137 results about "Envelope (radar)" patented technology

Exemplary methods, systems, apparatus, and computer programs are disclosed for an unmanned aerial system (UAS) inspection system that includes an unmanned aerial system and analysis system for exterior building envelopes and energy performance evaluation and simulation. The UAS can autonomously and systematically collect data for a building's exterior using a payload comprising (i) nondestructive testing (NDT) sensors configured for imaging (visible, infrared, or more) the building and (ii) one or more multi-spectral sensors (LiDAR, ultrasound, radar, or more). The acquired sensor data are provided to an analysis system comprising computer vision (CV) and signal processing modules configured to analyze the acquired data to i) identify building objects (doors, windows, rooftop units, and others) ii) characterize envelope properties (components, heat resistivity, or others) and 3) identify initial thermal anomalies (thermal bridges, physical defects, or infiltration / exfiltration) in a processing pipeline.

The invention discloses an unmanned aerial vehicle cluster cooperative control system and method, and relates to the technical field of unmanned aerial vehicle cluster control, and the system comprises a multi-source sensing unit, an integrated laser radar, an RGB-D camera and a millimeter wave radar array, and is used for generating a centimeter-level precision three-dimensional map and tracking a dynamic obstacle in real time; the collaborative decision-making unit comprises an artificial intelligence prediction module which is used for predicting a collision point based on the movement state of the obstacle; the safety space construction module is used for generating a dynamic safety sphere according to the formation envelope size and the obstacle volume; the artificial intelligence correction module is used for constructing a safety section and generating an optimization path; and the dynamic communication unit is used for carrying out cluster data interaction by adopting hybrid networking of 5G and LoRa adaptive switching. The unmanned aerial vehicle cluster can be used as a whole to avoid obstacles, the original forms of the unmanned aerial vehicles are synchronously kept, and it is guaranteed that multiple unmanned aerial vehicles in the cluster do not collide.

The invention relates to a robot path planning method based on multi-sensor fusion and free space topology composition, and belongs to the technical field of robot autonomous navigation. The method comprises the following steps: firstly, fusing laser radar and millimeter wave radar data, constructing multi-modal point cloud data, extracting a three-dimensional obstacle boundary by combining depth and normal vector mutation features, and generating a three-dimensional obstacle map and a free region tree; according to the constructed space model, factors such as energy consumption, dynamic obstacles, path smoothness and the like are integrated, target selection weights are dynamically regulated and controlled, and self-adaptive screening of intermediate navigation targets is achieved. And based on the intermediate navigation target, generating a safe trajectory satisfying dynamic constraints by adopting geometric-dynamic dual-mode fusion modeling, and enhancing the feasibility and robustness of the trajectory through trajectory envelope optimization and pre-execution fault-tolerant control. The method can be widely applied to autonomous navigation systems such as mobile robots and unmanned vehicles, and has good environment adaptability and path execution stability.

The invention provides a nonlinear amplitude-phase error correction method and device suitable for broadband FMCW radar imaging. The method comprises the following steps: establishing a frequency modulated continuous wave radar difference frequency signal model containing a nonlinear error; correcting the amplitude error by adopting an envelope normalization correction method; estimating the high-order polynomial phase error by adopting a method of combining a phase unwrapping recursive least square method and an OShea optimization strategy to obtain a high-order polynomial phase parameter; estimating the periodic multi-sine phase error by adopting a method of combining a MUSIC algorithm and a trust region algorithm to obtain a periodic multi-sine phase parameter; and based on estimation results of the high-order polynomial phase parameters and the periodic multi-sine phase parameters, phase error correction is carried out by adopting a time domain resampling method. The device comprises a nonvolatile memory in which the executable code is stored and a processor, and is used for implementing the method. According to the technical scheme of the invention, the problem that the existing method is generally insufficient in noise immunity can be solved.

The invention belongs to the technical field of radar signal processing, and discloses a sea surface small target detection method based on optimized characteristic mode decomposition, which comprises the following steps: S1, acquiring to-be-detected signal data; s2, decomposing an original signal into a plurality of modal components by using FMD, and selecting an envelope spectrum entropy as a fitness function; s3, performing global optimization on the fitness function in the FMD by using an SOS algorithm; s4, introducing a PSO algorithm to carry out local optimization on key parameters of the FMD; s5, components with low envelope spectrum entropy values and correlation coefficients larger than a threshold value are reserved; s6, extracting an envelope spectrum entropy and frequency band energy ratio feature from the screened modal components, introducing a Gini coefficient as a weighting factor, and constructing a GSEBE joint feature; and S7, inputting the entropy value of the envelope spectrum into a DELM classifier with a controllable false alarm, and realizing target detection based on comparison between a predicted value and a judgment threshold. According to the invention, the capability of distinguishing sea clutters and target echoes is enhanced, and more accurate classification detection is realized.

The invention discloses a lunar radar horizon tracking method based on a dynamic search center, and solves the problems that an existing method is high in dependence on artificial experience and low in processing efficiency, and the false horizon misjudgment rate is high due to lunar soil non-uniformity interference. Comprising the following steps: performing Hilbert transform on a radar signal to extract an envelope; based on historical horizon data, predicting a dynamic search center of a current channel through Gaussian weighted average and determining a search window; screening local maximum value points in the window as candidate points, and calculating signal intensity, smoothness and edge direction scores of the candidate points; selecting an optimal candidate point as a horizon position through multi-feature linear fusion; and according to the lunar soil interface form and the signal-to-noise ratio dynamic adjustment parameters, tracking and outputting a final horizon path one by one. According to the method, historical path constraints and local signal features are fused, the identification precision and robustness of the lunar soil layered interface in the complex electromagnetic environment are remarkably improved, and the method is suitable for radar data processing of lunar exploration tasks such as Chang'e 4 and the like.

The invention discloses an unmanned aerial vehicle channel inspection path optimization method based on dynamic environment perception, and relates to the technical field of unmanned aerial vehicle intelligent path planning. Comprising the following steps: establishing a three-dimensional environment model based on channel geographic information data and surveying and mapping point cloud data, and generating an initial routing inspection path set with a coverage range meeting requirements; predicting and generating an obstacle envelope sequence changing along with time by using a dynamic obstacle trajectory collected by an airborne radar and a camera, performing space-time superposition calculation on the obstacle envelope sequence and the initial inspection path, and removing path fragments conflicting with a future obstacle movement range to obtain an inspection path set after obstacle avoidance correction; and according to elevation information in the three-dimensional environment model, predicting a local area and a spatial range in which communication shielding may occur in the inspection path of the unmanned aerial vehicle, carrying out secondary correction on a path segment which is about to enter a communication shielding area, and outputting a corresponding flight height and speed sequence.

The invention discloses an ISAR (Inverse Synthetic Aperture Radar) multi-pulse accumulation cross-correlation distance and phase correction system based on an FPGA (Field Programmable Gate Array). The ISAR multi-pulse accumulation cross-correlation distance and phase correction system comprises an upper computer and the FPGA, the upper computer is used for controlling the inverse synthetic aperture radar system to transmit a signal and receiving an echo signal; performing de-line frequency modulation on the echo signal to obtain an echo signal after pulse compression, and preprocessing the echo signal to obtain a to-be-processed echo signal; quantizing the echo signal to be processed, acquiring a quantized echo signal, transmitting the quantized echo signal to the FPGA, and receiving the distance returned by the FPGA and the echo signal after phase correction; and the FPGA is used for executing a multi-pulse cumulative cross-correlation envelope alignment algorithm to perform alignment processing on the quantized echo signal, obtaining a corrected echo signal and returning the corrected echo signal. The register transfer stage circuit based on the multi-pulse cumulative cross-correlation envelope alignment algorithm is designed based on the FPGA, high-parallelization acceleration based on the multi-pulse cumulative cross-correlation envelope alignment algorithm module is achieved, and the processing speed and efficiency of the algorithm are remarkably improved.

The invention discloses an active layer depth identification method based on an envelope fusion algorithm, and belongs to the technical field of seasonal frozen depth survey. The method comprises the following steps: optimizing survey line arrangement and radar frequency through field survey and ground temperature data, and collecting data by using a ground penetrating radar; performing background removal, gain compensation, band-pass filtering and time-depth conversion preprocessing on the data; then, a gravity center method and an edge detection method are adopted to extract a bottom interface track, and noise and abnormal values are effectively suppressed according to self-adaptive weighted fusion of signal definition and continuity; and finally, carrying out cross validation and error correction by taking the earth temperature 0 DEG C isotherm depth as a reference, outputting a continuous and smooth interface fusion curve with centimeter-level precision, and calculating the depth of an active layer. According to the method, the high-efficiency and lossless advantages of the GPR are kept, meanwhile, the limitation of traditional interpretation precision is broken through, and a practical technical scheme which can be directly used for designing parameter values is provided for engineering investigation of the permafrost region.

The invention relates to the technical field of radar imaging, and discloses a low signal-to-noise ratio envelope alignment algorithm for sea target ISAR imaging by a synthetic aperture radar, and the algorithm comprises the steps: transmitting a linear frequency modulation signal to a sea target through a synthetic aperture radar system, and determining an echo signal path; acquiring real-time echo data of the echo signal based on the sub-data acquisition time node; calculating a first echo signal change coefficient according to the first real-time echo data; calculating a second echo signal change coefficient according to the second real-time echo data; calculating an echo signal change coefficient based on the first echo signal change coefficient and the second echo signal change coefficient; according to the method, the rotation angular velocity of the echo signal is optimized according to the change coefficient of the echo signal, the optimized rotation angular velocity of the echo signal is obtained, and envelope alignment is carried out, so that the low-signal-to-noise-ratio envelope alignment precision of sea target ISAR imaging can be ensured, real-time monitoring of the sea target is realized, the image definition and resolution are effectively enhanced, and the sea target ISAR imaging quality is ensured.

The invention relates to the technical field of radars, in particular to a weather radar distance resolution calibration method and system. The method comprises the following steps: collecting oversampling original baseband I / Q data of a point target in a plurality of continuous pulse periods; determining a pulse signal-to-noise ratio, and screening out effective pulses according to a threshold value; carrying out sub-sampling stage time alignment on the effective pulses based on cross-correlation analysis, and carrying out incoherent averaging on power module values of all the aligned pulses to generate an average pulse power envelope; converting the average pulse power envelope to a logarithm domain, and selecting discrete data points in a main lobe region; according to the discrete data points, a nonlinear least square method is adopted to carry out iterative fitting on the generalized Gaussian mathematical model, and a continuous analytic function describing the pulse envelope is obtained; according to the continuous analytic function, determining a pulse time width when the power is reduced to a peak value of-6dB; and determining the real distance resolution according to the pulse time width. The measurement robustness is improved, and sub-meter calibration precision is achieved.

The invention relates to the technical field of electromagnetic wave detection and imaging, and discloses a radar target echo generation method based on a physical information neural radiation field, which effectively improves the physical consistency of generated echo signals, accurately simulates the energy attenuation characteristics at different observation angles, and improves the radar target echo generation efficiency. The problem of signal completion under the sparse view angle condition is solved. The signal generated by the method is highly matched with measured data in the aspects of amplitude distribution, phase continuity and energy envelope form, a reliable data basis is provided for radar target identification and feature analysis, and the perception capability of a network on target geometric details is enhanced through high-dimensional position coding. Therefore, the generated echo signal can accurately reflect the spatial distribution characteristics of the scattering center. Meanwhile, due to the introduction of the multi-frequency coding sequence, the network can adaptively capture electromagnetic scattering characteristics under different scales, and a reliable technical means is provided for echo generation of a complex target.

The invention relates to a method for measuring soil moisture content based on coupling of a ground penetrating radar early signal average amplitude envelope (AEA) method and an autoregressive moving average power spectrum (ARMA) method, and belongs to the field of soil moisture content measurement, and the method comprises the following implementation steps: (1) researching the relationship between the early signal average amplitude envelope and the soil moisture content; (2) researching the relationship between a radar signal power spectrum below an early signal time window and the soil moisture content, and exploring the effective detection depth of the AEA method for inverting the soil moisture content; (3) calculating a radar signal power spectrum by adopting ARMA (autoregressive moving average), and preferably selecting attributes which are closely related to the soil moisture content and are mutually independent according to a fitting relation between each attribute of the power spectrum and the soil moisture content and a cross-correlation relation among the attributes; (4) combining the effective detection depth of the AEA method, and selecting a proper Gaussian window to divide the radar signal to obtain power spectrums of different depths; and (5) inverting the soil moisture content according to the relationship between each power spectrum attribute and the soil moisture content obtained by BP neural network training. According to the method provided by the invention, nondestructive detection of the field scale soil moisture content can be realized, detection of the soil moisture content in the whole detection range of the ground penetrating radar can be realized, and the error of the moisture content is less than 1%.

The invention discloses a wide-angle staring SAR moving target trajectory reconstruction method and device based on a Gauss-Newton method. The method comprises the following steps: carrying out sub-aperture division on an original radar echo signal; performing two-dimensional compression on the original echo signal of each channel in distance and azimuth dimensions to obtain a distance-Doppler domain echo of each channel; the distance-Doppler domain echo is preprocessed in the distance-Doppler domain; based on the preprocessed distance-Doppler domain echoes, the phase history and envelope of the moving target are extracted, and the radial speed of the moving target is estimated; estimating each order of phase parameter in the extracted phase history by adopting a maximum likelihood algorithm; based on the relation between the phase parameter of each order and the motion parameter, obtaining the motion parameter of the motion target; obtaining a rough motion track reconstruction result based on the motion parameters of the motion target; segmenting the rough movement track of the moving target to obtain the accurate reconstruction position of the moving target of each segment; and splicing the reconstruction positions to obtain a complete motion trail reconstruction result.

The invention discloses a ground penetrating radar adaptive gain method comprising the following steps: S1, selecting a to-be-gained radar data profile, and obtaining the overall attenuation trend; s2, acquiring an analysis signal; s3, calculating the envelope of each column of signals and the average value of each row of the envelope matrix; s4, fitting an average value of each row of the envelope matrix according to a least square method and a model function to obtain an attenuation coefficient; and S5, obtaining a gain coefficient through the attenuation coefficient, and gaining each column in the radar data profile in the step S1 based on the gain coefficient. The method has the beneficial effects that the gain process and the calculation method have a good gain effect on original data acquired by ground penetrating radars with different frequencies under different working conditions, and parameter setting is not needed, so that the signal-to-noise ratio and the image definition of radar signals in the whole effective depth range are improved.

The invention discloses a multi-channel multi-frame signal accumulation detection method for a distributed coherent MIMO radar, and is applied to the technical field of radars. The method aims to solve the problem that when distributed coherent MIMO radar echo signals are accumulated, due to space-variant characteristics of target echo signal envelopes and phases between different channels and time-variant characteristics of target echo signal envelopes and phases between different frames, multi-channel and multi-frame coherent accumulation cannot be achieved. Firstly, signal accumulation in channels is realized by utilizing generalized Radon-Fourier transform (GRFT), and a multi-channel accumulation method is designed by fully utilizing output characteristics of the GRFT and a topological structure of a radar system so as to compensate difference of envelopes and phases of target signals among different channels and further realize target energy coherent accumulation among the different channels. Finally, a multi-frame accumulation processing method is provided, envelope and phase differences among multi-frame echo signals are corrected and compensated, and therefore multi-channel multi-frame coherent accumulation of the echo signals is completed, and the target detection performance of the radar is remarkably improved.

The invention provides a translation compensation method for an inverse synthetic aperture radar image of a non-cooperative target, and relates to the technical field of radar signal processing and radar imaging, and the method comprises the steps: carrying out the calculation of a target motion and a radar echo signal based on the inverse synthetic aperture radar image of the non-cooperative target, and obtaining a receiving signal; filtering the received signal to obtain a high-resolution range profile sequence; obtaining a motion offset prediction model by using a spatial feature extraction module and a time sequence decoding module; processing the high-resolution range profile sequence by using the trained motion offset prediction model to obtain a translation offset estimation sequence; and constructing a translation compensation item by using the translation offset estimation sequence, performing translation compensation on the compressed echo to obtain a translation compensation result, and completing envelope and phase joint compensation and inverse synthetic aperture radar imaging. According to the method, the problem of translational motion compensation caused by uncertainty and complexity of a non-cooperative target motion mode is solved.

The present application provides a pulse detection method for radar signals, which relates to the field of digital signal technology. The method includes: obtaining a digital time-domain signal corresponding to the radar signal, calculating the amplitude of the digital time-domain signal to obtain the signal amplitudes of each sampling point on the digital time-domain signal, performing a delay process on the signal amplitudes of each sampling point for a preset number of clock cycles, using the signal amplitudes of each sampling point after the delay to perform envelope detection on the digital time-domain signal to obtain the envelope signal of the digital time-domain signal, performing time-domain alignment on the digital time-domain signal and the envelope signal according to a preset number of clock cycles, finally calculating the pulse width of the digital time-domain signal based on the envelope signal after time-domain alignment to obtain the signal pulse width of the digital time-domain signal, calculating the signal amplitude of the digital time-domain signal according to the envelope signal after time-domain alignment and the signal amplitudes of each sampling point, and performing envelope detection on the digital time-domain signal, which can improve the detection accuracy of the signal pulse width and the signal amplitude.

The invention discloses a ground-based radar space object long-time energy accumulation method based on an orbital element model, and the method comprises the following implementation steps: 1, building an orbital element parameter space, and mapping the grid points of the parameter space into the distance between a target and a radar; and step 2, calculating an envelope position and a phase which need to be compensated according to the mapped distance history at each parameter space grid point. And step 3, compensating a corresponding phase for the echo signal after pulse compression along the calculated envelope position, and then performing coherent superposition, thereby realizing long-time coherent accumulation of echo energy. According to the method, the orbital elements are adopted to construct the parameter space, energy accumulation is carried out in the parameter domain, due to the fact that the orbital elements can better represent the actual motion of a space object, the energy accumulation effect can be improved, meanwhile, the orbital elements are small in parameter space dimension, and the algorithm calculation amount can be greatly reduced.

The application provides a PMEPR optimization method of a large-bandwidth OFDM radar communication integrated waveform, and the method is based on a reserved subcarrier method, an l p norm is introduced to remodel PMEPR under a high reservation rate as a target function that can be used for gradient analysis, the PRP conjugate gradient descent method is used to efficiently and quickly solve the target function, and the radar communication integrated waveform with good PMEPR reduction performance is obtained. The application has an important role in the actual application of the radar communication integrated waveform.

The present application provides a nonlinear amplitude and phase error correction method and device suitable for broadband FMCW radar imaging. The method includes: establishing a frequency modulated continuous wave radar difference frequency signal model containing nonlinear errors; correcting the amplitude error using an envelope normalization correction method; estimating the high-order polynomial phase error using a method combining a phase unwrapping recursive least squares method with an O'Shea optimization strategy to obtain high-order polynomial phase parameters; estimating the periodic multi-sine phase error using a method combining a MUSIC algorithm with a trust region algorithm to obtain periodic multi-sine phase parameters; based on the estimation results of the high-order polynomial phase parameters and the periodic multi-sine phase parameters, using a time domain resampling method to perform phase error correction. The device includes a non-volatile memory storing executable code and a processor for implementing the above method. The technical solution of the present application can solve the problem of insufficient noise resistance that is common in existing methods.

The invention discloses a rotor unmanned aerial vehicle micro-motion parameter estimation method, which comprises the steps of performing pulse compression on radar echoes of a rotor unmanned aerial vehicle, and taking slow time data of a distance envelope peak value position as an observation signal of sparse reconstruction; constructing a dictionary matrix based on observation signals, and converting a micro-Doppler parameter estimation problem into a sparse reconstruction problem; and on the basis of the dictionary matrix, utilizing a Bayesian sparse reconstruction algorithm to estimate the rotation frequencies of a plurality of rotors of the rotor unmanned aerial vehicle. The method is applied to the field of radar signal processing, can perform parameter estimation on a plurality of micro-Doppler signals in an aliasing state in a noise environment, has the advantages of high estimation precision and good robustness, can be widely applied to searching and monitoring of air rotor type unmanned aerial vehicle targets, and has wide application prospects. The method can be effectively suitable for micro-motion parameter estimation of the hovering unmanned aerial vehicle under the low signal-to-noise ratio.

The invention discloses a radar signal gain method. The method comprises the following steps: S1, acquiring data bscan and preprocessing the data bscan; s2, absolute values of all the numerical values are obtained, and the maximum value is solved; s3, linearly connecting the maximum values to form an extreme value envelope A (i), performing inverse function on the extreme value envelope A (i) to obtain a gain function, and multiplying the original bscan by the gain function; s4, the maximum value hmax of the absolute value of each row is taken and connected to obtain a function H (t), Hilbert transform is carried out on H (t), and the signal is analyzed to take the absolute value to obtain an envelope signal; and S5, obtaining a coefficient M, taking the reciprocal of the A (t), multiplying the reciprocal by the coefficient M to obtain a gain function Wm ', and processing the two-dimensional data by using the gain function. According to the method, envelope gain is added when ground penetrating radar signals are processed, extreme value envelope is taken from each row of bscan, a gain function is obtained through Hilbert transformation, then the bscan is processed through the gain function, new bscan is obtained, undifferentiated amplification of all signals is prevented, strong gain is achieved for echo signals, and the adaptability and pertinence of an algorithm are improved.

The invention discloses a radar electronic countermeasure intermediate frequency data pulse batch identification and edge detection method based on a GPU, and the method comprises the steps: quickly searching a pulse segmentation flag bit in batch intermediate frequency data through the GPU, and generating a pulse segmentation index list; establishing a Hash mapping table from the intermediate frequency data to the pulse segmentation index list so as to facilitate subsequent pulse envelope extraction and edge detection; in the pulse envelope extraction process, extracting envelope data according to pulse separation information by utilizing GPU parallel calculation; a one-dimensional edge detection mode is adopted to detect the upper edge and the lower edge of the pulse so as to determine the starting position and the ending position of the pulse. According to the method, the parallel computing capability of the GPU is fully utilized, the efficiency and the real-time performance of radar electronic countermeasure intermediate frequency data processing are improved, efficient pulse recognition and edge detection are achieved, the method is suitable for processing large-scale data, and the combat requirement of a high-performance radar electronic countermeasure system can be met.

The invention provides a high-speed terahertz radar coarse speed inversion and fusion fine speed estimation method and device. Each slow time signal corresponding to an obtained full-aperture terahertz echo signal is uniformly divided into # imgabs0 # sub-aperture signals in the distance direction; performing distance pulse pressure processing on each sub-aperture signal to obtain # imgabs 1 # sub-aperture pulse pressure signals, wherein # imgabs 2 # is the total number of slow time signals; screening out sub-aperture pulse pressure signal samples from the sub-aperture pulse pressure signals; determining a coarse velocity according to the pulse pressure signal sample of each sub-aperture; performing coarse velocity error compensation on the full-aperture terahertz echo signal to obtain a coarse velocity error compensated signal, and determining a distance differential velocity according to the compensated signal; compensating the full-aperture terahertz echo signal to obtain a signal after secondary speed compensation; determining an envelope error velocity and a Doppler velocity according to the signal after secondary velocity compensation; according to the distance differential velocity, the envelope error velocity and the Doppler velocity, the precise velocity of the radar is estimated, and the estimation precision is improved.

Directional antenna for a motor vehicle radar system includes a housing comprising a reflecting envelope comprising an inner volume forming a reflecting cavity for electromagnetic waves, characterized in that the reflecting envelope is bounded by a set of walls including a first transmission wall comprising an electromagnetic wave transmission zone between the inside and the outside of the housing; a second guide wall, opposite the first wall, able to guide electromagnetic waves in a privileged direction; and a set of reflective lateral walls connecting the first and second walls, wherein each lateral wall is able to reflect the electromagnetic waves within the reflective cavity.

The invention discloses a distributed radar target detection method and device based on space-time unified compensation, and the method comprises the steps: determining a slope distance process expression between each radar in a distributed radar and a target object for each echo signal group; based on the slant range process expression, respectively constructing an envelope range walking correction function and a frequency domain phase compensation function between radars; according to the to-be-solved parameters of the target object and the parameters of the target radar corresponding to the echo signal group, respectively constructing a range walk correction function and a time domain phase compensation function in each radar; constructing a space-time two-dimensional compensation function according to the envelope range walk correction function, the frequency domain phase compensation function, the range walk correction function and the time domain phase compensation function; the phase-coherent accumulation echo signal expression constructed according to the space-time two-dimensional compensation function and the to-be-solved parameters of the target object is solved, the parameter target value of the target object can be obtained, and the target detection accuracy of the distributed radar is improved.

A method of analyzing and correcting a complex dynamic waveform, such as a radar wave or communication wave. The method comprises dividing a complex waveform into its real and imaginary components, then separately analyzing each such waveform in a dedicated neural to determine respective real and imaginary loss functions as the difference between the actual characteristics and desired characteristics of the mean squared error and at least one of frequency-domain power, time-domain envelope, and frequency-domain phase. The real waveform and imaginary waveform are independently corrected, then recombined into a single corrected complex waveform. These differences are fed into a neural network to improve prediction correction to bring the actual waveform closer to a benchmark waveform. The method of the present invention displays increased accuracy over the prior art without increased computing time or sacrificing notch depth.

The invention provides a same-measuring-point rockfill material grading upper envelope line prediction method and device, electronic equipment and a storage medium, and relates to the technical field of engineering geophysical exploration, and the method can realize the nondestructive detection of the initial quality of each particle group in a same-measuring-point rockfill material by using a surface image and a ground penetrating radar profile map in combination with a standard radar map. And the grading upper envelope line is calculated by adopting the maximum dry density, so that the obtained grading upper envelope line is closer to the real crushing and grading evolution state of the rockfill material. Moreover, the method adopts a nondestructive testing mode to predict the grading upper envelope line of the rockfill material at the same measuring point, the amount of data required to be detected is small, the calculation model is clear, the prediction efficiency can be improved, the prediction cost can be reduced, the influence on the construction progress of the dam can be avoided, the interference on the grading upper envelope line caused by introduction of human factors can be avoided, and the prediction accuracy is improved. And the accuracy of the grading upper envelope line is improved.

The present invention discloses a three-frequency-in-one transceiver assembly for a meteorological phased array radar, and specifically relates to the technical field of meteorological radars, including a phased array antenna substrate, wherein the upper end surface of the phased array antenna substrate is provided with a plurality of TR structures. The present invention realizes L-band wind profile detection and transceiver, L-band meteorological satellite reception, and C-band meteorological satellite reception through multi-layer cavity division and same-frequency common cavity design, and the overall component size envelope is nearly within 10 cubic centimeters, and each functional cavity design is very reasonable, and the passive network cavity takes into account the resonant natural frequency, and the active circuit cavity takes into account shielding, heat dissipation and other functions. In order to meet the requirements of easy maintenance in the later stage, it is designed as an overall modular design, and all device binding data are stored in an internal calibration data storage chip. If a module needs to be replaced in the later stage due to a fault, it can be directly replaced and automatically matched without recalibrating and calibrating the entire radar system.