摘要
为了提高舰载雷达抗箔条干扰的性能,提出了一种基于自适应模糊神经网络的抗箔条干扰方法。利用自适应模糊神经网络的非线性映射和学习能力,在舰载雷达目标回波信号受到箔条回波的强干扰下,对雷达目标进行识别,从而得到目标信号。仿真结果表明,该方法能有效地抑制箔条回波信号,且效果较好。
In order to improve anti-chaff-jamming capability of shipbrone radar system, this paper presents an anti-chaff-jamming method using adaptive fuzzy networks algorithm. When the target echo signals of shipbrone radar system is influenced by strong chaff-jamming, we can use the ability of nonlinear mapping and self-learning on adaptive fuzzy neural networks to recognize radar target and then get the target echo signals. The simulation result shows this method has a good performance in suppressing chaff-interference signals.
出处
《弹箭与制导学报》
CSCD
北大核心
2007年第1期204-206,210,共4页
Journal of Projectiles,Rockets,Missiles and Guidance
基金
企业协作攻关项目(校编11030401)
关键词
雷达
模糊神经网络
抗箔条干扰
目标识别
radar
fuzzy neural network
anti-chaff-jamming
target recognition
