48 results about "Field transformation" patented technology

The invention provides a passive antenna array beam forming test method and system, and relates to the technical field of beam forming test. According to the method, channel baseline parameters are established in a silencing environment, frequency hopping and channel switching are combined to realize multi-frequency-point synchronous sampling, a reference source and self-polling data are utilized to calculate a mutual coupling correction matrix and a feeder line consistency factor, and weight projection and equivalent aperture field generation are completed without changing physical wiring conditions; further extracting a main lobe direction, a beam width, a side lobe level and a scanning consistency index through far field transformation, and unwrapping and smoothing a frequency-point-crossing phase result; and meanwhile, generating a unique traceability identifier, establishing full-link association between a test condition and a result, and outputting a criterion conclusion. According to the method, the accuracy, efficiency and traceability of passive array beam testing are improved.

Aspects of the present disclosure are directed to triggering object transitions between near-field and far-field regions in an artificial reality environment. For example, the near-field region can be within arm's length for the user, while the far-field region can be greater than arm's length from the user. Objects can be displayed within these regions such that the user can interact with the objects in the artificial reality environment. A field manager can cause a displayed object to transition from the near-field region to the far-field region and / or from the far-field region to the near-field region. The field manager can compare sensed user movements to one or more trigger criteria (e.g., distance threshold(s), velocity threshold(s), etc.) to trigger transition of an object between field regions.

The invention relates to the technical field of data processing, and discloses a cable joint arc multi-physical field simulation method and system. The method comprises the following steps: establishing a defect-containing geometric model, judging according to a temperature gradient change rate and a current rising rate to obtain an adaptive time step length, and carrying out bidirectional coupling iteration on an arc temperature field and a material dielectric parameter based on the time step length to obtain an accumulated damage factor; arranging a virtual temperature detection point to convert the simulation temperature field into a virtual monitoring signal, extracting temperature characteristic parameters and ultrasonic spectrum characteristic parameters, and projecting the temperature characteristic parameters and the ultrasonic spectrum characteristic parameters to a two-dimensional characteristic space to obtain a fault mode fingerprint spectrum. According to the method, adaptive adjustment of the time step length is realized by establishing an arc evolution phase discrimination mechanism, and the problems of low calculation efficiency and insufficient transient characteristic capture caused by a fixed time step length are solved.

The invention discloses a power distribution network fault type diagnosis and section positioning method and equipment, and the method comprises the steps: selecting eight-channel waveforms of a single measurement point of a fault line: three-phase zero-sequence voltage, zero-sequence voltage, three-phase current and zero-sequence current as research and judgment waveforms; based on a fault waveform data set and a batch simulation waveform data set collected by an actual line, a waveform data set with high quality, wide coverage scene and balanced type distribution is generated through a conditional generative adversarial network; each channel of waveform of the fault waveform is subjected to classification complete set normalization, feature region interception and field transformation dimension expansion to form a two-dimensional field matrix, eight groups of two-dimensional matrixes are preprocessed to form eight-channel two-dimensional matrix tensors, and a model training set is formed in combination with fault types and fault section labels; according to the invention, classified identification of the fault type and the fault section of the fault waveform is realized; according to the method, troubleshooting can be accelerated, the power supply reliability of the power distribution network is improved, and technical support is provided for grounding fault diagnosis completely depending on data driving.

The invention discloses a phase-free antenna measurement method, a phase-free antenna measurement system and a storage medium. The phase-free antenna measurement method comprises the following steps: constructing a measurement system comprising an antenna to be measured, a measurement probe, a fixed auxiliary reference antenna and software defined radio; the probe is controlled to move and sample on the scanning plane, and the SDR synchronously collects receiving signals of the probe and the reference antenna; based on the frequency domain transformation result of the two paths of signals, the radiation field amplitude of each sampling point and the relative phase relative to the reference antenna are directly calculated through non-iterative operation, so that complete complex electric field distribution on the scanning plane is reconstructed; and finally, obtaining a far-field directional diagram through near-field-far-field transformation. The fixed reference antenna is introduced to serve as a phase reference, synchronous acquisition and direct calculation are achieved in combination with the SDR, the antenna radiation field can be rapidly and accurately recovered without direct phase measurement or complex iteration in the single scanning plane and single scanning process, and the method has the advantages of being simple in system, high in measurement efficiency and high in signal drift resistance.

The invention discloses a smart watch arrhythmia early warning method and system based on deep learning. The method comprises the steps that firstly, PPG signals are collected through a photoelectric volume pulse wave sensor, and denoising and standardization processing are conducted through an adaptive filtering algorithm; then, the heart beat position is recognized through a wavelet transform peak value detection algorithm, and a heart rate variability feature sequence is obtained; converting the one-dimensional heart rate variability feature sequence into a two-dimensional heart rhythm image by using an improved Gramian angular field transformation algorithm; and training an arrhythmia classification model by adopting a ResNet-50 convolutional neural network to realize automatic identification of different types of arrhythmia. And finally, continuous monitoring and timely alarming are realized through a sliding window technology and an early warning mechanism. The key technical problems of low detection precision, poor real-time performance, high equipment cost, poor user experience and the like in the existing arrhythmia detection technology are effectively solved, and an innovative solution is provided for heart rhythm health monitoring of the intelligent wearable equipment.

This invention provides a method for rapid planar near-field measurement of large-aperture antennas, relating to the field of antenna technology. The method obtains sparse field amplitude and phase information of several sampling surfaces in the near-field radiation region of the antenna under test through large-step uniform sampling. Simultaneously, it samples a finite number of precise field amplitude and phase information points for each sampling surface and obtains the field distribution characteristics by calculating the fluctuation of the amplitude at the sampling points. Based on the sparse field amplitude and phase information and field distribution characteristics of the sampling surfaces, it uses partitioned interpolation and field distribution calibration methods to obtain the initial electric field of each sampling surface. Based on planar wave spectrum theory, iterative numerical calculations are performed on the initial electric field to recover the near-field distribution of each sampling surface. Finally, the far-field radiation characteristics of the antenna are obtained through near-field-to-far-field transformation. This invention can significantly shorten the testing time while obtaining key indicators of the antenna's far-field characteristics, including the normalized radiation pattern main lobe and first sidelobe, 3dB beamwidth, sidelobe level, and axial ratio.

The invention provides a wind wheel device for reducing wind load and wind-induced vibration of a photovoltaic module, and relates to the technical field of structural vibration control, the wind wheel device comprises wind wheel bases arranged on two sides of a photovoltaic panel, the left end and the right end of each wind wheel base are respectively provided with two circular hole grooves, and wind wheel bearings are arranged in the circular hole grooves; the two ends of a wind wheel rotating shaft penetrate through the wind wheel bearings on the two sides respectively, and a wind wheel is arranged on the wind wheel rotating shaft. According to the wind wheel device, flow field transformation caused by passive rotation of the light wind wheel along with wind acts on the surface of the photovoltaic panel, the pressure difference between the upper surface and the lower surface of the photovoltaic panel can be effectively improved, and the vibration phenomenon generated when the photovoltaic panel is subjected to wind loads is reduced; the wind wheel devices are installed on the front edge and the rear edge of the windward side of the photovoltaic panel and passively rotate along with wind through light wind wheels. Flow separation at the windward front edge can be effectively reduced by mounting the front edge, shedding of trailing edge trailing vortex can be effectively reduced by mounting the front edge on the trailing edge, and the influence of flow-induced vibration is further improved.

This invention relates to the field of distribution network fault diagnosis technology, specifically to a method and device for fault line selection in distribution networks based on a multimodal enhancement and hybrid deep learning model. The method includes the following steps: acquiring zero-sequence current and voltage transient waveform data of each line in the distribution network at the time of a fault; performing Gram angle field transformation on the one-dimensional waveform data using a penalized inner product to convert it into two-dimensional GASF and GADF images, respectively, and stitching them together to generate a four-channel E-GAF image; inputting the E-GAF image into a Trans-DenseNet model for fault discrimination, and fusing local-global features by embedding a Transformer encoder layer in the DenseNet to output the final fault line selection result. Compared with existing technologies, this invention can adapt to complex faults such as high resistance and arcing, achieving high-precision fault location and providing reliable support for intelligent fault self-healing in new distribution networks.

The application discloses a kind of deep neural network gas identification method and system based on internet of things electronic nose, gas sample response signal obtained by gas sensor array collection is sent to cloud data center by terminal equipment with sensor array and internet of things module.In the pre-processing of data to microcontroller MCU, gram angle field transformation is carried out, so that the two-dimensional sensor response data received by host computer becomes three-dimensional data that can be input into convolutional neural network after dimensionality increasing, and the gas label is output through classifier, which can represent gas category and concentration grade, realizes the real-time, anti-interference and high detection accuracy of remote monitoring.Gives play to the advantages of strong feature extraction ability, fast model convergence and high recognition accuracy of convolutional neural network.It can be widely applied in environmental detection, industrial production, medical treatment and safety fields.

This invention discloses a method and device for fault type diagnosis and fault segment location in distribution networks. The method includes selecting eight-channel waveforms from a single measurement point on a faulty line: three-phase zero-sequence voltage, zero-sequence voltage, three-phase current, and zero-sequence current as the judgment waveforms. Based on fault waveform datasets collected from actual lines and batch simulation waveform datasets, a high-quality waveform dataset with broad coverage and balanced type distribution is generated through a conditional adversarial generative network. Each channel of the fault waveform undergoes classification and normalization, feature regions are extracted, and then the dimensions are expanded into a two-dimensional field matrix through field transformation. The eight sets of two-dimensional matrices are preprocessed into eight-channel two-dimensional matrix tensors. These tensors, combined with fault type and fault segment labels, form a model training set. This invention enables the classification and identification of fault types and fault segments in fault waveforms. This invention can accelerate fault investigation, improve the power supply reliability of distribution networks, and provide technical support for ground fault diagnosis that relies entirely on data-driven methods.

The invention provides a CSI behavior recognition training method based on meta-learning. The method comprises the following steps: establishing a CSI data acquisition system to obtain a data set; carrying out linear interpolation completion and Hampel filtering noise reduction on the data, and generating a two-dimensional feature map through Grubby angle difference field transformation; based on a task division strategy, dividing the CSI data into a support set and a query set, and constructing a cross-domain small sample learning task; in the model optimization stage, different meta-learning strategies are adopted for cross-domain differences, one meta-learning strategy is Mixup-MAML, Mixup data is introduced in an outer cycle of the MAML to enhance and generate a virtual query set so as to improve rapid adaptation and cross-domain generalization ability, the other meta-learning strategy is MixMeta-SGD, model parameters, learning rates and updating directions are jointly updated under a Meta-SGD framework, and a virtual sample is generated in combination with Mixup so as to enhance robustness; and finally, small sample fine tuning is carried out on the optimized model, final model parameters adapted to the target task are obtained, and the result can be used as input of a subsequent CSI behavior recognition module or a deep network, so that generalization and stability of the system are improved.

The invention discloses a display anti-shake method and system for intelligent riding glasses, and the method comprises the steps: carrying out the time alignment of an angular velocity and an accelerated velocity collected by an inertial measurement unit, and estimating and compensating an offset and scale factor; performing dual-channel adaptive filtering on the inertial data stream; detecting and identifying a glancing or turning intention of the wearer based on an angular velocity threshold value, acceleration abrupt change and short-time pause, and generating a gating coefficient for continuously adjusting the image stabilization intensity; according to the low-frequency attitude component and the gating coefficient, view field transformation and viewport offset used for stabilizing the superposed content are solved; and according to the angular motion state, performing prediction compensation to the display moment on the view field transformation to offset the rendering and display link time delay, taking the relative displacement of the key content of the adjacent frames as stability feedback, and updating offset and parameters on line to realize long-term self-correction. According to the technical scheme of the invention, the readability and security of the superposed information can be integrally improved.

The invention relates to the technical field of digital signal processing and communication data links, in particular to a data link waveform data preprocessing method based on digital operation, which comprises the following steps: acquiring high-speed continuous discrete time sequence data acquired by a data source as original waveform data; a sign bit is extracted, an absolute value is taken, numerical field transformation is carried out by utilizing leading zero detection logic, and linear field data is mapped into approximate logarithm field representation data comprising an order code and a mantissa; dividing the mantissa into a reserved high order and a discarded low order; inputting the approximate logarithm domain representation data into a main addition path of a logarithm domain addition filtering topology to carry out additive operation, and carrying out error compensation on the discarded low bits by utilizing an error compensation lookup table to generate logarithm domain preprocessing data; in combination with sign bits, converting back to a linear domain through anti-logarithm mapping logic, and outputting preprocessed waveform data; according to the invention, dynamic optimal balance between cross-environment processing quality and system resource allocation is realized.

The application provides a flat panel detector image correction method and device, which comprises the following steps: firstly, collecting a bright field image at an initial angle and a bright field image at a plurality of preset swing angles, and processing the bright field image at the initial angle to obtain a gain correction template at the initial angle; then, processing the bright field images at all swing angles according to the gain correction template at the initial angle to obtain a light field conversion coefficient template at each swing angle; obtaining an angle light field conversion function according to the light field conversion coefficient template at the initial angle and the light field conversion coefficient templates at all swing angles; obtaining a gain correction template at a to-be-tested angle based on the angle light field conversion function; and performing gain correction on the bright field image at the to-be-tested angle according to the gain correction template at the to-be-tested angle, and obtaining a corrected image at the to-be-tested angle. The application can quickly perform gain correction on multiple angles, improves work efficiency and saves cost under the premise of ensuring image quality.

The invention relates to the technical field of target scattering characteristic testing, in particular to a compact range double-station RCS plane scanning testing method and system. The system comprises a transmitting antenna, a double-cylindrical-surface reflecting surface module, a plane scanning frame, a receiving antenna, radio frequency receiving and transmitting equipment and a test computer. According to the method, a mode of combining single compact range plane wave irradiation and plane scanning near field receiving is adopted. The transmitting end forms a plane wave in a quiet zone through the double-cylinder compact range to irradiate a to-be-measured target; the receiving antenna is driven by the plane scanning frame to scan in a two-dimensional plane and acquire a target near-field bistatic scattering signal; and the test computer processes the signal based on a near-far field transformation algorithm, and performs inversion to obtain the far-field double-station RCS of the target. According to the method, a receiving end compact range is replaced by plane scanning, the system cost, complexity and site requirements are remarkably reduced, and the prominent problems that a traditional indoor double-station RCS test technology is difficult to implement and high in cost are solved.

The application discloses a kind of unmanned vehicle path planning method and device based on unmanned aerial vehicle orthographic image, wherein the method comprises: obtaining the orthographic image photographed by unmanned aerial vehicle, the orthographic image is handled with semantic segmentation, the object class identified in semantic segmentation result is labeled;Extract the pixel region corresponding to each semantic label, generate the corresponding semantic category image, and perform TDF truncated euclidean distance field transformation on each semantic category image;Obtain the 3D point cloud data of the laser radar sensor of unmanned vehicle, map the 3D point cloud data of unmanned vehicle to the coordinate system of unmanned aerial vehicle TDF image using particle filtering algorithm, obtain the corresponding unmanned vehicle positioning information from unmanned aerial vehicle TDF image, and obtain obstacle positioning information according to unmanned vehicle positioning information;According to unmanned vehicle positioning information and obstacle positioning information, the path planning of unmanned vehicle is carried out.The application can improve the positioning accuracy of unmanned vehicle in complex environment and the accuracy and reliability of navigation path.

The invention relates to the technical field of optical fiber sensors, and discloses a low-coupling-loss spot size converter based on a film lithium niobate platform, which comprises a substrate, a lower cladding and a lithium niobate film layer located on the lower cladding, the lithium niobate film layer comprises a first waveguide part, a second waveguide part, a third waveguide part and a lens body which are connected in sequence, the lens body is located on the lower cladding, the lens layer is connected with the lens body, the first waveguide part and the second waveguide part are coated with the lens layer, and the first end of the first waveguide part is connected with the lens body; light is sequentially transmitted in the lens body, the first waveguide part, the second waveguide part and the third waveguide part, and in the light transmission direction, the transverse sizes of the first waveguide part, the second waveguide part and the third waveguide part are sequentially increased, and the transverse size of the lens layer is sequentially reduced, so that mode field conversion between the single-mode optical fiber and the ridge waveguide structure is realized; the structure size is smaller, the coupling loss is lower, and the matching between the waveguide and an optical fiber with a larger mode field diameter can be efficiently realized.

The application discloses a long-text-oriented episodic screenplay generation method and system, and belongs to the technical field of artificial intelligence content generation and digital video production. The method forms multiple episode objects through voice-over role initialization, text semantic compression and episode segmentation, and extracts role candidate objects and location time sequence candidate objects; based on normalization rules, an identity register of roles and a location time sequence register are constructed respectively, and unified identification reuse or new registration is performed on the candidate objects; under the constraint of the register, scene planning results and structured screenplay constraint patterns are generated, and multiple generation agents are called to output screenplay objects; and then, through structure verification, field completion and unified field transformation, the standardized results of episodes, roles, locations and screenplays are output. The application can improve the consistency of cross-episode roles and locations, the stability of the screenplay structure and the reuse efficiency of downstream production.

The application discloses a kind of double-channel rolling bearing fault diagnosis methods of image time sequence fusion, belong to rotating machinery intelligent fault diagnosis technical field.It includes: collecting rolling bearing vibration signal, constructs fixed length one-dimensional time sequence sample by segmented pretreatment, and generates corresponding image by gram angle difference field transformation;Then respectively establish image channel and time sequence channel, image channel extracts overall spatial feature and local detail feature, time sequence channel uses LSTM to extract time sequence dependent feature, and sets fusion node in multilevel;Further, the corresponding level features of two channels are complementarily fused based on joint context channel-by-channel gating, obtain joint fault feature layer by layer, finally input classification module to complete fault identification.The application solves the problem of insufficient single feature expression and insufficient cross-modal information fusion in rolling bearing fault diagnosis, and improves the diagnosis accuracy and robustness.

Disclosed in the present invention are a conversion core member (9), a double-lens mode field conversion device and a manufacturing method therefor. The conversion core member (9) comprises a solid-core optical fiber part (1), a hollow-core optical fiber part (2) and a calibration sleeve (3), wherein the solid-core optical fiber part (1) comprises a solid-core-end lens (12) and a solid-core single-mode optical fiber (11) having a first mode field diameter, and the solid-core end lens (12) is located at the tail end of the solid-core optical fiber part (1); the hollow-core optical fiber part (2) comprises a hollow-core-end lens (22) and a hollow-core optical fiber (21) having a second mode field diameter; the calibration sleeve (3) has a hollow cavity I (31) in the axial direction thereof; the solid-core optical fiber part (1) and the hollow-core optical fiber part (2) respectively extend into the cavity I (31) of the calibration sleeve (3) via two open ends of the cavity I (31); and the solid-core-end lens (12) and the hollow-core-end lens (22) are arranged opposite each other. In the device, the conversion of different mode field diameters between the single-mode optical fiber and the hollow-core optical fiber (21) is implemented by means of two lenses, such that a reliable and stable connection between the single-mode optical fiber and the hollow-core optical fiber (21) is achieved.

The invention relates to the technical field of near-far field transformation processing, in particular to a multi-module-integrated spherical near-field-to-far-field rapid transformation calculation method, which comprises the following steps: reading a field identification angle label and extracting measurement data, generating a complex field by frequency clustering normalization amplitude, matching a directional diagram to extract an amplitude-phase factor compensation complex field, and calculating the near-field-to-far-field rapid transformation of a spherical surface. And generating direction distribution according to the included angle superposition complex field, and extracting module length and argument to generate an amplitude-phase mapping set. According to the method, structured measuring point data are constructed by extracting angle labels, amplitude-phase consistency is enhanced by combining frequency clustering and amplitude normalization, direction corresponding precision is improved by utilizing angle difference matching, a direction response factor is introduced to carry out complex compensation correction, and a phase factor is constructed according to an included angle between a measuring point and an output direction to realize complex exponential superposition expression. And a structured amplitude-phase result is output, so that the continuity of far-field distribution, the accuracy of direction mapping and the consistency of frequency data are improved.

The invention provides an antenna near-field plane attribute evaluation and detection method, electronic equipment and a storage medium. The method comprises the following steps: carrying out gridding movement in a two-dimensional plane by adopting an electromagnetic field probe according to a lambda / 2 sampling step length interval, and synchronously measuring an amplitude value and a phase value of an electric field vector at each sampling point; analyzing, identifying and screening a sub-region of a feed phase fault based on the phase distribution characteristics; analyzing and outputting the boundary of a continuous abnormal adjacent region according to the sub-region with the feed phase fault and the sub-region with the abnormal near-field amplitude, performing far-field transformation on the continuous abnormal adjacent region, and outputting far-field radiation characteristic data for the continuous abnormal adjacent region so as to perform abnormal result verification on the continuous abnormal adjacent region; according to the processing method, a closed-loop diagnostic logic is formed through abnormal region identification and association and secondary detection verification in combination with near-field fine scanning positioning and far-field back-stepping verification. According to the mode, the reliability of a final output abnormal result is improved, and quality misjudgment is reduced.

The application aims to provide a distance compensation based RCS near far field transformation calculation method, and belongs to the technical field of RCS testing. The calculation method uses a large enough metal plate for calibration when measuring the near field echo signal, can shorten the overall test end face, improve the dynamic range of the test, and effectively reduce the loss interference of the intermediate path; then by measuring the echo signal received by the near field, and considering the actual situation that the distance from the test surface to the target will change with the rotation angle when the target rotates, a distance compensation function is introduced, the traditional NFFFT calculation formula is extended to the NFFFRT calculation formula based on distance compensation, and a more accurate RCS calculation method is provided for the stealth performance of the test target.

The invention relates to a transformation ratio detection method for a low-voltage spike pulse type mutual inductor. The method comprises the following steps: S1, obtaining the representation of the transformation ratio N of the mutual inductor based on five basic parameters; s2, obtaining five basic parameters of the transformation ratio N of the mutual inductor; and S3, obtaining a basic parameter calculation formula of the transformation ratio N of the transformer. According to the invention, a transformer transformation ratio detection technology of a transformer substation current transformer and a transformer substation voltage transformer is deduced by virtue of low-voltage direct current in a human body bearing range for the first time; the current situations that the transformation ratio detection is high in personal risk, expensive in equipment, heavy in weight and easy to damage are changed, so that the field transformation ratio detection work becomes simple and convenient without personal risk; the current situation that transformer substation mutual inductor acceptance equipment assets are heavy at present is changed, and reference is provided for transformation of a traditional on-site acceptance process to lean, scientific and technical and high-end.

The application relates to the technical field of video frame interpolation, and provides a video frame interpolation method and system based on all-to-many field conversion, which comprises the following steps: based on a pair of video frames, obtaining a bidirectional correlation container, bilateral optical flow, intermediate frame features and a plurality of levels of input frame feature pairs, and updating the bilateral optical flow and the intermediate frame features through a plurality of intermediate layers to obtain an output video frame; in each intermediate layer, the bilateral optical flow is first scaled and converted into bidirectional optical flow, and then the correlation features in the bidirectional correlation container are taken out according to the bidirectional optical flow, the residual error of the bidirectional optical flow and the residual error of the intermediate frame features are calculated, the bilateral optical flow and the intermediate frame features are updated according to the residual errors, the updated bilateral optical flow is used for performing a distortion operation on the input frame features, and the distorted input frame features and the intermediate frame features are input into a decoder to be enlarged in a spatial scale. The fidelity of the cross-scale optical flow is ensured, the accumulation and amplification of errors are reduced, and the video frame interpolation result is more accurate.

This invention discloses a noise separation method and system based on spatial sound suppression and equivalent field transformation. The method includes: constructing mutually independent target space, observation space, and virtual sound insulation space; constructing the sound pressure transmission relationship between the target space, observation space, and virtual sound insulation space based on analytical Green's function; establishing a mathematical model using the virtual source point location in the target space, and introducing weighting coefficients to construct a weighted calculation model for the sound pressure at the point to be measured in the observation space; constructing a regularized optimization problem with physical constraints, using the zero sound field amplitude in the virtual sound insulation space as a constraint, and solving for the weighting coefficients of the observation array; using the weighting coefficients to perform spatial domain weighting processing on the signals acquired by the observation array, and extracting the target sound field signal. This invention solves the technical problems of low separation accuracy, numerical instability, and high sampling requirements of existing equivalent source methods under strong noise interference environments, and has many advantages such as strong noise suppression capability, low engineering cost, and high flexibility.

The invention belongs to the technical field of antennas, and particularly relates to a phased-array antenna beam comprehensive online adjusting and testing system and method based on a light-operated scanning testing technology, a semiconductor wafer is placed in front of a phased-array antenna, laser is used for irradiating the semiconductor wafer, and photo-generated plasma is formed on the semiconductor wafer; according to the invention, the photo-generated plasma can scatter the radiation electromagnetic wave of the phased-array antenna, and the scattering signal is proportional to the radiation electromagnetic wave of the phased-array antenna, so that the electric field signal of the phased-array antenna at the laser irradiation position of the semiconductor chip can be obtained by receiving the scattering signal; therefore, the electric field distribution can be measured at an ultra-high speed, and the beam radiation characteristics of the phased-array antenna can be obtained by further combining near-far field conversion. Due to the high-efficiency test characteristic of the light-operated scanning test technology, a large amount of measured data can be provided and introduced into the beam synthesis process of the phased-array antenna, and accurate and high-efficiency beam synthesis is realized.

The invention relates to the technical field of electromagnetic field analysis, and discloses an electromagnetic characteristic near-far field equivalent conversion mapping method. The method comprises the following steps: acquiring original electromagnetic field data of a target electromagnetic radiation source to form a field intensity, phase and frequency spectrum data set; performing time sequence feature extraction on the field intensity data, performing fluctuation analysis on the phase data and performing distribution analysis on the frequency spectrum data to obtain corresponding feature vectors; and fusing the feature vectors to generate a multi-dimensional electromagnetic feature matrix. Matching an initial conversion parameter group in a conversion rule base based on the matrix, and performing iterative optimization on the initial conversion parameter group by using a parameter optimizer to obtain an optimized conversion parameter group; and constructing a near-field-to-far-field mapping relation model according to the optimization parameter group, processing real-time data by using the model, and outputting a far-field equivalent electromagnetic characteristic pattern. According to the invention, through multi-dimensional feature fusion and data-driven parameter dynamic optimization, the accuracy and adaptability of near-far field conversion in a complex environment are improved.