89results about How to "High time-frequency resolution" patented technology

The invention discloses an intelligent road sweeper and a road pollutant identification method and a control method thereof. The road sweeper comprises a road sweeper body, a laser radar, a camera, anencoder, a dust concentration detector, an inertial sensor, a GPS system and a processing controller. A method for identify road pollutants include acquiring RGB images of clean road surface and roadfacilities to be cleaned, convert that acquired RGB images into HSV space, and obtaining a BP neural network model capable of identifying the clean road surface and road facilities; The real-time image information of the road to be cleaned is input to the BP neural network model to identify the pollutants. The method for identifying pollutants such as garbage in the present invention utilizes theHSV feature of a road image, which has a larger information amount of the gray value of the image than that of a single image, and has a better effect for identifying pollutants such as garbage.

The invention relates to a power transmission line short circuit fault diagnosis method based on empirical wavelet transformation and local energy. The method is characterized by comprising the following steps of: collecting short-circuit fault voltage signals; using an empirical wavelet transformation method to process the short-circuit fault voltage signals to obtain an empirical mode; performing short-circuit fault detection on the basis of empirical wavelet transformation; and performing short-circuit fault classification feature extraction on the basis of block local energy. The method has the advantages of scientificity, rationality, high time-frequency resolution, high noise resistance, high adaptability, good application effect and the like.

The invention discloses a microseismic signal noise reduction filtering method based on a VMD and a wavelet packet and belongs to the signal processing technology field. In the invention, a mode of combining the VMD and the wavelet packet is adopted; adaptivity of a VMD decomposition method and characteristics of a high mathematical theory basis, high frequency noise suppression and the like in the algorithm are used; and the wavelet packet has the characteristics of carrying out multilevel division on a frequency band, further decomposing a high frequency portion which is not subdivided in multiresolution analysis, and adaptively selecting a frequency band according to a characteristic of an analyzed signal so that a time frequency resolution is increased. In the invention, based on a condition of maintaining randomness, non-stationary performance and a burst transient characteristic of a microseismic signal, the microseismic signal is filtered. The algorithm is simple and easy and an effect is ideal. Effective noise reduction filtering can be performed on a mine noisy microseismic signal. And a good technical value and an application prospect are possessed.

The invention discloses a method for diagnosing a fault of an automatic ammunition supply and transportation device, and aims to realize low maintenance cost and short period. The method comprises the following steps of: arranging measurement points on the large-aperture artillery automatic ammunition supply and transportation device, and selecting driving current of an ammunition supply motor and a hydraulic oil source motor as the measurement points according to a driving mode supplied by an automatic ammunition supply and transportation motion cyclic graph; simultaneously acquiring and recording angular displacement signals and angular speed signals of a rotary ammunition cabin, a coordination arm, a turning mechanism and an ammunition transportation mechanism as well as load current change signals of driving motors by a portable signal acquirer; performing signal data correction work of baseline drift correction and wild point removal on the acquired and recorded angular motion signals and current change signals; performing time domain analysis on an acquired acceleration impact signal and an acquired current impact signal, and making an amplitude probability density and probability distribution curve; and performing short-time-frequency characteristic extraction and small sample signal analysis on an impact response signal, analyzing a wavelet energy spectrum, and supplying peak values and frequencies in a frequency domain, and energy and entropy of each frequency band.

The invention relates to a seismic wave attenuation compensation method in a curvelet domain. The method comprises the following steps of (1) collecting a seismic signal and carrying out preprocessing to obtain a time domain signal x(t) of an earthquake, (2) carrying out curvelet transform on the time domain signal x(t) to obtain a curvelet domain signal psi j, l (omega j, Tk), (3) carrying out smoothing process on the curvelet domain signal psi j, l (omega j, Tk) to obtain a curvelet coefficient Phi j, l (omega j, Tk), (4) carrying out threshold iterative processing on the curvelet coefficient Phi j, l (omega j, Tk) to obtain a denoised signal Psi j, l (omega j, Tk), (5) carrying out pointwise recursion to obtain the deep and shallow layer energy ratio delta j, ll (omega j, Tk) of the denoised signal Psi j, l (omega j, Tk) in each frequency band compensation angle, (6) calculating all frequency band compensation factor coefficient matrices Dj, ll (omega j, Tk) in a compensation angle, (7) weighing the reciprocal values of the compensation factor coefficient matrices Dj, ll (omega j, Tk) in all frequency band compensation angles to obtain a signal Cj, l (omega j, Tk) after curvelet wave weighing, (8) carrying out inverse curvelet transform on the signal Cj, l (omega j, Tk) after the curvelet wave weighing to obtain a time domain signal xx(t) after frequency division directional compensation. The method can be widely applied to the seismic data processing.

The invention provides a spectrum analysis method of a seismic signal and an apparatus thereof. The method comprises the following steps: acquiring the seismic signal; carrying out Hilbert transformation operation on the seismic signal to obtain an analytic signal of the seismic signal; carrying out WVD processing on the analytic signal; according to a result of the WVD processing, determining a Gauss window function and an attenuation coefficient; according to the determined Gauss window function and the attenuation coefficient, carrying out smooth pseudo-WVD distribution time frequency analysis processing on the result of the WVD processing. Through the method and the apparatus in the invention, a high time frequency resolution of seismic signal spectrum analysis can be obtained.

The invention discloses a method for positioning an underwater sound pulse signal by double array elements on the basis of cross-correlation, which comprises the following steps of: a step 10 of carrying out estimation of time-frequency distribution with a self-adaption radial gaussian kernel function on a frequency of the underwater sound pulse signal; and a step 20 of implementing positioning on the underwater sound pulse signal received by the double array elements, wherein the step 10 comprises a step 101 of determining a fuzzy function on a two-dimensional frequency-deviation-time-lag region, a step 102 of setting a total dot number of a discretized frequency deviation and a total dot number of a discretized time lag, a step 103 of converting the fuzzy function in a rectangular coordinate system into a fuzzy function in a polar coordinate system and a step 104 of a central frequency and corresponding instantaneous time of the received signal; and the step 20 comprises a step 201 of determining a searching range of a sound source, a step 202 of determining corresponding copy channel pulse response and a step 203 of implementing matching field positioning on a target. The method utilizes two vertical receiving hydrophones to implement accurate positioning on the unknown underwater sound pulse signal of a transmitted signal.

The invention discloses a nonlinear signal time-frequency analysis method based on short-time fractional order Fourier transform, and the nonlinear signal time-frequency analysis method belongs to the technical field of target signal analysis. The nonlinear signal time-frequency analysis method utilizes short-time fractional order Fourier transform, subjects a signal to segmentation processing and combined processing of different orders of fractional order Fourier transform through short-time fractional order Fourier transform, adopts an angle constraint method for fractional-order order searching, improves the time-frequency resolution of the target signal and the precision of time-frequency analysis, completes the time-frequency analysis of single-component and multi-component nonlinear signals, solves the problems of low time-frequency resolution and difficult separation of the target nonlinear echo signal, is conductive to parameter estimation of the weak target signal, improve the precision of signal parameter estimation, has the advantages of high time-frequency resolution and precise separation of different signals in the time-frequency domain, significantly reduces the amount of computing, provides reliable data support for a follow-up system to complete tasks, and is worthy of adoption and popularization.

The invention discloses a method for positioning an underwater sound pulse signal on the basis of frequency estimation, which comprises the following steps of: a step 10 of receiving the underwater sound pulse signal by utilizing a single hydrophone and carrying out estimation of time-frequency distribution with a self-adaption radial gaussian kernel function on a frequency of the underwater sound pulse signal; and a step 20 of implementing positioning on a target by utilizing sound field matching, wherein the step 10 comprises the following steps of: firstly, receiving the underwater sound pulse signal by utilizing the single hydrophone and determining a fuzzy function on a corresponding two-dimensional frequency-deviation-time-lag region for the underwater sound pulse signal; then setting a total dot number of a discretized frequency deviation and a total dot number of a discretized time lag; converting the fuzzy function in a rectangular coordinate system into a fuzzy function in a polar coordinate system; measuring an optimal spread function by adopting an iterative algorithm to obtain time-frequency distribution of the received signal; and determining a central frequency and corresponding instantaneous time of the received signal. According to the positioning method, parameter estimation on the unknown underwater sound pulse signal of a transmitted signal can be implemented by utilizing the signal hydrophone and the transmitted signal is accurately positioned.

The invention discloses a seismic fluid prediction method based on VMD and TK energy operators. The method comprises the following steps: S1, performing variational mode decomposition on a seismic signal to obtain a set of modal components that reflect a natural mode of vibration inside the seismic signal and have an instantaneous frequency with real physical meaning; S2, getting TK energy spectrums of each modal component by using the TK energy operators to obtain more accurate energy distribution on a signal time frequency; and S3, performing effective and accurate seismic fluid prediction by searching fluid characteristics of ''enhanced low frequency energy and attenuated high frequency energy'' of oil and gas contained in the reservoir. The seismic fluid prediction method based on VMDand TK energy operators combines the variational mode decomposition with the TK energy operators, which has stronger identification for the fluid-containing characteristics of the reservoir, and can effectively improve the accuracy of seismic fluid prediction.

The invention discloses a traveling wave time-frequency analysis method based on variational mode decomposition and Wigner-ville distribution. The method includes the following steps that: fault traveling wave signals are detected, and Karebauer phase-mode transformation is performed on three-phase voltage traveling wave signals, so that a traveling wave aerial mode component is obtained; variational mode decomposition is performed on the traveling wave aerial mode component, so that K intrinsic mode components are generated; Wigner-Ville analysis is performed on each intrinsic mode component;and the Wigner-Ville distribution of each intrinsic mode component is linearly superimposed, so that the time-frequency domain distribution of original traveling wave aerial mode signals is obtained.With the method of the invention adopted, the interference of cross terms in Wigner-Ville distribution can be effectively suppressed; a good noise suppression effect enabling good VMD (Variational Mode Decomposition) is preserved; time-frequency resolution enabling high Wigner-Ville distribution and good time-frequency aggregation are preserved; traveling wave time-frequency domain information characteristics are truly and accurately represented; and fault traveling waves can be completely observed. The method is of important theoretical and practical significance for the practical application of fault traveling wave protection and positioning.

The invention discloses a method for carrying out separation and time-frequency analysis on respiration and heartbeat signals in non-contact life detection on the basis of HHT (Hilbert Huang Transform), which comprises the following steps of: by adopting a band-pass filter, separating the respiration and heartbeat signals and filtering out noise and harmonic waves to the greatest extent; by adopting EMD (Empirical Mode Decomposition), decomposing the filtered respiration and heartbeat signals into IMF (intrinsic mode functions) of single-frequency signals; filtering out the IMF comprising the respiration harmonic waves by adopting a maximum correlation criterion, i.e. extracting the IMF with the maximum correlation with an original signal and using the IMF as the respiration or heartbeat signal; and directly carrying out Hilbert transformation on the filtered output signal. Compared with a conventional time-frequency analysis technology, the method not only can effectively remove noise and harmonic wave interference of the respiration and heartbeat signals, but also has higher time-frequency resolution so as to effectively describe variation of life characteristics of a human body.

The present invention discloses a CEEMD-SPWVD time-frequency spectrum analysis-based post-stack seismic fluid prediction method which solves the defect in the prior art that due to a wavelet basis reason of the wavelet transform, the focusing capability of the extracted frequency domain data is insufficient, so that the accurate frequency component data can not be extracted correctly. The post-stack seismic fluid prediction method of the present invention comprises the steps of utilizing a complete ensemble empirical mode decomposition (CEEMD) method to decompose the seismic trace set data to obtain a plurality of IMF frequency components, carrying out the cross-correlation calculation on an original seismic trace set signal and the IMF components, removing the IMF Redundant components having low cross-correlation coefficients, and then carrying out the SPWVD calculation on the effective IMF components and superposing to obtain a CEEMD-SPWVD time frequency spectrum, and finally calculating the frequency attenuation gradient of the obtained CEEMD-SPWVD time frequency spectrum, thereby guaranteeing the situation that the effective frequency of the post-stack seismic data can be extracted most accurately.

The invention discloses a seismic attenuation qualitative estimation method based on self-adaptive optimal kernel time frequency distribution. The method comprises the following steps of 1) collecting original seismic data; 2) picking a position of a seismic data target layer; 3) determining a high frequency fH and a low frequency fL; 4) calculating self-adaptive optimal kernel time frequency distribution for each signal in the superimposed seismic data body to obtain a high-frequency component and a low-frequency component; 5) determining a correction factor; and 6) estimating the seismic attenuation. According to the method, the self-adaptive optimal kernel time frequency distribution is firstly used for carrying out the time frequency decomposition of the seismic data to obtain the high-frequency component and the low-frequency component of the seismic data, and then the seismic attenuation is qualitatively estimated by utilizing the difference of the low-frequency component and the high-frequency component. Compared with the traditional seismic attenuation qualitative estimation method based on the time frequency distribution, the method has high time-frequency resolution ratio, and the seismic attenuation can be more precisely reflected; and in addition, the technical scheme is easy to realize, and the operability is strong.

The invention proposes an unknown target recognition method for radar target recognition. The method comprises a recognition stage of an unknown target. According to the recognition stage of the unknown target, an MSTFT-WVD algorithm is adopted to obtain the micro-Doppler characteristic time-frequency graph of the unknown target; and the micro-Doppler characteristic time-frequency graph of the unknown target is inputted into a deep learning model which is trained in a second stage, so that the category information of the unknown target is obtained. With the method of the invention adopted, a higher recognition accuracy rate can be obtained.

The invention discloses a method for measuring a distance of a low-frequency underwater sound pulse signal on the basis of frequency dispersion features, which comprises the following steps of: a step 10 of receiving the low-frequency underwater sound pulse signal by a single hydrophone and then carrying out representation of time-frequency distribution with a self-adaption radial gaussian kernel function on the frequency dispersion features of the low-frequency underwater sound pulse signal; a step 20 of extracting a frequency dispersion curve of spread modes in the time-frequency distribution to obtain a time difference of arrival between the modes; and a step 30 of measuring the distance of a sound source according to the time difference between the extracted modes under each frequency point, i.e. firstly, measuring theoretical group velocity values corresponding to the extracted modes under each frequency point by using a normal mode model, then estimating the distance of the sound source under each frequency point in a frequency range in which a mode mc is the same with a mode nc, and finally, measuring an arithmetic mean of the estimated distances under all the frequency points so as to obtain the distance of the sound source. According to the measuring method, accurate measurement on the distance of the low-frequency underwater sound pulse signal of shallow sea can be implemented by utilizing the single hydrophone.

The embodiment of the invention discloses a rotational speed estimation method and device based on gear meshing vibration, which are used for enhancing the anti-noise capability and improving the precision of the estimated rotational speed curve. The rotational speed estimation method comprises the following steps: acquiring a gear meshing vibration signal; calculating the Wigner-Ville distribution and the wavelet scale spectrum of the gear meshing vibration signal; achieving time-frequency fusion of the Wigner-Ville distribution and the wavelet scale spectrum to obtain the time-frequency fusion distribution; according to the time-frequency fusion distribution, determining the gear meshing frequency curve; according to the gear meshing frequency curve and the number of gears of a driving wheel, determining the rotational speed curve of the driving wheel.

The invention discloses a multichannel HHT (Hilbert-Huang Transform) based UWB (Ultra Wideband) radar human body motion micro-Doppler feature extraction method, which comprises the steps of 1, acquiring UWB radar signals; 2, preprocessing the acquired UWB radar signals; 3, performing effective channel selection; and 4, carrying out multichannel time-frequency spectrum fusion. The micro-Doppler time-frequency analysis method provided by the invention has higher time-frequency resolution, micro-Doppler features corresponding to different components are more obvious in component differentiation, and transient features and detail changes of human body motions can be better reflected. The time-frequency analysis method provided by the invention is high in anti-interference ability, and obvious micro-Doppler features can still be captured under the conditions of long-distance through-wall detection and sharp signal attenuation. The time-frequency analysis method provided by the invention has better denoising capability, the acquired time-frequency spectrum is higher in signal-to-noise ratio, and micro-Doppler feature components are more obvious.

The invention relates to a propeller shaft frequency searching method based on improved noise envelope signal recognition. The method includes: enveloping an original hydrophone signal, and performingHilbert-Yellow transform on each wavelet packet signal to obtain a wavelet envelope signal; performing wavelet reconstruction to obtain an improved noise envelope signal; calculating a time correlation spectrum, take a line spectrum protruding at the peak of the low frequency band as the suspected shaft frequency; setting a step size smaller than the frequency resolution according to the demand;forming a suspected shaft frequency set with the suspected shaft frequency as the center; performing cyclic correlation calculation on a time correlation spectral signal on each suspected shaft frequency to obtain the frequency statistical amount of a cyclic modulation spectrum; and finally searching the shaft frequency of a target according to the frequency statistical amount. The method of the invention corrects axial frequency offset errors generated by the conventional cyclic modulation spectrum methods in the spectrum calculation process, improves the accuracy of the shaft frequency detection, greatly reduces the calculation amount of the loop iteration, and is convenient to implement in engineering application.

The invention discloses a fault diagnosis method for an AC / DC charging equipment power device based on wavelet packet analysis, and the method comprises the steps: analyzing a charging equipment powermodule, and determining a fault class; obtaining output signals of the charging equipment power module under the normal condition and various fault conditions; carrying out the high-low frequency decomposition of the output signals, carrying out the multilayer wavelet packet decomposition of the high-low frequency signals obtained through decomposition, and carrying out the reconstruction of a wavelet packet decomposition coefficient; calculating the extracted signal energy at all frequency bands, carrying out the normalized calculation of the signal energy, and finally determining a centralized frequency band range of the signal energy; carrying out the power spectrum analysis of the reconstructed wavelet packet decomposition coefficient, determining the feature frequency and power spectrum value of a frequency band signal, comparing the comparison with the fault analysis, and determining the type of a fault; and carrying out the fault type coding of the type of the fault. The methodimproves the time-frequency resolution of a signal, achieves the precise fault positioning through the spectrum features, and improves the precision of the fault diagnosis of the AC / DC charging equipment power device.

The invention discloses a series-type seismic signal optimization time frequency transformation method, which relates to an oil exploration data processing and interpretation technology. Complete set empirical mode decomposition is used for decomposing an original seismic trace x(t) to a plurality of different bands of intrinsic mode function (IMF) signal components, each signal component serves as a new input signal imf(t), an energy optimization criterion objective function is then used for solving the optimal frequency domain window parameter, an optimization time frequency distribution calculation formula is used for sequentially solving the time frequency distribution TFR(t, f) for each newly-inputted signal, and finally, the obtained time frequency distribution is overlapped to obtain a seismic signal time frequency spectrum TFR(t, f) with the time frequency resolution improved obviously. The technology makes full use of effective information of seismic exploration data, the time frequency resolution is high, the calculation speed can be improved exponentially, the information utilization rate in the seismic exploration data is improved, and the seismic data interpretation reliability is also improved.

The invention discloses a seismic data time frequency analysis method based on synchronization extraction S transformation. On the basis of S transformation, a synchronization extraction operator is introduced, coefficients of the S transformation result in tightest correlation with signal time-variant characteristics are extracted through the operator, so energy diffusion is compacted. The methodis advantaged in that the analysis result having the higher time frequency resolution can be acquired, the analysis result having the higher time frequency resolution is further applied to time frequency analysis of actual seismic data, not only can the position of underground reservoirs be accurately defined, the river and fault geological information can be more accurately described, but also further seismic data interpretation and well location determination are facilitated.

The invention provides a TV-OFDM multi-carrier modulation system. The system is obtained by introducing time-varying signal and processing on the basis of the conventional time-invariant OFDM multi-carrier modulation system. Different from the OFDM system, the amount of sub-carriers in the TV-OFDM system is time-varying, the amount of sub-carriers at a sending end varies according to the size of the peak to average power ratio (PAPR) of each frame of processing signal, and the amount of the sub-carriers is determined by calculating the PAPR, so that the PAPR and power consumption of the system can be reduced effectively. Compared with other methods for reducing the PAPR in the OFDM system, the TV-OFDM system can keep advantages of the OFDM system and is efficient in reducing the PAPR. The sending end of the TV-OFDM system needs to send the amount of each frame of sub-carriers to a receiving end as sideband information.

The invention relates to a method for identifying an operation mode under an underdetermined condition based on a blind source separation technology, and belongs to the field of detection of large land-based platforms, aerospace, ships and buildings. According to the invention, the modal parameter identification precision of the operation modal analysis method based on blind source separation under the conditions of underdetermined conditions, near-frequency modals and the like is improved, the calculation efficiency is improved, and the calculation cost is reduced. Moreover, the dependence ofthe method on prior knowledge such as modal orders in the modal parameter identification process is reduced, and the sensitivity to noise signals is reduced, so that the method is small in calculatedamount, high in robustness and convenient to use. The method can be operated even under the condition of lack of professional knowledge background, and can be widely applied to modal parameter identification under the linear structure underdetermined condition in structural dynamics engineering application.

The invention relates to a wavelet decomposition-based earthquake spectrum decomposition method, and includes the steps of: 1) inputting seismic data, and performing Hilbert conversion and spectral analysis on the seismic data; 2) presetting a Ricker wavelet function; 3) building a Ricker wavelet set according to a spectrum of the seismic data obtained by the Step 1) and the Ricker wavelet function in the Step 2); and 4) using the Ricker wavelet set to perform time-frequency decomposition on a seismic trace. The wavelet decomposition-based earthquake spectrum decomposition method has the beneficial effects that time-frequency resolution of earthquake spectrum decomposition can be greatly improved, and high-precision time-frequency domain seismic data can be obtained, thereby laying a solid foundation for improvement of seismic reservoir prediction; and the time-frequency resolution is improved by more than one time, playing an important role in using seismic frequency division information to perform reservoir prediction, and providing an important guarantee for oil companies and service companies to improve the success rate of exploration and development drilling.

The invention discloses an electroencephalogram signal emotion recognition method based on VMD and WPD, and the method comprises the steps: carrying out the variational mode decomposition of obtainedelectroencephalogram signal data, and obtaining a variational mode component; wavelet packet decomposition and reconstruction are performed on the variational mode components, so that reconstructed signals under beta and gamma frequency bands in the electroencephalogram signal frequency band can be obtained; wavelet packet entropies, improved multi-scale sample entropies, fractal dimensions and first-order difference values of the reconstructed signals are calculated respectively, and feature vectors for electroencephalogram signal emotion recognition are formed; and sending the feature vectorinto a classifier to carry out classification and identification of the emotion state. Compared with the prior art, the method has the advantages that better time-frequency resolution is obtained, nonlinear features of EEG signals can be better captured, EEG frequency bands more related to emotion can be obtained, a good EEG feature basis is provided for emotion recognition, and then a better emotion recognition effect is obtained.

The present invention provides a prestack seismic gather noise suppression method and device. The method comprises the steps of carrying out the derivative synchrosqueezing wavelet transforms (DSST) on the recordings of a prestack seismic gather to generate a DSST time-frequency spectrum of the prestack seismic gather; according to the DSST time-frequency spectrum, estimating a vector parallel with an effective signal in the prestack seismic gather; according to the prestack seismic gather, setting a noise suppression parameter; according to the DSST time-frequency spectrum, the vector and the noise suppression parameter, carrying out the noise suppression processing on the prestack seismic gather to generate a DSST time-frequency spectrum after the noise suppression; according to the DSST time-frequency spectrum after the noise suppression, reconstructing to obtain the prestack seismic gather after the noise suppression. The DSST time-frequency spectrum generated by the method and device of the present invention has the higher time frequency resolution, and the noise suppression parameter and the vector parallel with the effective signal enable the noise suppression parameter to be adjusted adaptively and the effective signal to be protected, thereby having a better signal-noise separation effect.

The invention provides a method for suppressing large-amplitude ionosphere phase diameter disturbance of a high-frequency radar, and the method comprises the following steps of establishing a pollution model of broadened sea clutter by taking the high-frequency sky-ground wave radar as a background, and providing a method for suppressing large-amplitude ionosphere phase diameter disturbance basedon a generalized parametric time-frequency analysis (GPTF) algorithm, and further verifying the effectiveness of the proposed method through simulation. Theoretical analysis and simulation experimentsshow that the processing method can effectively suppress the large-amplitude ionospheric phase diameter disturbance, and the method for suppressing large-amplitude ionosphere phase diameter disturbance of the high-frequency radar has the advantages of high resolution and no cross terms.

A method for analyzing and processing time - frequency of coarse - grain material ultrasonic detection includes obtaining best quality of time - frequency image, picking up defect information of time -frequency image, displaying A form of defect information. The method has more powerful ability to discover small defects and has excellent intensifier effect of signal to noise ratio.

The invention discloses a seismic data time-frequency analysis and attenuation estimation method based on Synchrosqueezing transform. A new time-frequency analysis tool Synchrosqueezing transform is first used for seismic data time-frequency analysis, more aggregated time-frequency representation is obtained through the rearrangement of transform domain coefficients, the time-frequency resolution is greatly improved, the obtained time-frequency representation is used for actual seismic data analysis and tight sandstone model gas bearing detection, the location of a reservoir can be accurately defined, the geological structure like a river channel, a fault and the like can be indicated, and further material interpretation and well location determination are facilitated. The invention provides the seismic attenuation estimation method based on the Synchrosqueezing transform and gives a specific implementation process, the attenuation estimation results of three-dimensional data of an oilfield tight sandstone reservoir and drilling results have a good consistency, and the method can be used for helping geologists to indicate a gas bearing reservoir and determine a drilling location.