The multiple-parameter fractional Fourier transform

The fractional Fourier transform （FRFT） has multiplicity, which is intrinsic in fractional operator. A new source for the multiplicity of the weight-type fractional Fourier transform （WFRFT） is proposed, which can generalize the weight coefficients of WFRFT to contain two vector parameters m,n ∈ Z^M . Therefore a generalized fractional Fourier transform can be defined, which is denoted by the multiple-parameter fractional Fourier transform （MPFRFT）. It enlarges the multiplicity of the FRFT, which not only includes the conventional FRFT and general multi-fractional Fourier transform as special cases, but also introduces new fractional Fourier transforms. It provides a unified framework for the FRFT, and the method is also available for fractionalizing other linear operators. In addition, numerical simulations of the MPFRFT on the Hermite-Gaussian and rectangular functions have been performed as a simple application of MPFRFT to signal processing.     

Research progress on discretization of fractional Fourier transform

As the fractional Fourier transform has attracted a considerable amount of attention in the area of optics and signal processing, the discretization of the fractional Fourier transform becomes vital for the application of the fractional Fourier transform. Since the discretization of the fractional Fourier transform cannot be obtained by directly sampling in time domain and the fractional Fourier domain, the discretization of the fractional Fourier transform has been investigated recently. A summary of discretizations of the fractional Fourier transform developed in the last nearly two decades is presented in this paper. The discretizations include sampling in the fractional Fourier domain, discrete-time fractional Fourier transform, fractional Fourier series, discrete fractional Fourier transform （including 3 main types： linear combination-type; sampling-type; and eigen decomposition-type）, and other discrete fractional signal transform. It is hoped to offer a doorstep for the readers who are interested in the fractional Fourier transform.     

Digital computation of the weighted-type fractional Fourier transform

The paper reveals the time-frequency symmetric property of the weighted-type fractional Fourier transform (WFRFT) by investigating the original definition of the WFRFT, and proposes a discrete algorithm of the WFRFT based on the weighted discrete Fourier transform (WDFT) algorithm with constraint conditions of the definition of the WFRFT and time-domain sampling. When the WDFT is considered in digital computation of the WFRFT, the Fourier transform in the definition of the WFRFT should be defined in frequency (Hz) but not angular frequency (rad/s). The sampling period Δt and sampling duration T should satisfy Δt = T/N = 1/N(1/2) when N-point DFT is utilized. Since Hermite-Gaussian functions are the best known eigenfunctions of the fractional Fourier transform (FRFT), digital computation based on eigendecomposition is also carried out as the additional verification and validation for the WFRFT calculation.     

离散分数阶Fourier变换的高速FPGA实现

介绍了一种直接在时域和频域对信号进行离散的数值计算方法.针对工程实际,提出了一种基于FPGA的硬件实现方法,同时给出了具体的算法和计算机仿真结果.     

Performance of dual tone multi-frequency signal decoding algorithm using the sub-band non-uniform discrete Fourier transform on the ADSP-2192 processor

Efficient decoding of Dual Tone Multi-Frequency (DTMF) signals can be achieved using the sub-band non-uniform discrete Fourier transform (SB-NDFT). In this paper, the details of its implementation on the ADSP-2192 processor are put forward. The decoder performance in terms of its computational complexity and computational speed of this algorithm, implemented on the ADSP-2192 processor, are compared for different implementations of the SB-NDFT algorithm, with and without optimization for the chosen DSP, ADSP-2912. The algorithm is tested for various types of input signals on the DSP and these are compared with the results from Matlab^®. Problems on using other DTMF decoding algorithms that use the conventional discrete Fourier transform (DFT) and the non-uniform discrete Fourier transform (NDFT) are also addressed.     

分数阶Fourier变换在多分量信号谱图分析中的应用

作为时频分析方法的一种,谱图对多分量信号分析时受交叉项影响,特别是当信号相隔很近时尤为严重,而且频率分辨率会受影响。给出了结合分数阶Fourier变换（FrFT）对多分量信号进行谱图分析的方法。首先利用分数阶二阶矩极值点而找到相应的最优旋转阶数,对所给多分量信号按此阶数做分数阶Fourier变换,再在此基础上做谱图分析。仿真实例表明,该方法对初始频率、调频率很接近的多分量的chirp信号能有效识别,交叉项可得到较好的抑制。     

Research progress of the fractional Fourier transform in signal processing

While solving a heat conduction problem in 1807, a French scientist Jean Baptiste Jo-seph Fourier, suggested the usage of the Fourier theorem. Thereafter, the Fourier trans-form (FT) has been applied widely in many scientific disciplines, and has played i…     

Oversampling analysis in fractional Fourier domain

Oversampling is widely used in practical applications of digital signal processing. As the fractional Fourier transform has been developed and applied in signal processing fields, it is necessary to consider the oversampling theorem in the fractional Fourier domain. In this paper, the oversampling theorem in the fractional Fourier domain is analyzed. The fractional Fourier spectral relation between the original oversampled sequence and its subsequences is derived first, and then the expression for exact reconstruction of the missing samples in terms of the subsequences is obtained. Moreover, by taking a chirp signal as an example, it is shown that, reconstruction of the missing samples in the oversampled signal is suitable in the fractional Fourier domain for the signal whose time-frequency distribution has the minimum support in the fractional Fourier domain. Supported partially by the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104), the National Natural Science Foundation of China (Grant Nos. 60890072, 60572094), and the National Basic Research Program of China (Grant No. 2009CB724003)     

基于分数阶Fourier变换的数字图像加密算法研究*

基于分数阶Fourier变换和混沌,提出了一种数字图像加密方法。具体算法为：先对图像进行混沌置乱,再进行X方向的离散分数阶Fourier变换;然后在分数阶Fourier域内作混沌置乱,再进行Y方向的离散分数阶Fourier变换;最后将加密图像的实部与虚部映射到RGB,形成可传输的彩色加密图像。实验结果表明,该加密算法具有很好的安全性,在信息安全领域有较好的应用前景和研究价值。     

MIMO-OFDM system based on fractional Fourier transform and selecting algorithm for optimal order

In the rapidly time-varying channel environment, the performance of traditional MIMO-OFDM system is deteriorated due to the intercarrier interference. In this paper, a novel MIMO-OFDM system is proposed, in which the modulation and de- modulation of the symbols are implemented by the fractional Fourier transform instead of traditional Fourier transform. Through selecting the optimal order of the fractional Fourier transform, the modulated signals can match the time-varying channel characteristics, which results in a mitigation of the intercarrier interference. Furthermore, an algorithm is presented for selecting the optimal order of fractional Fourier transform, and the impact of system parameters on the optimal order is analyzed. Simulation results show that the proposed system can concentrate the power of desired signal effectively and improve the performance over rapidly time-varying channels with respect to the traditional MIMO-OFDM system.     

分数阶傅里叶变换对OFDM系统峰均比的影响

分析并讨论了分数阶傅里叶变换对OFDM系统峰均功率比性能的影响,并与传统的采用离散傅里叶变换的OFDM系统的峰均功率比性能进行了比较。结果表明在子载波数较少的情况下,采用分数阶傅里叶变换的OFDM系统的峰均功率比性能要优于采用离散傅里叶变换的OFDM系统的峰均功率比性能,而随着系统子载波数量的逐渐增加,二者性能趋向一致。     

基于分数傅里叶变换的二维工程图水印算法

提出一种基于离散分数傅里叶变换（DFRFT）的二维工程图数字水印算法。该算法分块提取工程图中线段的相对坐标线构造复值信号量,将水印嵌入复值信号量的分数傅里叶变换频谱（FRT）中。实验表明,该算法对平移、旋转、缩放、部分实体删除或添加等攻击具有良好的鲁棒性,同时具有良好的安全性。     

基于快速分数阶傅氏变换的DDoS攻击检测

针对传统检测方法存在精度低、训练复杂度高、适应性差的问题,提出了基于快速分数阶Fourier变换估计Hurst指数的DDoS攻击检测方法。利用DDoS攻击对网络流量自相似性的影响,通过监测Hurst指数变化阈值判断是否存在DDoS攻击。在DARPA2000数据集和不同强度TFN2K攻击流量数据集上进行了DDoS攻击检测实验,实验结果表明,基于FFrFT的DDoS攻击检测方法有效,相比于常用的小波方法,该方法计算复杂度低,实现简单,Hurst指数估计精度更高,能够检测强度较弱的DDoS攻击,可有效降低漏报、误报率。     

量子混沌和分数阶Fourier变换的图像加密算法

针对传统的自然混沌系统安全性低的问题,提出了量子混沌和分数阶Fourier变换的图像加密算法。通过引入量子Logistic混沌映射,解决了Logistic映射存在的周期窗口、伪随机和非周期性不好等缺陷,还改善了计算机进行浮点数运算丢失精度的问题。同时将混沌系统和分数阶Fourier变换相结合,实现了介于空间域和频域的分数域置乱,克服了传统一些方法只在单一域变换和单纯使用某一种方案而导致参数变量少,系统结构简单,直方图不均匀等缺点。实验和仿真结果表明,该算法具有密钥空间大,计算复杂度低,敏感性强等优点,能够有效地抵御统计分析攻击。     

一种新型分数阶小波变换及其应用

小波变换和分数Fourier变换是应用非常广泛的信号处理工具.但是,小波变换仅局限于时频域分析信号;分数Fourier变换虽突破了时频域局限能够在分数域分析信号,却无法表征信号局部特征.为此,提出了一种新型分数阶小波变换,该变换不但继承了小波变换多分辨分析的优点,而且具有分数Fourier变换分数域表征功能.与现有分数阶小波变换相比,新型分数阶小波变换可以实现对信号在时间-分数频域的多分辨分析.此外,该变换具有物理意义明确和计算复杂度低的优点,更有利于满足实际应用需求.最后,通过仿真实验验证了所提理论的有效性.     

A novel fractional wavelet transform and its applications

The wavelet transform (WT) and the fractional Fourier transform (FRFT) are powerful tools for many applications in the field of signal processing.However,the signal analysis capability of the former is limited in the time-frequency plane.Although the latter has overcome such limitation and can provide signal representations in the fractional domain,it fails in obtaining local structures of the signal.In this paper,a novel fractional wavelet transform (FRWT) is proposed in order to rectify the limitations of the WT and the FRFT.The proposed transform not only inherits the advantages of multiresolution analysis of the WT,but also has the capability of signal representations in the fractional domain which is similar to the FRFT.Compared with the existing FRWT,the novel FRWT can offer signal representations in the time-fractional-frequency plane.Besides,it has explicit physical interpretation,low computational complexity and usefulness for practical applications.The validity of the theoretical derivations is demonstrated via simulations.     

基于分数阶傅里叶变换的多项式相位信号参数估计

研究了一种基于分数阶傅里叶变换(FRFT)的多项式相位信号快速估计方法,对于线性调频信号(LFM),即用信号延时相关解调的方法得到调频斜率的粗略估计,从而得到分数阶旋转角度的范围,简化为小范围的一维搜索问题。多项式相位信号的检测通过延时相关解调可转化为LFM信号的检测,再运用FRFT便可进行参数估计。理论分析与仿真结果表明该方法简单,估计性能好。