基于重排方法的多分量线性调频信号分析

多分量线性调频信号的魏格纳分布(WVD)交叉项严重，而其平滑伪魏格纳分布(SPWVD)虽然抑制了交叉项但降低了时频聚集性。本文利用重排平滑伪魏格纳分布(RSPWVD)分析多分量线性调频信号，并以旁瓣电平(SLL)、交叉项干扰抑制(CTR)、分辨率损失(RL)等指标定量比较了它们的性能。仿真结果表明，RSPWVD旁瓣电平最低，交叉项抑制最好，分辨率损失最少。     

基于Wigner-Ville分布的复杂时变信号的时频分析

对多分量线性调频(LFM)信号、单分量非线性调频(NLFM)信号以及多分量NLFM信号的Wigner-Ville分布进行了数值计算,探讨了信号项与交叉项之间的差异性特征,提出了信号时频曲线中点集的概念,研究了交叉项出现的一般规律.对于多分量信号,交叉项出现在信号项时频曲线之间的中点集之内.对于单分量NLFM信号,也有交叉项产生,交叉项出现在信号项时频曲线自身的自中点集之内.     

一种基于SPWVD-WVD的高质量时频分析方法及ISAR成像应用

交叉项干扰抑制与高时频聚集度是准确反应信号的时频分布特征的重要因素。传统的魏格纳-维尔分布(Wigner-Ville Distribution,WVD)算法虽能获得较高的时频分辨特征,但分析多成分信号时存在严重的交叉项干扰问题,限制了其实用性;而平滑伪魏格纳-维尔分布(Smoothed Pseudo Wigner-Ville Distribution,SPWVD)算法虽在一定程度上抑制交叉项干扰,但降低了时频聚集度。为了解决上述问题,提出了基于SPWVD-WVD的时频分析方法。该方法利用SPWVD与WVD之间的滤波互消效应,将SPWVD二值化结果与WVD结果进行矩阵运算,最终得到高质量的时频分析结果。实验结果表明,所提出的算法能够有效去除多分量信号的交叉项干扰,提高信号分析结果的时频聚集度,还原多分量信号的真实时频分布。最后将该算法成功应用于逆合成孔径雷达成像中。     

多Chirp信号的Cohen类时频分布的性能分析

以广泛出现在工程应用和许多物理现象中的多分量Chirp信号为对象,研究了Cohen类时频分布对这种信号时频表示性能,定量地描述了各种时频分布的时频聚集程度,分析了交叉项的特点和抑制机理,提出了现有的Cohen类时频分布对该类信号交叉项抑制存在局限,仿真结果验证了理论分析的正确性.     

一种针对多分量信号的复延迟型时频分布的实现方法

 复延迟型时频分布(CTD)是近年来提出的一种新型时频分布.对于单分量调频信号,CTD具有良好的时频聚集性.但是对于包含两个或两个以上分量的多分量调频信号,直接采用定义式或传统频域卷积方法实现的CTD会产生大量的互交叉项,影响了它在各领域的应用.本文对CTD的传统频域卷积实现方法进行了三方面的修正,提出了一种适合多分量调频信号的修正型CTD频域卷积实现方法.仿真结果表明,本文方法对于多分量调频信号,既保持了CTD所固有的时频聚集性高的优点又极大地抑制了不同信号分量间的互交叉项.     

一种抑制时频分布交叉项的新方法

 提出一种抑制时频分布交叉项的新方法,该方法在Wigner-Ville分布(WVD)的基础上,引入一相位校正函数,可抑制信号的非线性导致的自交叉项影响.对于多分量信号,文中采用洁净(CLEAN)技术对每个信号分量进行带通滤波,抑制了信号分量间的互交叉项影响.该方法在抑制时频分布交叉项的同时,保持着较高的时频聚集性,计算机仿真实验验证了本文算法的有效性.     

基于LPFT时频滤波器的WVD交叉项抑制方法

本文提出一种抑制Wigner-Ville分布(WVD)交叉项的新方法。利用局部多项式傅里叶变换(LPFT)构建时频滤波器,确定自项支撑区域,再利用此滤波器对WVD进行处理,从而达到抑制交叉项的目的。通过3dB信噪比的分析可以看出,LPFT具有比短时傅里叶变换(STFT)更好的时频聚集性,因此基于LPFT的时频滤波器能更有效抑制WVD中的交叉项干扰,同时又能保留WVD的高时频聚集性。通过与Chio-Williams分布、径向高斯核函数时频分布、基于STFT时频滤波器的交叉项抑制方法的比较,验证了该方法对抑制多分量信号及非线性调频信号的交叉项以及噪声干扰的有效性,显示了该方法在保持高时频聚集性,抑制交叉项干扰,以及抑制噪声干扰方面的优势。     

一种低副瓣无混叠的线性调频信号时频分析方法

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。     

基于Wigner分布时频遮隔的信号分解算法

综合特征值分解及Wigner分布时频遮隔提出了一种信号分解算法,并推广应用于其他交叉项抑制时频表示.对于由时频面上互不重叠分量合成的多分量信号,证明了信号分量可与各分量Wigner分布之和的逆Fourier变换的特征值分解相对应;通过阈值法可从抑制交叉项时频表示获得信号时频支撑区域,以此为模板遮隔Wigner分布可减少交叉项并保持自项聚集性,其逆Fourier变换的特征值分解就可实现多分量信号分解.仿真实例分析结果表明了该理论与算法的正确性和实用性.最后分析了算法性能并拓展了其实用范围.     

基于频域CLEANWigner-Ville分布中交叉项的抑制

针对ISAR飞机成像中出现的多分量线性调频(chirp)信号,该文提出一种基于频域CLEAN的信号分解方法,将其分解成多个单分量chirp信号,然后分别计算每个单分量的Wigner-Ville分布(WVD),以此来抑制此多分量信号WVD中的交叉项,与已有的chirp信号分解方法相比,该法减少了待估计参数的个数,使得计算更加简单,并能保证信号各分量正确的强度及时频变化特征。经过处理后的信号的WVD,保持了WVD高时频分辨率的特点,而交叉项得到了很好的抑制。实验表明,该方法应用于实测数据,成像质量明显提高了。     

A NEW QUADRATIC TIME-FREQUENCY DISTRIBUTIONAND A COMPARATIVE STUDY OF SEVERAL POPULARQUADRATIC TIME-FREQUENCY DISTRIBUTIONS

A new quadratic time-frequency distribution (TFD) with a compound kernel is proposed and a comparative study of several popular quadratic TFD is carried out. It is shown that the new TFD with compound kernel has stronger ability than the exponential distribution (ED) and the cone-shaped kernel distribution (CKD) in reducing cross terms, meanwhile almost not decreasing the time-frequency resolution of ED or CKD.     

一种新的二次时频分布和几种主要二次时频分布的比较研究

本文提出一种新的Cohen类时频分布并对几种主要Cohen类时频分布进行了实验比较研究。结果表明,基于指数分布(ED)和锥形核分布(CKD)的复合核分布(ECKD)具有更强的抑制交叉干扰性质,同时几乎不会使ED或CKD的时频分辨力降低。     

Analysis of Multi-Component Non-Stationary Signals Using Fourier-Bessel Series and Wigner-Hough Transform

We presented a novel Fourier-Bessel (FB) series and Wigner-Hough transform (WHT) method for the analysis of multi-component non-stationary signals. The FB series decomposed multi-component non-stationary signals into mono-component signals. The Wigner-Ville distribution (WVD) was applied to each mono-component signal to analyze its time-frequency distribution (TFD). Summing up the WVDs of the individual components resulted in TFDs of the multi-component signals, where the cross terms and noise were significantly reduced. The Hough transform (HT) was applied on the TFD of the multi-component signal (obtained from FB-WVD). The HT provides an important tool for mapping the signals onto a parameter space where the detection and estimation problems are made easier. This mapping can be used in the detection and parameter estimation of signals which are unknown and embedded in noise.     

Tomography time-frequency transform

The paper shows that the fractional Fourier transform (FRFT) of a signal is the Radon transform of the time-frequency distribution of the same signal. Therefore, a time-frequency distribution known as the tomography time-frequency transform (TTFT) is defined as the inverse Radon transform of the FRFT of the signal. Because the computation of the TTFT does not explicitly require any window or kernel function, high resolutions in both the frequency and time domains can be achieved. When the signal contains multiple components, the cross terms can be effectively removed by an adaptive filtering process that is applied on the FRFT rather than the final result. Therefore, distortions made by the filtering process on the desired signal components can be minimized     

基于能量峰区域时频滤波的信号估计

本文提出了一种基于能量峰时频区域滤波的信号估计方法。首先,设计了一种基于能量阈值的时频区域提取方法,识别出信号在时频面上的能量峰,并提取出能量峰所占据的时频区域;利用线性时频滤波器获取信号中的分量,将这些分量的时频分布叠加得到改善的时频分布。仿真结果表明,对于由时频不相交分量组成的信号,本方法可以分离出其中的信号分量,并能得到较优的时频分布。     

基于稀疏时频分布的跳频信号参数估计

基于常规时频分析方法的跳频信号参数估计中,采用核函数抑制时频分布交叉项会导致时频聚集性的下降,不利于信号参数提取。针对此问题,该文提出一种基于稀疏时频分布(STFD)的跳频信号处理方法。该方法首先根据Cohen类分布的原理和跳频信号模糊函数的特点,以模糊域矩形窗为核函数,构建了一种Cohen类的矩形核分布(RKD)。RKD可有效抑制交叉项,但其时频分辨率较低。为提高RKD的时频性能,在压缩感知框架下,利用跳频信号时频分布的稀疏特性,对RKD附加稀疏性约束,建立稀疏时频分布(STFD)的优化求解模型。STFD不仅能有效抑制交叉项,而且具有良好的时频聚集性。仿真分析表明,与传统时频分析方法相比,该文提出的基于STFD的跳频信号参数估计方法性能更优。     

Adaptive optimal kernel smooth-windowed Wigner-Ville bispectrum for digital communication signals

Higher-order time-frequency distribution (HO-TFD) outperforms the bilinear TFD in noisy conditions but suffers more severely from cross-terms when used to analyze multi-component signals. Various kernel functions have been introduced to suppress cross-terms in bilinear TFD but in general TFD with a fixed kernel do not give accurate TFR for all type of signals. In this paper, adaptive optimal TFR is obtained by extending the separable kernel design in bilinear TFD to the third-order TFD and is able to achieve accurate time-frequency representation at SNR as low as −2 dB. This globally adaptive optimal kernel smooth-windowed Wigner-Ville bispectrum (AOK-SWWVB) is designed where its separable kernel is determined automatically from the input signal, without prior knowledge of the signal parameters. It is shown that this system performance is comparable to the system when priori knowledge of the signal is known.     

Kernel decomposition of time-frequency distributions

Bilinear time-frequency distributions (TFDs) offer improved time-frequency resolution over linear representations, but suffer from difficult interpretation, higher implementation cost, and the lack of associated low-cost signal synthesis algorithms. In the paper, the authors introduce some new tools for the interpretation and quantitative comparison of high-resolution TFDs. These tools are used in related work to define low-cost high-resolution TFDs and to define linear, low-cost signal synthesis algorithms associated with high-resolution TFDs. First, each real-valued TFD is associated with a self-adjoint linear operator ψ. The spectral representation of ψ expresses the TFD as a weighted sum of spectrograms (SPs). It is shown that the SP decomposition and Weyl correspondence do not yield useful interpretations for high-resolution TFDs due to the fact that ψ is not positive     

High Resolution Time-Frequency Distribution Based on Short-Time Sparse Representation

This paper focuses on the high resolution time-frequency distribution (TFD) of multicomponent signals with amplitude and frequency modulations, and a concise method named short-time sparse representation (STSR) is proposed. In STSR, both analysis and synthesis of the discrete signal can be achieved by exploiting the signal’s sparsity in frequency domain at each time instant. In order to fasten the STSR procedure, an efficient sparse recovery algorithm named SL0 is applied, and the signal model for each sliding window is modified to form the same dictionary, which guarantees that the whole recovery procedure adapts to the matrix form. The performance of STSR is compared with other TFD techniques and assessed in various configurations. It is shown that both preferable representation and acceptable computational cost can be obtained.     

间歇采样转发式干扰的时频域辨识与抑制

间歇采样转发式干扰利用数字射频存储器(DRFM)对雷达发射信号进行截获与转发,具有小型化、轻量化和灵活多变的优势,可搭载在目标上形成多点源主瓣干扰,对现代雷达构成了严重威胁。该文对上述干扰的辨识与抑制方法进行了研究。通过推导干扰脉冲压缩与时频分布的解析表达式,分析了目标回波与典型干扰信号的时频特征差异;在此基础上,提出一种时频域干扰辨识方法,并构造时频域滤波器进行干扰抑制。仿真结果表明:在原始信号干噪比大于–3 dB的情况下,算法辨识率可达90%;在此基础上,通过时频域滤波可以对3种典型策略下干扰都进行有效抑制,其峰值信干噪比改善可达18 dB。