基于Takagi-Sugeno-Kang模糊集合的噪声干扰检测方法

为识别混合在接收机热噪声中的人为噪声干扰信号，提出了基于 TSK ( Takagi-Sugeno-Kang)模糊集合的干扰检测方法。首先将无干扰环境下信道热噪声数据和有人为噪声干扰下的混合噪声数据组合成训练数据序列，利用训练序列对TSK模糊集合模型进行训练，调节模型中规则的多项式系数，使TSK模糊模型对接收信号中的噪声特性与干扰判决之间建立确定函数关系，实现对噪声干扰的检测。通信电台的实验验证表明：尽管接收机的自动增益控制将外部噪声干扰缩小到与本机噪声相当水平，所提方法仍能有效检测出信道中是否有人为噪声干扰存在。

A Takagi-Sugeno-Kang fuzzy approach to noise jamming detection

This paper proposes a Takagi-Sugeno-Kang(TSK) fuzzy approach to detect if there is artificial noise mixed in the radio channel. The TSK fuzzy system needs to build a training sequence by sampling the signal with and without artificial noise separately and arranging it properly. The training sequence makes the TSK fuzzy system study the character of noise from different generating sources by adjusting the polynomial coefficients of fuzzy rules and enables it to detect the artificial noise interference. The test of the approach in a radio demonstrates that the proposed method can detect the artificial noise correctly even the automatic gain control of radio has reduced its power to the same level as that of thermal noise.