181 results about "Electromagnetic spectrum" patented technology

The invention relates to the technical field of electromagnetic spectrum monitoring, and particularly discloses a distance-based electromagnetic spectrum monitoring abnormal data detection method, which comprises the following steps of: performing short-time Fourier transform and normalization processing on an acquired original signal to generate an energy density distribution characteristic graph; constructing a multivariate Gaussian distribution model based on non-abnormal historical data; during real-time monitoring, the mahalanobis distance between the collected data and the mean vector of the historical model is calculated after the collected data is preprocessed. And comparing the distance metric value with a preset threshold value to preliminarily judge abnormity, and calculating a distance fluctuation variance through a sliding window mechanism to perform secondary verification. And finally, processing and positioning anomalies by using image morphology, and dividing the degree of anomalies according to the relative deviation between the energy density and the mean value of the historical model. According to the method, the mahalanobis distance and the multivariate Gaussian distribution are introduced, secondary verification and abnormal positioning are combined, the limitation of a traditional method is overcome, the detection accuracy and reliability are effectively improved, the misjudgment and missing judgment rate is reduced, and the method does not depend on a large amount of labeled data and is high in practicability.

The invention provides an unmanned aerial vehicle full-band countering method and system based on acousto-optic-electric composite detection. According to the invention, through synchronous cooperative detection of sound wave sensing, optical imaging and electromagnetic spectrum analysis, a composite detection signal is generated; based on the relevance between the acoustic characteristic frequency band and the electromagnetic control frequency band, extracting the working mode characteristics of the unmanned aerial vehicle and generating dynamic interference parameters; generating a synchronous interference instruction according to the time domain modulation characteristic of the dynamic interference parameter; in combination with abnormal noise distribution characteristics captured by the acoustic module and flight path offset identified by the optical module, power distribution and frequency band coverage of the interference instruction are corrected in real time, and optimized interference parameters are generated; and finally, a dynamic interference map is generated through overlapping frequency spectrum fusion of the dynamic interference parameters and the optimized interference parameters, accurate cooperative suppression is realized, full-band real-time accurate suppression of navigation, communication and power control signals of the target unmanned aerial vehicle is realized, and the countering efficiency in a complex scene is remarkably improved.

The invention belongs to the technical field of electromagnetic confrontation and intelligent decision making, and particularly relates to an electromagnetic situation intelligent confrontation decision making method and system based on deep learning. Threat level evaluation and resource adaptation degree analysis are carried out based on a multi-head self-attention mechanism, and a dynamic electromagnetic confrontation strategy knowledge graph is generated; a game confrontation engine driven by deep reinforcement learning is used for deducing an enemy countering path and a situation evolution result under different interference strategies of our party, interference parameters are optimized through a multi-agent collaborative learning model, weight parameters of a strategy network are updated in real time through online confrontation element learning, and historical confrontation efficiency data and current task constraints are combined to obtain a confrontation result. And dynamically generating a target interference decision sequence and an electromagnetic confrontation efficiency prediction report, and synchronously updating the electromagnetic confrontation strategy library. Therefore, the problems of serious disjunction of deduction results, low real-time antagonism and the like in the prior art are solved.

The invention relates to the field of electric power material warehouse management and control, in particular to an electric power material digital intelligent professional warehouse management and control method, which comprises the following steps: acquiring electromagnetic spectrum data, identifying a central frequency point energy distribution diagram and an electromagnetic interference intensity level, constructing a three-dimensional electromagnetic field intensity distribution model of a professional warehouse, and dynamically adjusting the working mode of an RFID reader-writer; the method comprises the following steps: deploying a multi-modal check node in a storage area of a professional warehouse, and generating a composite check result through an infrared contour matching method and a UWB coordinate verification method when the confidence coefficient of electric power material data read by an RFID reader-writer is lower than a preset confidence coefficient threshold value; updating an electric power material inventory database according to a composite verification result, and performing electric power material inventory state analysis in real time through an edge computing node; the problems that inventory data distortion and material positioning deviation are caused by reduction of the accuracy rate of RFID in a strong electromagnetic environment, and inventory accuracy management of an electric power material warehouse is seriously restricted are solved.

The invention discloses a partial discharge online monitoring method based on an ultrahigh frequency original signal, and relates to the field of partial discharge monitoring, and the method comprises the steps: autonomously switching an ultrahigh frequency signal capturing frequency band according to the real-time electromagnetic spectrum distribution of a monitoring environment, and obtaining an original signal sequence covering a potential partial discharge feature; the method comprises the following steps: preprocessing an original signal sequence through multi-scale pulse contour extraction, and suppressing environmental noise interference to retain pulse characteristics of partial discharge signals; through real-time electromagnetic spectrum analysis, ultrahigh frequency capture frequency bands are automatically switched, environmental noise changes are dynamically adapted, original signal capture accuracy is improved, through multi-scale pulse contour extraction preprocessing, noise interference is effectively suppressed, key pulse features are reserved, and the accuracy of signal capture is improved. A multi-dimensional feature data set constructed based on the pulse peak gradient, the duration spectrum and the waveform similarity provides a comprehensive basis for partial discharge recognition.

The invention discloses an electromagnetic spectrum prediction method and system based on fractional Fourier transform. The method comprises the following steps: constructing historical spectrum observation data in a target area; mapping the collected spectrum observation data to a corresponding fractional order Fourier domain by using adaptive fractional order Fourier transform, and adaptively adjusting fractional order parameters of a fractional order Fourier transform layer to output a fractional order Fourier domain containing predictable spectrum components; in the mapped fractional order Fourier domain, non-predictive noise in the converted data is filtered out; performing feature extraction and prediction on the frequency spectrum data of the fractional order Fourier domain after noise filtering by using a complex valued linear network to obtain a prediction result of the fractional order Fourier domain; and mapping the prediction result of the fractional Fourier domain back to the original time domain by adopting inverse fractional Fourier transform, and generating final frequency spectrum prediction output. According to the method, the accuracy of weak periodic spectrum prediction is effectively improved through fractional Fourier transform and a filtering strategy.

An automatic heat-sealing quality control system to automatically control a quality of a heat-sealing of a sealing strip to a longitudinal edge of a packaging web at a heat- sealing station in a packaging machine, where sealed packages containing pourable food products are continuously produced from a continuous vertical tube filled with the pourable food product and formed by longitudinally folding the packaging web to overlap longitudinal edges thereof and then heat-sealing the overlapping longitudinal edges. The system comprises a visible-light imaging camera designed to operate in the electromagnetic spectrum visible to human eye to capture and output visible-light digital images.

The invention belongs to the technical field of cognitive radio, and particularly relates to an open set modulation identification method based on time-frequency domain feature learning and fusion. The method comprises the following steps of: receiving a signal by adopting a receiving antenna through electromagnetic spectrum monitoring equipment, capturing a space electromagnetic radiation signal, converting the space electromagnetic radiation signal into an electric signal, amplifying the signal through a low-noise amplifier, performing frequency conversion and filtering through an analog receiver, and converting the received signal into an intermediate-frequency signal. Then, the signal is digitalized through AD sampling, and the intermediate frequency signal is converted into a baseband complex signal through frequency mixing and digital filtering in a digital receiver. Then performing time domain characterization calculation and frequency domain characterization calculation on the signal sampling data to form a plurality of time domain characterization vectors and a plurality of frequency domain characterization vectors; and then the vectors are sent to a trained deep neural network model, reasoning is carried out by using the network model, a reasoning result is post-processed, and a signal modulation identification result is finally obtained. According to the invention, the recognition accuracy of unknown signals is improved.

The invention discloses an obstacle avoidance tracking method based on deep reinforcement learning, and belongs to the field of path planning. The invention relates to a multi-unmanned aerial vehicle reconnaissance near-end strategy optimization method based on a distributed reinforcement learning framework, and the implementation method is as follows: through deep fusion of a pressure sensing mechanism and an improved SAC reinforcement learning method, precise avoidance of dynamic obstacles and efficient pursuit of abnormal radiation sources are realized. According to the pressure sensing module designed by the invention, the environmental pressure is quantized into a numerical index, and the conservative degree of a decision strategy is dynamically adjusted according to the numerical index. On this basis, decision optimization is carried out by using a double-Q network architecture of an improved SAC algorithm, and a conservative strategy and an aggressive strategy are adopted for parallel evaluation, so that the robustness of the strategies is improved while the exploration efficiency is ensured. The method operates in a continuous action space, and the smoothness and stability of the motion trail of the unmanned aerial vehicle are ensured. According to the invention, the unmanned aerial vehicle can intelligently track an abnormal radiation source in a high-voltage environment in complex urban electromagnetic spectrum combat.

The invention belongs to the technical field of cognitive radio, and particularly relates to a broadband multi-signal detection method based on a large-size convolution kernel. The method mainly comprises the following steps of: receiving a signal by adopting a receiving antenna through electromagnetic spectrum monitoring equipment, capturing a space electromagnetic radiation signal and converting the space electromagnetic radiation signal into a baseband complex signal, carrying out large FFT point short-time Fourier transform on signal sampling data to form a high-resolution and large-size time-frequency matrix, and carrying out time-frequency spectrum detection along a frequency axis of the time-frequency matrix; a time-frequency matrix is cut into a plurality of time-frequency matrix fragments adapted to neural network processing, and parameters such as confidence probability, center frequency, bandwidth, arrival time, duration and the like of existence of signals in each time-frequency matrix fragment are automatically calculated and generated by using a specially designed and trained deep neural network model. The method has the advantages that the operation of monitoring equipment is simplified, the signal detection speed is high, the detection accuracy is high, the detection recall rate is high, and the time-frequency occupancy parameter estimation precision is high.

The invention provides a multi-agent cooperation method and device for electromagnetic spectrum monitoring and analysis, and belongs to the technical field of artificial intelligence. The method comprises the following steps: receiving a task demand, and obtaining interface information of an electromagnetic detection tool model; analyzing the task demand through the first agent to generate a preliminary task intention; generating a task planning book containing a plurality of subtasks based on the preliminary task intention and the interface information; calling an electromagnetic detection tool model to execute a subtask through a task scheduling module of the second agent, and obtaining intermediate result information and final label information; and based on the intermediate result information and the final label information, performing feature fusion and intention inference through a second agent, and generating an intention inference result of the electromagnetic signal and an evidence chain supporting the intention inference result. Based on the method, the invention also provides a multi-agent cooperation device for electromagnetic spectrum monitoring and analysis. According to the invention, the recall rate and robustness of spectral analysis are improved, and the detection rate of anomaly detection is improved.

The invention discloses a power inspection-oriented low-altitude electromagnetic abnormal trend early warning method and system, and the method comprises the steps: synchronously collecting electromagnetic spectrum data and flight state data of an unmanned plane when the unmanned plane executes a low-altitude power inspection task, and generating a space-time aligned electromagnetic-flight data sequence; performing feature extraction and matching on the electromagnetic-flight data sequence based on an electromagnetic interference feature library of a typical power interference source, and constructing a dynamic electromagnetic environment situation map by fusing spatial position information of the unmanned aerial vehicle; performing electromagnetic abnormal risk analysis on the dynamic electromagnetic environment situation map by adopting an analysis model trained by a historical power electromagnetic interference event to obtain a dynamic risk assessment coefficient; according to the dynamic risk assessment coefficient, predicting an electromagnetic anomaly trend index in a future preset time period; and comparing the pre-warning threshold value with the multi-level pre-warning threshold value conforming to the electric power safety regulation, and when the pre-warning threshold value exceeds the multi-level pre-warning threshold value, triggering a corresponding pre-warning level and generating a risk avoidance strategy adaptive to the low-altitude electric power inspection scene.

The invention discloses an unmanned aerial vehicle illegal intrusion countering system and method based on electromagnetic spectrum detection, and relates to the technical field of unmanned aerial vehicle countering, and the system comprises an electromagnetic spectrum detection module, a spectrum analysis processing module, an intelligent decision module and a countering execution module. By constructing a distributed electromagnetic spectrum detection network, the comprehensiveness and the accuracy of signal acquisition are improved, a spectrum analysis algorithm is combined, spectrum features are deeply mined, illegal intrusion signals of the unmanned aerial vehicle are accurately identified, high-precision detection and rapid early warning of illegal intrusion behaviors of the unmanned aerial vehicle are realized, and an intelligent self-adaptive countering strategy is utilized, so that the safety of the unmanned aerial vehicle is improved. According to the real-time state information of the unmanned aerial vehicle, the intensity, frequency and mode of countering measures are automatically adjusted, the countering effect is improved, the working frequency band of surrounding legal electronic equipment can be dynamically avoided in the countering process, interference to the electronic equipment is greatly reduced, stability of the electromagnetic environment in the area is guaranteed, and the safety of the unmanned aerial vehicle is improved. And the capability of preventing and coping with illegal invasion of the unmanned aerial vehicle is effectively improved.

A molecular-spin qubit includes a molecular color center having a ground state and an excited state. The ground state has non-zero spin with at least first and second sublevels. The molecular-spin qubit also includes a host matrix that is non-isostructural with the molecular color center. The molecular color center is diluted in the host matrix. An optical transition between the ground and excited states lies in the optical region of the electromagnetic spectrum. A spin transition between the first and second sublevels lies in the microwave or millimeter-wave regions of the electromagnetic spectrum. Each of the first and second sublevels is first-order insensitive to magnetic fields near zero magnetic. The molecular color center and host matrix may each be formed from strong-field ligands bound to a metal-atom center. One example of the molecular-spin qubit is Cr(IV)(o-toyl)4 diluted in a host matrix of Sn(IV)(4-fluoro-2-methylphenyl)4.

An automatic heat seal quality control system (12) for automatically controlling the quality of heat seals at the longitudinal ends of a packaging web (3) of a sealing strip (6) in a heat seal station (7) of a packaging machine (1). A sealed package (5) containing a cast food product is continuously manufactured from a continuous longitudinal tube (2) filled with the cast food product. The automatic heat seal quality control system (12) is formed by folding the packaging web (3) longitudinally and overlapping its longitudinal ends, and heat sealing the overlapping longitudinal ends. This system (12) includes a visible light camera (19) designed to operate in the electromagnetic spectrum visible to the human eye in order to capture and output a visible light digital image, and captures and outputs a visible light digital image.

The invention provides a regional electromagnetic intelligent evaluation method and system based on spectral entropy weighting, and the method comprises the following steps: collecting electromagnetic spectrum data and the motion state of a patrol vehicle, and constructing a virtual aperture data matrix through the motion information; space covariance analysis and subspace projection are carried out on the matrix, multipath scattering interference is separated and eliminated, and a pure field intensity sequence is obtained through reconstruction. By calculating the normalized spectrum entropy of the Doppler power spectrum of the pure field intensity sequence, an inverse proportion weight coefficient representing the signal confidence is generated; and weighting the weight to a pure field intensity sequence, and mapping the pure field intensity sequence to a geographic space. And dynamically adjusting the density of the evaluation grid according to the field intensity gradient, and finally carrying out weighted centroid calculation based on inverse proportion weight to obtain a regional electromagnetic environment evaluation result. According to the method, the technical problem that a regional evaluation result is not accurate due to the fact that multipath components cannot be separated and single-point data quality cannot be evaluated in traditional mobile patrol is solved.

The invention relates to the technical field of Internet of Things physical layer security, in particular to an Internet of Things digital twinborn antagonism defense method and system oriented to an electromagnetic spectrum. Comprising the following steps: constructing an electromagnetic spectrum digital twin of a target Internet of Things system to simulate a physical signal environment in a high-fidelity manner; in the twinborn body, an intelligent optimization algorithm is utilized to generate an antagonistic signal sample aiming at the communication model; carrying out adversarial training on a communication model by using the samples to enhance the robustness of the communication model, wherein a meta-learning framework can be adopted in the training process to improve the generalization adaptive capacity; establishing a dynamic synchronous closed loop between the digital twinborn body and a real physical environment, and realizing model calibration and real threat sample back feeding; when an attack is detected in a real environment, multiple defense strategies are simulated and evaluated in the twin, and an optimal strategy is selected and issued to physical equipment for execution. According to the invention, digital twinning, antagonistic machine learning and real-time closed-loop control are combined, and the anti-interference capability of the Internet of Things system is actively refined in advance at low cost.

A time-of-flight (ToF) sensor includes a photodetector array and a processing circuit. The photodetector array includes a plurality of photodetectors wherein each photodetector of the photodetector array includes a silicon-based, light-sensitive diode. Each silicon-based, light-sensitive diode includes a photosensitive layer comprising a plurality of quantum dot particles sensitive to a near infrared (NIR) region of an electromagnetic spectrum, wherein the plurality of quantum dot particles converts optical energy into electrical energy to generate an electrical current in response to receiving NIR light having a wavelength in the NIR region. The processing circuit is configured to receive the electrical current and calculate a time-of-flight of the received NIR light based on the electrical current.

The invention provides an unmanned aerial vehicle high-voltage environment electromagnetic interference multi-level protection method and system, and belongs to the field of unmanned aerial vehicle anti-electromagnetic interference. Comprising the steps of collecting electromagnetic spectrum data, identifying an interference type and setting an initial anti-interference parameter; monitoring the electric field intensity in the flight process of the unmanned aerial vehicle, and dynamically adjusting an active anti-interference strategy according to the interference type; differential electromagnetic shielding and wave absorbing treatment is carried out on the unmanned aerial vehicle structure module; correcting the navigation positioning information by adopting a data fusion algorithm, and compensating the sensor data in real time based on a preset interference-error mapping model; key performance indexes of communication, positioning and sensor data are monitored in real time, and when the key performance indexes exceed a threshold value, an adjustment instruction is generated for feedback iteration, and closed-loop optimization is achieved. According to the invention, full-process collaborative protection from sensing, suppression, isolation to compensation is realized, and the communication reliability, positioning precision and data accuracy of the unmanned aerial vehicle in high-voltage strong electromagnetic environments such as a high-voltage transmission line and a transformer substation are improved.

The invention discloses an automobile atmosphere lamp control method, which relates to the technical field of automobile atmosphere lamp control, and comprises the following steps of: setting a working frequency range and a harmonic sensitive bandwidth of a vehicle-mounted communication bus, and deploying a high-sensitivity electromagnetic sensing probe at the edge of a communication bus wiring area, the sensor is used for acquiring electromagnetic radiation signal intensity in a sensitive frequency band in real time; after the atmosphere lamp PWM control module is started, a dynamic brightness adjusting task is executed under the conditions of different PWM switching frequencies and duty ratios, and electromagnetic spectrum density change data in a sensitive frequency band is recorded at the same time. According to the invention, the electromagnetic sensing probe monitors the interference frequency spectrum in real time, combines the PWM parameters to establish frequency mapping and quantify the coupling strength, generates a continuous electromagnetic coupling strength index, and dynamically drives the filter to accurately suppress the target frequency band, thereby effectively suppressing the electromagnetic interference on the CAN / LIN bus while guaranteeing the effect of the atmosphere lamp, and improving the reliability of the atmosphere lamp. And the whole vehicle communication safety and the system stability are improved.

The present invention discloses a method for mapping electromagnetic spectrum in complex three-dimensional urban environments, comprising: determining the scope, frequency points, and signal recovery threshold of the area to be mapped; representing the spectrum data intensity corresponding to each cube obtained after discretizing the area to be mapped in tensor form; determining the number of samples in the area to be mapped, an optimized set of sampling position indexes, and determining the optimal sampling trajectory of an unmanned aerial vehicle; collecting corresponding spectrum data vectors, recovering the electromagnetic target signals in the area to be mapped, and obtaining a preliminary complete spectrum map; calculating the shadow fading components at all locations based on the sparse electromagnetic target signals and the sampled spectrum data, and correcting the spectrum map; correcting the reconstructed spectrum map based on the shadow fading components to obtain a three-dimensional electromagnetic spectrum map of the area to be mapped. The present invention comprehensively considers the characteristics of the scene and the optimization of sampling positions, and only needs to collect spectrum data from a small amount of key locations to achieve high-precision spectrum mapping.

The invention discloses an electromagnetic spectrum identification and tracking algorithm based on transform. Comprising the following steps: step 1, electromagnetic spectrum signal acquisition, step 2, electromagnetic spectrum data preprocessing, step 3, Transform model construction, step 4, target identification, step 5, frequency hopping logic analysis, step 6, target signal parameter acquisition, step 7, target signal type customization, step 8, alarm and countering processing, step 9, historical information playback, and step 10, electromagnetic spectrum signal acquisition, step 5, frequency hopping logic analysis, step 6, target signal parameter acquisition, step 7, target signal type customization, step 8, alarm and countering processing, step 9, historical information playback, and step 10. And optimizing and updating the algorithm. According to the method, interlaced signals in a complex electromagnetic environment are accurately identified, long-distance weak signals are detected with high sensitivity, frequency hopping signals are accurately tracked, the false alarm rate and the missing report rate are reduced, preprocessing is optimized through a band-pass filter and wavelet transform, the feature extraction capacity is improved through a Transform model, the type of a user-defined target signal is supported, continuous optimization is carried out according to feedback, and the detection accuracy is improved. And high performance and adaptability are maintained.

Disclosed are systems, devices and methods for quantifying unique features of an object such as an artistic work to identify and authenticate the object and specific characteristics thereof using multi-spectral diagnostic characterization techniques and analytical algorithms. In some aspects, a method for creating an identification for an object includes acquiring image data of an object in two or more electromagnetic spectrums along a coordinated array of sample regions of the object; analyzing the acquired image data to produce a quantitative data set including specific characteristics of the object associated with the two or more electromagnetic spectrums for each sample region; generating a digital identification associated with a unique data fingerprint, based on the specific characteristics, in which the digital identification solely corresponds to the object; and storing the generated digital identification.

The invention discloses an unmanned aerial vehicle three-dimensional path planning method and system for electromagnetic spectrum data acquisition, and belongs to the technical field of path planning, the unmanned aerial vehicle three-dimensional path planning method for electromagnetic spectrum data acquisition comprises the following steps: rasterizing a three-dimensional target area to be measured, and marking the obstacle state of each grid; selecting data sampling height layers, and extracting grid slices corresponding to each selected height layer to form a plurality of two-dimensional grid maps; selecting a first sampling point set of each height layer; determining a second sampling point set; based on the first sampling point set and the second sampling point set of each height layer, a final sampling point set is formed through integration; executing a two-dimensional grid path planning algorithm of a fixed starting point at each height layer, and generating a sampling path of each height layer; and connecting the sampling paths of each height layer end to end to form a three-dimensional sampling path. According to the method, the accuracy of spectrum situation construction can be improved while the flight energy consumption is reduced.

This invention relates to the field of radio technology, specifically disclosing a method and system for constructing a high-precision electromagnetic spectrum map of a terrain-undulating environment. The method includes: acquiring spectrum data within a region to be constructed, the spectrum data including signal strength and geographical location; combining the terrain undulation elevation information of the region to be constructed with the signal strength and matching it with observation points according to resolution to obtain the terrain undulation elevation information of the observation points; establishing a model for the terrain undulation elevation information of the observation points based on a Gaussian regression process, and optimizing the model using hyperparameters of a kernel function; and constructing a spectrum map of the region to be constructed using the monitored values ​​of the spectrum data within the region to be constructed as input, according to the posterior probability estimation formula of the Gaussian regression process.

According to an example aspect, there is provided a military decoy laminate (100) comprising a plastic substrate (110) having a first side (111) and an opposite second side (112); a first reinforcing layer (121) on the first side (111) of the plastic substrate (110); a second reinforcing layer (122) on the second side (112) of the plastic substrate (110); and one or more than one functional layer (130) on the first side (111) and / or the second side (112) of the plastic substrate (110), which functional layer(s) (130) is / are configured to output a spectral response observable in an electromagnetic spectrum.

The application discloses a hexagon-based electromagnetic spectrum monitoring network deployment method, which comprises the following steps: constructing a minimum circumscribed rectangle of an electromagnetic spectrum coverage task area, establishing a plane rectangular coordinate system with any two adjacent sides of the minimum circumscribed rectangle as an x-axis and a y-axis; taking a center point of a regular hexagon as a center point of the regular hexagon, taking a side length of the regular hexagon as the side length of the regular hexagon, and making the x-axis coincide with a horizontal symmetry axis of the regular hexagon to construct a first regular hexagon; translating the first regular hexagon to the y-axis direction to obtain a second regular hexagon; translating the first regular hexagon to the x-axis direction and then to the y-axis direction to obtain a third regular hexagon, and the process is repeated until the regular hexagon grid covers the minimum circumscribed rectangle and the number of the regular hexagons is the least; and taking a sensing radius of an electromagnetic spectrum monitoring device as the sensing radius of the electromagnetic spectrum monitoring device. The application can effectively process and solve the task area boundary coverage problem, and is easy to plan, design and solve the number of the electromagnetic spectrum monitoring devices in the task area.

The application discloses a frequency planning method based on an electromagnetic spectrum large model, aiming at solving the problems of low analysis efficiency caused by relying on manual checking of a large number of ITU documents in the existing frequency planning process, and the problem of incomplete analysis results caused by a single retrieval mode being difficult to simultaneously consider information correlation and diversity. The method comprises the following steps: step one, preprocessing ITU related documents, and adopting a vector embedding model to construct a vectorized knowledge base; step two, acquiring service parameters and scene parameters input by a user; step three, based on a multi-path retrieval mechanism jointly driven by a service-scene, retrieving the vector knowledge base; step four, utilizing an electromagnetic spectrum large model, combining the retrieval result to carry out spectrum compatibility and planning feasibility analysis; and step five, outputting a frequency planning feasibility analysis result. Through deep fusion of the vector knowledge base and the electromagnetic spectrum large model, the application effectively improves the intelligent level, accuracy and efficiency of frequency planning, and provides a new paradigm for rational allocation of spectrum resources and multi-service coexistence analysis.

The invention relates to the technical field of electromagnetic spectrum maps, and particularly discloses a three-dimensional spectrum map generation method, which comprises the following steps: dividing a three-dimensional geographic space of an electromagnetic environment to be measured into grids, and constructing a three-dimensional spectrum map tensor according to multiple pieces of spectrum data in the grids; the frequency spectrum data is the average received signal strength of one time slot in the grid; slicing the spectrum map tensor to obtain tensor slices, and calculating a local factor of the tensor slices to obtain a tensor local factor; applying smooth constraint to the tensor local factor to obtain a local smooth tensor; modeling according to the local smooth tensor to obtain a completion model; and solving the completion model by adopting an ADMM algorithm to obtain a completed three-dimensional electromagnetic spectrum map. According to the three-dimensional spectrum map generation method provided by the invention, the three-dimensional electromagnetic spectrum map can be accurately and efficiently constructed by using limited sampling data in a multi-radiation source scene.