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The W transform and its improved methods for time-frequency analysis of seismic data
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作者 WANG Yanghua RAO Ying ZHAO Zhencong 《Petroleum Exploration and Development》 SCIE 2024年第4期886-896,共11页
The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improv... The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra. 展开更多
关键词 time-frequency analysis W transform Wigner-Ville distribution matching pursuit energy focusing RESOLUTION
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LOCALIZED RADON-WIGNER TRANSFORM AND GENERALIZED-MARGINAL TIME-FREQUENCY DISTRIBUTIONS
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作者 Xu Chunguang Gao Xinbo Xie Weixin (School of Electronic Engineering, Xidian University, Xi’an, 71007l) 《Journal of Electronics(China)》 2000年第2期116-122,共7页
This paper introduces the localized Radon transform (LRT) into time-frequency distributions and presents the localized Radon-Wigner transform (LRWT). The definition of LRWT and a fast algorithm is derived, the propert... This paper introduces the localized Radon transform (LRT) into time-frequency distributions and presents the localized Radon-Wigner transform (LRWT). The definition of LRWT and a fast algorithm is derived, the properties of LRWT and its relationship with Radon-Wigner transform, Wigner distribution (WD), ambiguity function (AF), and generalized-marginal time-frequency distributions are analyzed. 展开更多
关键词 time-frequency distributionS LOCALIZED Radon-Wigner transform Generalized-marginal time-frequency distributionS
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A NEW QUADRATIC TIME-FREQUENCY DISTRIBUTIONAND A COMPARATIVE STUDY OF SEVERAL POPULARQUADRATIC TIME-FREQUENCY DISTRIBUTIONS
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作者 Liu Guizhong Liu Zhimei(information Engineering Institute, Xi’an Jiaotong University, Xi’an 710049) 《Journal of Electronics(China)》 1997年第2期104-111,共8页
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 stron... 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. 展开更多
关键词 SIGNAL processing time-frequency analysis time-frequency distribution of Cohen’s CLASS
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Adaptive Time-Frequency Distribution Based on Time-Varying Autoregressive and Its Application to Machine Fault Diagnosis
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作者 WANG Sheng-chun HAN Jie +1 位作者 LI Zhi-nong LI Jian-feng 《International Journal of Plant Engineering and Management》 2007年第2期116-120,共5页
The time-varying autoregressive (TVAR) modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-i... The time-varying autoregressive (TVAR) modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing , and the experiment result shows that the proposed method is effective in feature extraction. 展开更多
关键词 time-varying autoregressive modeling parameter estimation time-frequency distribution fault diagnosis
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基于自适应VMD和WVD的配电网故障行波检测方法
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作者 张帝 宋兴荣 +3 位作者 唐海国 李泽文 孙健 彭维馨 《电力科学与技术学报》 CAS CSCD 北大核心 2024年第2期80-90,共11页
精确检测故障行波信号是保证故障定位结果准确可靠的重要因素,针对Wigner Ville分布(Wigner Ville distribution,WVD)在检测故障行波时易产生交叉项的问题,提出一种基于改进变分模态分解(variational mode decomposition,VMD)和WVD的故... 精确检测故障行波信号是保证故障定位结果准确可靠的重要因素,针对Wigner Ville分布(Wigner Ville distribution,WVD)在检测故障行波时易产生交叉项的问题,提出一种基于改进变分模态分解(variational mode decomposition,VMD)和WVD的故障行波检测方法。首先,通过波形相似性确定VMD参数的选取,利用改进的VMD对线模行波信号自适应分解,实现对故障行波不同频段信号提取的同时保留重要故障信息;然后,分别求取各分量信号的WVD后叠加得到原始信号的WVD,由此解决WVD交叉项带来的影响;最后求取VMD-WVD能量谱密度分布,利用WVD良好的时频聚集性检测故障行波[150,170]kHz频段波头位置,从而实现故障行波波头的精准检测。仿真实验结果表明,该文所提方法相比小波和HHT的故障行波检测方法更加快速、准确。 展开更多
关键词 配电网 行波检测 改进VMD wvd
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Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics
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作者 Feiyan Zhou HuiYin +4 位作者 Chen Luo Haixin Tong KunYu Zewen Li Xiangjun Zeng 《Energy Engineering》 EI 2023年第9期1979-1990,共12页
The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sus... The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper. 展开更多
关键词 Low voltage distribution systems series fault arcing grid search time-frequency characteristics
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TVAR Time-frequency Analysis for Non-stationary Vibration Signals of Spacecraft 被引量:7
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作者 杨海 程伟 朱虹 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2008年第5期423-432,共10页
Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional... Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive (TVAR) model based on the process neural network (PNN) and the empirical mode decomposition (EMD) is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions (IMFs). Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution. 展开更多
关键词 non-stationary random vibration time-frequency distribution process neural network empirical mode decomposition
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Wigner-Ville distribution and its application in seismic attenuation estimation 被引量:9
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作者 李艳东 郑晓东 《Applied Geophysics》 SCIE CSCD 2007年第4期245-254,共10页
The attenuation of seismic signals is often characterized in the frequency domain using statistical measures of the power spectrum. However, the conventional Fourier transform-based power spectrum estimation methods s... The attenuation of seismic signals is often characterized in the frequency domain using statistical measures of the power spectrum. However, the conventional Fourier transform-based power spectrum estimation methods suffer from time-frequency resolution problems. Wigner-Ville distribution, which is a member of Cohen class time-frequency distributions, possesses many appealing properties, such as time-frequency marginal distribution, time-frequency localization, etc. Therefore, Wigner-Ville distribution offers a new way for estimating the attenuation of seismic signals. This paper initially gives a brief introduction to Wigner-Ville distribution and the smoothed Wigner-Ville distribution that is effective in reducing the cross-term effect, and then presents a method for seismic attenuation estimation based on the instantaneous energy spectrum of the Wigner-Ville distribution. A real data example from central Tarim Basin in western China is presented to illustrate the effectiveness of the proposed method. The results show that the Wigner-Ville distribution-based seismic attenuation estimation method can effectively detect the difference between reef, shoal and lagoon facies by their attenuation properties, indicating that the estimated seismic attenuation can be used for reef and shoal carbonate reservoir characterization. 展开更多
关键词 Wigner-Ville distribution time-frequency analysis seismic attenuation reservoir characterization
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Adaptive Time Frequency Distribution Based on Linear Chirp Modulated Gaussian Functions 被引量:3
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作者 Shi-wei Ma Guang-hua Chen +1 位作者 Jia-mei Deng Jia-lin Cao 《Advances in Manufacturing》 2000年第1期31-37,共7页
We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an ... We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an improved adaptive time frequency distribution is developed, which is non negative, free of cross term interference, and of better time frequency resolution. The paper presents an effective numerical algorithm to estimate the optimal parameters of the basis. Simulations indicate that the proposed approach is effective in analyzing signal's time frequency behavior. 展开更多
关键词 adaptive time frequency distribution elementary function subspace decomposition STFT wvd
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Parametric adaptive time-frequency representation based on time-sheared Gabor atoms 被引量:2
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作者 Ma Shiwei Zhu Xiaojin Chen Guanghua Wang Jian Cao Jialin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第1期1-7,共7页
A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization ... A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing. 展开更多
关键词 time-frequency analysis Gabor atom Time-shear Adaptive signal decomposition time-frequency distribution.
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Quasi-LFM radar waveform recognition based on fractional Fourier transform and time-frequency analysis 被引量:3
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作者 XIE Cunxiang ZHANG Limin ZHONG Zhaogen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第5期1130-1142,共13页
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio... Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition. 展开更多
关键词 quasi-linear frequency modulation(quasi-LFM)radar waveform time-frequency distribution fractional Fourier transform(FrFT) assembled classifier
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Digital modulation classification using multi-layer perceptron and time-frequency features
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作者 Yuan Ye Mei Wenbo 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第2期249-254,共6页
Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributio... Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals: The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio (SNR) variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron (MLP) classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier. 展开更多
关键词 Digital modulation classification time-frequency feature time-frequency distribution Multi-layer perceptron.
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DOPPLERLET BASED TIME-FREQUENCY REPRESENTATION VIA MATCHING PURSUITS
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作者 Zou Hongxing Zhou Xiaobo Dai Qionghai Li Yanda(State Key Lab. of Intelligent Technology and Systems, Tsinghua University, Beijing 100084) 《Journal of Electronics(China)》 2001年第3期217-227,共11页
A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fou... A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fourier transform (including Gabor transform), wavelet transform, and chirplet transform are formulated in one framework of Dopplerlet transform accordingly.It is proved that the matching pursuits based on Dopplerlet basis functions are convergent, and that the energy of residual signals yielded in the decomposition process decays exponentially. Simulation results show that the matching pursuits with Dopplerlet basis functions can characterize compactly a nonstationary signal. 展开更多
关键词 time-frequency analysis Dopplerlet TRANSFORM PSEUDO time-frequency distribution MATCHING PURSUIT
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Joint Time-Frequency Analysis of Seismic Signals:A Critical Review
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作者 Roshan Kumar Wei Zhao Vikash Singh 《Structural Durability & Health Monitoring》 EI 2018年第2期65-83,共19页
This paper presents an evaluation of time-frequency methods for the analysis of seismic signals.Background of the present work is to describe,how the frequency content of the signal is changing in time.The theoretical... This paper presents an evaluation of time-frequency methods for the analysis of seismic signals.Background of the present work is to describe,how the frequency content of the signal is changing in time.The theoretical basis of short time Fourier transform,Gabor transform,wavelet transform,S-transform,Wigner distribution,Wigner-Ville distribution,Pseudo Wigner-Ville distribution,Smoothed Pseudo Wigner-Ville distribution,Choi-William distribution,Born-Jordan Distribution and cone shape distribution are presented.The strengths and weaknesses of each technique are verified by applying them to a particular synthetic seismic signal and recorded real time earthquake data. 展开更多
关键词 time-frequency distribution Seismic signals Cross-term interference Autoterm Gabor transform Wigner-Ville distribution
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NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING
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作者 Liu Xiaofeng Qin Shuren Bo Lin 《Journal of Electronics(China)》 2007年第6期776-781,共6页
Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal fea... Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal. 展开更多
关键词 time-frequency decomposition Elementary function time-frequency distribution Series (TFDS) Curve surface fitting Noise suppressing
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ESMD Method for Frequency Distribution of Tank Surface Temperature under Wind Effect
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作者 Jinliang Wang Xianshui Fang 《International Journal of Geosciences》 2015年第5期481-486,共6页
Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature seq... Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature sequences extracted from the infrared photographs are decomposed into several empirical modes of general periodic forms. The corresponding analyses on the modes reveal that, within certain limits, both spatial and temporal frequencies increase along the wind speed. As for the amplitudes, the existence of wind may result in fold increasing of their values. In addition, when the wind speed is added from 4 m/s to 5 m/s, both frequency and amplitude of the surface temperature decrease and it implies an enhanced mixing and a weakened temperature gradient under the force of wind blowing. 展开更多
关键词 Extreme-Point SYMMETRIC Mode DECOMPOSITION (ESMD) Surface Temperature time-frequency distribution WIND Wave TANK Experiment
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Non-Stationary Signal Segmentation and Separation from Joint Time-Frequency Plane
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作者 Abdullah Ali Alshehri 《Journal of Signal and Information Processing》 2012年第3期339-343,共5页
Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, t... Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments. 展开更多
关键词 Signal Segmentation time-frequency distribution Short-Time FOURIER TRANSFORM NON-STATIONARY WIENER MASKING
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Novel Time-frequency Analysis and Representation of EEG
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作者 ZHOU Wei-dong1,YU Ke,JIA Lei1 . Shandong University collego of information, Jinan 250100, China 《Chinese Journal of Biomedical Engineering(English Edition)》 2003年第2期80-85,共6页
A novel method of EEG time-frequency analysis and representation based on a wavelet network is presented. The wavelet network model can represent the EEG data effectively. Based on the wavelet network model, a novel t... A novel method of EEG time-frequency analysis and representation based on a wavelet network is presented. The wavelet network model can represent the EEG data effectively. Based on the wavelet network model, a novel time-frequency energy distribution function is obtained, which has the same time-frequency resolution as Wigner-Ville distribution and is free of cross-term interference. There is a great potential for the use of the novel time-frequency representation of nonstationary biosignal based on a wavelet network in the field of the electrophysiological signal processing and time-frequency analysis. 展开更多
关键词 Electroencephalograpm (EEG) WAVELET networks time-frequency REPRESENTATION Wigner-Ville distribution (wvd)
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基于多谱图叠加阈值的抑制WVD交叉项的新方法 被引量:15
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作者 李雨青 水鹏朗 林英 《电子与信息学报》 EI CSCD 北大核心 2006年第8期1435-1438,共4页
本文提出了一种抑制Wigner-Ville分布(WVD)交叉项的新方法。首先对多幅具有不同时-频分辨率的谱图进行叠加,然后对叠加结果进行阈值处理,确定WVD自项在时频平面的支撑区域。最后,用该区域的示性函数乘以WVD得到一个新的时频分布。不同... 本文提出了一种抑制Wigner-Ville分布(WVD)交叉项的新方法。首先对多幅具有不同时-频分辨率的谱图进行叠加,然后对叠加结果进行阈值处理,确定WVD自项在时频平面的支撑区域。最后,用该区域的示性函数乘以WVD得到一个新的时频分布。不同于传统的抑制交叉项的核函数方法,该方法抑制交叉项的同时,保持WVD了高时频聚集性。实验结果表明,该方法对由多个LFM信号构成的多分量信号和非线性调频信号都非常有效。 展开更多
关键词 WIGNER-VILLE分布 谱图 交叉项 自项 阈值处理
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基于WVD改进算法的跳频信号参数估计 被引量:19
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作者 陈超 郝雁中 +1 位作者 高宪军 孙强 《吉林大学学报(信息科学版)》 CAS 2010年第2期124-130,共7页
针对平滑伪维格纳分布(SPWVD:Smoothed Pseudo Wigner-Ville Distribution)在跳频信号参数估计中存在的分辨率下降和运算量过大等问题,提出基于STFT(Short-Time Fourier Transform)与WVD(Wigner-VilleDistribution)的联合算法(STFT-WVD)... 针对平滑伪维格纳分布(SPWVD:Smoothed Pseudo Wigner-Ville Distribution)在跳频信号参数估计中存在的分辨率下降和运算量过大等问题,提出基于STFT(Short-Time Fourier Transform)与WVD(Wigner-VilleDistribution)的联合算法(STFT-WVD),实现了跳频周期、跳变时刻和跳频频率等参数的盲估计。在参数估计的过程中,STFT-WVD算法有效地抑制了WVD的交叉干扰项,保持了WVD较高的时频分辨率,在运算量上和WVD相近,没有增加运算的复杂程度。仿真实验证明,STFT-WVD比SPWVD具有更好的整体性能,在信噪比优于-1 dB时,能得到更为精准的估计值。 展开更多
关键词 跳频信号 参数估计 维格纳分布 联合算法
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