一种低副瓣无混叠的线性调频信号时频分析方法

刘会杰; 高新海; 郭汝江

doi:10.11999/JEIT181190

一种低副瓣无混叠的线性调频信号时频分析方法

doi: 10.11999/JEIT181190

刘会杰¹,
高新海^{1, 2, 3, ,},
郭汝江¹

1.
中国科学院微小卫星创新研究院上海 201203
2.
中国科学院上海微系统与信息技术研究所上海 200050
3.
中国科学院大学北京 100049

基金项目: 国家自然科学基金(91738201)，上海市青年科技英才扬帆计划(17YF1418200)

详细信息

作者简介:
刘会杰：男，1972年生，博士，研究员，博士生导师，研究方向为卫星移动通信系统理论与通信系统设计

高新海：男，1995年生，硕士生，研究方向为复杂电磁环境下的时频分析

郭汝江：男，1977年生，博士，研究员，研究方向为新体制雷达、保密通信、无源定位

通讯作者:
高新海　gxh777@mail.ustc.edu.cn

中图分类号: TN911
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出版历程
- 收稿日期: 2018-12-28
- 修回日期: 2019-05-27
- 网络出版日期: 2019-08-23
- 刊出日期: 2019-11-01

A Time-frequency Analysis Method for Linear Frequency Modulation Signal with Low Sidelobe and Nonaliasing Property

Huijie LIU¹,
Xinhai GAO^{1, 2, 3
, ,},
Rujiang GUO¹

1.
Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 201203, China
2.
Shanghai Institute of Microsystem and Information Technology, Shanghai 200050, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Natural Science Foundation of China (91738201), Shanghai Sailing Program (17YF1418200)

摘要

摘要: 作为通信与勘探中广泛使用的一类信号，线性调频信号的参数分析经常采用基于Wigner-Ville分布(WVD)的时频分析方法。该方法具有高时频分辨率，但在交叉项、高副瓣以及频谱混叠问题上存在缺陷。该文提出一种名为空间变迹重排Wigner-Ville分布(SVA-rWVD)的时频分析方法，结合空间变迹技术(SVA)的副瓣抑制能力及短时傅里叶变换(STFT)的无混叠无交叉项特性，得到一个新的时频分布。基于单分量和多分量线性调频信号的仿真实验结果表明，该方法得到的时频分布可以降低副瓣水平至–40 dB以下同时消除交叉项及频谱混叠现象。
- 时频分析 /
- 线性调频信号 /
- Wigner-Ville分布 /
- 空间变迹 /
- 短时傅里叶变换
Abstract: Chirp signals are widely used in communication and exploration. The parameter analysis of the chirp signals often uses a Wigner-Ville Distribution (WVD) based time-frequency analysis method, which achieves high time-frequency resolution. However, this method has defects in cross terms, high sidelobes, and spectral aliasing problems. To solve these problems, a time-frequency analysis method called Spatially Variant Apodiztion-rearrange Wigner Ville Distribution (SVA-rWVD) is proposed, which achieves low sidelobes by exploiting the Spatially Variant Apodization (SVA) techniques, and avoids the cross terms and the spectral aliasing problems by applying the Short Time Fourier Transform (STFT). Furthermore, a new time-frequency distribution is obtained from the proposed method. Extensive simulations show that the time-frequency distribution obtained by the proposed method not only reduces the sidelobe level to –40 dB but also eliminates cross terms and spectral aliasing for both single-component and multi-component chirp signals.
- Time-frequency analysis /
- Linear Frequency Modulation (LFM) /
- Wigner-Ville Distribution (WVD) /
- Spatially Variant Apodization (SVA) /
- Short Time Fourier Transform (STFT)

HTML全文

图 1 单分量LFM信号的时频分析结果对比

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图 2 时间切片比较结果(取对数进行分析)

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图 3 SVA-rWVD方法消除混叠现象的原理

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图 4 多分量LFM信号的时频分析结果对比

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图 5 时间切片比较结果(取对数进行分析)

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图 6 多分量LFM信号的时频分析结果对比

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图 7 时间切片比较结果(取对数进行分析)

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图 8 不同信噪比下瞬时频率估计的均方根误差

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表 1 仿真参数设置

参数名称	单分量LFM(图1)	多分量LFM(图4)	多分量LFM(图6)
脉冲宽度(μs)	1024	1024	1204
带宽(MHz)	1	1	1
采样率(MHz)	1	1	1
时间切片(μs)	400	500	300
频率范围(kHz)	–500～500	3个分量均为–500～500，且时间间隔相同	–300～–100 0～300 –500～500

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