﻿ 基于压缩感知的单脉冲雷达欺骗干扰机研究<sup>*</sup>
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Research on deception jammer against monopulse radar based on compressed sensing
WANG Caiyun, HE Zhiyong, GONG Jun
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Received: 2016-09-07; Accepted: 2016-12-09; Published online: 2017-01-18 16:07
Foundation item: National Natural Science Foundation of China (61301211); A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions
Corresponding author. WANG Caiyun, E-mail:wangcaiyun@nuaa.edu.cn
Abstract: Deceptive jamming is a common radar jamming technology. This paper presents a novel deception jammer against monopulse radar. First, the characteristics of angle deceptive signal is analyzed. Then, according to energy aggregation properties of the linear frequency modulation (LFM) signal in fractional domain, a digital radio frequency memory (DRFM) under compressed sensing (CS) framework is proposed in order to generate angle deceptive jamming signal. In order to achieve effective jamming against the monopulse radar tracking system, the angle pull-off jamming and glint jamming achieving method is considered by controlling the power of jamming signal. Simulation results show that origin signal can be recovered with the proposed method very well, and the jammer can achieve a stable angle pull-off and blink jamming.
Key words: deceptive jamming     fractional Fourier transform     digital radio frequency memory (DRFM)     compressed sensing (CS)     angle jamming

1 理论基础 1.1 压缩感知基本理论

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1.2 分数阶傅里叶变换基本概念

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1.3 单脉冲雷达相干干扰原理

 图 1 相干干扰原理 Fig. 1 Principle of coherent jamming
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2 基于DRFM的单脉冲雷达角度欺骗干扰机 2.1 欺骗干扰信号分析

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2.2 DRFM压缩感知角度欺骗干扰机

DRFM是一种可以存储一定带宽范围内的射频信号并对其进行精确复制输出的电子战设备，其关键技术在于对信号的量化存储和重构。DRFM一般有全脉冲存储转发、短脉冲存储循环转发和间歇采样存储转发3种工作方式。相比于后2种存储方式，全脉冲存储信号具有良好的相干性，处理复杂信号的能力较强[10]。但是全脉冲存储时数据量较大，对存储器、采样器等都具有极高的要求。DRFM技术的重点是实现信号的精确采样与恢复，因此，笔者设计了一种基于压缩感知框架的DRFM系统，在保留信号相干性的同时，降低DRFM系统对存储器、采样器等的需求。图 2为本文所提出的DRFM压缩感知交叉眼干扰机模型。图中：DFRFT为离散分数阶傅里叶变换。

 图 2 DRFM压缩感知相干干扰机模型 Fig. 2 Model of CS-DRFM coherent jammer

2.2.1 欺骗干扰信号的构建方法

2.1节中分析了角度欺骗干扰信号应具有的一般特性，为了能够得到较好的欺骗干扰信号，本文干扰机根据LFM信号在分数阶傅里叶域的能量聚集特性，采用压缩感知算法得到欺骗干扰信号，在精准重构信号的同时，可以降低DRFM对高速采样器和存储器的需求。根据FRFT理论可知，调频率相同的LFM信号所对应的最佳能量聚集阶次相同。

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Pei采样型算法能够保证离散分数阶变换的正交性和可逆性。由于LFM信号在FRFT域的能量聚集特性，Xp应为一个稀疏信号。对比式(4) 与式(1)，可以得到Xp是源信号x在分数阶傅里叶域的稀疏表示结果，则逆变换矩阵Fp可以看作正交基字典。而压缩恢复算法可以根据正交基字典从压缩采样信号中得到恢复信号。

2.2.2 干扰机工作方式

3 仿真实验与分析 3.1 LFM压缩感知性能分析

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 图 3 LFM源信号(SNR=5 dB) Fig. 3 LFM source signal (SNR=5 dB)
 图 4 LFM信号在FRFT域二维分布(SNR=5 dB) Fig. 4 Two-dimensional distribution of LFM signal in FRFT domain (SNR=5 dB)
 图 5 LFM信号稀疏表示结果(SNR=5 dB) Fig. 5 Sparse representation of LFM signal (SNR=5 dB)
 图 6 稀疏系数重构结果(SNR=5 dB) Fig. 6 Reconstruction of sparse coefficient (SNR=5 dB)
 图 7 压缩恢复信号(SNR=5 dB) Fig. 7 Compressive recovery signal (SNR=5 dB)

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 图 8 压缩感知损耗因子 Fig. 8 Loss factor of compressed sensing

3.2 干扰机干扰效果仿真

3.2.1 单脉冲雷达系统仿真模型

 图 9 单脉冲雷达测角系统框架 Fig. 9 Framework of monopulse radar system

 系统模块 模块参数模型 天线模块 改进sinc函数模型 噪声模块 高斯白噪声 目标模块 点目标 信号模块 LFM信号 测角模块 比幅测角

3.2.2 干扰机干扰性能仿真分析

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1) 干扰信号强度比对干扰效果的影响

 图 10 不同干扰信号强度比下测角误差 Fig. 10 Angle measurement error at different interference signal intensity ratios

2) 相位差对测角结果的影响

 图 11 不同相位差下测角误差 Fig. 11 Angle measurement error under different phase offset

3) 回波信号强度比对测角结果的影响

 图 12 不同回波信号强度比下测角误差 Fig. 12 Angle measurement error under different echo signal intensity ratios

4) 噪声对交叉眼干扰的影响

 图 13 不同信噪比下测角误差 Fig. 13 Angle measurement error under different SNR
3.3 角度拖引和闪烁干扰分析

3.3.1 角度拖引干扰

 图 14 拖引干扰示意图[12] Fig. 14 Schematic diagram of pull-off jamming[12]

 图 15 角度跟踪滤波仿真结果 Fig. 15 Simulation results of angle tracking filter

3.3.2 角度闪烁干扰

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 闪烁时间 干扰机1相对强度 干扰机2相对强度 干扰信号强度比 误差角度/(°) nΔT≤t≤nΔT+ΔT/2 100 99 b=0.99 1.97 nΔT+ΔT/2 < t≤(n+1)ΔT 98 99 bI=0.99 -2.03

3.4 干扰机性能分析

4 结论

#### 文章信息

WANG Caiyun, HE Zhiyong, GONG Jun

Research on deception jammer against monopulse radar based on compressed sensing

Journal of Beijing University of Aeronautics and Astronsutics, 2017, 43(9): 1789-1797
http://dx.doi.org/10.13700/j.bh.1001-5965.2016.0723