传统的融合检测方法。 Aiming at how to reduce the influence of the uncertainty of each sensor state on the fusion detection performance in the interference environment, an adaptive neural network-fuzzy inference fusion detection system is proposed in this paper. The system achieves reliable fusion detection results by adaptively integrating sensor status and sensor performance information. The simulation results show that the new fusion detection system in interference environment is obviously better than the other several traditional fusion detection methods.