分数阶傅里叶和压缩感知自适应抗频谱弥散干扰

赵杨; 尚朝轩; 韩壮志; 韩宁; 解辉

doi:10.11999/JEIT180569

分数阶傅里叶和压缩感知自适应抗频谱弥散干扰

doi: 10.11999/JEIT180569

赵杨^1, ,,
尚朝轩¹,
韩壮志¹,
韩宁²,
解辉¹

1.
陆军工程大学石家庄 050003
2.
中国人民解放军32181部队西安 710032

基金项目: 国家自然科学基金(61601496)

详细信息

作者简介:
赵杨：男，1992年生，博士，研究方向为压缩感知、信号处理、雷达抗干扰

尚朝轩：男，1964年生，博士，教授，博士生导师，研究方向为武器系统性能检测、雷达信号处理

韩壮志：男，1972年生，博士，副教授，硕士生导师，研究方向为雷达信号处理、武器系统性能评估

韩宁：男，1985年生，博士，工程师，研究方向为双基地雷达、SAR雷达

解辉：男，1983年生，博士，讲师，研究方向为雷达、通信信号侦察及信道编码识别

通讯作者:
赵杨　zhaoyang_oec@foxmail.com

中图分类号: TN974
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出版历程
- 收稿日期: 2018-06-11
- 修回日期: 2018-12-12
- 网络出版日期: 2018-12-28
- 刊出日期: 2019-05-01

Fractional Fourier Transform and Compressed Sensing Adaptive Countering Smeared Spectrum Jamming

1.
Army Engineering University, Shijiazhuang 050003, China
2.
32181 of PLA, Xi’an 710032, China

Funds: The National Natural Science Foundation of China (61601496)

摘要

摘要:
频谱弥散(SMSP)干扰与线性调频雷达信号之间存在大量的时频域耦合，干扰效能突出。该文提出一种信息域的抗SMSP干扰的信号处理算法，根据SMSP干扰信号的形式与特点，通过自适应改变压缩感知的干扰基字典，同时匹配雷达信号与干扰信号的调频率，构建压缩感知求解模型并基于凸优化算法完成信号重构，最终实现干扰信号的识别及雷达信号的提取。该算法中冗余字典的构造采用了Pei型分数阶傅里叶快速分解方法，不需要反复对信号进行时频域解耦，并且迭代次数较少，运算效率较高。
- 信号处理 /
- 频谱弥散 /
- 分数阶傅里叶变换 /
- 压缩感知 /
- 形态理论
Abstract:
SMeared SPectrum (SMSP) jamming has lots of coupling in time and frequency domain with Linear Frequency Modulated (LFM) radar signals, which has good jamming performance. This paper proposes a signal processing method for countering SMSP jamming in information domain. According to the formulation and characteristics of SMSP signal, the jamming dictionary is changed automatically, the frequency modulation rate of LFM and SMSP signal is matcheal at the same time, the compressed sampling model is consructed and reconstruction of signal is carried out based on convex optimization. Finally, the recognition of jamming signal and extraction of radar signal are achieved. Pei type fractional Fourier decomposition method is used in construction of redundant dictionary. Modulation and demodulation between time and frequency domain are avoided in this method, which leads to improvement in fewer iteration times and higher arithmetic speed.
- Signal processing /
- SMeared SPectrum (SMSP) /
- Fractional Fourier Transform (FrFT) /
- Compressed sensing /
- Morphological theory

HTML全文

图 1 时域波形

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图 2 脉冲压缩结果

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图 3 混合干扰后时域波形

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图 4 混合干扰后脉冲压缩结果

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图 5 STFT结果

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图 6 STFT等高线图

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图 7 3组仿真实验结果

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图 8 3种算法的干扰抑制曲线

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表 1 恢复结果的均方误差统计值(×10^–14)

调频倍数切片数
2 4 6 8

3 1.5126 1.4837 1.5018 1.5525
5 1.5246 1.5539 1.5187 1.4641
7 1.4727 1.5415 1.5443 1.5563
9 1.4811 1.5656 1.5707 1.5487

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