129 results about "Electromagnetic spectrum" patented technology

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 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 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.

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.

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 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.

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 discloses a reasoning method and system for complementing the three-dimensional space position of an electromagnetic radiation source based on spectrum situation data, and the method comprises the steps: obtaining the GIS data of a target region, constructing a geographic model of the target region, simulating the channel loss between a radiation source and each receiving point in the geographic model through a dominant path propagation model, obtaining the intensity value of an original received signal, and calculating the intensity value of the original received signal. Forming electromagnetic spectrum situation initial data; complementing a received signal strength vacant area in the electromagnetic spectrum situation initial data to form a three-dimensional electromagnetic spectrum situation matrix, and storing the matrix locally according to a radiation source position index; the three-dimensional electromagnetic spectrum situation matrix is input into a pre-trained neural network, a corresponding three-dimensional probability thermodynamic diagram is output, and the position coordinate with the maximum probability value in the thermodynamic diagram is the corresponding radiation source position. The method has good expansibility, and can be widely applied to complex scenes depending on spatial spectrum sensing, such as spectrum resource planning, electromagnetic situation evaluation and network electric countermeasure.

A vegetation monitoring device with at least one camera unit (28) for monitoring vegetation health in a garden (10), wherein the at least one camera unit (28) is configured to detect the garden area (30, 32, 34) in at least a first range of the electromagnetic spectrum, in particular in the visible light range, and in at least a second region of the electromagnetic spectrum, in particular in the infrared range, in order to determine at least one vegetation index of at least one garden area (30, 32, 34) of the garden (10), in particular in the region of visible light, and in at least one second region of the electromagnetic spectrum, in particular in the infrared range, wherein the camera unit (28) is provided for an arrangement at least substantially above ground level of the garden (10) and for an at least substantially stationary arrangement outside or in the vicinity of the garden (10), and a vegetation monitoring system is proposed.

Provided are glasses containing silicon dioxide (Si02) and / or boron oxide (B203) as glass formers and having a refractive index n greater than or equal to 1.9 d (at 587.56 nm) and a density (measured at 25 °C) less than or equal to 5.5 g / cm 3 Optionally, the glasses can be characterized by high transmission in the visible and near-ultraviolet (near-UV) range of the electromagnetic spectrum and / or good glass forming ability.

The invention relates to a three-dimensional stacked microsystem for communication, navigation and electromagnetic spectrum monitoring application. The three-dimensional stacked microsystem comprises a high-density interconnection substrate; the plurality of functional core particles comprise radio frequency direct sampling core particles and digital baseband processing core particles; the at least one radio frequency channel micro module is arranged on the first side of the high-density interconnection substrate; area array vertical electrical interconnection among the radio frequency channel micro module, the functional core particles and the high-density interconnection substrate and among the functional core particles is realized through micro salient points. The internal structure of the microsystem does not comprise a lead bonding structure. According to the invention, a lead bonding process can be abandoned, a full-flip and wafer-level stacking technology is adopted, and the limitation of volume, weight and signal bandwidth is further broken through through a more optimized radio frequency direct acquisition layout and a full-silicon-based cavity structure, so that the urgent demand of a lightweight unmanned platform on a conduction, guidance and supervision integrated load is met; the system has the characteristics of high performance, miniaturization and low power consumption.

A method for making an uncoated fine mesh design on a coated surface. The aim of this design is to completely or partially reflect or transmit specific frequencies of the electromagnetic spectrum. Such design is referred to as a frequency selective surface (FSS). More particularly, the invention relates to masking a portion of the surface of the substrate prior to deposition of the coating and later removing the mask by water washing in the process, leaving the designed fine mesh FSS pattern.

The invention relates to an optical article comprising at least: (a) a substrate having a front main face and with a rear main face: (b) at least one photochromic compound that is able to undergo a transformation from one state, defined as “deactivated state” to another state, defined as “activated state” in response to predetermined wavelengths of the electromagnetic spectrum, (c) coated directly or indirectly onto the front face of said substrate (a), a mirror coating, said mirror coating—comprising at least two layers having a low refractive index which is lower than 1.55, defined as “LI layer”, and at least two layers having a high refractive index which is equal to or higher than 1.55, defined as “HI layer”,—and having a mean light reflection factor for wavelengths ranging into said predetermined wavelengths of the electromagnetic spectrum, defined as Rm(predetermined spectrum) that is lower than or equal to 1.0%, for an angle of incidence of 15°; a mean light reflection factor in the visible region Rv that is lower than or equal to 10.0% for an angle of incidence of 15°; and an optical robustness corresponding to the standard deviation of said mean light reflection factor in the visible region Rv, defined as “σRv” that is lower than or equal to 0.7% for an angle of incidence of 15°.

The invention relates to the field of electromagnetic spectrum, and provides a lightweight high-precision signal time difference extraction method, device and equipment, a medium and a product, and the method comprises the steps: two stations sample signal sampling data; performing signal processing on the signal sampling data to form pulse description word sets of the two stations and initial signal sampling data in one-to-one correspondence with pulse description words, and transmitting the pulse description word sets and the initial signal sampling data to a data center; pulse description word matching is carried out based on the pulse description word set in the data center, and signal time difference extraction is completed based on initial signal sampling data. According to the method, the cost problem caused by large link transmission bandwidth requirement, large data processing calculation amount and the like confronted by original signal sampling data mutual transmission is solved, high-precision time difference extraction at a low transmission rate can be realized, the resource processing requirement is low, and the method can adapt to an application scene of multi-target high-precision positioning.

The embodiment of the invention provides a multi-site collaborative electromagnetic spectrum situation prediction method based on multi-source data fusion and an attention mechanism, and the method comprises the steps: 1, collecting spectrum observation data, spatial data and meteorological data of multiple sites, and carrying out the data preprocessing; step 2, based on prior knowledge and GIS data, calculating a theoretical field intensity value of a known emission source at each monitoring station by using a radio wave propagation model; step 3, constructing a multi-branch fusion neural network MFNN based on 3D-CNN, LSTM, GCN and MLP, extracting joint feature representation of multi-source data in the step 1 and the step 2, and introducing an adaptive attention mechanism to perform weighted fusion on each branch feature; and 4, generating a predicted value of a future frequency spectrum state through a prediction output layer, and performing data inversion to obtain a physical power value to realize channel state inference. Structured information capable of directly driving a decision is output through data inversion and channel state inference.

The invention discloses an unmanned aerial vehicle detection method and device, relates to the technical field of unmanned aerial vehicle detection, and aims to solve the problems of high cost and complex system caused by the fact that detection can be realized only by configuring expensive equipment when an unmanned aerial vehicle uses a wireless silent scene in an existing unmanned aerial vehicle detection method. The method comprises the following steps: acquiring electromagnetic spectrum data of a monitoring area; extracting an EMI noise signal from the electromagnetic spectrum data by adopting a signal modulation mode recognition algorithm; measuring the bandwidth of the EMI noise signal, and determining the noise source type of the EMI noise signal according to the bandwidth; and calculating a correlation coefficient between the frequency spectrum of the EMI noise signal and the frequency spectrum fingerprint, and determining the unmanned aerial vehicle type corresponding to the frequency spectrum fingerprint with the maximum correlation coefficient as a target unmanned aerial vehicle type. The unmanned aerial vehicle detection method provided by the invention is used for unmanned aerial vehicle detection when the unmanned aerial vehicle is in a wireless silent scene.

Rearview arrangement for a vehicle, the rearview arrangement encompassing: a reflective element designed to provide a driver of the vehicle with a rearward view in relation to the vehicle, wherein the reflective element is substantially transparent in an infrared region of the electromagnetic spectrum; an infrared lighting source arranged behind the reflective element and configured to emit infrared light through the reflective element to illuminate a field of view with infrared light, wherein the field of view comprises at least part of a vehicle interior; and an optical element arranged behind the reflective element and designed to direct infrared light from the infrared illumination source onto the field of view, comprising the optical element: a shaped section consisting of a visibly opaque material that is substantially transparent to infrared light, wherein the shaped section has a front surface and a rear surface; and a reflector arranged on the rear surface of the shaped section and designed to substantially reflect infrared light emitted by the illumination source that passes through the shaped section in the direction of the field of view.

The application discloses an oily structural color pigment ink and application thereof, and belongs to the technical field of photonic crystal material preparation. Components of the oily structural color pigment ink include at least one block polymer brush, at least one resin or at least one precursor of the resin, and at least one organic solvent. The oily structural color pigment ink provided by the application is a layered structural color material obtained by self-assembly based on the microphase separation principle of the block polymer brush. The provided oily structural color pigment ink can be compatible with most common pigment coloring methods, including but not limited to screen printing, spraying, inkjet printing and intaglio printing. The structural color of the oily structural color pigment ink is not limited to the visible light band, and covers ultraviolet spectrum, visible spectrum and infrared spectrum, and the wavelength range of the covered electromagnetic spectrum is 200 nm to 2000 nm.

The application provides an electromagnetic suppression maximum distance prediction method, device, equipment and storage medium, and particularly relates to the technical field of electromagnetic spectrum management and control. The method comprises the following steps: acquiring electromagnetic management and control equipment spectrum characteristic parameters and suppressed target radio station spectrum characteristic parameters; calculating minimum harmful interference power, a frequency suppression factor and interference equivalent radiation power; calculating according to the electromagnetic management and control equipment spectrum characteristic parameters, the suppressed target radio station spectrum characteristic parameters, the frequency suppression factor, the minimum harmful interference power and the interference equivalent radiation power; and considering the earth great circle line-of-sight blocking factor to predict the electromagnetic suppression maximum distance. The application solves the problems that the existing electromagnetic management and control situation has a single influencing factor and low universality and low operation efficiency caused by field strength vector operation in the maximum distance prediction method, thereby improving the practicability of displaying the maximum management and control region of the electromagnetic management and control equipment in the electromagnetic management and control situation presentation, and improving the efficiency and accuracy of the electromagnetic management and control.

The present application relates to the technical field of electromagnetic spectrum management, more particularly to a light spectrum prediction method based on knowledge distillation, comprising the following steps: S1, pre-processing the received spectrum data; S2, determining the step of input data according to the time domain autocorrelation of the collected spectrum data; S3, constructing a spectrum prediction network model based on a knowledge distillation strategy; S4, training the spectrum prediction network model using training set data; S5, determining whether the training is completed; if yes, inputting the training set data into the trained spectrum prediction network model, obtaining the output of the prediction result and ending the training process; if no, returning to S4 after adding one to the iteration number of the training. The present application introduces knowledge in the technical field of knowledge distillation, overcomes the model complexity of traditional deep learning networks, and has good applicability in small sample cases.

The invention provides a radiation source positioning method and device of an electromagnetic signal, electronic equipment and a storage medium, and relates to the technical field of electromagnetic spectrum detection. The method comprises the following steps: receiving electromagnetic signals by using an antenna array of a master station, and obtaining a measurement phase difference group of the electromagnetic signals; comparing the measurement phase difference group with a sample phase difference group library of the antenna array to obtain a matched sample phase difference group and a sample incident angle so as to obtain an electromagnetic signal incident angle; the radiation source position of the electromagnetic signal is determined based on the time difference information of the electromagnetic signal and the incident angle, and the time difference information comprises the time difference of the electromagnetic signal received by the main station and the auxiliary station. According to the invention, the measurement phase difference group is matched according to the sample phase difference group library, the incident angle can be accurately determined in a complex and changeable electromagnetic environment, and the accuracy of subsequently determining the position of the radiation source is further improved. According to the invention, the position of the radiation source is solved according to the time difference information and the incident angle, and accurate prediction of the position of the radiation source is realized.

The present invention provides diatomaceous earth and borosilicate glass having a high refractive index, low density, and high transmittance to blue light. [Solution] It contains silicon dioxide (SiO2) and / or boron oxide (B2O3) as a glass-forming agent and has a refractive index n of 1.80 or higher when measured at 587.56 nm. d And, when measured at 25℃, it was 5.5 g / cm³. 3 A glass is provided having the following density and, in particular, high transmittance to blue light. Optionally, the glass may be characterized by high transmittance in the visible and near-ultraviolet (near-UV) ranges of the electromagnetic spectrum, and / or good glass-forming properties.

The invention provides an intelligent judgment method for relative advantages and disadvantages of an electromagnetic spectrum situation, and belongs to the crossing field of electromagnetic spectrum management and artificial intelligence. The method comprises the following steps: constructing an electromagnetic spectrum situation judgment data set based on expert experience and domain knowledge, constructing an electromagnetic spectrum situation advantage and disadvantage judgment model, training a cross-contrast deep neural network by using the data set, and carrying out advantage and disadvantage judgment on the input electromagnetic spectrum situation. The method constructs an electromagnetic spectrum situation determination data set based on expert experience and domain knowledge, designs a cross-contrast deep neural network capable of extracting advantages and disadvantages of the electromagnetic spectrum situation, forms an electromagnetic spectrum situation advantages and disadvantages determination model, breaks through mathematical mapping of a complex determination relationship, realizes relative advantages and disadvantages intelligent determination, and improves the accuracy of electromagnetic spectrum situation determination. The structure is clear and easy for engineering realization.

According to the interferometer system antenna real-time calibration method based on dynamic fitting, a phase correction table building method and a physical model parameter method thought are combined, a phase difference correction number and a matched weight table updating method are provided, a mathematical model calibration parameter fitting thought is combined, and the calibration accuracy of the interferometer system antenna is improved. Real-time parameter fitting updating is carried out on the phase correction table on line, and the thought is suitable for real-time processing of the motion platform and can effectively shorten the table building period; a judgment strategy based on azimuth pitch angle external polygon table building coverage and mathematical model parameter fitting residual conditions is designed, and the requirement for automatic calibration and use of the electromagnetic spectrum monitoring motion platform can be met.

Embodiments of the present application disclose a radiation source positioning method, a computer device and a computer storage medium. A general radiation source positioning technology based on an efficient neural network is proposed. For a light-weight electromagnetic spectrum sensing terminal, the energy load is limited, the computing power is limited, the computing chip carried by the terminal has limited operators, and the real-time requirement of the positioning algorithm. Therefore, research on a general target positioning technology based on an efficient neural network is needed. In the embodiments, network parameters are optimally selected to realize a sensing field covering a full image, so that the computing cost is reduced, the output delay is reduced, the computing efficiency of the neural network model is improved, and a higher degree of general operator is used, so that the algorithm can be deployed to a wider computing platform, and practical deployment is possible.