69 results about "Multiple echo" patented technology

The invention discloses a liquid information detection method and system based on an ultrasonic technology. The method comprises the following steps: firstly, acquiring ultrasonic multiple echo signals under a preset working condition; the peak information, the time domain characteristic, the waveform characteristic, the phase characteristic and other information of the echo are obtained; secondly, establishing a machine learning model, and inputting feature information such as echo peak voltage, time delay and phase into the machine learning model for training; obtaining a trained machine learning model; and finally, inputting an actually detected ultrasonic echo signal into the trained machine learning model for processing to obtain the liquid information distribution condition of the detected target. According to the method, liquid component identification and high-precision detection of liquid information of different liquid levels are realized through array ultrasonic transducer and echo signal analysis, echo signal characteristics can be quickly mapped to liquid attribute information in combination with a machine learning model, and excellent intelligent processing capacity is shown. The method is high in real-time performance and applicability, can adapt to different liquid types and densities and various environmental conditions, and meets the detection requirements in an industrial environment and the application scene of higher-precision detection.

The invention 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, and the method comprises the steps: obtaining a plurality of echo signal profiles continuously observed by a laser radar, and carrying out the preprocessing of each echo signal profile; for the preprocessed echo signal profiles, sorting the echo signal profiles by using an unsupervised manifold learning sorting method to generate an echo signal profile sequence; wherein the sorting target is that the sum of differences between adjacent echo signal profiles is minimum; and identifying an abnormal echo signal profile in the echo signal profile sequence, performing quality marking on the abnormal echo signal profile, and outputting a signal data set with a quality mark. According to the method, the mode of the normal signal can be adaptively learned from the data, so that intelligent and automatic anomaly detection is realized, a complex anomaly mode can be effectively identified, and the defects that a traditional method depends on artificial experience and is poor in adaptability and low in efficiency are overcome.

The present invention relates to a radar multiple echo classification method based on the combination of oversampling and ensemble learning, and relates to the technical field of radar signal processing. The method of the present invention extracts the amplitude and phase information in the radar echo data, and uses ADASYN adaptive synthetic oversampling in the data preprocessing stage to balance the number of samples of various categories of radar multiple echoes, so as to improve the recognition rate of the subsequent established classifier for the echo categories with fewer samples. The random forest algorithm in ensemble learning is selected for classification to avoid overfitting. Applying this classification method to radar signal processing can effectively distinguish the multiple echoes received by the radar, and further screen out the target traces of interest to the current radar, improving the tracking performance of radar data processing.

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.

The invention provides a method, a device, equipment and a medium for improving the angle measurement accuracy of a millimeter-wave radar, and the method comprises the steps: driving the millimeter-wave radar to rotate at a constant speed through a control rotary table, and enabling a to-be-detected target to be located at different detection angles of the millimeter-wave radar. And controlling the millimeter-wave radar to perform detection every preset time period, and obtaining multiple echo data during multiple times of detection. And processing each piece of echo data to obtain a plurality of pieces of phase information. And performing fitting based on the multiple pieces of phase information and the turntable angle corresponding to each piece of phase information, and determining an antenna phase center distance and an initial phase difference. And determining a steering vector based on the antenna phase center distance, the initial phase difference and the plurality of preset detection angles. And determining a target detection angle of the to-be-detected target based on the steering vector and the phase information. And based on the target detection angle and the turntable angle corresponding to the target detection angle, determining a detection angle error so as to compensate the angle of the millimeter wave radar detection target based on the detection angle error.

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 provides a target reconstruction method and system based on passive sensing radar echo signals, and the method comprises the steps: obtaining a passive sensing radar echo signal set of a target scene, the passive sensing radar echo signal set comprising a plurality of echo signal sequences; performing signal preprocessing operation on the passive sensing radar echo signal set to obtain a preprocessed radar echo signal set; multi-level feature extraction operation is executed on the preprocessed radar echo signal set, a multi-dimensional state feature set of the target object is generated, and the multi-dimensional state feature set comprises scattering characteristic features, motion correlation features and environment interference suppression features; and calling a pre-trained target state analysis model to carry out state transition modeling processing on the multi-dimensional state feature set, generating a reconstructed state vector of the target object, and carrying out reverse mapping based on the reconstructed state vector to obtain a geometric parameter set and a motion parameter set of the target object.

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 present application belongs to the field of radar signal processing technology, and in particular relates to an improved tailing multiple echo signal model analysis method. The method comprises: step one, constructing a time domain echo signal model of a pulse laser radar; step two, constructing a single echo signal model based on the time domain echo signal model; step three, constructing a multi-target spot detection model, and determining the target distance and spot ratio coefficient corresponding to each target based on the multi-target spot detection model; step four, constructing a multiple echo signal model based on the single echo signal model, as well as the spot ratio coefficient and target distance of each target. The improved tailing multiple echo signal model analysis method of the present application can provide a technical basis for extracting echo information of multiple targets by analyzing the multiple echo signal model, and can overcome the problems of information loss and low ranging accuracy in pulse laser radar signal processing.

Techniques and systems for motion detection of a logging tool. A system includes a nuclear magnetic resonance (NMR) logging tool configured to perform at least one Carr-Purcell-Meiboom-Gill (CPMG) scan utilizing a plurality of distinct echo times (tE) in conjunction with a single excitation pulse and a single wait time as a multiple echo spacing sequence to acquire NMR logging measurements and a processing system coupled to the NMR logging tool, wherein the processing system is configured to process the NMR logging measurements acquired by the NMR logging tool to determine whether the NMR logging measurements were affected by lateral motion of the NMR logging tool.

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 nuclear magnetic resonance signal noise suppression method and device based on a convolutional neural network. The method comprises the following steps: configuring a CPMG pulse sequence in nuclear magnetic resonance equipment; carrying out nuclear magnetic resonance testing on the shale sample based on the CPMG pulse sequence, setting a plurality of groups of echo intervals by utilizing a multi-time micro-variation echo interval technology, and generating a time-aligned multi-dimensional data set; segmenting a multi-dimensional data set by using a sliding window technology, performing segmented data processing through a pre-trained CNN network, removing noise components and performing signal reconstruction; a reinforcement learning mechanism is introduced, and according to the quality of de-noised echo signals, pulse sequence configuration parameters and a sliding window segmentation strategy are reversely optimized, so that the continuous and stable noise suppression effect is ensured. According to the method, the signal acquisition and processing process is optimized, the interference of noise on the fast relaxation component signal is reduced by using the convolutional neural network, the recognition accuracy of the signal is improved, and technical support is provided for accurate representation of the reservoir.

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 utility model discloses a ranging precision adjusting device applied to a laser radar and the laser radar, and the device comprises a photoelectric conversion module which receives a plurality of echo optical signals, converts the echo optical signals into current signals in sequence, and carries out the gain amplification according to bias voltage signals; the signal processing module is connected with the photoelectric conversion module, receives the current signal and converts the current signal into a voltage signal; the FPGA processing module is connected with the signal processing module, and the FPGA processing module determines the adjustment amount Yn of the bias voltage of the photoelectric conversion module according to the light intensity information of the echo light signal in the nth unit time; the bias voltage Xn = bias voltage Xn-1 + the adjustment amount Yn; and the bias voltage circuit is connected with the FPGA processing module and the photoelectric conversion module and is used for setting the bias voltage signal of the nth unit time according to the bias voltage Xn. According to the utility model, the bias voltage of the photoelectric detector can be adaptively adjusted according to the light intensity level in the environment, so that the ranging precision of the laser radar is higher.

The invention discloses a beam position division method, system and device for phased array radar echo pulse signals and a medium, and relates to the field of beam position division, and the method comprises the steps: obtaining aliasing echo pulse signals of multiple types of phased array radars; constructing a pulse width prior knowledge base; the pulse width priori knowledge base comprises a plurality of pulse width typical value ranges of echo pulse signals; purifying and cleaning the aliasing echo pulse signal according to the pulse width typical value range to obtain echo pulse flows of phased array radars of various models; based on the pulse amplitude dynamic threshold, performing preliminary wave position division on the echo pulse streams of the phased array radars of various models to obtain a plurality of initial wave positions of the phased array radars of various models; and based on the characteristic parameters of the echo pulse signals, carrying out combination and secondary division on the plurality of initial wave potentials of the phased array radars of various models. According to the invention, the accuracy and efficiency of wave potential division are improved.

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 an oil cylinder displacement real-time calculation method and system based on sonar, relates to the technical field of hydraulic equipment measurement and control, and is used for solving the problem that the displacement calculation precision of a long-stroke oil cylinder is reduced under complex working conditions. Before the oil cylinder is put into use, a piston rod (4) is driven to move point by point according to a constant step pitch, sonar pulses are emitted at each step pitch position, echo waveforms, timestamps and position indexes are recorded, meanwhile, the oil temperature is collected, the sound velocity is converted, and a binding data table is established. Then, multiple echo waveforms are analyzed, features are extracted, the amplitude change rate, the peak drift rate and the envelope distortion rate are calculated, fluctuation abnormal values are generated and sorted, and a trunk step position is selected to establish a comprehensive feature vector; the comprehensive feature vectors are matched in real time, displacement is calculated in combination with the real-time sound velocity, and displacement data are smoothly processed through Kalman filtering and a time window. In the maintenance stage, the piston rod (4) is pushed to the limit position, updated features are collected again, and synchronous correction of the feature chain is completed.

The present application embodiment discloses a denoising method for a LIDAR and a LIDAR. The method first obtaining the echo signal corresponding to a pixel unit in a receiving array of the LIDAR; obtaining a target measurement distance and echo feature information based on the echo signal, wherein the echo feature information is an echo amplitude and / or an echo width; obtaining a target noise point threshold based on a pixel position of the pixel unit and the target measurement distance; determining whether the echo signal is a noise signal according to the echo feature information and the target noise point threshold; if so, deleting the echo signal. Different pixel positions or different target measurement distances correspond to different target noise thresholds. The target noise threshold changes with the change of the pixel position or the target measurement distance to effectively remove the noise signals in multiple echo signals received at the pixel position and improve the accuracy of the LIDAR.

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 invention relates to an improved mute multi-gradient echo magnetic resonance imaging system and method. Methods and systems for generating muted multi-gradient echo magnetic resonance images include employing iterative applications of small updates to the magnetic field gradient followed by short non-selective radio frequency pulse excitation, and for free induction decay data acquisition. Updating of the magnetic field gradient allows for a muted self-refocusing pulse sequence. Each magnetic field gradient is based in part on a k-space spoke. A closed k-space trajectory is generated when multiple spokes are cascaded, which results in a self-refocusing pulse sequence. The k-space spokes in the k-space spoke sequence forming the closed k-space trajectory oscillate inside and outside the plane of the frequency space. Subsequent application of the magnetic field gradient allows multiple echo data acquisition.

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 provides a wafer graph processing method, device and equipment, and relates to the technical field of ultrasonic detection. The method comprises the steps that a plurality of echo signals of a plurality of ultrasonic signals sequentially transmitted to a wafer to be detected by target ultrasonic equipment are received, the target ultrasonic equipment comprises a plurality of transducer units which are annularly arranged, and the transducer units are independently and obliquely installed; establishing a reference reflection signal of the cavity structure on the to-be-detected wafer according to the preset reflection characteristics of the cavity structure on the to-be-detected wafer; and generating and displaying a bubble distribution diagram of the wafer to be detected according to the reference reflection signal and the plurality of echo signals. According to the invention, high-precision identification and visual presentation of the bubble defect of the wafer to be detected are realized.

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.

A radar system (600), a mobile device (100), and a radar detection method. A laser module (610) in the radar system (600) generates a multi-wavelength optical signal, a two-dimensional scanner (620) performs two-dimensional scanning using the multi-wavelength optical signal, and receives echo signals within the receiving field of view of the two-dimensional scanner (620). After the wavelength division module (630) performs spectroscopic processing on the echo signals, the detection module (640) converts multiple single-wavelength optical signals into multiple electrical signals, and the processor (650) obtains first point cloud data accordingly. The inclusion of multiple echo signals within a unit receiving field of view of the two-dimensional scanner (620) overcomes the limitation of flight time on the number of point clouds for a single-wavelength optical signal and the limitation of the environmental adaptability of a single-wavelength optical signal, thereby increasing the number of point clouds detected by the radar and increasing the effective information carried in the point cloud data. This is beneficial for improving the detection performance of the laser radar and reducing the safety risks of the autonomous driving process caused thereby.