Anti-ISRJ Method Based on Intrapulse Frequency-coded Joint Frequency Modulation Slope Agile Radar Waveform
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摘要: 间歇采样转发干扰(ISRJ)是一种脉内相参干扰,能在目标斜距前后形成多个逼真假目标来严重影响雷达检测,是当前电子反对抗的热点之一。针对这一问题,该文提出了一种基于脉内频率编码联合调频斜率捷变波形的抗ISRJ方法。首先,雷达发射脉内频率编码联合调频斜率捷变信号,通过子脉冲中心频率、调频斜率捷变提高子脉冲间相互掩护能力。之后依据发射信号子脉冲斜率变化时序将回波信号划分为多个切片。然后利用模糊C均值(FCM)算法对回波切片进行干扰识别。最后在分数阶域和时域对回波信号进行级联滤波。仿真结果表明,FCM方法在信噪比(SNR)大于-2.5 dB和干信比(JSR)大于5 dB时,能100%识别干扰机同步采样场景下回波中的受干扰回波切片。在较高JSR和低SNR下,所提方法能有效减少目标能量损失并抑制剩余干扰产生的距离旁瓣。在JSR为50 dB时,干扰抑制后的目标检测概率可达90%以上。
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关键词:
- 间歇采样转发干扰 /
- 频率编码联合调频斜率捷变 /
- 分数阶傅里叶变换 /
- 时域滤波 /
- 电子反对抗
Abstract: Interrupted Sampling Repeater Jamming (ISRJ) is a type of intrapulse coherent jamming that can form multiple realistic false targets that lead or lag behind the actual target, severely affecting radar detection. It is one of the hotspots of current research on electronic counter-countermeasures. To address this problem, an anti-ISRJ method based on an intrapulse frequency-coded joint Frequency Modulation (FM) slope agile waveform is proposed in this paper. In this method, the radar first transmits an intrapulse frequency-coded joint FM slope agile signal to improve the mutual coverability of subpulses by manipulating subpulse center frequency and FM slope agility. Next, the echo signal is divided into several slices according to the subpulse timing of the transmitted signal. Then, the Fuzzy C-Means (FCM) algorithm is used to classify the echo slices. Finally, the interference is suppressed via fractional-domain joint time domain filtering. Simulation results show that the FCM-based method can identify 100% of the interfered echo slices in a jammer synchronous sampling scenario when the Signal-to-Noise Ratio (SNR) is greater than −2.5 dB, and the Jamming-to-Signal Ratio (JSR) is greater than 5 dB. For high JSRs and low SNRs, the proposed method can effectively reduce the target energy loss and suppress the range sidelobes generated via residual interference. Moreover, the target detection probability after interference suppression exceeds 90% when JSR = 50 dB. -
1 模糊C均值算法
1. Fuzzy C-mean algorithm
输入:X:样本集;N:样本数;K:类别数; 输出:$ {\mathrm{Label}}\left( {{x_i}} \right),i = 1,2, \cdots ,N $:样本所属类别 初始化:U:隶属度矩阵; $\ell = 2$:模糊加权指数; $\varepsilon = {10^{ - 5}}$:阈值; $h = 1$:迭代次数 1: repeat 2: 根据式(12)计算各聚类中心 3: 根据式(11)更新隶属度矩阵U 4: until $\left\| {{{\boldsymbol{U}}_h} - {{\boldsymbol{U}}_{h - 1}}} \right\| \le \varepsilon $ 5: else 6: $h = h + 1$ 7: return $ {\mathrm{Label}}\left( {{x_i}} \right),i = 1,2, \cdots ,N $ 表 1 仿真实验的参数设置
Table 1. Parameter settings for simulation experiments
参数 数值 雷达发射信号脉宽${T_{\rm p}}$ 100 μs 子脉冲脉宽${T_{{\mathrm{sub}}}}$ 5 μs 子脉冲数N 20 子脉冲最小带宽${B_{\min }}$ 2 MHz 子脉冲最大带宽${B_{\max }}$ 10 MHz 子脉冲载频最大间隔${B_0}$ 10 MHz 采样频率${f_{\mathrm{s}}}$ 20 MHz 干扰机采样脉冲宽度${\tau _{\mathrm{j}}}$ 5 μs 间歇采样重复周期${T_{\mathrm{s}}}$ 25 μs 干信比(JSR) 20 dB 信噪比(SNR) 0 dB 表 2 不同方法在不同SNR下的JSR容限(dB)
Table 2. The JSR tolerance of different methods at different SNRs (dB)
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