30 results about "Time frequency filtering" patented technology

The invention discloses a time-varying mixed-phase seismic wavelet extraction method based on time-frequency spectrum simulation. The method is characterized in that on the basis that improved generalized S transformation is carried out on a non-stationary seismic record, a time-frequency filter is introduced for the first time to filter a time-frequency spectrum of the seismic record, then a wavelet amplitude spectrum at each moment is estimated according to the spectrum simulation method, a mixed-phase spectrum of the wavelets is reconstructed in the seismic record with the time-varying wavelet amplitude spectrums removed according to the bispectrum method of high-order cumulants under the assumed condition that the phases of the wavelets are time-invariant, and the amplitude spectrums and the phase spectrum are combined to achieve extraction of the time-varying mixed-phase wavelets. Compared with a conventional stage extraction method, the time-varying wavelet extraction method has the advantages that the assumption that stages of the wavelets are stable is not needed, the time-varying wavelets can be accurately estimated even though the attributes of the wavelets at adjacent stages vary greatly, the mixed phase of the extracted wavelets is more consistent with the reality and seismic data can be analyzed and processed more finely and more accurately. The method has great application value in improving the resolution of the seismic data.

A method of catching systematic eigenfunctions and signal eigenvalues under the condition of only response output available belongs to the parametric recognition technique in dynamic test field. The technique is a method of adopting cross spectral density functions of each response point instead of frequency response functions to perform time-frequency filtering and the parametric recognition of frequency domain, and includes the following steps: (1) carrying out analytic calculation of the cross spectral density functions of different metering signal of output points; (2) analyzing and calculating the nonorthogonal wavelets in the time-frequency domain according to the cross spectral calculating result; (3) inversing the fourier transformation to gain the time-frequency analyse coefficient; (4) adding a rectangular window to perform the time-frequency filtering; (5) calculating the cross spectrum of the output signal after filtering as the systematic function for recognition; (6) performing curvefitting to obtain the systematic parameter; the technique improves the recognition precision of the systematic parameters, precisely recognizes modal parameters, is simple and convenient, and is suitable for the dynamic analyses, the performance verification and the failure diagnosis of large civil engineering establishments such as large and complex mechanical equipments under operation status, high-rise buildings, bridges, etc.

In accordance with an embodiment, a time-frequency post-processing method of improving perceptual quality of a decoded audio signal, the method includes determining a time-frequency representation (such as filter bank analysis and synthesis) of an audio signal, estimating a time-frequency energy distribution of an audio signal from a time-frequency filter bank, computing a modification gain for each time-frequency representation point to have a modified time-frequency representation, and outputting audio signal from a modified time-frequency representation.

The invention discloses a magnetostriction guided wave detector. The invention comprises a host computer data process system, an embedded control system and a probe part. A signal control and processing module of the embedded control system is connected with a processing module and the host computer data process system; a coil adapter in the probe part is connected with a power amplification module and a preposition amplification module in the embedded control system; magnetostriction band in the probe part is pasted on a detecting tube by epoxy resin or directly coupled on the detecting tube by a machinery mode and carries out magnetization; and a coil is covered outside the magnetostriction band and connected with the coil adapter and the power amplification module. Compared with a traditional detection technology, the detector of the invention uses time frequency filtering technology to analyze detected waveform, so as to increase signal to noise ratio and make a defect signal easier to be identified. The invention can detect pipeline member in media such as soil, cement and ground, or overhead wire rope suspension rod suspension rod and wire rope and locate position and size of the defect.

The method includes following steps: system receiver makes Fourier transform for time domain pilot frequency signal to get frequency domain pilot frequency signals; makes LS estimation to get channel estimation of pilot frequency carrier; the time frequency filter is made for channel estimation of pilot frequency carrier to get new channel estimation result of pilot frequency carrier; the interpolation is made for the acquired pilot frequency channel estimation result to get channel estimation of data carrier. The invention also provides a relating device. The invention not only considers correlation of channel on frequency domain, but also considers correlation of channel on time domain so that the accuracy of channel estimation is remarkably improved.

The invention provides an adaptive decomposition method generating filters based on the image segmentation technology. The method comprises the steps of firstly performing time-frequency transformation on to-be-analyzed signals to obtain corresponding time-frequency coefficients and time-frequency planes; secondly, performing threshold segmentation on the time-frequency planes to obtain binaryzation images; thirdly, marking connected domains in the binaryzation images; fourthly, generating a group of time-frequency filters according to the connected domains, performing filtering on time-frequency systems based on the time-frequency filters and outputting filtering results; fifthly, performing time-frequency inverse transformation on the filtering results to obtain decomposition results. When the sampling time of each frequency component of a to-be-decomposed signal is long enough, the method can have any frequency resolution; compared with the frequently-used empirical mode decomposition algorithm, the method increases the frequency resolution greatly, can perform adaptive decomposition on the signals with dense distribution of frequencies, and thus can calculate the instantaneous frequency and the instantaneous amplitude of each component, so that the application range of the adaptive decomposition algorithm is widened.

The invention discloses a novel harmonic high-precision detection method. The method comprises: establishing a novel time-frequency filter, restraining frequency of a minus semiaxis by Hilbert transformation, and detecting frequency, amplitude, and phase positions of each subharmonic and inter-harmonics by a time domain convolution method in a high precision manner. From theoretical analysis basis and calculation formula derivation of the method, the method prevents Fourier (FFT) region spectrum leakage, picket fence effect, and non-integral subwave phenomenon. Results of experiment simulation shows that the time domain filtering convolution method is flexible in design and realization, and convenient in engineering real-time realization, and overcomes influence of fundamental frequency on harmonic analysis, and detection precision of frequency, amplitude values, and initial phases of signals including multiple harmonics and inter-harmonics. Frequency, amplitude, and phase of a voltage flicker signal can be obtained by a signal converting equation. For flicker signals polluted by the inter-harmonics, detection results are not influenced.

The invention provides a multi-dimensional domain joint SAR broadband interference suppression method based on low-rank matrix decomposition. Broadband interference signals exist in a plurality of pulses of current echo data. The short-time Fourier transform matrixes of the pulse echo signals are vectorized respectively; RPCA decomposition is performed to obtain a low-rank matrix and a sparse matrix; each row of the decomposed sparse matrix is rearranged into a short-time Fourier matrix form; the rearranged short-time Fourier matrix is subjected to inverse short-time Fourier transform, the reconstructed interference signal is subtracted from the original echo signal to realize broadband interference suppression, and data subjected to interference suppression is imaged by using an existingimaging algorithm to obtain a high-resolution image. According to the method, the problem of useful signal loss caused by time-frequency filtering is avoided, compared with a traditional method basedon energy characteristic difference, useful signal information can be effectively reserved while interference is suppressed, and the image quality after broadband interference suppression can be improved to a large extent.

The invention discloses a current signal filtering and denoising method based on generalized S transformation containing a variable factor. The method comprises the following steps: firstly, converting a discrete sampling sequence of a group of continuous time domain current signals into a two-dimensional time-frequency complex matrix through generalized S transformation containing the variable factor; secondly, performing threshold filtering method processing on the two-dimensional time-frequency matrix, performing processing by using a time-frequency filter based on time-frequency spectrum distribution, reserving effective signals in a time-frequency domain, and extracting effective current signal components; and finally, obtaining a noise-removed one-dimensional time domain current signal through generalized S inverse transformation. According to the method, the current pure signal under the noise background can be effectively extracted, so that the current signal can be analyzed and processed under various working condition environments.

The invention discloses a cable fundamental frequency characteristic identification method based on S transformation, and the method comprises the following steps of expressing an acquired cable-stayed bridge cable acceleration signal in a time-frequency domain by using S transformation, and finding out noises in different time periods and different frequency bands; filtering noise by an acting time-frequency filter to obtain a time-frequency domain signal of the filtered environment noise; and performing S inverse transformation on the signal subjected to the environmental noise filtration toa time domain, performing fast Fourier transformation on the signal subjected to the environmental noise filtration, converting a time domain signal into a frequency domain signal, and finally identifying the fundamental frequency characteristic. The cable fundamental frequency characteristic identification method based on S transformation can filter the environmental noise interference near thefundamental frequency of the cable vibration signal, thereby highlighting the characteristics of the fundamental frequency of the cable and further obtaining accurate and reliable fundamental frequency characteristic information.

The invention discloses a method for denoising a geophysical signal. The method herein includes the following steps: 1. conducting S transformation on an original geophysical signal, obtaining the time-frequency spectrum of the original geophysical signal; 2. conducting time frequency filtering on the time-frequency spectrum; 3. conducting threshold filtering on the signal after the time frequencyfiltering; 4. conducting s inverse transformation on the result from the threshold filtering, obtaining an initial denoised signal; 5. conducting empirical mode decomposition on the initial denoisedsignal, obtaining a plurality of intrinsic mode function components of the initial denoised signal; 6. conducting hilbert transformation and spectrum analysis on all the intrinsic mode function components of the initial denoised signal, selecting an intrinsic mode function which is associated with the original geophysical signal; and 7. reconstructing a signal by using the intrinsic mode function,obtaining the required denoised signal. According to the invention, the method herein can efficiently denoise the geophysical signal.

The invention discloses a radar echo signal normalized window filtration method which comprises the following steps of: acquiring a radar echo original signal and performing normalized window Stockwell transformation and spectrum transformation; acquiring a radar echo signal with a high-frequency clutter and a low-frequency clutter, performing normalized window Stockwell transformation, and analyzing and determining a time-frequency filtration operator according to a two-dimensional time frequency; filtering the high-frequency clutter from the radar echo signal with the high-frequency clutter and the low-frequency clutter through a time-frequency filter, and performing TT transformation; filtering the high-frequency clutter according to the designed time-frequency filter, and performing TT transformation; extracting elements, namely the suppressible low-frequency clutter, near the diagonal line; and performing TT inversion transformation, and thus obtaining the filtered radar echo signal. The radar echo signal normalized window filtration method has the advantages of effectively filtering the clutters and keeping good characteristics of the original signal with small calculation amount, simplicity in implementation and the like.

The invention relates to a micro-motion signal separation method based on radar missing sampling, which comprises the following steps: firstly, establishing a narrow-band radar micro-motion signal echo model of missing sampling, secondly, converting the signal model into a sparse regularization model, and solving through a soft threshold iterative algorithm (ISTA) to obtain reconstructed time-frequency distribution; then extracting a maximum value point of the frequency spectrum during reconstruction, defining a maximum value point association problem as an assignment problem, solving the problem through Kalman filtering and a Hungary algorithm to obtain an instantaneous frequency trajectory, and finally, separating a micro-motion echo signal of each scattering point on a trajectory target by adopting an intrinsic linear frequency modulation component decomposition (ICCD) algorithm. Compared with a traditional time-frequency filtering group decomposition method, the method can better decompose signal components which are crossed and overlapped in a time-frequency domain, and is more suitable for micro-motion signal decomposition under the condition of radar sampling defect.

The invention relates to a receiving method of double-scattering signal components in a lattice multi-carrier parallel transmission system. According to the method, a new time-frequency filter group is constructed on inverse lattices corresponding to time-frequency lattices which send signals, so that the receiving of signal scattering components can be realized; by means of compactness simplification, signal scattering component receiving under a fast moving environment can be completed quickly; and therefore, the problem of the loss of information of a part of signal scattering components which is caused by the incompleteness of a filter group existing in a traditional receiver can be solved fundamentally, and compression redundancy and decoding performance can be both improved to a greater extent. With the receiving method of the invention adopted, defects in the receiving and processing of lattice orthogonal frequency division multiplexing (LOFDM) multi-carrier signals can be eliminated; the reliability of lattice multi-carrier data parallel transmission under the fast moving environment can be improved significantly; and the novel receiving of the lattice orthogonal frequency division multiplexing (LOFDM) multi-carrier signals can be realized; and based on parameter configuration adjustment, the receiving method can be used for a traditional multi-carrier system so as to improve the receiving performance of the traditional multi-carrier system.

A signal light pulse to be converted into a two-dimensional space signal and a reference ultra-short light pulse are directed to a dispersion device, a second-harmonic is generated by introducing a one-dimensional frequency light distribution obtained by a one-dimensional Fourier transform lens, the second-harmonic is then subjected to time-to-space conversion through a one-dimensional Fourier transform lens so as to obtain a light wave distribution, and the light wave distribution is then subjected to filtering by a time-frequency filter provided on a filter plane of a one-dimensional space frequency filtering optical system and is further converted into a two-dimensional space signal corresponding to a time-frequency expanded two-dimensional light distribution which represents a relation between time and frequency of the signal pulse light. Thereby, there is provided a specific technique of realizing ultra-fast conversion of signal form from time signal into two-dimensional space signal without any active-scan and also displaying the two-dimensional signal in a visible region with a temporally steady state.

The invention discloses a geophysical signal denoising method. The method comprises the following steps of S1, carrying out stockwell transform on an original geophysical signal, thereby obtaining a time-frequency spectrum of the original geophysical signal; S2, carrying out time-frequency filtering and threshold filtering on the time-frequency spectrum of the original geophysical signal; S3, carrying out two-dimensional Fourier transform on the time-frequency spectrum of a preliminarily denoised signal, thereby obtaining a two-dimensional Fourier frequency spectrum of the preliminarily denoised signal; S4, carrying out Gaussian filtering on the two-dimensional Fourier frequency spectrum; S5, carrying out two-dimensional inverse Fourier transform on a Gaussian filtering result, thereby obtaining the time-frequency spectrum of a further denoised signal; and S6, carrying out inverse stockwell transform on the time-frequency spectrum of the further denoised signal, thereby obtaining a required denoised signal. According to the method, noises in the geophysical signal can be simply, conveniently and efficiently removed.

The invention relates to a self-adaptive grid construction method and device used for bandwidth extended coding. The method comprises the steps of: S1, based on transient property analysis of input monophonic audio signals, carrying out frequency resolution selection, carrying out self-adaptive multi-resolution filtering on the input monophonic audio signals, and obtaining an optimum time frequency filtering signal; and S2, carrying out transient detection and positioning on each sub-band signal output after the filtering, carrying out self-adaptive grid construction respectively in a frequency direction and a time direction according to the transient property analysis of each sub-band signal and by considering set high frequency band code rates and ear critical frequency band characteristics, and obtaining an optimum time frequency grid under a current code rate. The invention further relates to bandwidth extended coding and decoding methods based on the method. According to the invention, based on audio signal characteristics and high frequency signal available code rate limits, multi-resolution filtering and self-adaptive time frequency grid construction are carried out, and the coding efficiency of high frequency parts of digital audio signals and the sound quality of the high frequency part signals are obviously improved.