44 results about "Radon transform" patented technology

The methods may include obtaining a frequency-domain seismic wavefield associated to grid points and organized into slices. Each slice is organized into a sequence of overlapping windows. The methods may further include, for each slice, determining a value of a first intermediate function using the frequency-domain seismic wavefield for each grid point in a first overlapping window, determining a value of the first intermediate function using the frequency-domain seismic wavefield for each incremental grid point in each n-th overlapping window, where n is an integer greater than one, and determining a value of the first intermediate function by selecting the previously-determined value of the first intermediate function for each common grid point in each n-th overlapping window. The methods may still further include determining, using a second intermediate function, a Radon-transformed seismic wavefield using the value of the first intermediate function for the grid points. A non-transitory computer-readable memory and systems are also disclosed.

The present invention claims protection for a strong robust blind watermarking algorithm in the NSCT-DCT domain that combines Polar codes with the SP (Successive Packing) two-dimensional interleaving algorithm, belonging to the field of image processing. This algorithm successively performs Logistic encryption on the watermark, Polar code encoding, SP two-dimensional interleaving, performs NSCT transformation on the carrier image, and embeds the watermark information according to the relationship between its coefficients and determinants, enabling blind extraction of the watermark. When extracting the watermark, geometric correction of the image is performed using the Radon transform. The results show that this algorithm not only makes the image after embedding the watermark have good invisibility, but also can effectively resist attacks such as adding noise, filtering, JPEG compression, shearing, translation, rotation, mosaic, and tampering. The NC value is above 0.9, and it also has strong robustness against combined attacks, having good practical value.

While convolutional neural networks have been prized for image-processing tasks, they have limitations. Embodiments introduce a new Hough-to-Radon Transform (HRT) layer into an artificial neural network, such as a convolutional neural network, to address one or more of these limitations, without compromising on the accuracy of the artificial neural network for image-processing tasks. The HRT layer converts an input image from a first parameter space into a second parameter space of reduced complexity. Inner layers may operate on the image in this second parameter space, instead of in the first parameter space, to reduce the overall computational cost of the artificial neural network.

The present application relates to a reinforced concrete defect positioning method and system based on ground penetrating radar feature fusion, belonging to the technical field of structure nondestructive testing and ground penetrating radar signal processing. The method comprises: obtaining the original ground penetrating radar B-scan image of the reinforced concrete structure, removing the direct wave by Radon transform, and combining Curvelet multi-scale directional decomposition, adaptive threshold and region of interest constraint to suppress the steel clutter, to obtain a clutter suppression image; calculating the pixel-by-pixel absolute difference value of the original gray image and the clutter suppression image to obtain a clutter image; constructing the original gray image, the clutter suppression image and the clutter image into a pseudo-color three-channel fusion image and inputting the target detection network, and outputting the defect category, the boundary box and the actual physical coordinates. The present application can improve the detection and positioning performance of the hollow, honeycomb and delamination defects in the reinforced concrete under complex steel environment.

The invention discloses a wing aerodynamic optimization design method based on wavelet and Radon transform, which comprises the following steps: acquiring a plurality of wing shape parameter vectors of a to-be-optimized wing, and taking each wing shape parameter vector as the input of a trained wing aerodynamic optimization model to obtain a plurality of aerodynamic performance index vectors corresponding to each wing shape parameter vector; according to the method, a wing aerodynamic optimization model is designed, the wing aerodynamic optimization model comprises a wavelet neural operator and Radon transformation, the wavelet neural operator carries out kernel integration in a wavelet domain, cross-scale features from a macroscopic structure to microscopic turbulence in a flow field are accurately captured, then the multi-scale features are projected to a Sinogram domain through Radon transformation, and the wing aerodynamic optimization model is obtained. The characterization capability of key flow structure directions such as shock waves and separation zones is enhanced by using angle reweighting, and direction-sensitive compact flow field characterization is constructed. On the premise that the calculation cost is remarkably reduced, rapid and high-precision prediction and optimization design of the aerodynamic performance of the wing are achieved.

The application provides a multiple wave suppression method, device, equipment and storage medium, and belongs to the technical field of seismic data processing. The method comprises the following steps: determining first seismic data of a plurality of first seismic trace sets; determining the curvature and frequency of each seismic trace in the first seismic trace set; determining the maximum curvature and minimum curvature in the curvatures of a plurality of seismic traces, and determining the maximum frequency in the frequencies of a plurality of seismic traces; generating a three-dimensional conical body filter based on the maximum curvature, the minimum curvature and the maximum frequency; performing three-dimensional Radon transform on the first seismic data of the first seismic trace set to obtain three-dimensional Radon transform data; filtering the three-dimensional Radon transform data based on the three-dimensional conical body filter to obtain three-dimensional Radon multiple wave data; and determining target seismic data after suppressing multiple waves based on the difference between the first seismic data of a plurality of first seismic traces and the three-dimensional Radon multiple wave data of a plurality of first seismic trace sets. The method improves the efficiency of suppressing multiple waves.

The present disclosure provides a data reconstruction method based on Radon domain sparse representation and related equipment, relating to the technical field of communication. The method comprises: obtaining low-resolution Radon coefficients; inputting the low-resolution Radon coefficients into a neural network of an encoding-decoding structure to obtain first high-resolution Radon coefficients; and increasing the sparsity of the first high-resolution Radon coefficients through an adaptive soft threshold function cascaded at the back end of the neural network to obtain second high-resolution Radon coefficients. The method can reduce the data size, operation time, and operation cost of time-domain inversion of reduced-time variable Radon transform, and improve the stability and resolution of reconstructed data.

The present invention discloses a chip placement collaborative control system for flexible production, comprising a perception module, a decision module, and an execution module. The system utilizes an improved Radon transform and polar coordinate screening, and employs dual-threshold segmentation and background compression to reduce noise interference and enhance feature extraction robustness. Multi-resolution chip positioning enables precise positioning of the chip within the machine coordinate system. An improved APF-RRT algorithm combines the artificial potential field's attraction-repulsion field with RRT random search to dynamically plan collision-free paths, optimizing path length, time, and safety. Master-slave collaborative control maintains collaborative spacing between devices, adapting to flexible production requirements. Quintic polynomial interpolation is used to generate smooth acceleration curves, reduce mechanical vibration, and improve placement stability. A closed loop of visual positioning, path planning, and dynamic control is formed, enabling adaptive adjustment of flexible production. This results in closed-loop management of chip placement production with higher precision, faster response, and greater adaptability than traditional methods.

The present invention provides a method for evaluating printing effects in volumetric bioprinting projection, which includes: taking transverse slice samples, performing Radon transform on each transverse slice sample to obtain projection data, then using a to-be-determined window function to perform filtered back-projection transform on the projection data obtained from each transverse slice sample, obtaining a back-projection reconstruction image, normalizing and pixelating it to obtain a simulated printed transverse slice, performing an operation on the simulated printed transverse slice and the transverse slice sample at the corresponding height, obtaining 254 similarity evaluation values corresponding to 254 simulated printed transverse slices at each height, respectively calculating the average value of the M similarity evaluation values corresponding to M simulated printed transverse slices under the same critical curing brightness value, and taking the optimal average value as the printing evaluation index of this to-be-determined window function. Comparing the printing evaluation indexes of different to-be-determined window functions, and taking the window function corresponding to the optimal printing evaluation index as the optimal window function.

The invention relates to a forward-looking sonar SLAM method and system based on depth Fourier registration. The method comprises the following steps: S1, collecting two sonar images; s2, performing feature extraction, Fourier transform and Radon transform on the two sonar images to calculate angle correlation curves of the sonar images; s3, performing rotation correction on the two sonar images, and performing feature extraction and phase correlation calculation to obtain a phase correlation heat map; s4, calculating a rotation variance and a displacement variance of the two sonar images; s5, performing weighted correction on the variance based on the SSIM correlation of the two images to obtain a covariance matrix; and S6, constructing a noise model, and explicitly assigning a noise model parameter for each observation factor. The Fourier registration technology and the deep learning technology are introduced to the front end of the SLAM system, so that the SLAM system can effectively eliminate interference caused by a complex seabed environment and better adapt to the complex underwater environment.

This invention provides a system and method for enhancing the trajectory of a moving object based on a grating array. The system comprises: an acquisition module for acquiring raw vibration signals based on the grating array; a filtering module for filtering the raw vibration signals to remove environmental noise, resulting in a filtered signal; a matrix generation module for combining the filtered signal data to form a multidimensional spatiotemporal signal matrix based on grating points and sampling time; a noise cancellation module for comparing and analyzing the multidimensional spatiotemporal signal matrix and performing local processing to eliminate abnormal grating noise and accompanying noise; and a trajectory enhancement module for performing Radon transform on the noise-cancelled signal to enhance the trajectory of the moving object. This invention can eliminate uncorrelated noise signals in the grating array vibration signals of the moving object's trajectory, effectively eliminate accompanying noise in the non-driving channels of the moving object, and enhance the trajectory of the moving object, making the trajectory more continuous in time and space.

The present invention discloses an image restoration method under complex optical imaging conditions based on measured data, belonging to the field of image restoration. The present invention removes the noise brought by the imaging system based on the morphological filtering method, performs edge detection on the image spectrum of the blurred image under a point light source to remove the blur brought by the imaging system, determines the motion blur parameters based on the Radon transform method, uses the method of flow field data simulation to remove the pneumatic thermal radiation noise, combines the ray tracing method and the background schlieren technology to simulate and model to remove the image blur and image distortion caused by the pneumatic optical effect, and calculates the image quality evaluation parameters to comprehensively evaluate the image restoration effect. The present invention uses two methods to model for the acquisition of flow field data, and can completely remove noise, remove blur and remove distortion and restore the degraded image under complex imaging conditions, which is convenient for subsequent target detection and positioning of the image.

A method for performing maneuvering in a land vehicle using synthetic aperture radar (SAR) is provided. The method includes: receiving digitized radar echo data from a vehicle-mounted SAR radar transmission; accumulating multiple frames of the digitized radar echo data; applying a RADON transform to the accumulated multiple frames of digitized radar echo data and odometer data from the vehicle to generate a transformed frame of data for each three-dimensional point, wherein the RADON transform is configured to perform coherent accumulation on each three-dimensional point, project a radar trajectory onto each three-dimensional point, and project Doppler information onto each three-dimensional point; generating a two-dimensional map of the area covered by the radar transmission from the SAR radar based on the transformed frames of data for each three-dimensional point; and performing maneuvering using the land vehicle by applying the generated two-dimensional map.

The invention provides a longitudinal and transverse wave separation water detection method and system based on a reflection coefficient and a stress gradient, and the method comprises the steps: collecting original seismic record data of a tunnel site, and carrying out the preprocessing; performing longitudinal wave and transverse wave separation on the pre-processed seismic wave data by adopting a multi-method combined longitudinal wave and transverse wave separation method; wherein the F-K filtering is used for separating wave fields with different apparent velocities through frequency-wave number domain conversion, so that primary separation of longitudinal waves and transverse waves is realized; the overlapping part of the residual longitudinal wave and transverse wave in the F-K domain; mapping the data from a time-space domain to a ray parameter domain by using linear Radon transform, and further separating wave fields with similar apparent velocities; carrying out final separation processing on the longitudinal waves and the transverse waves by using polarization characteristics through a polarization filter; respectively calculating reflection coefficient imaging and stress gradient imaging based on the separated longitudinal waves and transverse waves; according to the reflection coefficient imaging result and the stress gradient imaging result, the underground water occurrence condition is judged in a combined mode. And the identification precision of the underground water occurrence condition is improved.

The invention discloses a seismic reflection signal reconstruction method, which relates to the technical field of oil exploration, and comprises the following steps: inputting a missing seismic signal; constructing a target function, solving the target function by adopting a self-adaptive accelerated sparse optimization algorithm, and transforming the three-dimensional seismic data volume containing the primary reflected waves and the multiples missing 50% into a hyperbolic sparse domain to obtain a three-dimensional sparse constraint hyperbolic Radon positive transformation model; and converting the three-dimensional sparse constraint hyperbolic Radon positive transformation model into a seismic data field, and obtaining a seismic reflection signal reconstruction result until all data volumes are reconstructed. According to the rapid three-dimensional seismic data reconstruction method, an effective signal is reconstructed by adopting a three-dimensional hyperbolic Radon transform method based on an adaptive acceleration sparse optimization algorithm, missing data in a three-dimensional seismic data volume is better reconstructed, and the calculation cost is remarkably reduced.

This invention discloses a seismic surface wave array tomography method, storage medium, and device, relating to the field of surface wave tomography technology. The method includes: calculating the cross-correlation function between all pairs of seismic stations based on continuous waveform data recorded by seismic stations; determining the size of the subarray based on the spacing and number of seismic stations; processing all cross-correlation functions within each subarray using a linear Radon transform to obtain the dispersion curve of each subarray; moving the subarray along both the horizontal and vertical directions with a certain step size, and using a linear Radon transform to obtain the dispersion curves of subarrays at other positions; using the dispersion curves of different subarrays as input data, and constructing the phase velocity values ​​of each grid point in the study area using the seismic array tomography method. The solution of this invention can improve the imaging resolution of seismic array processing technology.

The invention relates to a bank industry electronic bill intelligent auditing method based on a rule engine, and relates to the technical field of electronic bill intelligent auditing, and the method comprises the following steps: S1, carrying out the graying processing of a document image; s2, carrying out noise reduction processing on the document image; s3, obtaining the contour of the document image; s4, restoring the document image by adopting a Radon transformation method; s5, identifying and classifying elements in the layout of the document image by adopting a LayoutLM-v1 model; s6, performing character recognition and extraction by adopting a Faster R-CNN algorithm, completing semantic entity recognition and relation extraction tasks based on a multi-modal DeepSeek-VL model, and organizing structured key value pair data to extract key information in the document image; and S7, checking the document image by using a Drools rule engine. According to the invention, the existing document auditing processing flow can be standardized, automatic and intelligent, the operation process of background business personnel is simplified, and meanwhile, the overall operation timeliness of the mechanism is continuously improved.

The present disclosure relates to a method and apparatus for directly suppressing multiple waves between onshore layers in the depth domain of a well-controlled area. The method comprises: determining a pre-stack CRP gather from which primary reflection wave information is removed based on acquired work area logging data and a stacked profile of pre-stack depth migration seismic results; calibrating the positions of the multiple waves; determining a stacked profile of the multiple waves based on the calibrated CRP gather; subtracting the stacked profile of the pre-stack depth migration seismic results from a stacked profile of multiple waves with a depth unit of m; and performing pulse deconvolution on the stacked profile after the subtraction to obtain a pre-stack depth migration result after direct suppression of multiple waves between onshore layers in the depth domain of the well-controlled area. This method solves the problem that in the past, when suppressing inter-layer multiple waves through Radon transform, the depth domain migration processing results need to be converted to the time domain through time-depth conversion. Distortion occurs during the time-depth conversion process, resulting in the obtained time domain gather having an inaccurate depiction of the onshore inter-layer multiple waves, which is not conducive to subsequent suppression processing.

The invention relates to the field of acoustic indoor positioning, in particular to a signal arrival time identification method based on WVD time-frequency analysis and a terminal thereof. According to the scheme, firstly, band-pass filtering and framing processing are carried out on collected detection signals, and a plurality of signal segments arranged in a time sequence are obtained; performing WVD analysis on each signal segment to obtain a WVD spectrum; secondly, constructing a reference signal, and performing feature extraction and information enhancement on a time-frequency component of a first path in the WVD spectrum by combining the slope of the reference signal, Radon transformation and Hough transformation; and finally, all edge points of the first path in all the time-frequency diagrams are found out by combining normalization, contrast stretching, expansion operation, Canny edge detection and other operations, and then the positions of the edge points corresponding to the signal arrival time are identified. In addition, time-frequency domain compensation is carried out in combination with the analyzed time domain offset of the signal. According to the invention, the problem of insufficient AAT detection precision caused by the fact that the existing acoustic indoor positioning technology is easily influenced by a multipath effect and a near-far effect is solved.

The invention provides a seismic data reconstruction method, which comprises the following steps of: executing Radon transformation on seismic data to convert missing seismic data from a time domain to a Radon transformation domain; combining the seismic data converted to the Radon transform domain with an orthogonal polynomial representing seismic AVO characteristics to form high-order Radon transform; performing inverse transformation on the high-order Radon transformation to obtain missing part data of the seismic data; filling the seismic data with the missing part data to obtain reconstructed new seismic data; according to the method, high-order Radon transformation and repeated iteration are carried out on the seismic data, high-fidelity reproduction of the missing seismic data is realized, and reconstruction of the missing and irregular seismic data plays an important role in the seismic data processing process.

The invention relates to a sliding element having a base layer and a coating arranged on an outer surface of the base layer, a profile is defined such that the profile forms an outer surface of the coating, and a Radon transform g (theta, rho) of a square segment of the profile is defined, the value domain of which is standardized to a value between 0 and 1, theta describes the angle and Rho describes the distance from the origin of the coordinates, and the Radon transform g (Theta, Rho) is shortened in the Rho direction in factorial symmetry. For any angle [theta], the standard deviation [sigma] [rho] ([theta]) of the Radon transform and the value of the Radon transform are defined, where is the average value of all g ([theta], [rho]) for the respective angle [theta]. [sigma] max, [sigma] min, being a maximum standard deviation, a minimum standard deviation, and an average value of each standard deviation, being a maximum value of each value, a minimum value of each value, and an average value of each value, parameter A being defined and the profile having a parameter Alt; 1.0, preferably lt; 0.9, particularly preferably lt; and 0.7.

According to the dark and weak point target image registration method based on the RPSF provided by the invention, the RPSF is adopted to convert and characterize a dark and weak non-feature point target in a spatial domain, affine transformation derivation and calculation are performed on the RPSF function, a rotation parameter and a translation parameter of the point target in the spatial domain are acquired, and parameter estimation of affine transformation is realized. Through integral operation of Radon transform, enhancement and anti-interference detection of a target signal under a low signal-to-noise ratio are realized. Algorithm simulation and parameter estimation are carried out on tiny translation and rotation transformation through different Radon transformation step lengths, and it is verified that the error of the method meets the sub-pixel level. Through a registration test of a space debris image collected by a ground-based telescope, the engineering application capability and robustness of the method under the condition of a low signal-to-noise ratio are verified.

The invention discloses a load identification method, system and device based on Radon transformation and deep learning and a storage medium, and the method comprises the steps: intercepting load measurement data, and converting the load measurement data into a load image through a Markov transfer field; de-noising processing is carried out on the load image containing noise by using wavelet transform; extracting image features of the de-noised load image by using Radon transform; dividing the image features into a training set and a test set, and performing normalization processing on the training set and the test set; and constructing a convolutional neural network, inputting the training set after normalization processing into the convolutional neural network to train the model to obtain a load identification model, testing the load identification model by using the test set after normalization processing, and performing load identification by using the tested load identification model. The method has the advantages of being easy to implement and high in recognition precision, and can be applied to the field of load regulation and recognition.

This disclosure relates to the field of seismic data processing technology, and particularly to a Radon transform method, apparatus, device, storage medium, and computer program. The method includes: acquiring target seismic data to be processed; constructing a time-domain Radon transform operator between the Radon domain model vector and the time-domain seismic data; constructing an objective function based on the time-domain Radon transform operator, wherein the objective function includes a data fitting term and a sparsity constraint term, the data fitting term being used to measure the error between the time-domain seismic data and the fitted seismic data, the fitted seismic data being generated by projecting the Radon domain model vector onto the data domain using the time-domain Radon transform operator, and the sparsity constraint term being used to apply norm sparsity constraints to the Radon domain model vector; and solving the objective function based on the target seismic data to obtain the target Radon domain model vector. Implementing the technical solution of this disclosure can improve the resolution of the Radon transform.

The present application relates to a discretization method, system, terminal, and storage medium for generalized Radon transform in the angle domain. The method includes: reading seismic trace data, setting the coordinates of imaging points of the seismic trace data, and reading the travel time, amplitude, and direction table of each imaging point coordinate; calculating the scattering angle and discrete interval; calculating the sampling point θ0 closest to the scattering angle and its partition boundary #imgabs0# and calculating the distance from the scattering angle to the partition boundary θ bound The distance l is used to determine the partition boundary θ bound Whether to split the scattering angle discrete surface, if so, use the discrete element splitting algorithm to split the partition boundary θ bound The nearby discrete cells are split into two cells, and the areas of the two cells after the split are calculated according to the discrete interval; the two cells after the split are used to calculate the imaging accumulation at the sampling point θ0 and θ0±Δθ. This application can obtain a continuous and smooth angle domain inversion result.

This invention discloses a method, apparatus, storage medium, and electronic device for seismic profile imaging. The method includes: performing a Radon transform on each first seismic wavefield at the shot point to obtain a first plane wave component and obtaining the value of a first ray parameter, thereby obtaining the incident ray angle corresponding to the first ray parameter; performing a Radon transform on each second seismic wavefield on one side of the receiver point to obtain a second plane wave component and obtaining the value of each second ray parameter, thereby obtaining the scattered ray angle corresponding to each second ray parameter; obtaining each dip angle based on the incident angle and each scattered angle; obtaining the single-shot imaging function for each dip angle through a single-shot imaging calculation formula; iteratively executing the imaging function for all shot points to obtain dip gathers; and superimposing the dip gathers to obtain seismic profile imaging. This method can efficiently obtain accurate dip gathers, thereby obtaining high-resolution, high signal-to-noise ratio seismic profile imaging.

The present invention provides a method for enhancing micro-Doppler characteristics of a rotary-wing unmanned aerial vehicle (UAV) using dual-station radars, comprising the following steps: obtaining echo signals of a target to be analyzed from two radars, determining a first radar and a second radar; preprocessing the echo signals of the two radars; estimating a local peak value occurrence period of the echo signal of the first radar; increasing the slow-time sampling rate of the echo signal of the second radar to the same as that of the first radar based on a characteristic of the local peak value period; performing a short-time Fourier transform on the echo signal to obtain a first time-frequency spectrum and a second time-frequency spectrum; performing a Radon transform on the first time-frequency spectrum and the second time-frequency spectrum, processing the Radon transform results in a Radon transform domain, and obtaining a time-frequency spectrum diagram with enhanced micro-Doppler characteristics; when the data transmission volume is limited, the radar with a low slow-time sampling rate can obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of the UAV target; and when the data transmission volume is sufficient, the micro-Doppler characteristics of the UAV target obtained in the time-frequency spectrum diagram are enhanced compared to those obtained directly.

To provide a method for designing an airframe shape of a supersonic flying body that can take off-track boom into consideration on the basis of a theoretical basis.SOLUTION: A method for designing an airframe shape of a supersonic flying body comprises: a sinogram creation step S20 of creating a sinogram defined as a result of performing a Radon transform on singular points representing an airframe of a supersonic flying body; and a shape reconstruction step S30 of reconstructing the airframe shape from the sinogram. The sinogram is defined using a function that satisfies the Helgason-Ludwig consistency condition for a non-circular region. The sinogram is obtained from physical quantities defined in a cylindrical coordinate system coaxial with the airframe.SELECTED DRAWING: Figure 3

The application discloses a multi-source data separation method and device based on wideband Radon transform, relates to the technical field of oil and gas resource exploration, and comprises the following steps: determining pseudo-separated data, performing frequency domain conversion on multi-source aliasing data and the pseudo-separated data to obtain a frequency-wavenumber spectrum, performing Radon transform calculation by using each theoretical bandwidth value in the frequency-wavenumber spectrum to obtain each Radon transform operator, and calculating corresponding each Radon parameter based on the Radon transform operator; constructing a self-adaptive filter by using each theoretical bandwidth value in the frequency-wavenumber spectrum, performing multi-source noise suppression based on each Radon parameter and the self-adaptive filter, and obtaining a coherent signal; performing calculation on the coherent signal by using an aliasing operator to obtain multi-source noise; and performing data separation on the multi-source aliasing data and the pseudo-separated data based on the multi-source noise. The application can avoid the situation that the amplitude is not preserved and noise is left in multi-source data separation, realizes multi-source noise suppression, and better preserves the horizontal propagation characteristics of seismic data.

The application relates to a three-dimensional imaging method for a spatial spin group target based on Kalman filtering, and relates to a three-dimensional imaging method for a spatial spin group target.The application aims to solve the problems of large search calculation amount, long operation time, and limited parameter estimation accuracy caused by search range and search parameter setting in the prior art three-dimensional imaging method for a spatial spin group target.The process is as follows: I. obtaining a one-dimensional range image based on a spatial spin group target; II. performing binaryzation processing on the one-dimensional range image, and performing skeleton extraction processing on the binaryzation image to obtain an image; III. extracting each sinusoidal curve in the image; IV. obtaining spin frequency estimation values of scattering points corresponding to each sinusoidal curve; V. estimating the z-axis direction coordinate values of the corresponding scattering points according to the values of the centers of each sinusoidal curve deviating from the center of the distance dimension; and VI. estimating the x-axis and y-axis direction coordinate values of the scattering points by using an I Radon transform.The application belongs to the technical field of radars.