31 results about "Multiple echo" patented technology

The invention relates to the technical field of radar ranging, and discloses a radar ranging method and device and a radar level meter, and the method comprises the steps: receiving a plurality of echo signals reflected by a ranging target, superposing the plurality of echo signals, and obtaining a superposed echo signal; screening a plurality of target spectral lines from the frequency spectrum of the superposed echo signals; performing Rife interpolation based on the plurality of target spectral lines to obtain a plurality of interpolation points, and calculating an initial distance to the distance measurement target; screening a plurality of target interpolation points from the plurality of interpolation points based on the initial distance; and performing cubic spline interpolation based on the plurality of target interpolation points to obtain a cubic spline interpolation function, and substituting the initial distance into the cubic spline interpolation function to obtain a target distance. According to the invention, by superposing a plurality of echo signals reflected by the ranging target, noise can be significantly suppressed, the signal-to-noise ratio can be improved, and efficient and accurate radar ranging is realized by adopting double interpolation of locally fine Rife interpolation and globally optimized cubic spline interpolation.

This invention discloses a clutter discrimination and suppression method based on multiple echo features, comprising: acquiring radar front-end clutter and target echo detection video data and dividing it into several connected regions; extracting multi-dimensional features and labeling prior information for each connected region; using the Relief feature selection algorithm to calculate and filter the weights of the multi-dimensional features, removing redundant features to obtain the optimal feature vector; using this feature vector to train a support vector machine classifier, and obtaining the optimal parameter model through cross-validation; acquiring measured clutter data, extracting corresponding features and inputting them into the model; and determining whether to remove clutter and retain targets based on the output. This invention effectively filters out dynamic clutter spots, avoids false deletion of weak targets, significantly reduces the false alarm rate of the system, and alleviates the computational burden of subsequent track processing.

This invention relates to a photoelectric conversion and beam combining device for multiple-channel reception of the same echo optical signal in lidar. The device includes: a sealed box, a single-photon detector, and multiple echo signal receiving lines. The multiple echo signal receiving lines receive the same echo optical signal, process the echo signal, and then transmit the processed optical signal to the single-photon detector. All echo signal lines are housed in the sealed box. Each echo signal receiving line includes: an echo signal fiber, a collimating and focusing lens group, and a narrowband filter. The echo signal fiber receives the echo optical signal. The collimating and focusing lens group includes a collimating lens and a focusing lens. The collimating lens shapes the optical signal into parallel light. The focusing lens focuses the parallel light. The narrowband filter filters out stray light and atmospheric background light from the optical signal. This invention simplifies the optical receiving system components of lidar, reduces system cost, and minimizes signal errors.

The invention belongs to the technical field of magnetic resonance signal processing, and aims to provide a spoke image correction method and system based on a constant gradient CPMG sequence. The method comprises the following steps: scanning a specified standard motif by adopting a constant gradient CPMG sequence, and obtaining a frequency-amplitude correction curve according to a scanning result; acquiring a frequency range of a specified standard motif, and fitting the correction curve according to the frequency range to obtain a fitted frequency-amplitude correction curve; a constant gradient CPMG sequence is adopted to scan a to-be-detected sample, and spoke images of the to-be-detected sample at multiple echo moments are obtained; and adopting the fitted frequency-amplitude correction curve to correct the spoke images of the sample to be measured at the plurality of echo moments to obtain the corrected spoke images of the sample to be measured at the plurality of echo moments. The spoke image of the to-be-tested sample can be corrected, and the analysis accuracy of the to-be-tested sample can be improved.

The application discloses a weather radar wind turbine clutter recognition method and system based on fuzzy reasoning, and belongs to the technical field of fuzzy reasoning. The monitoring area of a target weather radar is divided into multiple echo observation subunits according to distance gates and scanning azimuth angles, and the reflectivity factor, radial velocity, spectral width and differential reflectivity of each echo observation subunit are continuously acquired within a preset data acquisition time sequence. By analyzing the discrete characteristics of the reflectivity factor and the radial velocity in the time sequence, echo stability characteristic quantities are constructed, echo shape consistency characteristic quantities are constructed based on the consistency deviation of the spectral width and the differential reflectivity in the neighborhood, the echo stability characteristic quantities and the echo shape consistency characteristic quantities are subjected to fuzzy mapping, and the wind turbine clutter and meteorological echoes are distinguished and recognized through a fuzzy comprehensive judgment quantity, so that the accuracy and robustness of the wind turbine clutter recognition are improved, and the weather radar data quality control under complex background conditions is suitable.

The disclosure relates to a computer-implemented method for processing a magnetic resonance data set of an acquisition area, which is based on an acquisition in an examination procedure in a magnetic resonance facility with a magnetic resonance sequence in which multiple echoes are acquired in an echo train, in particular after a common radio-frequency excitation pulse. For the magnetic resonance data set, a path data set describing the signal path of the measured magnetic resonance signal over an acquisition period, in particular the echo train, in the magnetic resonance sequence is determined in the k-space. A trained image processing function for determining a result data set is transferred together with the magnetic resonance data set as input data.

The invention discloses a distribution network insulation bucket arm vehicle riding anti-touch automatic alarm method and device, and relates to the technical field of anti-touch automatic alarms, and the method comprises the following steps: obtaining continuous echo signals and bucket arm motion trail data of a bucket arm vehicle in an operation process, and carrying out correlation analysis to obtain a reflection trail set; performing feature extraction on the bucket arm movement track data to obtain bucket arm movement features, and extracting a reflection interference sequence of a reflection track set based on the bucket arm movement features; based on the reflection interference sequence, the delay change of the continuous echo signal is repositioned, a first reflection sequence is obtained, and a reflection characteristic matrix of the first reflection sequence is extracted; and determining the safety distance between a bucket of the bucket arm vehicle and a live wire based on the reflection characteristic matrix, and performing anti-touch automatic alarm according to the safety distance, so that when the bucket arm slightly moves, the phase and delay of a plurality of echo paths are suddenly changed, and the position identification of a reflection point and the calculation of the safety distance are further influenced.

The application provides a laser radar echo signal quality control method and system based on manifold learning, and relates to the technical field of atmospheric remote sensing.The method comprises the following steps: obtaining multiple echo signal profiles observed continuously by a laser radar, and preprocessing each echo signal profile; for the preprocessed echo signal profile, using an unsupervised manifold learning sorting method to sort the echo signal profile to generate an echo signal profile sequence; wherein the sorting target is to minimize the sum of the differences between adjacent echo signal profiles; identifying abnormal echo signal profiles in the echo signal profile sequence, marking the quality of the abnormal echo signal profiles, and outputting a signal data set with quality marks.The application can adaptively learn the mode of normal signals from the data itself, thereby realizing intelligent and automatic anomaly detection, and effectively identifying complex anomaly patterns to overcome the defects of traditional methods, such as dependence on manual experience, poor adaptability and low efficiency.

This document describes various techniques for unsupervised thickness measurement and corrosion estimation in materials using ultrasonic inspection systems that utilize non-destructive testing (NDT) methods. The system uses cepstrum analysis to analyze the spectral power of the acoustic data signal acquired after the ultrasonic probe assembly emits ultrasound, identifying different frequency contents associated with multiple echoes. Cepstrum analysis allows the system to distinguish between different types of echoes, such as echoes from the front and back walls of the material, as well as echoes from any defects present within the material.

The invention provides a blind area ranging method and device of a laser radar, the laser radar and a storage medium. The method comprises the steps of obtaining first waveform information of a received first echo; the first waveform information comprises a first waveform trailing edge position, a first waveform width and a first echo number of the first echo; the first echo number is the waveform number of the first echo exceeding the preset amplitude; under the condition that the first waveform width is greater than a first threshold value, determining that the first echo is an overlapped echo of the blind area echo and the first target echo; the waveform of the first target echo is a multiple echo waveform; determining a first target waveform leading edge position of the first target echo based on the first waveform trailing edge position, the first echo number and a preset first target waveform width; and based on the leading edge position of the first target waveform, determining a distance value from the first measured target corresponding to the first target waveform to the laser radar. According to the invention, the problem that the laser radar cannot effectively measure the distance in the short-distance blind area can be solved.

The invention discloses a multi-parameter quantitative method and system based on multi-overlap echo steady-state free procession and a multi-task learning network, and relates to magnetic resonance imaging. The method comprises the following steps: designing and debugging a multi-overlap echo steady-state free precession sequence to obtain a magnetic resonance image with multiple contrast (T1, T2, T2 *) weighting; generating a training sample of the deep neural network; designing a multi-task deep learning network fusing interlayer information; training a network weight by adopting the training sample; and the trained multi-task deep learning network is adopted to map the actually acquired magnetic resonance image, and quantitative images of a plurality of parameters are obtained at the same time. Rich multi-contrast multi-echo information is provided based on multi-overlap echo steady-state free precession, a multi-task deep learning network fuses characteristics of different tasks in different levels, multiple times of scanning are not needed, and rapid and accurate multi-parameter simultaneous quantitative imaging can be achieved in one time of scanning.

The application provides a radar echo real-time simulation method based on FPGA and digital array, relates to the technical field of radar system simulation and test, and comprises the following steps: receiving a radar transmitting signal and performing digitization and down-conversion processing to obtain a baseband I / Q signal; in the FPGA, performing multi-scattering point range image generation processing on the baseband I / Q signal to form multiple echo components corresponding to different scattering points of a target; performing micro-motion characteristic modulation processing on the multiple echo components; through a multi-stage phase modulation unit, sequentially performing main Doppler modulation and micro-Doppler modulation on each echo component to generate an echo signal with main motion and micro-motion characteristics; superimposing and synthesizing the echo signal after micro-motion characteristic modulation and a simulated environmental effect signal to obtain a synthesized signal; performing up-conversion and digital-to-analog conversion on the synthesized signal and outputting the synthesized signal to a radar under test through a digital array feed system.

The invention discloses a polarization characteristic-based inter-satellite scattering mutual interference detection method, which comprises the following steps of: synchronously dividing an echo matrix of a cross polarization channel and an echo matrix of a co-polarization channel of a satellite-borne SAR (Synthetic Aperture Radar) in a dual-polarization mode into a plurality of echo matrix blocks along an azimuth direction, and on the basis of an incoherent accumulation result and a relative entropy, carrying out inter-satellite scattering mutual interference detection on the echo matrix blocks; determining echo matrix blocks containing MTSI interference, and calculating the energy of each row; clustering the pulses based on energy, screening out interference pulses containing MTSI, and generating an initial interference mask; constructing a polarizability index sequence for each interference pulse containing the MTSI; according to the polarizability index sequence, positioning an area where the MTSI interference is located in each MTSI-containing interference pulse based on a self-adaptive threshold value; and according to positioning results of all MTSI interferences, updating the initial interference mask to obtain a final time domain interference mask, and completing interference detection. According to the invention, high-precision positioning of MTSI interference in spaceborne SAR echo data can be realized, and improvement of the anti-interference capability of a spaceborne SAR system is facilitated.

The application relates to a signal reconstruction method based on a MEMS high-precision ultrasonic sensor and related equipment, comprising the following steps: envelope extraction is performed on an original echo sequence of the MEMS high-precision ultrasonic sensor to obtain a signal envelope line, and peak point detection is performed on the signal envelope line to obtain a peak time point sequence; the original echo sequence is segmented and intercepted based on the peak time point sequence to obtain multiple echo slices, waveform symmetry analysis is performed on each echo slice, effective echo slices meeting a symmetry threshold are screened out from the multiple echo slices to obtain a target echo section; point-by-point amplitude compensation is performed on the target echo section based on a preset standard waveform template to generate a compensated waveform, and the compensated waveform is subjected to phase alignment splicing to obtain a reconstructed signal, thereby solving the technical problem of how to improve the recognition accuracy of effective waveform segments in the ultrasonic echo signal reconstruction process.

The invention discloses a weather radar wind turbine clutter identification method and system based on fuzzy reasoning, and belongs to the technical field of fuzzy reasoning. A monitoring area of a target weather radar is divided into a plurality of echo observation subunits according to a range gate and a scanning azimuth angle, and a reflectivity factor, a radial speed, a spectral width and a differential reflectivity of each echo observation subunit are continuously acquired in a preset data acquisition time sequence. By analyzing discrete characteristics of a reflectivity factor and a radial velocity on a time sequence, an echo stable characteristic quantity is constructed, an echo form consistent characteristic quantity is constructed based on consistency deviation of a spectral width and a differential reflectivity in a neighborhood, fuzzy mapping is performed on the echo stable characteristic quantity and the echo form consistent characteristic quantity, and the echo stable characteristic quantity and the echo form consistent characteristic quantity are calculated. The wind turbine clutter and the meteorological echo are distinguished and recognized through the fuzzy comprehensive judgment quantity, the accuracy and robustness of wind turbine clutter recognition are improved, and the method is suitable for weather radar data quality control under the complex background condition.

The application discloses a kind of laser guidance radar's anti high frequency interference method and device, method includes: receiving multiple echo signals and according to multiple echo signals real-time setting multiple self-adapting overlapping wave gates;Echo signal is the signal formed after reflection for the pulsed signal that laser target indicator emits in random frequency mode;According to multiple wave gates, obtain multiple candidate pulse echo combinations from multiple echo signals;According to each echo signal and the target distance of target to be hit, with the motion attribute of seeker for hitting target to be hit, obtain target pulse echo combination from multiple candidate pulse echo combinations;According to target pulse echo combination, determine the position of target to be hit.The application can improve the anti high frequency interference ability of laser guidance system, realize accurate laser guidance, and can be widely applied in laser guidance field.

This invention provides a full-space staring digital array radar system. The system includes a digital antenna array, a radio frequency front-end, a beamforming network, and a control and processing center. The digital antenna array adopts a structure combining hemispherical and cylindrical surfaces, and the height of the cylindrical array and the radius of the hemispherical array must satisfy a certain relationship. During transmission, the radar controls the beamforming network and corresponding antenna elements of each subarray to transmit signals through the control and processing center. During reception, the radar echo is received by the receiving elements of the digital antenna array to form multiple echo signals, which are then processed by the control and processing center for target detection and tracking. The full-space staring digital array radar system of this invention has superior multi-target and full-space simultaneous surveillance capabilities, improving the radar's early warning efficiency across the entire airspace. It can simultaneously track multiple targets from various airspace angles, providing strong real-time full-space surveillance capabilities.

This application provides a calibration method, apparatus, storage medium, and calibration device for radar angle measurement. The radar includes a radar body and a cover. The radar body includes a receiving antenna. The calibration method includes: acquiring a first phase change, which is determined based on the distance between different receiving antennas; acquiring a second phase change, which includes the phase change caused by the radar body's influence on the reflected wave and the phase change caused by the cover's influence on the reflected wave; calculating the sum of the first and second phase changes to obtain a phase calibration value in the echo direction; and calibrating the phases to be calibrated measured in multiple echo directions based on the phase calibration value to obtain multiple calibration data. This application solves the problem that traditional radar angle measurement calibration methods do not consider the influence of the radar cover on the angle measurement accuracy by calibrating the radar body and the cover as a whole.

The application discloses a sonar-based real-time calculation method and system for displacement of an oil cylinder, relates to the technical field of hydraulic equipment measurement and control, and is used to solve the problem of decreased displacement calculation accuracy of a long-stroke oil cylinder under complex working conditions; before the oil cylinder is put into use, a piston rod (4) is driven to move point by point at constant steps, a sonar pulse is emitted at each step position, echo waveforms, time stamps and position indexes are recorded, oil temperature is collected and sound velocity is converted, and a binding data table is established. Subsequently, multiple echo waveforms are analyzed, features are extracted, amplitude change rates, peak drift rates and envelope distortion rates are calculated, wave fluctuation abnormal values are generated and sorted, and a main step position is selected to establish a comprehensive feature vector. The comprehensive feature vector is matched in real time, displacement is calculated in combination with real-time sound velocity, and displacement data is smoothed through Kalman filtering and a time window. In the maintenance stage, the piston rod (4) is advanced to the limit position, features are re-collected and updated, and synchronous correction of the feature chain is completed.

The invention discloses an automatic detection system for the thickness of a wandering star wheel based on an ultrasonic probe, and relates to the technical field of semiconductor grinding process detection. The probe with a flexible sealing structure is arranged, and residual liquid on the surface of the wandering star wheel is utilized to form a micro liquid cavity to realize near-dry coupling; the probe is controlled to measure at a plurality of preset positions, and comprehensive thickness data is obtained by combining the rotating station; and the signal processing module is adopted to carry out filtering, multi-time echo average calculation and temperature compensation on the echo signal so as to obtain a high-precision thickness value, the wear state is judged according to fixed and dynamic threshold values, and automatic and high-precision online detection and early warning of the thickness of the wandering star wheel are achieved.

This application provides a vehicle position determination method, apparatus, radar, and storage medium. The method includes: acquiring M-frame echo signals corresponding to a radar with a frame length of M frames; wherein each echo signal in the M-frame echo signals includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by a vehicle on a target road, and the target road is the road detected by the radar; determining the lane where the vehicle is located on the target road in each echo signal based on the M-frame echo signals; if the lane where the vehicle is located on the target road includes a first lane and an adjacent lane of the first lane, calculating the probability values ​​of the vehicle being in the first lane and the adjacent lane in each echo signal based on the M-frame echo signals; wherein the first lane is the lane where the vehicle is located as determined based on the previous echo signal from the radar; and determining the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each echo signal. This application can accurately determine the vehicle position.

The application discloses a kind of based on magnetic resonance auxiliary ablation treatment method and device, method includes: detecting the current operation process of tumor ablation operation;When detecting preoperative simulation, scan image is obtained based on three-dimensional magnetic resonance scanning, and organ region and tumor region are segmented, to assist in generating optimal probe strategy;When detecting intraoperative navigation, real-time magnetic resonance scanning is carried out in the process of probe insertion, current magnetic resonance image is obtained, and probe tip, probe angle and tumor coordinates are identified, to assist probe to reach tumor;When detecting intraoperative thermometry, magnetic resonance sequence scanning is carried out in the process of probe ablation, multiple echo magnetic resonance image is obtained, and current temperature distribution and thermal ablation range are displayed in real time until tumor is completely inactivated.

The application discloses a kind of fast high-resolution multi-parameter quantitative magnetic resonance imaging method and system, comprising: design fast high-resolution multiple echo imaging pulse sequence;Determine the sampling parameter of pulse sequence;Construct the deep neural network for multi-parameter quantitative magnetic resonance image reconstruction;Generate the training sample of deep neural network;Using training sample, the trained deep neural network is obtained by training deep neural network;Using pulse sequence is scanned under the set sampling parameter to entity imaging object, and the k space data of entity imaging object is obtained;The k space data of the entity imaging object is preprocessed, and the image domain data of the entity imaging object is obtained;The image domain data of the entity imaging object is input into trained deep neural network and is reconstructed, and high-resolution multi-parameter quantitative magnetic resonance image is obtained.The application can realize fast high-resolution multi-parameter quantitative magnetic resonance imaging, and can resist the image distortion caused by main magnetic field inhomogeneity.

The application relates to an ultrasonic imaging method, device, electronic equipment and computer storage medium. The method comprises the following steps: acquiring positions of multiple transmitting focal points in a target imaging area; the multiple transmitting focal points are located at multiple depths in the target imaging area; controlling each transmitting element in multiple transmitting elements of a transducer to emit a first beam based on the positions of the multiple transmitting focal points; obtaining multiple echo signals based on multiple first beams; processing the multiple echo signals by using a back-projection beam synthesis algorithm to obtain an ultrasonic image. The multiple echo signals solve the problem that an ultrasonic image obtained by combining a traditional focused transmission method with a back-projection beam synthesis algorithm forms an image dark area, thereby affecting the quality of the ultrasonic image.

The application relates to the technical field of radar ranging, and discloses a radar ranging method, a radar ranging device and a radar level gauge.The method comprises the following steps: receiving multiple echo signals reflected by a ranging target, superimposing the multiple echo signals to obtain superimposed echo signals; screening multiple target spectrum lines from the spectrum of the superimposed echo signals; obtaining multiple interpolation points based on the multiple target spectrum lines and calculating an initial distance from the ranging target; screening multiple target interpolation points from the multiple interpolation points based on the initial distance; performing cubic spline interpolation based on the multiple target interpolation points to obtain a cubic spline interpolation function; and substituting the initial distance into the cubic spline interpolation function to obtain a target distance.The application can significantly suppress noise and improve the signal-to-noise ratio by superimposing multiple echo signals reflected by a ranging target, and can realize efficient and accurate radar ranging by adopting double interpolation of local fine Rife interpolation and globally optimized cubic spline interpolation.

The invention discloses a forest sample plot vertical layered vegetation coverage estimation method, which comprises the following steps of S10, acquiring laser radar point cloud data and optical image data of a target plot, and performing preprocessing; s20, vertically layering the laser radar point cloud data, respectively extracting the uppermost point cloud of each vegetation layer in a visible and sheltered region based on the first echo and the multiple echoes, and calculating the initial projection area of each layer according to the extracted uppermost point cloud; s30, fusing the optical features with the point cloud structure features, constructing a vegetation layer projection area correction model, and correcting the initial projection area of the vegetation layer by using the model to obtain a corrected projection area; and S40, establishing a quantitative conversion model of the two-dimensional FVC and the three-dimensional FVC based on a geometrical optical model and a clearance rate theory. According to the method, the dependence on point cloud classification precision is overcome, the estimation precision of the FVC of the under-forest vegetation, especially the herbaceous layer, is remarkably improved, and the method has the advantages of being clear in physical mechanism and high in adaptability.

This invention discloses a method and system for detecting bonding defects in bridge steel plates based on dual-mode sequential ultrasonic C-scan, belonging to the field of non-destructive testing technology for concrete bridge structures. The method includes ultrasonic scanning of the steel plate-adhesive interface, the interior of the adhesive layer, and the adhesive-concrete interface to determine void defects. For the steel plate-adhesive interface, a local bright area identification and attenuation rate threshold comparison method in multiple echo mode is used. First, a gate is set to acquire C-scan images; if a bright area is present, it indicates a local void, which is quantified; if no bright area is present, the attenuation rate is calculated to determine the overall state. Based on this, a defect depth localization method in single echo mode is used for the interior of the adhesive layer and the adhesive-concrete interface. A second gate is set to acquire C-scan images, and the defect type is determined based on the position of the reflected signal. This solves the problems of existing technologies, such as the inability to identify three types of defects, the inability to achieve depth localization and quantification of defects, low detection efficiency, and high subjectivity.

This application relates to the field of meteorological data processing technology, specifically to a method, electronic device, and storage medium for identifying severe convective weather using radar echo images. This application constructs a three-dimensional radar echo image of the target space through multi-elevation angle stereo scanning of radar. It then utilizes a three-dimensional convolutional neural network to extract and analyze multiple echo intensities, radial velocities, and velocity spectral widths contained in the three-dimensional radar echo image, outputting three-dimensional features such as echo hangs, bounded weak echo areas, and mesoscale cyclones upon which the confirmation of severe convective weather is based. This application can identify complex weather phenomena such as severe convection with high accuracy, providing technical support for meteorological station forecasters in nowcasting.

This application discloses a target recognition system and method based on hybrid active-passive imaging. On one hand, it encodes waveforms of multiple echo signals acquired by multiple millimeter-wave radars using a first convolutional neural network to obtain multiple first feature matrices, and constructs these first feature matrices into a three-dimensional first feature map along the channel dimension. On the other hand, it encodes multiple images acquired by multiple cameras using a second convolutional neural network to obtain second feature matrices, and arranges these second feature matrices along the channel dimension to construct a three-dimensional second feature map. Then, it fuses the first and second feature maps to identify the target. This system integrates active imaging from multiple millimeter-wave radars and passive imaging from multiple cameras to perceive the target from different perspectives, thereby improving the accuracy of target recognition.