15 results about "Electromagnetic propagation" patented technology

The application discloses a kind of marine low-altitude electromagnetic propagation environment evaluation method and system, it is related to marine electromagnetic environment monitoring and evaluation technical field, the method is constructed standardization dataset by collecting multi-source data, combined with physical-data collaborative constraint is carried out mesoscale waveguide prediction, and small-scale waveguide model is constructed by descending scale, and then cross-scale modeling is realized using space-time adaptive fusion algorithm, finally simulates electromagnetic wave propagation characteristics and carries out multi-dimensional evaluation and visual display;The application realizes the all-around characterization to marine low-altitude electromagnetic wave propagation characteristics by cross-scale accurate modeling and multi-dimensional comprehensive evaluation, can accurately present the constraint enhancement effect and blind area distribution of atmospheric waveguide, provides accurate technical support and data reference for the practical application of marine communication, detection and navigation system, effectively guarantees electromagnetic performance research and system efficiency play under marine environment.

The application discloses an electric power distribution cabinet electric leakage detection system and method, belongs to the field of intelligent detection, data processing and safety technology, and through joint optimization of electric field and magnetic field transient signals, distinguishes real electric leakage from interference and avoids false positives. Combined with the event authenticity verification of the temperature field and the vibration field of the distributed optical fiber, the reliability of the electric leakage event is ensured. Using the time domain reversal technology in the electromagnetic propagation model considering the internal metal components of the power distribution cabinet, through the spatial coincidence constraint of the electric field and magnetic field focusing area, the positioning error caused by the multipath effect is overcome, and the accurate positioning of the electric leakage point is realized. Through the physical consistency verification of the electromagnetic positioning result and the cumulative physical field characteristics of the distributed optical fiber, the reliability and accuracy of the electric leakage positioning result are improved.

The invention provides a low-altitude flexible HMIMO-oriented spatial characteristic evaluation and port configuration method and system, and the method comprises the steps: constructing the array geometry of a flexible HMIMO array, and setting a user position and an electromagnetic propagation environment model; secondly, visibility judgment and gating processing are carried out on the sight distance model; then, the whole array is divided into sub-arrays, and available sub-arrays are screened out; calculating an autocorrelation matrix and quantizing a channel statistical difference distance between any two sub-arrays to generate a spatial non-stationary heat map; meanwhile, the full-aperture space freedom degree is calculated; and finally, obtaining an average achievable port mode number by taking a statistical expectation from a target direction domain, and obtaining a port configuration engineering upper bound by integrating a theoretical degree of freedom and hardware constraints. According to the method, the problems of spatial non-stationary quantization, sub-array availability judgment and port-level realizable mode number determination of the flexible curved surface array under near-field and shielding conditions are solved, and a direct basis is provided for engineering design and resource allocation of flexible HMIMO in low-altitude communication.

This invention relates to a carbon / carbon composite material with microwave absorption properties and its preparation method, belonging to the field of microwave absorbing materials technology. The material uses chopped carbon fibers and nanodiamond powder as raw materials, which are uniformly mixed, dried, ground, and then mixed with paraffin wax and pressed into shape. The chopped carbon fibers form a continuous conductive network within the nanodiamond matrix, introducing conductivity loss and polarization relaxation. The nanodiamond enhances dielectric loss through interfacial polarization and increases the electromagnetic propagation path. The synergistic effect of these two materials achieves excellent impedance matching and electromagnetic wave absorption performance. This method is simple, requires no high-temperature sintering, exhibits good microwave absorption characteristics in the X-band, and is suitable for the preparation of microwave absorbing materials.

The application discloses an underground disease intelligent identification method based on multi-physical field feature fusion. The method uses multi-source information such as ground penetrating radar B-scan data, dielectric constant distribution and conductivity distribution, extracts time domain, frequency domain and medium parameter features through a learnable wavelet transform and a multi-network structure, realizes cross-domain feature alignment and importance weighting in an adaptive fusion module, and forms a comprehensive underground target representation. Via a detection network, the positioning and classification of diseases such as cavities, voids, loose and leakage are output. The model is trained by using a joint loss containing classification, position regression, frequency domain consistency and electromagnetic propagation constraints. The method can effectively improve the accuracy and physical credibility of underground disease identification.

This invention provides a deployment method for mobile electromagnetic spectrum monitoring equipment integrating multi-physics sensing, relating to the field of electromagnetic spectrum monitoring technology. The method includes: performing electromagnetic propagation modeling with multi-physics coupling; performing Pareto front screening to obtain H global candidate solutions; S1: performing diversity-enhanced global exploration and outputting a set of diverse potential solutions; S2: performing constraint-aware local optimization and outputting a set of compliant physical field deployment schemes; iteratively executing S1 to S2, performing two-layer physical field collaborative iterative optimization until convergence conditions are met, and outputting a multi-physics constrained deployment coordinate set; performing robustness verification, outputting an anti-interference optimized deployment scheme, and deploying the monitoring network. This solves the technical problem that existing spectrum monitoring technologies mostly rely on fixed monitoring point deployments, where the monitoring range of these devices is statically set, lacking dynamic adaptability, resulting in incomplete signal coverage and ineffective monitoring of electromagnetic interference sources.

The present application belongs to the field of radio wave propagation theory and electromagnetic field numerical calculation technology, and discloses a low-dispersion very low frequency radio wave propagation characteristic prediction method.The present application method aims at the defects of large numerical dispersion, low calculation efficiency and high resource occupation of the existing FDTD method in long-distance, complex layered medium scene, and realizes high-precision and high-efficiency prediction of the very low frequency radio wave propagation characteristic in seawater-air-ionosphere medium by combining HIE-FDTD method and M(2,4)FDTD method through three-layer processing of the whole calculation area.The present application method solves the contradiction between reducing numerical dispersion error and reducing computer consumption of the traditional FDTD method, can greatly reduce computer memory resource occupation and improve calculation speed while ensuring prediction accuracy, is suitable for electromagnetic propagation simulation of large-size, complex medium and terrain, and has obvious advantages in phase delay prediction of very low frequency ground wave propagation.

The present application belongs to the field of radio wave propagation theory and electromagnetic field numerical calculation technology, and discloses a low-dispersion very low frequency radio wave propagation characteristic prediction method.The present application method aims at the defects of large numerical dispersion, low calculation efficiency and high resource occupation of the existing FDTD method in long-distance, complex layered medium scene, and realizes high-precision and high-efficiency prediction of the very low frequency radio wave propagation characteristic in seawater-air-ionosphere medium by combining HIE-FDTD method and M(2,4)FDTD method through three-layer processing of the whole calculation area.The present application method solves the contradiction between reducing numerical dispersion error and reducing computer consumption of the traditional FDTD method, can greatly reduce computer memory resource occupation and improve calculation speed while ensuring prediction accuracy, is suitable for electromagnetic propagation simulation of large-size, complex medium and terrain, and has obvious advantages in phase delay prediction of very low frequency ground wave propagation.

The application discloses a shipborne marine atmospheric boundary layer refractive index profile detection system and method, relates to the technical field of marine atmospheric environment monitoring and electromagnetic wave propagation guarantee, and comprises the following steps: acquiring sea-air downward infrared radiation spectrum data and sea surface air temperature, relative humidity and air pressure data; constructing a background atmospheric profile by using reanalysis data, and correcting the initial profile bottom layer by using the sea surface observation air temperature, relative humidity and air pressure data to form a prior state vector; constructing an inversion cost function containing an observation residual term, a background prior term and a sea surface boundary constraint term, and inverting to obtain an atmospheric temperature profile and a relative humidity profile; and calculating an atmospheric refractive index profile according to the temperature profile, the relative humidity profile and the air pressure profile. The application can continuously acquire the marine atmospheric refractive index profile under the shipborne dynamic observation condition, and provides reliable data support for marine electromagnetic propagation environment analysis and waveguide diagnosis.

This invention discloses a cross-domain WiFi sensing action recognition method based on a physical information neural network, belonging to the field of wireless sensing technology. The method includes: acquiring raw CSI data; eliminating phase offset using the CSI quotient and performing multi-level filtering preprocessing to construct an amplitude feature map; extracting high-dimensional spatiotemporal data features using a backbone network; inputting the data features into a physical enhancement module and reconstructing a virtual CSI waveform through a synthesizer decoder; calculating multi-dimensional physical constraint loss based on the law of radio propagation; dynamically fusing data features and physical features using an adaptive attention gating mechanism; and finally inputting the data features into a classifier to output the action category. This invention embeds the deterministic electromagnetic propagation law as a differentiable constraint into the deep learning optimization process, effectively decoupling multipath interference in specific environments from real human kinematic features, significantly improving the robustness and generalization ability of action recognition in complex domain offset scenarios such as cross-location, cross-user, and cross-orientation.

The application discloses a low-altitude atmospheric waveguide analysis method and system for electromagnetic propagation optimization, and relates to the technical field of ocean atmospheric environment detection and electromagnetic propagation. The specific steps of the method are as follows: synchronously collecting multiple types of marine meteorological data of a target sea area, and constructing a standardized data set after processing; constructing a physical constraint deep neural network to generate a mesoscale parameter field; constructing a model with a correction mechanism to generate a small-scale profile model; constructing a multi-scale fusion model to output a spatio-temporal prediction result; analyzing characteristics, outputting an optimization strategy and feeding back reversely to complete whole-process optimization. The application realizes fine waveguide modeling from mesoscale to small scale, and improves the accuracy of atmospheric waveguide feature representation by constructing a physical constraint deep neural network and introducing an interface inclination angle correction mechanism. The application realizes cross-scale adaptive fusion, improves prediction accuracy, establishes a reverse feedback mechanism to promote whole-process optimization, and better adapts to the requirements of a marine electromagnetic system by constructing a multi-scale fusion model.

The application is suitable for the technical field of electromagnetic simulation calculation, and provides a multi-radiation-source space electromagnetic field solving method and a terminal based on space structure reconstruction. The method comprises the following steps: analyzing a grid model of a three-dimensional electromagnetic propagation scene and converting the grid model into a triangular facet element set used for electromagnetic ray tracing; generating a one-dimensional triangular facet element sequence of the triangular facet element set according to the Morton coding of the center vector of each triangular facet element; clustering the triangular facet elements according to the geometric connection relationship between the triangular facet elements and reconstructing the order of the triangular facet elements in each cluster; constructing a BVH scene tree according to the reconstructed triangular facet element sequence, determining the triangular facet elements intersecting with the electromagnetic rays in the grid model according to the BVH scene tree, eliminating the triangular facet elements not intersecting with the electromagnetic rays, and determining the propagation path of the electromagnetic rays in the grid model and the electromagnetic field distribution. The application is more in line with the electromagnetic propagation direction characteristics, optimizes the traversal path, improves the traversal efficiency, and shortens the calculation time.

The application discloses a waveguide electromagnetic wave transmission loss dynamic prediction method and device. A directed attribute graph is constructed according to the physical connection structure of a waveguide network. After port radio frequency observation data and environmental sensor data are coded, the posterior distribution of the degradation state of each node is inferred by combining a graph variational inference network with an electromagnetic propagation attenuation model constraint. The degradation state is predicted by a multi-scale time sequence evolution prediction through a double-channel neural state space model. The link total transmission loss prediction value is obtained by aggregation along the directed attribute graph through a loss mapping network, and the future evolution trend is extrapolated. The application can accurately infer the degradation state of each node and predict the dynamic evolution of the transmission loss under incomplete observation conditions.

This invention discloses a method for 3D environmental feature extraction and electromagnetic propagation path modeling based on neural networks, belonging to the field of channel modeling technology. The method includes: S1: acquiring wireless channel data of the target scene and corresponding 3D spatial point cloud environmental data; S2: obtaining a physical environment feature dataset for neural network training; S3: constructing a 3D environmental feature extraction model to generate implicit environmental feature representations reflecting the relationship between environmental spatial distribution and material properties; S4: constructing an electromagnetic propagation direction prediction model and a power prediction model to predict the step-by-step evolution of the electromagnetic propagation path and output electromagnetic propagation path-level characteristics. This invention solves the problems of complex and inefficient existing modeling processes, difficulty in directly utilizing measured point cloud data, and difficulty in efficiently generating multipath propagation paths. This invention improves modeling efficiency and reduces labor costs, enabling direct modeling of point cloud geometry and material properties while reducing the computational complexity of multipath path inference.

This invention discloses an electromagnetic situational awareness and visualization system based on geospatial positioning, comprising: a geospatial grid construction module, which acquires GIS engine data and divides the target area into a multi-scale non-uniform three-dimensional computational grid according to monitoring requirements; a geographic constraint inference and modeling module, which executes an adaptive electromagnetic propagation model and calculates physical trend values; a multi-source residual compensation module, which acquires the measured signal strength values ​​of monitoring nodes, calculates the residuals between the measured signal strength values ​​and the physical trend values, performs Kriging interpolation on the residuals using the residual Kriging algorithm, and synthesizes a global reconstructed situational map; and an interactive multi-dimensional display module, which renders the global reconstructed situational map as a dynamic heatmap superimposed on the geographic model, and synchronously displays the instantaneous spectrum map and waterfall map of the associated frequency points, outputting the electromagnetic situational field. This system can achieve high-precision situational awareness in complex geographic environments, providing a reliable basis for the analysis and management of the electromagnetic environment.