基于差分特征的间歇采样转发干扰辨识与抑制方法

盖季妤; 姜维; 张凯翔; 梁振楠; 陈新亮; 刘泉华

doi:10.12000/JR22058

基于差分特征的间歇采样转发干扰辨识与抑制方法

DOI: 10.12000/JR22058

盖季妤^{1, 2},
姜维³,
张凯翔¹,
梁振楠¹,
陈新亮^{1, 2, 4, ,},
刘泉华^{1, 2}

1.
卫星导航电子信息技术教育部重点实验室(北京理工大学) 北京 100081
2.
北京理工大学重庆创新中心重庆 401120
3.
电子信息控制重点实验室成都 610036
4.
北京理工大学长三角研究院(嘉兴) 嘉兴 314019

基金项目: 国家自然科学基金(61771050)，电子信息控制重点实验室开放基金(6142105190313)，重庆市自然科学基金(2020ZX3100039)

详细信息

作者简介:
盖季妤，硕士生，主要研究方向为干扰辨识与抑制、自适应阵列信号处理、扩展目标检测

姜　维，博士，高级工程师，主要研究方向为阵列信号处理、雷达信号处理

张凯翔，博士生，主要研究方向为分布式阵列雷达抗干扰

梁振楠，博士，主要研究方向为数字阵列雷达系统和宽带雷达信号处理

陈新亮，博士，硕士生导师，主要研究方向为自适应阵列信号处理、双/多基地合成孔径雷达成像

刘泉华，博士，教授，博士生导师，主要研究方向为高分辨雷达、分布式雷达系统及信号处理

通讯作者:
陈新亮 chenxinliang@bit.edu.cn

责任主编：全英汇 Corresponding Editor: QUAN Yinghui
中图分类号: TN974
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出版历程
- 收稿日期: 2022-04-02
- 修回日期: 2022-05-24
- 网络出版日期: 2022-06-21
- 刊出日期: 2023-02-28

A Method for Interrupted-Sampling Repeater Jamming Identification and Suppression Based on Differential Features

GAI Jiyu^{1, 2},
JIANG Wei³,
ZHANG Kaixiang¹,
LIANG Zhennan¹,
CHEN Xinliang^{1, 2, 4
, ,},
LIU Quanhua^{1, 2}

1.
Key Laboratory of Electronic and Information Technology in Satellite Navigation (Beijing Institute of Technology), Ministry of Education, Beijing 100081, China
2.
Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China
3.
Science and Technology on Electronic Information Control Laboratory, Chengdu 610036, China
4.
Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China

Funds: The National Natural Science Foundation of China (61771050), Science and Technology on Electronic Information Control Laboratory (6142105190313), The Natural Science Foundation of Chongqing (2020ZX3100039)

More Information

Corresponding author: CHEN Xinliang, chenxinliang@bit.edu.cn

摘要

摘要: 间歇采样转发式干扰机通过对其接收到的雷达发射信号进行采样、存储、处理和多次转发，在雷达接收端形成逼真的假目标干扰效果。为提升上述干扰场景下的雷达探测性能，该文提出了一种新的信号差分特征提取方法，在此基础上，利用目标回波和干扰信号在差分特征空间的差异设计判决准则，从而在有效辨识并抑制干扰的同时实现目标检测。仿真结果表明：该方法干扰抑制效果显著，相比于3种典型的时频域滤波算法等效信噪比改善4.2 dB以上。
- 间歇采样转发干扰 /
- 差分特征 /
- 干扰辨识 /
- 干扰抑制 /
- 目标检测
Abstract: The interrupted-sampling repeater jammer can sample, store, process and transmit part of the radar transmitter signal multiple times and the fake targets will form on the radar receiver. To improve the radar performance in the aforementioned jamming scenario, in this study, a new signal differential feature extraction method is proposed, and a judgment criterion is formulated based on the difference between the target echo and the Interrupted-Sampling Repeater Jamming (ISRJ) in the differential feature space to effectively identify and suppress the ISRJ while achieving target detection. Simulation results show that the proposed method has a remarkable ISRJ suppression performance. The equivalent signal-to-noise ratio is improved by at least 4.2 dB compared with three typical time-frequency domain filtering algorithms.
- Interrupted-Sampling Repeater Jamming (ISRJ) /
- Differential features /
- Jamming identification /
- Jamming suppression /
- Target detection

HTML全文

图 1 间歇采样转发干扰示意图

Figure 1. Schematic diagram of ISRJ

下载: 全尺寸图片幻灯片

图 2 目标与间歇采样转发干扰差分特征对比

Figure 2. Comparison of the differential features between target and ISRJ

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图 3 基于差分特征的间歇采样转发干扰辨识与抑制流程图

Figure 3. Flow chart of the ISRJ identification and suppression based on differential features

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图 4 不同干噪比、信噪比下，干扰、目标处差分特征能量比值的概率分布

Figure 4. The probability distribution of differential features energy ratio under different jamming-to-noise ratio and signal-to-noise ratio for ISRJ and target

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图 5 由最小错误概率准则确定辨识门限$\epsilon $

Figure 5. The determination of identification threshold $\epsilon $ by minimizing the probability of error

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图 6 仿真数据间歇采样转发干扰辨识与抑制结果

Figure 6. ISRJ identification and suppression results for simulation data

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图 7 目标检测概率

Figure 7. Target detection probability

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图 8 4种方法检测性能对比(仿真数据)

Figure 8. The detection performance comparison of the four methods (simulation data)

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图 9 实测数据间歇采样转发干扰辨识与抑制结果

Figure 9. ISRJ identification and suppression results for measured data

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图 10 时频图

Figure 10. Time-Frequency distribution

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表 1 归一化差分序列

Table 1. Normalized differential sequence

M	各项系数$ {c_M}(m),m = 0,1, \cdots ,M - 1 $
1	1
2	$ 1/\sqrt{2},-1/\sqrt{2} $
3	$ 1/\sqrt{6},-2/\sqrt{6},1/\sqrt{6} $
4	$ 1/2\sqrt{5},-3/2\sqrt{5},3/2\sqrt{5},-1/2\sqrt{5} $
5	$ 1/\sqrt{70},-4/\sqrt{70},6/\sqrt{70},-4/\sqrt{70},1/\sqrt{70} $

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表 2 仿真数据信源参数

Table 2. Source parameters for simulation data

信源	波形参数	脉压后信(干)噪比
目标	脉宽100 μs，带宽5 MHz	10~50 dB，间隔1 dB
干扰1	切片宽度16.67 μs，切片1次重复转发5次	10~50 dB，间隔1 dB
干扰2	切片宽度10 μs，切片1次立即重复转发2次，共切片3次	10~50 dB，间隔1 dB

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表 3 仿真参数

Table 3. Simulation parameters

参数	数值
常规检测门限	13.82
最高差分阶数	6
辨识门限	1.79

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表 4 不同干噪比下，检测概率为95%时所需的信噪比

Table 4. When the detection probability is 95%, the required signal-to-noise ratios under different jamming-to-noise ratios

干噪比(dB)	所需信噪比(dB)
无干扰	15.5
10	17.9
20	17.4
30	21.4
40	29.5
50	38.5

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表 5 实测数据信源参数

Table 5. Source parameters for measured data

目标参数	数值	干扰参数	数值
脉宽(μs)	20	脉宽(μs)	10
带宽(MHz)	2	带宽(MHz)	1
脉压后信噪比(dB)	33	脉压后信噪比(dB)	45

下载: 导出CSV

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