基于高斯加权分数阶傅里叶变换的LFM信号参数估计

王鹏; 邱天爽; 李景春; 谭海峰

doi:10.11959/j.issn.1000-436x.2016077

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基于高斯加权分数阶傅里叶变换的LFM信号参数估计

学术论文 | 更新时间：2024-06-05

- 基于高斯加权分数阶傅里叶变换的LFM信号参数估计
- Parameters estimation of LFM signal based on Gaussian-weighted fractional Fourier transform
- 通信学报 2016年37卷第4期页码：107-115
- 作者机构：
  
  1. 大连理工大学电子信息与电气工程学部，辽宁大连116024
  2. 国家无线电监测中心，北京100037
  3. 北京邮电大学信息与通信工程学院，北京100876
- 作者简介：
  
  [ "王鹏（1989-），男，河北宁晋人，大连理工大学博士生，主要研究方向为无线电信号处理和阵列信号处理。" ]
  [ "邱天爽（1954-），男，江苏海门人，博士，大连理工大学教授、博士生导师，主要研究方向为统计信号处理、射频与通信信号处理等。" ]
  [ "李景春（1966-），男，河北宁晋人，博士，国家无线电监测中心副主任兼总工程师，主要研究方向为无线电监测理论与应用等。" ]
  [ "谭海峰（1977-），男，湖北枝江人，国家无线电监测中心高级工程师，主要研究方向为无线电监测理论技术等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61139001);国家自然科学基金资助项目(61172108);国家自然科学基金资助项目(81241059)
- DOI：10.11959/j.issn.1000-436x.2016077
  中图分类号： TN911.7
- 网络出版日期：2016-04，
  
  纸质出版日期：2016-04-25
- 稿件说明：
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王鹏, 邱天爽, 李景春, 等. 基于高斯加权分数阶傅里叶变换的LFM信号参数估计[J]. 通信学报, 2016,37(4):107-115.

Peng WANG, Tian-shuang QIU, Jing-chun LI, et al. Parameters estimation of LFM signal based on Gaussian-weighted fractional Fourier transform[J]. Journal of communications, 2016, 37(4): 107-115.
王鹏, 邱天爽, 李景春, 等. 基于高斯加权分数阶傅里叶变换的LFM信号参数估计[J]. 通信学报, 2016,37(4):107-115. DOI： 10.11959/j.issn.1000-436x.2016077.

Peng WANG, Tian-shuang QIU, Jing-chun LI, et al. Parameters estimation of LFM signal based on Gaussian-weighted fractional Fourier transform[J]. Journal of communications, 2016, 37(4): 107-115. DOI： 10.11959/j.issn.1000-436x.2016077.

摘要

针对低占空比下传统算法参数估计性能下降的问题，提出了一种高斯加权分数阶傅里叶变换(GFRFT

Gaussian-weighted fractional Fourier transform)参数估计方法。给出了时限信号GFRFT的定义并推导了其模值平方的特性，研究了高斯白噪声背景下GFRFT 的输出信噪比并给出了闭式表达式，进行了仿真实验并讨论说明了该方法的适用条件。仿真结果表明，该方法在低占空比的情况下可以有效地提高参数估计精度。

Abstract

To overcome the performance degradation of conventiona methods in low duty ratio condition

a novel me-thod of parameters estimation for LFM signal based on the Gaussian-weighted fractional Fourier transform (GFRFT) was proposed. Firstly

the GFRFT definition was given and the LFM signal GFRFT with finite duration was derived. Secondly

the statistical characteristics of the GFRFT for the LFM signal under the Gaussian white noise were studied

and a closed mathematical expression of output signal-to-noise ratio was derived. Finally

simulation experiments are conducted

and the applicable condition of the GFRFT is also discussed

which demonstrates that the proposed method can effectively improve parameters estimation performance

especially in the low duty ratio condition.

关键词

Keywords

references

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