遗传算法在分数阶Fourier变换域极值优化中的应用

分数阶Fourier变换采用线性调频基,因此,线性调频（Linear Frequency Modulation,LFM）信号在分数阶Fourier域平面能够聚焦,并形成峰值。为了克服传统步进式搜索法在LFM信号峰值搜索中效率低下的缺点,将遗传算法引入到分数阶Fourier变换极值搜索中。仿真结果表明,该方法优于传统的步进式搜索法。     

分数阶傅立叶变换的线性调频信号降噪

本文在分数阶Fourier变换原理的基础上,提出了一种基于分数阶傅里叶变换的线性调频（LFM）信号的滤波方法,利用该变换等同于对信号在时频平面进行旋转,将混迭有噪声的信号以特定的旋转角作分数阶傅里叶变换,使得信号与噪声在变换域中的交迭达到最小：然后通过窄带通滤波器对LFM信号进行抽取,再经过分数阶傅里叶反变换,恢复出原信号。     

宽带体制下混响和目标空时分布特征研究

传统的空时自适应处理(Space-Time Adaptive Processing,STAP)利用窄带混响和目标在空时平面的可分辨特征抑制窄带混响。对宽带混响和目标在空时平面分布特征进行研究,并通过理论推导,得出带宽对混响和目标空时分辨特征的影响公式。结果表明:宽带混响和目标在空时平面分布特征部分重叠,导致传统STAP效果不佳。在此基础上,借鉴STAP思想,并利用线性调频(Linear Frequency Modulation,LFM)信号在分数阶Fourier变换域上的聚焦性,分析了在空-分数阶Fourier域三维空间上抑制宽带LFM混响的可行性。     

基于Kaiser窗的分数阶Fourier变换与时频分析

分数阶Fourier变换作为传统Fourier变换的推广,与传统Fourier变换分析平稳信号类似,在实现对非平稳信号的时频分析过程中往往出现同样的频谱泄漏问题。为了提高分数阶Fourier变换与时频分析的精度,依据Kaiser窗可自由选择主瓣和旁瓣宽度的特性,提出一种基于Kaiser窗的分数阶Fourier变换算法,论述了Kaiser窗在分数阶Fourier变换中的作用原理,从理论上推导出一般信号基于Kaiser窗的分数阶Fourier变换解析时频表达式以及特性,最终得到非平稳信号的时频分布与时变结构参数识别算法。通过任意线性调频信号的仿真算例以及非平稳激励三层框架结构振动台试验,对结构进行瞬时频率识别和算法的验证。结果表明,瞬时频率识别值与理论值和试验结果吻合良好,Kaiser窗可以提高分数阶Fourier变换算法时频分析的精度,体现出该方法有一定的鲁棒性。     

基于分数阶Fourier变换的经验模式分解方法研究

在分析了经验模式分解(EMD)及分数阶Fourier变换的基础上,提出了一种基于分数阶Fourier变换的经验模式分解方法,并且深入探讨了该方法的分解特性.对仿真和实际振动信号的分析结果表明,对直接采用经验模式分解分析结果不够明确的信号,基于分数阶Fourier变换的经验模式分解方法对信号进行分析是比较有效的方法.     

基于分数阶傅里叶变换的邻近阶比分离研究

提出了一种基于分数阶傅里叶变换（Fractional Fourier Transform, FRFT）的邻近阶比分离方法。根据变速器输入轴转速信号及传动比确定FRFT最佳阶次,对变速器升速过程振动信号进行最佳阶次FRFT,在该分数阶域分离邻近阶比分量,并对分离出的单分量信号进行阶比分析。试验结果表明,根据转速信号确定FRFT最佳阶次,准确、快速、鲁棒性好,并具有自适应性;最佳阶次的FRFT能准确分离提取邻近阶比分量,对分离出的目标阶比分量进行单分量分析,能有效解决邻近阶比胶合问题。     

基于分数Fourier变换的自适应信号降噪方法

提出了一种新的基于分数Fourier变换的自适应信号降噪方法,该方法的核心是利用不同信号在分数Fourier域具有不同的相关性,从而由信号本身得到自适应的滤波器.这种方法克服了传统时域或者频域滤波器需要确定窗函数的位置和形状的缺陷.通过与小波变换构造的滤波器进行比较.以数值仿真信号及实测滚动轴承振动信号降噪两个算例证明了方法的有效性.     

基于线性调频信号二次相位变换的主动声呐目标速度估计

分数阶傅里叶变换常用于主动声呐线性调频信号的分析,通过搜索变换参数可以估计目标的相对速度.但是由于其参数搜索计算量偏大,在自主式水下航行器等计算力有限的小平台难以实时处理.针对该问题提出了一种基于二次相位变换的线性调频信号速度估计方法,根据多普勒频移后线性调频信号的二次相位变换的解析解,分析了二次相位变换后变换域频谱展...     

基于分数阶聚能带分析的微弱故障特征提取研究

提出了一种分数阶聚能带时频累加谱方法,快速实现长数据的时频分析,突出目标分量,用于提取变速器急加速过程微弱故障特征。根据变速器输入轴转速信号及传动比确定分数阶傅里叶变换（Fractional Fourier Transform, FRFT）最佳阶次,对变速器急加速过程振动信号进行最佳阶次FRFT,根据FRFT模值谱确定聚能带,计算分数阶聚能带时频累加谱,通过对比多组正常和故障数据的分数阶聚能带时频累加谱结果和阶比谱结果,验证该方法的有效性。试验结果表明：根据转速信号能快速、准确确定FRFT最佳阶次;选取聚能带内的FRFT结果进行时频分析,计算量小,分辨率高,分数阶聚能带时频累加谱具有聚焦和局部放大的特点, 能很好地突出目标分量,抑噪噪声,是提取变速器急加速过程信号微弱故障特征的有效方法。     

基于阶次窄带包络分析的直驱风机轴承微弱故障诊断

针对变转速工况下直驱风电机组滚动轴承早期微弱故障难以诊断的技术难题,提出一种基于阶次窄带包络的滚动轴承早期故障诊断新方法。首先,求出变转速下直驱风电机组滚动轴承故障信号时频谱,并设定等效转频。再利用时频自动搜峰算法搜索出等效转频对应阶次时频峰值。进一步,采用最小二乘法拟合得到转速信号变化曲线,通过该转速曲线计算出重采样鉴相时标,并对原信号进行等角域重采样。最后,对采样后角域信号进行窄带包络分析得到含滚动轴承故障信号的阶次窄带包络谱,该阶次窄带包络谱可用于滚动轴承故障诊断。该方法同时克服了变转速影响和低频调制微弱信号难以提取的问题,为滚动轴承故障诊断提供新方法。直驱风机滚动轴承应用实例验证了方法的有效性。     

Separation of overlapping linear frequency modulated (LFM) signals using the fractional fourier transform

Linear frequency modulated (LFM) excitation combined with pulse compression provides an increase in SNR at the receiver. LFM signals are of longer duration than pulsed signals of the same bandwidth; consequently, in many practical situations, maintaining temporal separation between echoes is not possible. Where analysis is performed on individual LFM signals, a separation technique is required. Time windowing is unable to separate signals overlapping in time. Frequency domain filtering is unable to separate signals with overlapping spectra. This paper describes a method to separate time-overlapping LFM signals through the application of the fractional Fourier transform (FrFT), a transform operating in both time and frequency domains. A short introduction to the FrFT and its operation and calculation are presented. The proposed signal separation method is illustrated by application to a simulated ultrasound signal, created by the summation of multiple time-overlapping LFM signals and the component signals recovered with ±0.6% spectral error. The results of an experimental investigation are presented in which the proposed separation method is applied to time-overlapping LFM signals created by the transmission of a LFM signal through a stainless steel plate and water-filled pipe.     

Suppression of smeared spectrum ECM signal

Abstract

Three electronic counter‐countermeasures (ECCM) techniques for suppressing smeared spectrum (SMSP) jamming, a new electronic counter measures (ECM) technique, are presented. The analytical representations of the SMSP ECM signal in the time domain and the frequency domain are first derived, and then the differences between the SMSP jamming signal and the radar linear frequency modulation (LFM) signal are analyzed. Based on the differences, a jamming suppression system specifically for SMSP jamming interference excision is designed, which applies three different signal processing tools, i.e. fractional Fourier transform (FRFT), Fourier transform (FT) and atomic decomposition (AD). The jamming suppression performance of the presented methods is evaluated through simulations. The simulation results show that the presented methods can successfully suppress SMSP jamming.     

飞机颤振试飞试验信号的广义时频滤波

针对飞机颤振试飞试验信号噪声过大的问题,提出了一种广义时频域滤波算法。算法采用分数阶傅里叶变换对线性扫频激励及其响应信号进行广义时频分析,利用该类信号在分数阶傅里叶域内的聚焦特性,有效提取真实响应信号,达到信噪分离的目的。给出了具体的滤波算法,并将其应用于仿真算例和实际试飞数据,结果表明该方法可显著提高信号的信噪比。     

Efficient computation of joint fractional Fourier domain signal representation

A joint fractional domain signal representation is proposed based on an intuitive understanding from a time-frequency distribution of signals that designates the joint time and frequency energy content. The joint fractional signal representation (JFSR) of a signal is so designed that its projections onto the defining joint fractional Fourier domains give the modulus square of the fractional Fourier transform of the signal at the corresponding orders. We derive properties of the JFSR, including its relations to quadratic time-frequency representations and fractional Fourier transformations, which include the oblique projections of the JFSR. We present a fast algorithm to compute radial slices of the JFSR and the results are shown for various signals at different fractionally ordered domains.     

应用分数傅立叶变换方法的水下目标特征提取

针对基于传统时频分析方法的水下目标特征提取方法的缺陷,引入了一种新的时频分析方法——分数阶傅立叶变换（FRFT）方法用于处理水下目标特征提取问题。仿真信号和实际试验数据的处理结果表明,当主动声纳的发射信号为线性调频信号时,分数阶傅立叶变换方法可以使目标的回波能量在分数阶域的对应区域聚集,使目标和混响的分数阶傅立叶变换在分数阶域上不仅呈现明显不同的特征,而且较其他时频分析方法具有抗混响的优点。     

Importance of the phase and amplitude in the fractional Fourier domain

The importance of the amplitude and phase in the fractional Fourier transform (FT) domain is analyzed on the basis of the rectangular signal and the real-world image. The quality of signal restoration from only the amplitude or from only the phase of its fractional FT by applying the inverse fractional FT is considered. It is shown that the signal reconstructed from the amplitude of the fractional FT usually reveals the main features of the original signal only for relatively low fractional orders. On the basis of phase information in the fractional FT domains, significant details of the signal can be obtained for nearly all fractional orders.     

分数傅里叶变换域的调频信号稀疏性研究

调频信号广泛应用于声纳、雷达、激光和新兴光学交叉研究领域,其紧致性(稀疏性)是调频信号采样、去噪、压缩等研究中面临的共性基础问题。本文致力于研究调频信号在分数傅里叶变换域的稀疏性,提出了一种最大奇异值法来估计调频信号的紧致分数傅里叶变换域。该方法利用调频信号幅度谱的最大奇异值来度量其紧致域,并应用鲸鱼优化算法来搜寻紧致域,有效改善了现有方法的不足。与MNM和MACF方法相比,本文方法给出了调频信号在分数傅里叶变换域更加稀疏的表征,具有更少的重要振幅数。最后,给出了该方法在调频信号滤波中的初步应用。