针对复杂电磁环境下相位编码(Phase Shift Key,PSK)信号干扰识别问题,研究瞄准式干扰(Spot Jamming,SJ)、阻塞式干扰(Blocking Jamming,BJ)、线性扫频式干扰(Linear Sweep Jamming,LSJ)、灵巧噪声卷积干扰(Noise Convolution Jamming,NCJ)、灵巧噪声乘积干扰(Noise Product Jamming,NPJ)、间歇采样直接转发干扰(Interrupted-Sampling and Direct Repeater Jamming,ISDJ)、间歇采样重复转发干扰(Interrupted-Sampling and Periodic Repeater Jamming,ISPJ)及间歇采样循环转发式干扰(Interrupted-Sampling and Cyclic Repeater Jamming,ISCJ)的匹配滤波序列,人工提取16 维特征组成特征向量放入支持向量机(Support Vector Machine,SVM)进行分类识别.仿真实验表明:干噪比(Jamming Noise Ratio,JNR)为-20～30 dB至16～30 dB时,识别率随JNR的增加而提高;JNR为-2～30 dB时,识别率为 94.89%;模拟JNR为-2～30 dB的真实环境时,保留8维特征参数,算法识别率可达 93.62%,仅降低1.27%.
Active Interference Identification Algorithm for PSK Radar Signal Based on Matched Filter Domain
In response to the interference recognition problem of PSK signals in complex electromagnetic environments,this study investigates the matching filtering sequences of Spot Jamming(SJ),Blocking Jamming(BJ),Linear Sweep Jamming(LSJ),Noise Convolution Jamming(NCJ),Noise Product Jamming(NPJ),Interrupted-Sampling and Direct Repeater Jamming(ISDJ),Interrupted-Sampling and Periodic Repeater Jamming(ISPJ)and Interrupted-Sampling and Cyclic Repeater Jamming(ISCJ).Manually extract 16 dimensional features to form feature vectors and place them into Support Vector Machine(SVM)for classification and recognition.Simulation experiments show that when Jamming Noise Ratio(JNR)is between-20～30 dB and 16～30 dB,the recognition rate increases with the increase of JNR,being 94.89%while JNR is-2～30 dB;when simulating a real environment with JNR being-2～30 dB,the algorithm's recognition rate reach 93.62%while retaining 8-dimensional feature parameters,reducing by 1.27%,which has excellent recognition efficiency.
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