基于多尺度线调频基信号稀疏分解的 信号分离和瞬时频率估计

提出了一种基于多尺度线调频基信号稀疏分解的多分量多项式相位信号分离和瞬时频率估计方法.该方法采用多尺度的线调频基函数对多分量多项式相位信号进行投影分解,通过从不同的时间支撑区内投影系数最大的基函数中寻找出使分解信号能量最大的基元函数组合,逐次获得信号包含的能量最大的多项式相位信号分量,从而实现多分量多项式相位信号的分离,而从基元函数连接形成的频率曲线则可获得多项式相位信号分量瞬时频率的估计.仿真信号分析表明,本文方法能在信噪比较低情况下有效分离多分量多项式相位信号中包含的多项式相位信号分量,准确地估计其瞬时频率.     

一种时频分布核函数构造方法

立足于信号的参数化模型—多分量多项式相位信号,提出了一种新的时频分布并给出了其构造方法.该方法根据待分析的瞬时相关函数中自项分量及交叉项分量相位的不同特点,采用相位匹配的方法估计各信号分量的瞬时频率.所构造的时频分布不仅具有理想的频率聚集性,而且实现了绝大多数交叉项分量的有效抑制,有效克服了多线性时频分析方法的局限性.     

基于广义周期性的单通道多分量正弦调频信号分离和参数估计

针对噪声条件下的单通道多分量正弦调频(SFM)信号,该文提出一种信号分离和参数提取方法。利用正弦调频信号的广义周期性进行奇异值分解,以求出分量信号的调制频率;通过离散点搜索,估计出分量信号的调频(FM)初始相位、调制指数及载频,并对这些估计值利用信赖域算法进行优化,减小误差;利用内积计算,估计分量信号的幅度和初始相位。此外,还利用自相关矩阵特征值分解估计混合信号的信噪比(SNR),并根据信噪比确定停止分解的阈值。在仿真与分析中,针对具体的信号详细说明了该方法的各步骤,并在不同信噪比条件下分析了该方法的参数估计精确度。     

基于RPRG+ICCD与RANSAC的多分量多项式相位信号参数估计

多分量多项式相位信号的检测和参数估计是多项式相位信号处理的一大难点。时频分析方法能够通过时频分布表征多项式相位信号的瞬时频率,通过对提取的瞬时频率进行多项式拟合得到其系数,经过简单的变换即可获得多项式相位信号的参数。文中利用RPRG+ICCD分离多分量多项式相位信号得到各个分量的瞬时频率,再使用RANSAC进行多项式拟合,最终实现了多项式相位信号的参数估计。实验结果表明,文中提出的方法能够实现在时频域部分重叠的多分量多项式相位信号的分离和参数估计。     

基于瞬时频率估计的进动锥体目标微多普勒频率提取方法

该文针对进动锥体目标的微动特性提取,建立等效散射点模型下的微多普勒频率与目标运动参数关系。结合进动调制的微多普勒频率近似正弦变化规律的特点,提出基于瞬时频率估计和随机抽样一致性(RANSAC)的进动目标微多普勒频率提取方法。该方法将回波信号分为若干段,每一段的回波信号近似为若干线性调频(LFM)信号分量之和,通过调频Relax算法估计各信号分量的瞬时频率,并通过随机抽样一致性算法估计散射点的微多普勒曲线。基于仿真数据和电磁计算数据的实验验证了该方法的有效性及稳健性。     

基于改进带宽自适应ACMD的信号分离方法

针对复杂电磁环境下出现多个辐射源信号混叠造成的多分量信号分离问题,提出了基于改进带宽自适应线性调频模态分解（ACMD）的信号分离方法。该方法利用频谱集中性指标对各信号分量的瞬时频率进行估计,将估计的瞬时频率值作为改进算法的预设频率;利用递归框架和改进带宽自适应更新方法对各信号分量进行循环迭代;直到剩余信号能量小于阈值,完成所有信号分离。仿真实验表明,该方法能够在复杂电磁环境下分离出多分量信号,相比较已有算法对紧邻信号具有更好的分离性能和抗噪声性能。     

基于DSP的通信信号瞬时频率时域提取

通信信号瞬时频率的提取是许多调制识别方法正确识别频率调制信号和相位调制信号的基础,绝大多数瞬时频率提取方法计算复杂、硬件实现难度大。提出一种信号瞬时频率的时域提取新方法,直接从正交分量和同相分量估计通信信号瞬时频率,结合DSP阐述了该方法的特性。利用Matlab软件对6种调制信号进行算法仿真,表明该方法的可行性,且不仅适合DSP硬件实现,而且计算简便、效果良好。     

一种新的宽带信号正交分量的解调方法

在D通道均匀DFT分析滤波器组基础上给出了一种新的信号正交分量的解调结构 ,为解调宽带信号 (B fc)的正交分量 ,系统采用两组D通道均匀DFT分析滤波器组通带互补方法 ,以克服单组滤波器中滤波器的非理想性所造成的信号失真。在频域中当信号频谱处于两个或更多个滤波器通道时 ,通过频谱组合办法直接得到实信号的正半谱或负半谱。在载波频率已恢复的情况下给出了IQ正交分量的解调算法。仿真证明该系统结构和算法的正确性和高效性     

基于HHT的多分量LFM信号检测与参数估计

文中将Hilbert—Huang变换应用到多分量线性调频信号（LFM）信号的分析中：首先利用经验模态分解法（EMD）将原信号分解成有限个本征模态函数（IMF）；然后埘各个IMF进行Hilbert变换，获取瞬时频率、瞬时振幅，得到信号的Hilbert谱，该谱反映r瞬时振幅在频率一时间平面上的分布，从而可以比较准确地检测和估计各LFM分量的初始频率和调频斜率等参数。仿真结果验证了该方法的有效性。     

多分量多项式相位信号瞬时频率变化率的估计

引入了一个二维双线性相位匹配变换.对相位阶次不大于5的多分量多项式相位信号(mc-PPS)而言,各信号分量的瞬时频率变化率(IFR)在变换结果中表现为局部极值点,而交叉项则很少表现为极值点.又由于各信号分量IFR随时间变化表现出连续性,而由交叉项所产生的各极值点无此特征,因此,该变换可用于实现mc-PPS中各信号分量IFR的估计.对估计性能进行了理论分析,并同仿真结果进行了比较.     

A linear model for TF distribution of signals

We describe a new linear time-frequency model in which the instantaneous value of each signal component is mapped to the curve functionally representing its instantaneous frequency. This transform is linear, uniquely defined by the signal decomposition, and satisfies linear marginal-like distribution properties. We further demonstrate the transform generated surface may be estimated from the short time Fourier transform by a concentration process based on the phase of the short-time Fourier transform (STFT), differentiated with respect to time. Interference may be identified on the concentrated STFT surface, and the signal with the interference removed may be estimated by applying the linear-time-marginal to the concentrated STFT surface from which the interference components have been removed.     

一种基于经验模态分解的锥体目标雷达微动特征提取新方法

本文以锥体目标为对象,分析了目标进动对雷达回波的调制作用,研究了基于经验模态分解算法的多分量正弦调频信号分离方法,使用短时傅里叶变换得到了每个本征模态函数的瞬时频率,提取了进动周期、进动角、不同散射点间的微动幅度比值等微动特征及目标纵横比,并用暗室测量数据进行了验证,证明了本文的观点和特征提取方法的有效性.     

Analysis and filtering using the optimally smoothed Wignerdistribution

The authors consider the analysis and filtering of a deterministic signal with slowly time-varying spectra using the optimally smoothed Wigner distribution (OSWD). They compare this mixed time-frequency representation (MTFR) to other MTFRs such as the spectrogram, the short-time Fourier transform (STFT), and the Wigner and pseudo-Wigner distributions. The authors propose an approach to designing linear time-varying filters for slowly time-varying signals which is based on the concept of local nonstationarity cancellation and show that it is equivalent to masking the optimal STFT. The performance of the filter in suppressing white noise and in decomposing a slowly time-varying signal into its components is studied and compared to the performance of the techniques based on the STFT     

Blind Calibration of Timing Offsets for Four-Channel Time-Interleaved ADCs

In this paper, we describe a blind calibration method for timing mismatches in a four-channel time-interleaved analog-to-digital converter (ADC). The proposed method requires that the input signal should be slightly oversampled. This ensures that there exists a frequency band around the zero frequency where the Fourier transforms of the four ADC subchannels contain only three alias components, instead of four. Then the matrix power spectral density (PSD) of the ADC subchannels is rank deficient over this frequency band. Accordingly, when the timing offsets are known, we can construct a filter bank that nulls the vector signal at the ADC outputs. We employ a parametrization of this filter bank to develop an adaptive null steering algorithm for estimating the ADC timing offsets. The null steering filter bank employs seven fixed finite-impulse response filters and three unknown timing offset parameters which are estimated by using an adaptive stochastic gradient technique. A convergence analysis is presented for the blind calibration method. Numerical simulations for a bandlimited white noise input and for inputs containing several sinusoidal components demonstrate the effectiveness of the proposed technique     

基于联合对角化的声信号深度卷积混合盲分离方法

声信号在空间中的传播具有较强的多径效应,在接收端往往以卷积形式相互叠加,尤其在海洋、剧场等强混响条件下,混合滤波器冲激响应的长度会显著增加,现有的频域卷积盲分离算法将失效。为了消除长脉冲响应导致解混合模型失效的问题,该文对观测信号进行两次短时傅里叶变换(STFT),第1次STFT缩短了脉冲响应长度,第2次STFT将信号模型转化为瞬时盲分离,最终利用联合对角化(JD)技术估计出分离矩阵。与现有方法相比,所提方法解决了深度卷积混合下模型失效的问题,并且当源信号数较多或存在加性噪声时,可以得到更好的分离性能。仿真结果验证了方法的有效性和性能优势。     

一种快速雷达信号脉内调制识别分析方法

针对类信号的脉内调制识别问题,提出了一种基于短时傅里叶变换(STFT)和瞬时累加自相关的快速雷达信号脉内调制识别方法。采用由粗到细的识别方案,依据累加STFT频谱带宽将信号分为调频和调相信号。采用时域累加瞬时自相关识别BPSK和QPSK信号,利用STFT频谱的时域特征识别LFM和NLFM信号,经仿真实验分析,在较低信噪比下可正确实现信号识别,该方法适于FPGA的快速实现。     

基于小波变换的MSK信号码速率盲估计

针对最小频移键控调制信号的码速率估计问题,提出一种基于Haar小波变换的MSK信号码速率盲估计方法。首先对接收信号作傅里叶变换得到信号频谱,对频谱频点分析粗估计信号的码速率,接着通过粗估计的码速率选取短时傅里叶变换窗函数长度和3个小波尺度,利用短时傅里叶变换得到信号瞬时频率变化,再利用小波的边缘检测特性对信号瞬时频率序列相位跳变点检测,最后对检测结果作频谱分析,估计频率得到MSK信号的码速率。仿真结果表明,高于信噪比门限时本算法可以对MSK信号码速率有效估计。     

Regularized Spectral Matching for Blind Source Separation. Application to fMRI Imaging

The main contribution of this paper is to present a Bayesian approach for solving the noisy instantaneous blind source separation problem based on second-order statistics of the time-varying spectrum. The success of the blind estimation relies on the nonstationarity of the second-order statistics and their intersource diversity. Choosing the time-frequency domain as the signal representation space and transforming the data by a short-time Fourier transform (STFT), our method presents a simple EM algorithm that can efficiently deal with the time-varying spectrum diversity of the sources. The estimation variance of the STFT is reduced by averaging across time-frequency subdomains. The algorithm is demonstrated on a standard functional resonance imaging (fMRI) experiment involving visual stimuli in a block design. Explicitly taking into account the noise in the model, the proposed algorithm has the advantage of extracting only relevant task-related components and considers the remaining components (artifacts) to be noise.     

Investigating the nonlinear dynamics of cellular motion in theinner ear using the short-time Fourier and continuous wavelet transforms

The short-time Fourier transform (STFT) and the continuous wavelet transform (CWT) are used to analyze the time course of cellular motion in the inner ear. The velocity responses of individual outer hair cells and Hensen's cells to sinusoidal and amplitude modulated (AM) acoustical signals applied at the ear canal display characteristics typical of nonlinear systems, including the generation of harmonic and half-harmonic components. The STFT proves to be valuable for following the time course of the frequency components generated using sinusoidal and ARM input signals. The CWT is also useful for analyzing these signals; however, it is generally not as effective as the STFT when octave-band-based CWT's are used. For the transient response, the spectrogram (which is the squared magnitude of the STFT) and the octave-band-based scalogram (which is the squared magnitude of the CWT) prove equally valuable, and the authors have used both to study the responses of these cells to step-onset tones of different frequencies. Such analyses reveal information about the preferred vibration frequencies of cells in the inner ear and are useful for deciding among alternative mathematical models of nonlinear cellular dynamics. A modified Duffing oscillator model yields results that bear some similarity to the data     

Two-channel IIR QMF banks with approximately linear-phase analysisand synthesis filters

Perfect linear-phase two-channel QMF banks require the use of finite impulse response (FIR) analysis and synthesis filters. Although they are less expensive and yield superior stopband characteristics, perfect linear phase cannot be achieved with stable infinite impulse response (IIR) filters. Thus, IIR designs usually incorporate a postprocessing equalizer that is optimized to reduce the phase distortion of the entire filter bank. However, the analysis and synthesis filters of such an IIR filter bank are not linear phase. In this paper, a computationally simple method to obtain IIR analysis and synthesis filters that possess negligible phase distortion is presented. The method is based on first applying the balanced reduction procedure to obtain nearly allpass IIR polyphase components and then approximating these with perfect allpass IIR polyphase components. The resulting IIR designs already have only negligible phase distortion. However, if required, further improvement may be achieved through optimization of the filter parameters. For this purpose, a suitable objective function is presented. Bounds for the magnitude and phase errors of the designs are also derived. Design examples indicate that the derived IIR filter banks are more efficient in terms of computational complexity than the FIR prototypes and perfect reconstruction FIR filter banks. Although the PR FIR filter banks when implemented with the one-multiplier lattice structure and IIR filter banks are comparable in terms of computational complexity, the former is very sensitive to coefficient quantization effects