Time-Frequency Analysis Method Based on Short-Time Fractional Fourier Transform

PANG Cun-suo; LIU Lei; SHAN Tao

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Time-Frequency Analysis Method Based on Short-Time Fractional Fourier Transform

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- Time-Frequency Analysis Method Based on Short-Time Fractional Fourier Transform
- Acta Electronica Sinica Vol. 42, Issue 2, Pages: 347-352(2014)
- 作者机构：
  
  1. 北京理工大学信息与电子学院,北京,100081
  2. 中北大学信息与通信工程学院,山西,太原,030051
  3. 北京理工大学信息与电子学院,北京,100081
  4. 中北大学信息与通信工程学院,山西,太原,030051
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61172176);Armament Pre-research Project (No.51307060802)
- DOI：
  CLC： TN911.72
- Published：2014
- 稿件说明：
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PANG Cun-suo, LIU Lei, SHAN Tao. Time-Frequency Analysis Method Based on Short-Time Fractional Fourier Transform[J]. Acta Electronica Sinica, 2014, 42(2): 347-352.
DOI：

PANG Cun-suo, LIU Lei, SHAN Tao. Time-Frequency Analysis Method Based on Short-Time Fractional Fourier Transform[J]. Acta Electronica Sinica, 2014, 42(2): 347-352. DOI：

摘要

本文研究了短时分数阶傅里叶变换（STFRFT）时频分析方法的分辨率精度和算法性能.首先，文中给出了一种STFRFT时频分辨率的数学计算表达式，其有利于时频分辨率的量化比较，仿真结果表明该理论量化值与观察值基本吻合；其次，针对算法运算量大的问题，提出了一种STFRFT的快速计算方法，它较传统的穷举搜索方法运算量约降低1个数量级；最后，给出了算法估计误差的理论分析并运用该方法对多目标信号进行了分析，仿真表明该方法可有效抑制交叉项和解决多分量时频信号的分离问题.

Abstract

The resolution precision and algorithm stability of the short-time fractional Fourier transform (STFRFT) time-frequency method was studied.Firstly

the mathematical expression of the STFRFT time-frequency resolution was given in this paper

which is beneficial to the time-frequency resolution theory quantitative comparison

and simulation results showed that the theoretical quantitative value is basically consistent with the observed value.Secondly

this paper proposed a fast calculation method of STFRFT to decrease the computational complexity

its calculation amount comparing with the traditional search method was reduced about an order of magnitude;Finally

the paper gave the estimation error theoretical analysis of the algorithm and applied the method to analyze the multi-target signal.The simulation results showed that this method could effectively suppress cross-terms and resolve the problem of multi-component signal separation.

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