Joint time-frequency interpretation of scattering phenomenology indielectric-coated wires

The scattering phenomenology in dielectric-coated wire structure is investigated using the joint time-frequency processing of simulated and measurement data. The method of moments is applied to carry out the simulation. The computed results are compared to measured data in both the frequency and time domains. The scattering data are next analyzed in the joint time-frequency plane by using the short-time Fourier transform (STFT) technique to provide further insight into the scattering phenomenology. The dispersive Goubau mode excited along the coated wire can be clearly observed in the joint time-frequency plane. In addition, the time-frequency distribution series, which improves the resolution of the STFT while overcoming the cross-term interference problem of the Wigner-Ville distribution, is applied to better identify backscattering returns that are difficult to resolve in the joint time-frequency plane     

Interpretation of scattering phenomenology in slotted waveguidestructures via time-frequency processing

The scattering phenomenology in slotted waveguide structures is investigated using time-frequency processing of numerically simulated data. Two geometries are studied, a finite waveguide with one slot on each end and a linear slotted waveguide array comprised of 16 equally spaced slots. The numerical simulation is accomplished via a three-dimensional moment-method procedure in conjunction with a connection scheme which makes possible the simulation of a long waveguide structure spanning over 32 wavelengths at 10 GHz. The resulting numerical data are then processed using the short-time Fourier transform to identify the dominant scattering mechanisms. In the joint time-frequency plane, the unique scattering physics associated with slotted waveguide structures are more clearly revealed. In particular, the Floquet harmonics due to the exterior slot structure, the dispersion due to the interior waveguide modes, and the “interior Floquet” phenomenon can be readily identified and fully interpreted     

基于线性正则变换与短时傅里叶变换联合的时频分析方法

线性正则变换作为傅里叶变换、分数阶傅里叶变换更为广义的形式,已经在光学和信号处理等领域得到了应用.短时傅里叶变换是一种线性时频分布,避免了其他双线性时频分布中出现的交叉项干扰,是分析时频信号的有力工具.本文从线性正则变换的定义和性质出发,研究了线性正则变换与短时傅里叶变换的时频关系,提出了基于线性正则变换与短时傅里叶变换联合的时频分析方法,避免了交叉项问题能够实现chirp信号干扰抑制和多分量时频信号分离.最后用仿真实例表明,该方法是分析时频信号的有效手段.     

Local spectral analysis of short-pulse excited scattering fromweakly inhomogeneous media. II. Inverse scattering

For Pt.I see ibid., vol.47, no.7, p.1208-17 (July 1999). This paper is concerned with the reconstruction of a weakly inhomogeneous scattering profile from data generated by a short-pulse incident plane wave, which is postprocessed so as to localize the interrogated region to a space-time resolved scattering cell, The phase-space localization due to postprocessing is brought about by applying local (i.e., windowed) slant-stack transforms to the time-dependent scattered fields. In the domain of the scatterer, this processing corresponds to applying windowed Radon transforms to the induced field distribution, which, in turn, generates pulsed-beam (PB) wave packets traveling toward the observer. The forward analysis parameterizing this new form of time-domain (TD) diffraction tomography has been performed in a companion paper and furnishes the framework for the investigation here. Via the forward parameterization, the three-dimensional (3-D) global scattering phenomenology has been reduced to scattering from an equivalent one-dimensional (1-D) scattering cell oriented along the bisector between the direction of the incident plane pulse and the direction of the scattered pulsed beam (PB) to the observer. For the inverse problem, this process is reversed by windowing the scattered field and backpropagating the resulting PBs so as to form local images of any selected region in the scattering domain. The phase-space signature of the scattering cell is related to the Radon transform of the medium in the cell so that the local profile function can be recovered by Radon inversion. An illustrative numerical example is included. Also discussed is the ultimate localization achieved by incident PB excitation and PB postprocessing of the scattered field     

基于短时迭代自适应-逆Radon变换的微多普勒提取方法

对于频率交叠严重且频率成分接近的多分量信号,常用的短时傅里叶变换(Short Time Fourier Transform,STFT)和S方法(S-Method,SM)频率分辨能力不足,重构精度低.针对该问题,本文结合逆Radon变换提出了基于短时迭代自适应-逆Radon变换(Short Time Iterative Adaptive Approach-Inverse Radon Transform,STIAA-IRT)的微多普勒特征提取方法.首先采用基于加权迭代自适应的STIAA时频分析方法分析了散射点模型的微多普勒特性,然后利用逆Radon变换分离重构不同散射点的微多普勒分量.该方法在低信噪比、邻近时频分布情况下能获得高分辨的多分量信号的完整微多普勒信息,性能分析显示STIAA-IRT重构精度较高,明显优于STFT-IRT (Short Time Fourier Transform-Inverse Radon Transform)和SM-IRT (S-Method-Inverse Radon Transform)特征提取方法.     

基于S变换的线性调频信号时频滤波

线性调频(LFM)信号是一种典型的非平稳信号。对非平稳信号的分析和处理不能仅依靠传统的基于傅里叶变换的分析方法,必须采用时域和频域联合的时频分析方法。将S变换(ST)的时频分析方法应用到LFM信号的滤波中,用tST-tIST和fST-fIST 2种算法组合分别实现了对LFM信号的滤波,然后采用均方误差(MSE)的衡量标准,仿真对比了以上2种算法组合的滤波性能。仿真结果表明:fST-fIST算法的滤波误差较大,不适合对LFM信号的滤波;tST-tIST算法的滤波性能较好,适合对LFM信号的滤波。     

Fast implementations of generalized discrete time-frequencydistributions

Cohen's class of time-frequency distributions (TFDs) have significant potential for the analysis of complex signals. In order to evaluate the TFD of a signal using its samples, discrete-time TFDs (DTFDs) have been defined as the Fourier transform of a smoothed discrete autocorrelation. Existing algorithms evaluate real-valued DTFDs using FFTs of the conjugate-symmetric autocorrelation. Although the computation required to smooth the autocorrelation is often greater than that for the FFT, there are no widely applicable fast algorithms for this part of the processing. Since the FFT is relatively inexpensive, downsampling is ineffective for reducing computation. If the DTFD needs only to be evaluated at a few frequencies for each time instant, the cost per time-frequency sample can be extremely high. The authors introduce two approaches for reducing the computation time of DTFDs. First, they define approximations to real-valued DTFDs, using spectrograms, that admit fast, space-saving evaluations. Frequency downsampling reduces the computation time of these approximations. Next, they define DTFDs that admit fast evaluations over sparse sets of time-frequency samples. A single short time Fourier transform is calculated in order for DTPD time-frequency samples to be evaluated at an additional, fixed cost per sample     

Signal Analysis by Time-Frequency Distributions–Applications to Impulse Radar Scattering Echoes of Plate and Dihedral Corner

The scattering phenomenology of the plate and the dihedral corner are investigated using the time-frequency processing of simulated data. The FDTD method is applied to carry out the simulated data. The simulated data are next analyzed in joint time-frequency plane by using the STFT (short time Fourier transformation) technology to provide further insight into the scattering phenomenology. In addition, the time-frequency distribution series, which improves the resolution of the STFT while overcoming the cross-term interference problem of the Wigner-Ville distribution, is applied to better identify back scattering returns that are difficult to resolve in the joint time-frequency plane.     

Super-resolved time-frequency analysis of wideband backscattereddata

A time-frequency super-resolution procedure is presented for processing wideband backscattered data containing both scattering center and natural resonance information. In this procedure, Prony's method is first applied in the frequency domain to locate scattering centers. The data is processed one slice at a time through the use of a sliding window function. Parameterized models for the scattering centers are obtained by a weighted average of the results from each segment. A similar procedure is used in the time domain to fully parameterize the natural resonances. In contrast to other time-frequency techniques, the time-frequencg display from the present super-resolution procedure is not constrained in resolution by the Fourier limit     

Short-pulse three-dimensional scattering from moderately rough surfaces: a comparison between narrow-waisted Gaussian beam algorithms and FDTD

In this paper, with reference to short-pulse three-dimensional scattering from moderately rough surfaces, we present a comparison between Gabor-based narrow-waisted Gaussian beam (NW-GB) and finite-difference time-domain (FDTD) algorithms. NW-GB algorithms have recently emerged as an attractive alternative to traditional (ray-optical) high-frequency/short-pulse approximate methods, whereas FDTD algorithms are well-established full-wave tools for electromagnetic wave propagation and scattering. After presentation of relevant background material, results are presented and discussed for realistic parameter configurations, involving dispersive soils and moderately rough surface profiles, of interest in pulsed ground penetrating radar applications. Results indicate a generally satisfying agreement between the two methods, which tends to improve for slightly dispersive soils. Computational aspects are also compared.     

Radar Polarimetry Analysis Applied to Single-Hole Fully Polarimetric Borehole Radar

A fully polarimetric borehole radar system using four combinations of dipole and slot antennas was developed to acquire fully polarimetric data sets in drilled boreholes. First, to implement radar polarimetry analysis, a processing scheme suitable for analyzing a single-hole reflection data set acquired by the system is presented. This processing consists of antenna-characteristic compensation, migration for image reconstruction, and time-frequency analysis for single-frequency data set construction. Two polarimetric target decomposition methods, namely: 1) Pauli decomposition and 2) eigenvector-based decomposition, are applied to characterize the scattering problem of the subsurface fractures. The Pauli decomposition method provided important radar polarimetry information of fractures, and the eigenvector-based decomposition method made a significant contribution to understanding the scattering mechanisms from different fractures with different properties. Furthermore, information about fracture classification can be obtained by analysis of the H-alpha distribution provided by eigenvector-based decomposition of local radar image regions. The potential of polarimetric target decomposition techniques to fracture characterization is shown, which, in turn, provides valuable information about water permeabilities of fractures in hydrogeological studies     

Fast Algorithms for Polynomial Time-Frequency Transforms of Real-Valued Sequences

This paper presents fast algorithms for computing the polynomial time-frequency transform that deals with a real-valued sequence of length-a^pb, where a, b and p are positive integers. In particular, it shows that the polynomial time-frequency transform has a conjugate symmetric property, similar to that of the discrete Fourier transform, if the input sequence is real-valued. The computational complexities needed by these proposed algorithms are analyzed in terms of the numbers of real additions and real multiplications. When a=3,4, and 8, comparisons show that the computational complexities required by the proposed algorithms are less than 60% of those needed by the fast algorithms for complex-valued sequences.     

Short-pulse plane-wave scattering from buried perfectly conductingbodies of revolution

The method of moments is used to analyze short-pulse plane-wave scattering from perfectly conducting bodies of revolution buried in a lossy, dispersive half space. The analysis is performed in the frequency domain, with the time-domain fields synthesized via Fourier transform. To make this analysis efficient, the method of complex images is used to compute the frequency-dependent components of the half-space dyadic Green's function. Results are presented for short-pulse scattering from buried spheres and cylinders, using measured frequency-dependent soil parameters (permittivity and conductivity)     

基于CM-OMEMD和小波散射网络的语音情感识别

语音情感识别（Speech Emotion Recognition,SER）是人机交互的重要组成部分,具有广泛的研究和应用价值。针对当前SER中仍然存在着缺乏大规模语音情感数据集和语音情感特征的低鲁棒性而导致的语音情感识别准确率低等问题,提出了一种基于改进的经验模态分解方法（Empirical Mode Decomposition,EMD）和小波散射网络（Wavelet Scattering Network,WSN）的语音情感识别方法。首先,针对用于语音信号时频分析的EMD及其改进算法中存在的模态混叠问题（Mode Mixing）和噪声残余问题,提出了基于常数Q变换（Constant-Q Transform,CQT）和海洋捕食者算法（Marine Predator Algorithm,MPA）的优化掩模经验模态分解方法（Optimized Masking EMD based on CQT and MPA,CM-OMEMD）。采用CM-OMEMD算法对情感语音信号进行分解,得到固有模态函数（Intrinsic Mode Functions,IMFs）,并从IMFs中提取了可以表征情感的时频特征作为第一个特征集。然后采用WSN提取了具有平移不变性和形变稳定性的散射系数特征作为第二个特征集。最后将两个特征集进行融合,采用支持向量机（Support Vector Machine,SVM）分类器进行分类。通过在含有七种情感状态的TESS数据集中的对比实验,证明了本文提出的系统的有效性。其中CM-OMEMD减小了模态混叠,提升了对情感语音信号时频分析的准确性,同时提出的SER系统显著提高了情绪识别的性能。      

Near-field time-frequency localization method using sparse representation

This paper presents a novel near-field source localization method based on the time-frequency sparse model.Firstly,the method converts the time domain data of array output into time-frequency domain by time-frequency transform;then constructs sparse localization model by utilizing the specially selected time-frequency points,and finally the greedy algorithms are chosen to solve the sparse problem to localize the source.When the coherent sources exist,we propose an additional iterative selection procedure to improve the estimation performance.The proposed method is suitable for uncorrelated and coherent sources,moreover,the improved estimation accuracy and the robustness to low signal to noise ratio(SNR) are achieved.Simulations results verify the efficiency of the proposed algorithm.     

Novel Inverse S Transform With Equalization Filter

The S transform is a useful linear time-frequency distribution with a progressive resolution. Since it is linear, it filters efficiently in a time-frequency domain by multiplying a mask function. Several different inverse algorithms exist, which may result in different filtering effects. The conventional inverse S transform (IST) proposed by Stockwell is efficient but suffers from time leakage during filtering. The recent algorithm proposed by Schimmel and Gallart has better time localization during filtering but suffers from a reconstruction error and the frequency leakage during filtering. In this paper, two new IST algorithms are proposed that have better time-frequency localization in filtering than the previous two methods.     

多分量信号快速时频分析方法

针对目前多分量时频分析方法计算复杂度高,难以实现持续信号实时处理的问题,提出一种多分量信号快速时频分析方法。该方法通过信号流逐窗时频变换,实现信号的快速时频分析,其主要计算过程为短时傅立叶变换,时间和空间复杂度低,易于工程实现。性能分析结果表明:该方法时频分辨率高,避免了交叉项干扰,能有效分析低信噪比信号。     

A General Description of Linear Time-Frequency Transforms and Formulation of a Fast, Invertible Transform That Samples the Continuous S-Transform Spectrum Nonredundantly

Examining the frequency content of signals is critical in many applications, from neuroscience to astronomy. Many techniques have been proposed to accomplish this. One of these, the S-transform, provides simultaneous time and frequency information similar to the wavelet transform, but uses sinusoidal basis functions to produce frequency and globally referenced phase measurements. It has shown promise in many medical imaging applications but has high computational requirements. This paper presents a general transform that describes Fourier-family transforms, including the Fourier, short-time Fourier, and S- transforms. A discrete, nonredundant formulation of this transform, as well as algorithms for calculating the forward and inverse transforms are also developed. These utilize efficient sampling of the time-frequency plane and have the same computational complexity as the fast Fourier transform. When configured appropriately, this new algorithm samples the continuous S-transform spectrum efficiently and nonredundantly, allowing signals to be transformed in milliseconds rather than days, as compared to the original S-transform algorithm. The new and efficient algorithms make practical many existing signal and image processing techniques, both in biomedical and other applications.     

CORDIC-Based Unified Architectures for Computation of DCT/IDCT/DST/IDST

In this paper, CORDIC (coordinate rotation digital computer)-based Cooley-Tukey fast Fourier transform (FFT)-like algorithms for power-of-two point discrete cosine transform/discrete sine transform/inverse discrete cosine transform/inverse discrete sine transform are proposed and their corresponding unified architectures are developed by fully reusing the unique two basic processing elements. The proposed algorithms have some distinguished advantages, such as FFT-like regular data flow, unique post-scaling factor, and arithmetic-sequence rotation angles. The developed unified architectures can compute four different transforms by simple routing the data flow according to the specific transform without feeding different transform coefficients or different transform kernels. The unfolding technique is used to overcome the problem of difficult to realize pipeline that occur in iterative CORDIC algorithms. Compared to existing unified architectures, the proposed architectures have a superior performance in terms of hardware complexity, control complexity, throughput, scalability, modularity, and pipelinability.     

The discrete rotational Fourier transform

We define a discrete version of the angular Fourier transform and present the properties of the transform that show it to be a rotation in time-frequency space, this new transform is a generalization of the DFT. Efficient algorithms for its computation can then be based on the FFT and the eigenstructure of the DFT