Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The ...Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.展开更多
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
In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal s...In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal spectra appear at early arrival time like discrete spectrum, at last time a hyperbolic curve lies in the time-frequency spectrum which corresponds to the frequency-group delay curve of plasma. To understand the time-frequency the property of a signal is helpful for obtaining the plasma parameters.展开更多
钢轨波磨作为地铁线路中最为常见的轨道损伤问题之一,始终未得到根本性的解决。为研究不同轨道结构形式产生钢轨波磨后车辆内部振动噪声以及轨道结构振动的时频域特性,探究钢轨波磨对车辆和轨道的影响,对某地铁线路进行现场动静态测试,...钢轨波磨作为地铁线路中最为常见的轨道损伤问题之一,始终未得到根本性的解决。为研究不同轨道结构形式产生钢轨波磨后车辆内部振动噪声以及轨道结构振动的时频域特性,探究钢轨波磨对车辆和轨道的影响,对某地铁线路进行现场动静态测试,获取了钢轨波磨激励下车辆内部的振动和噪声响应以及轨道各部件的振动响应,使用时域指标统计、1/3倍频程谱分析等方法分析轨道振动响应特征和车内振动及噪声响应特征。结果表明:在小半径曲线地段,浮置板轨道产生了特征波长约为200 mm的钢轨波磨,整体道床轨道产生了特征波长约为60 mm的钢轨波磨;浮置板轨道的钢轨、道床板、隧道壁振动加速度有效值分别是整体道床的1.8、5.8倍及0.3倍;钢轨波磨对轨道振动的影响主要体现在中高频范围,在300~400 Hz附近,浮置板轨道振级从钢轨至隧道壁共衰减66 d B,而整体道床共衰减49 d B;列车通过测试区域时,转向架上方与客室中部垂、纵向振动加速度有效值基本一致,而客室中部横向振动加速度有效值约为转向架上方的2倍;车内转向架位置处的异常振动主要来源于钢轨波磨的激励,且短波长波磨所激励的车内振动及噪声更加剧烈。因此,地铁钢轨波磨产生后在轨道及车辆的振动噪声响应中均占主要成分,应及时对钢轨进行打磨处理,研究结果可为地铁工务维修提供理论指导。展开更多
Due to the disturbances arising from the coherence of reflected waves and from echo noise,problems such as limitations,instability and poor accuracy exist with the current quantitative analysis methods.According to th...Due to the disturbances arising from the coherence of reflected waves and from echo noise,problems such as limitations,instability and poor accuracy exist with the current quantitative analysis methods.According to the intrinsic features of GPR signals and wavelet time–frequency analysis,an optimal wavelet basis named GPR3.3 wavelet is constructed via an improved biorthogonal wavelet construction method to quantitatively analyse the GPR signal.A new quantitative analysis method based on the biorthogonal wavelet(the QAGBW method)is proposed and applied in the analysis of analogue and measured signals.The results show that compared with the Bayesian frequency-domain blind deconvolution and with existing wavelet bases,the QAGBW method based on optimal wavelet can limit the disturbance from factors such as the coherence of reflected waves and echo noise,improve the quantitative analytical precision of the GPR signal,and match the minimum thickness for quantitative analysis with the vertical resolution of GPR detection.展开更多
The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formul...The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formula based on continuous wavelet transform. For an arbitrary given square-integrable function f(t),g(t) = f(t/λ) is derived by continuous wavelet transform and its inverse transform. The result shows that time-scale transformation may be obtained through the modification of the time-scale of wavelet function filter using equivalent substitution. The paper demonstrates the result by theoretic derivations and experimental simulation.展开更多
文摘Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.
基金This project was supported by the National Natural Science Foundation of China (60472102)Shanghai Leading Academic Discipline Project (T0103).
文摘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.
文摘In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal spectra appear at early arrival time like discrete spectrum, at last time a hyperbolic curve lies in the time-frequency spectrum which corresponds to the frequency-group delay curve of plasma. To understand the time-frequency the property of a signal is helpful for obtaining the plasma parameters.
文摘钢轨波磨作为地铁线路中最为常见的轨道损伤问题之一,始终未得到根本性的解决。为研究不同轨道结构形式产生钢轨波磨后车辆内部振动噪声以及轨道结构振动的时频域特性,探究钢轨波磨对车辆和轨道的影响,对某地铁线路进行现场动静态测试,获取了钢轨波磨激励下车辆内部的振动和噪声响应以及轨道各部件的振动响应,使用时域指标统计、1/3倍频程谱分析等方法分析轨道振动响应特征和车内振动及噪声响应特征。结果表明:在小半径曲线地段,浮置板轨道产生了特征波长约为200 mm的钢轨波磨,整体道床轨道产生了特征波长约为60 mm的钢轨波磨;浮置板轨道的钢轨、道床板、隧道壁振动加速度有效值分别是整体道床的1.8、5.8倍及0.3倍;钢轨波磨对轨道振动的影响主要体现在中高频范围,在300~400 Hz附近,浮置板轨道振级从钢轨至隧道壁共衰减66 d B,而整体道床共衰减49 d B;列车通过测试区域时,转向架上方与客室中部垂、纵向振动加速度有效值基本一致,而客室中部横向振动加速度有效值约为转向架上方的2倍;车内转向架位置处的异常振动主要来源于钢轨波磨的激励,且短波长波磨所激励的车内振动及噪声更加剧烈。因此,地铁钢轨波磨产生后在轨道及车辆的振动噪声响应中均占主要成分,应及时对钢轨进行打磨处理,研究结果可为地铁工务维修提供理论指导。
文摘依据FFT→优化窗→IFFT思路,突破线性时频变换的窗函数积分性能桎梏,实现高性能优化窗函数的线性时频变换应用,建立新型时频变换算法——K-S变换.对信号x(t)的FFT频谱向量进行频移处理后,与该频移点下Kaiser优化窗的频谱向量进行Hadamard乘积,再将乘积结果进行FFT逆变换(IFFT),构造出K-S变换复时频矩阵,由此获得x(t)的时间-频率-幅值、时间-频率-相位三维信息;给出逆变换的数学推导与局部性质、线性性质和变分辨率特性;0~150 kHz电网的稳态与时变超谐波信号仿真实验表明,K-S变换的时域、频域分辨能力均优于流行的短时傅里叶变换、S变换,具有优良的变分辨率性能;0~40 kHz超谐波信号的实测证明,基于K-S变换的超谐波电压幅值测量绝对误差均小于0.032 3 V.
基金Projects(51678071,51278071)supported by the National Natural Science Foundation of ChinaProjects(14KC06,CX2015BS02)supported by Changsha University of Science&Technology,China
文摘Due to the disturbances arising from the coherence of reflected waves and from echo noise,problems such as limitations,instability and poor accuracy exist with the current quantitative analysis methods.According to the intrinsic features of GPR signals and wavelet time–frequency analysis,an optimal wavelet basis named GPR3.3 wavelet is constructed via an improved biorthogonal wavelet construction method to quantitatively analyse the GPR signal.A new quantitative analysis method based on the biorthogonal wavelet(the QAGBW method)is proposed and applied in the analysis of analogue and measured signals.The results show that compared with the Bayesian frequency-domain blind deconvolution and with existing wavelet bases,the QAGBW method based on optimal wavelet can limit the disturbance from factors such as the coherence of reflected waves and echo noise,improve the quantitative analytical precision of the GPR signal,and match the minimum thickness for quantitative analysis with the vertical resolution of GPR detection.
文摘The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formula based on continuous wavelet transform. For an arbitrary given square-integrable function f(t),g(t) = f(t/λ) is derived by continuous wavelet transform and its inverse transform. The result shows that time-scale transformation may be obtained through the modification of the time-scale of wavelet function filter using equivalent substitution. The paper demonstrates the result by theoretic derivations and experimental simulation.
基金Acknowledgments
This work was supported by the National High Technology Research and Development Program of China under grant No. 2006AAOAA102-12 and the National Natural Science Foundation of China （Grant No. 40774064）. The authors would like to express their sincere thanks to TH oil field for providing field data sets.
