Lightning positioning method and system based on multi-source data fusion

Abstract

The invention discloses a thunder and lightning positioning method and system based on multi-source data fusion, and belongs to the technical field of thunder and lightning monitoring and positioning. The method comprises the following steps: in a preset time window, collecting first and second arrival time of a lightning event received by each ground lightning detection device, and calculating the arrival time difference; and extracting a lightning detection distance, a capture time difference and an observation included angle in combination with the lightning area image, obtaining an electric field change rate, a radar reflectivity and an equipment distance, substituting into a combined lightning positioning formula, and calculating a space distance between a lightning striking point and the first receiving equipment. Through the position information of the equipment, the geographical coordinate of the lightning striking point is calculated. According to the scheme, the spatial resolution and accuracy of lightning positioning can be effectively improved, positioning errors caused by a traditional radar or single-point monitoring method are reduced, simultaneous positioning of a plurality of lightning striking points is supported, and accurate data support and spatial decision basis are provided for subsequent lightning risk early warning, power equipment protection and disaster traceability.

Description

Technical Field

[0001] The present application belongs to the technical field of lightning monitoring and positioning, and specifically relates to a lightning positioning method and system based on multi-source data fusion. Background Art

[0002] Lightning activity, a violent natural discharge phenomenon, is instantaneous, highly destructive, and has complex spatial distribution. Its precise positioning is of great significance to power facility protection, aviation safety, forest fire prevention, and other fields. With the expansion of power grids and the frequent occurrence of extreme weather, traditional single-source lightning location technology has become unable to meet the needs of high-precision, multi-dimensional monitoring. Especially in complex terrain or areas with dense lightning, a single data source is susceptible to environmental interference, equipment errors, and algorithmic limitations, resulting in significant deviations in positioning results and an inability to support refined risk assessment and emergency decision-making. Therefore, there is an urgent need to integrate multi-dimensional observation data and build a collaborative location model to overcome the bottlenecks of existing technologies.

[0003] Existing lightning location technologies mainly achieve positioning through a single physical quantity or data source: the time difference of arrival method (TDOA) uses the time difference between ground detection equipment receiving lightning electromagnetic waves to calculate the position, the electromagnetic field direction method determines the lightning position by the intersection of the magnetic field loop directions, and the radar reflectivity method inverts the lightning occurrence area based on the echo intensity captured by the meteorological radar.

[0004] The shortcomings of existing lightning location technology are mainly reflected in four aspects: First, the data dimension is single, relying only on electromagnetic waves or radar data, and lacks the integration of key parameters such as the electric field change rate and equipment spacing, resulting in insufficient modeling capabilities for the dynamic evolution process of the lightning channel; second, it is unable to handle multiple strike point scenarios. It assumes that a single lightning event only corresponds to a single strike point, resulting in the neglect of the spatiotemporal correlation of multiple discharges, causing underreporting or positioning offset; third, it has poor environmental adaptability. In complex terrains such as mountainous areas and cities, factors such as equipment spacing and observation angle will significantly amplify positioning errors, and traditional algorithms lack an adaptive correction mechanism; fourth, the accuracy is limited. Affected by sensor noise, signal attenuation and algorithm simplification assumptions, the positioning error is generally on the order of hundreds of meters, which makes it difficult to meet the high-precision application requirements such as differentiated lightning protection for power grids. Summary of the Invention

[0005] The embodiments of the present application provide a lightning location method and system based on multi-source data fusion, which solves the shortcomings of existing lightning location technology mainly reflected in four aspects: first, the data dimension is single, relying only on electromagnetic waves or radar data, and lacks the integration of key parameters such as the electric field change rate and device spacing, resulting in insufficient modeling capabilities for the dynamic evolution process of the lightning channel; second, it is unable to handle multiple strike point scenarios, and assumes that a single lightning event corresponds to only a single strike point, resulting in the neglect of the spatiotemporal correlation of multiple discharges, causing underreporting or positioning offset; third, it has poor environmental adaptability. In complex terrains such as mountainous areas and cities, factors such as device spacing and observation angle will significantly amplify positioning errors, and traditional algorithms lack an adaptive correction mechanism; fourth, the accuracy is limited. Affected by sensor noise, signal attenuation and algorithm simplification assumptions, the positioning error is generally on the order of hundreds of meters, which makes it difficult to meet the needs of high-precision applications such as differentiated lightning protection for power grids.

[0006] In a first aspect, an embodiment of the present application provides a lightning location method based on multi-source data fusion, the method comprising: Obtaining a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculating an arrival time difference of each lightning event based on the first arrival time and the second arrival time; Acquire a lightning area image corresponding to each lightning event, and determine the lightning detection distance, lightning capture time difference, and lightning observation angle based on the lightning area image; Obtain the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, as well as the equipment distance between each ground lightning detection device that collected each lightning event. Calculate the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that received the lightning event based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula; the number of lightning strike points is at least two. The location information of the first ground lightning detection device that receives the lightning event is obtained, and the geographical coordinates of each lightning strike point are calculated based on the location information and the spatial distance.

[0007] In a second aspect, an embodiment of the present application provides a lightning location system based on multi-source data fusion, the system comprising: an arrival time difference calculation module, configured to obtain a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculate an arrival time difference of each lightning event based on the first arrival time and the second arrival time; A lightning area image analysis module is used to obtain a lightning area image corresponding to each lightning event, and determine the lightning detection distance, lightning capture time difference, and lightning observation angle based on the lightning area image; A spatial distance calculation module is used to obtain the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, as well as the equipment distance between each ground lightning detection device that collects each lightning event. Based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula, it calculates the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that receives the lightning event; the number of lightning strike points is at least two; The geographic coordinate calculation module is used to obtain the position information of the first ground lightning detection device that receives the lightning event, and calculate the geographic coordinates of each lightning strike point based on the position information and the spatial distance.

[0008] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0009] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] In an embodiment of the present application, a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window are obtained, and the arrival time difference of each lightning event is calculated based on the first arrival time and the second arrival time; an image of a lightning area corresponding to each lightning event is obtained, and the lightning detection distance, the lightning capture time difference, and the lightning observation angle are determined based on the lightning area image; the electric field change rate and the radar reflectivity of the lightning area corresponding to each lightning event and the device distance between each ground lightning detection device that collects each lightning event are obtained, and the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that receives the lightning event is calculated based on the arrival time difference, the lightning detection distance, the lightning capture time difference, the lightning observation angle, the electric field change rate, the radar reflectivity, the device distance, and a preset joint lightning positioning formula; wherein the number of lightning strike points is at least two; the position information of the first ground lightning detection device that receives the lightning event is obtained, and the geographic coordinates of each lightning strike point are calculated based on the position information and the spatial distance. The above-mentioned lightning location method based on multi-source data fusion can effectively improve the spatial resolution and accuracy of lightning location, reduce the positioning error caused by traditional radar or single-point monitoring methods, support the simultaneous positioning of multiple lightning strike points, and provide accurate data support and spatial decision-making basis for subsequent lightning risk warning, power equipment protection and disaster tracing. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 This is a flow chart of a lightning location method based on multi-source data fusion provided in Example 1 of the present application; Figure 2 This is a flow chart of a lightning location method based on multi-source data fusion provided in Example 2 of the present application; Figure 3 This is a structural diagram of a lightning location system based on multi-source data fusion provided in Example 3 of the present application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in Example 4 of the present application. DETAILED DESCRIPTION

[0012] To further clarify the objectives, technical solutions, and advantages of this application, specific embodiments of the present application are described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are intended only to illustrate this application and are not intended to limit it. It should also be noted that, for ease of description, the drawings only illustrate portions relevant to this application, not all of them. Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts depict the various operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process may terminate upon completion of its operations, but may also include additional steps not shown in the accompanying drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, or the like.

[0013] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0014] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0015] Below, in conjunction with the accompanying drawings, an RSMC chip, a chip multi-stage startup method, and a Beidou communication and navigation device provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0016] Example 1 Figure 1 This is a flow chart of the lightning location method based on multi-source data fusion provided in Example 1 of this application. Figure 1 As shown, the specific steps include: S101 , obtaining a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculating an arrival time difference of each lightning event based on the first arrival time and the second arrival time.

[0017] The preset time window can be a continuous time interval set by the system, which is used to synchronously analyze the lightning signals collected by multiple ground lightning detection devices within this time period to ensure that the lightning events detected by different devices belong to the same lightning strike activity.

[0018] Ground lightning detection equipment can be a device installed on the ground that has the ability to receive lightning electromagnetic waves or electric field signals. It usually includes a low-frequency electromagnetic induction antenna, an electric field sensor, a time synchronization module (such as GPS), etc., and can be used to receive and record electromagnetic signals or electric field changes generated by lightning discharges.

[0019] A lightning event can be a complete process of lightning activity triggered by thundercloud discharge, a physical event with clear starting time and spatial positioning characteristics, and can be recorded by one or more detection devices.

[0020] The first arrival time can be the time point when a lightning event signal is first detected by multiple ground lightning detection devices. This time represents the time when the lightning signal is first received by the ground system.

[0021] The second arrival time may be a time point at which the second detection device detects the signal of the same lightning event relative to the first arrival time, and is used to construct an arrival time difference to support subsequent lightning location.

[0022] The time difference between the first and second arrival times is used to calculate the propagation delay of a lightning wave at different detection points during propagation. This value is a key input parameter in lightning location algorithms (such as TOA and TDOA).

[0023] A preset time window can be set, ranging from hundreds of milliseconds to several seconds, depending on the system's positioning accuracy requirements. Whenever a lightning event occurs, multiple ground-based lightning detection devices deployed at different locations collect the signal generated by the lightning event through electric field induction or electromagnetic wave signal induction. The internal clock system of each detection device is typically connected to a high-precision time synchronization source (such as a GPS timing system) to ensure that all devices record external signals with a unified time reference. At the data receiving end, the system clusters and compares the data collected by each device using event identification algorithms (such as waveform feature matching or signal similarity matching) to identify which signals belong to the same lightning event. For the same event, the time recorded by the device that receives the event signal earliest among all detection devices is recorded as the first arrival time, and the second arrival time is recorded as the second arrival time. The system then calculates the arrival time difference of the lightning event by directly taking the difference between the two time records.

[0024] S102 , obtaining a lightning area image corresponding to each lightning event, and determining a lightning detection distance, a lightning capture time difference, and a lightning observation angle according to the lightning area image.

[0025] A lightning area image can be image data captured or scanned by remote sensing equipment (such as infrared imagers, visible light cameras, or lightning imagers) or radar systems during a lightning event. This image typically includes information such as the lightning discharge intensity distribution, the visible trajectory of the lightning channel, and cloud distribution outlines, and is tagged with a timestamp and geographic coordinates.

[0026] The lightning detection range is the spatial distance from the location of a ground-based lightning detection device to the center of lightning activity (or the center of a lightning channel) observed in the image. This parameter is obtained by projecting lightning pixels in the image onto known geographic coordinates, and then back-calculating the distance using image calibration information and the location of the detection device.

[0027] Lightning capture time difference refers to the time difference between different lightning detection devices (such as cameras or sensors) when observing the same lightning event due to differences in imaging frame rate, response speed, or signal processing time. This time difference must be compensated in subsequent signal timing calibration or positioning algorithms to ensure consistency and accuracy in spatial calculations.

[0028] The lightning observation angle can be formed by pointing two or more lightning detection devices at the lightning occurrence point. This angle can be calculated from the angle between the direction vector of the detection device and the lightning event location direction. It is used to construct a multi-view lightning location model and improve spatial inversion accuracy.

[0029] To obtain images of the lightning area corresponding to each lightning event, the system utilizes multi-source remote sensing imaging equipment (such as high-resolution optical imagers, high-frame-rate electromagnetic imaging equipment, or weather radar systems) deployed within the target area to capture real-time images of the lightning activity area with a preset time accuracy (e.g., millisecond-level). Each lightning area image carries a precise timestamp and the geographic coordinates of the observation equipment, and covers the visible range of the lightning event. For each lightning event, the system extracts the closest image frame from the image sequence based on the first arrival time or unified lightning event number recorded by the ground-based lightning detection equipment. Using image enhancement and edge detection algorithms, the system extracts the brightness intensity region of the electro-optical channel in the image, accurately identifying the pixel trajectory of the lightning channel in the image. Using device calibration parameters (including field of view angle, focal length, attitude matrix, and imaging azimuth), the pixel coordinates are projected into a real-world three-dimensional coordinate system. Combining the Euclidean distance between the lightning channel's starting point in the image and the device's coordinates, the system calculates the lightning event's detection distance relative to the device (i.e., the spatial distance from the device to the lightning starting point, in meters). If the same lightning event is recorded by multiple ground imaging devices, the timestamps of the corresponding image frames are extracted and interpolated to calculate the frame difference time between the different devices that recorded the lightning event. The lightning capture time difference is obtained, which is used to evaluate the time consistency of the lightning channel when it is observed from different angles. In addition, the system further calculates the spatial angle between the line of sight direction vector of each observation device and the main direction vector of the lightning channel, and obtains the lightning observation angle of the device in degrees through the cosine theorem or vector projection relationship. This angle can be used to compensate for lightning imaging errors and spatial positioning deviations. By extracting the above three core parameters: lightning detection distance, lightning capture time difference and lightning observation angle, they can be used as important input feature parameters for subsequent joint lightning positioning, multi-perspective reconstruction and lightning hazard assessment.

[0030] S103, obtaining the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, and the equipment distance between each ground lightning detection equipment that collects each lightning event, and calculating the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection equipment that receives the lightning event based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula; wherein the number of lightning strike points is at least two.

[0031] A lightning zone refers to a spatial range where electromagnetic activity is significantly enhanced when a lightning event occurs.

[0032] The electric field change rate can refer to the rate of change of the electric field intensity in the lightning area per unit time, usually in units of kV / m / s or V / m / ms.

[0033] Radar reflectivity can be an indication of the energy intensity of a radar signal reflected from a target object (such as precipitation particles), and the unit is usually dBZ.

[0034] Device distance may refer to the geometric spatial distance between a group of ground lightning detection devices (such as TOA, VLF or LF antennas) used for lightning location, in meters (m).

[0035] Spatial distance can refer to the three-dimensional Euclidean distance between a lightning strike point and the first ground lightning detection equipment that receives the lightning event, with the unit being meter (m).

[0036] First, the system obtains the lightning area corresponding to each lightning event. This area is determined by combining the geographic coordinates of the strike point recorded by the lightning location system and synchronized meteorological radar imagery, clarifying the spatial extent of the lightning activity. Based on this, the system uses data on the instantaneous electric field changes during lightning discharges, recorded by multiple electric field sensors within the lightning area, to extract the electric field change rate corresponding to each lightning event. This parameter reflects the speed and intensity of charge released by lightning. Simultaneously, the system retrieves radar reflectivity image data corresponding to the lightning area from the meteorological radar platform, analyzes and obtains the radar reflectivity of each lightning event in the corresponding area. The radar reflectivity, expressed in dBZ, reflects the liquid or solid water content of the lightning cloud, thus assisting in determining the structural characteristics of the lightning activity. Furthermore, the system calculates the device distances for each lightning event by deriving the fixed spatial baseline distances between ground-based lightning detection equipment (such as TOA receivers and VLF antennas) from a pre-set geographic information database based on the deployment coordinates of each lightning detection device. Combined with the above data, the system further uses the following pre-calculated parameters: the arrival time difference of each lightning event (that is, the time difference between the first and second devices receiving the same lightning pulse); the lightning detection distance of the lightning signal in each direction; the lightning capture time difference between different detection devices capturing the lightning signal; the lightning observation angle between the lightning signal incident path and the device array baseline; finally, the system substitutes the above variables into the preset joint lightning location formula, which is based on the multi-base station time difference positioning (TDOA) model and integrates a three-dimensional positioning algorithm (such as the spherical intersection positioning method or the least squares method) to calculate the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that received the lightning event.

[0037] Based on the above technical solution, an optional, preset joint lightning location formula is: in, is the spatial distance; c is the speed of light; is the arrival time difference; is the preset refractive index correction coefficient; Calibrate weight coefficients for preset satellites; Lightning detection distance; is the device distance; is the lightning observation angle; Capturing time differences for thunder and lightning; is the preset electric field response weight coefficient; is the rate of change of the electric field; Correction weight coefficient for preset radar; is the radar reflectivity.

[0038] In this solution, the preset refractive index correction coefficient can be a coefficient used to correct the speed of light by taking into account the phase velocity changes caused by air humidity, temperature, pressure, etc. when lightning electromagnetic waves propagate in the atmosphere.

[0039] The preset satellite calibration weight coefficient can be used to adjust the degree of influence of the lightning area image information observed by the remote sensing satellite (or meteorological satellite) on the positioning distance.

[0040] The preset electric field response weight coefficient can measure the influence of the electric field change rate on the calculation of lightning location distance, reflecting the modulation effect of charge movement on the spatial propagation path in lightning events.

[0041] The preset radar correction weight coefficient can represent the impact of radar reflectivity on the intensity and coverage of the lightning activity area, and correct the contribution of lightning spatial distribution characteristics to the positioning distance.

[0042] The preset process of the above coefficients can be achieved by constructing a data set with the actual strike points of historical lightning as the true value, combining the observation parameters such as arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity and equipment distance collected by ground lightning detection equipment, establishing a loss function that minimizes spatial error, and using optimization algorithms (such as gradient descent, genetic algorithm, etc.) to jointly train and tune the above coefficients to ensure that the preset coefficients can minimize the error between the predicted lightning strike point and the actual strike point, thereby improving the accuracy and robustness of the lightning location model.

[0043] S104: Acquire the location information of the first ground lightning detection device that receives the lightning event, and calculate the geographical coordinates of each lightning strike point according to the location information and the spatial distance.

[0044] Position information can be the precise spatial location of ground-based lightning detection devices used for lightning location. This information typically comes from a GIS platform, a measurement system, or fixed installation data. Specifically, it includes the device's longitude, latitude, and sometimes the device's altitude or installation height.

[0045] Geographic coordinates are the spatial coordinates of the lightning strike point, derived from the detection data. They are generally expressed in the following format: longitude and latitude.

[0046] First, it is necessary to obtain the location information of the first ground-based lightning detection device that received the lightning event. This information can be obtained by numbering and calibrating the detection devices deployed in the lightning monitoring network. Specifically, this includes extracting the three-dimensional spatial coordinate parameters such as the longitude, latitude, and optional altitude of the detection device as the fixed spatial reference point of the device. This location information is usually stored in the device information database or GIS platform of the lightning monitoring system and can be obtained through device number matching query. Subsequently, based on this device location information, combined with the spatial distance of the lightning event calculated previously using the joint lightning location formula (i.e., the propagation path distance from the lightning strike point to the detection device), further calculation methods such as spherical coordinate inversion algorithm, trilateration method, or time difference positioning method are used to determine the actual geographic coordinates of the lightning event.

[0047] In an embodiment of the present application, a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window are obtained, and the arrival time difference of each lightning event is calculated based on the first arrival time and the second arrival time; an image of a lightning area corresponding to each lightning event is obtained, and the lightning detection distance, the lightning capture time difference, and the lightning observation angle are determined based on the lightning area image; the electric field change rate and the radar reflectivity of the lightning area corresponding to each lightning event and the device distance between each ground lightning detection device that collects each lightning event are obtained, and the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that receives the lightning event is calculated based on the arrival time difference, the lightning detection distance, the lightning capture time difference, the lightning observation angle, the electric field change rate, the radar reflectivity, the device distance, and a preset joint lightning positioning formula; wherein the number of lightning strike points is at least two; the position information of the first ground lightning detection device that receives the lightning event is obtained, and the geographic coordinates of each lightning strike point are calculated based on the position information and the spatial distance. The above-mentioned lightning location method based on multi-source data fusion can effectively improve the spatial resolution and accuracy of lightning location, reduce the positioning error caused by traditional radar or single-point monitoring methods, support the simultaneous positioning of multiple lightning strike points, and provide accurate data support and spatial decision-making basis for subsequent lightning risk warning, power equipment protection and disaster tracing.

[0048] Based on the above technical solution, optionally, after calculating the geographical coordinates of each lightning strike point according to the location information and the spatial distance, the method further includes: Obtain the spatial positioning information of the power line tower, perform spatial buffer matching on the geographic coordinates and spatial positioning information, and determine the target power line tower that meets the spatial proximity relationship.

[0049] In this scheme, power line towers can refer to poles or tower structures on transmission lines. They are important infrastructure supporting high-voltage transmission cables, have clear spatial locations and asset numbers, and are recorded in the power asset database.

[0050] Spatial positioning information can refer to the spatial geographic coordinate information of power line towers, which usually includes latitude and longitude coordinates and elevation information. It can be provided by a GIS platform or a power inspection system to describe the precise location of the tower in geographic space.

[0051] The target power line tower may refer to a specific tower that is determined to be spatially adjacent to the geographic coordinates of a lightning strike (i.e., within a set buffer radius) during the process of performing lightning strike point positioning and asset matching through spatial buffer matching. This tower is a tower object that may be affected by lightning and will subsequently be the target of key analysis or early warning.

[0052] First, by accessing the power company's power asset database, the spatial location information of all power line towers is obtained, including the latitude and longitude coordinates, altitude, and unique identifier of each tower. Subsequently, combined with the geographic coordinates of the lightning strike point obtained in real time by the lightning location system, a spatial buffer analysis algorithm is used in the GIS platform to construct a buffer layer with a set radius (e.g., 50 meters) centered on each lightning strike point. Through spatial overlay operations, the system compares the lightning strike buffer zone with the distribution layer of power line towers, identifying all towers falling within the buffer zone as target power line towers that meet the spatial proximity relationship. This process is implemented based on vector layer operations and spatial indexing technology, supporting batch processing and real-time response, ensuring that critical power infrastructure that may be affected can be quickly located after a lightning strike occurs.

[0053] In this solution, by spatially buffering and matching the lightning strike point with the power line tower, target power facilities that may be affected by lightning strikes can be quickly and accurately identified, which helps to achieve automatic tracing of the source and response scheduling of lightning disasters, improve fault detection efficiency, shorten operation and maintenance response time, and enhance the safety and stability of power grid operation.

[0054] Based on the above technical solution, optionally, after determining the target power line tower that satisfies the spatial proximity relationship, the method further includes: Obtaining the occurrence timestamp of the lightning event and the operation log corresponding to the target power line tower, performing a time consistency check based on the occurrence timestamp and the time record of the operation log to confirm whether the lightning event corresponds to the target power line tower; If the lightning event corresponds to a target power line tower, the target power line tower is marked as being in a state of being affected by a lightning strike, and the target power line tower and the corresponding state of being affected by a lightning strike are recorded in a lightning disaster record database.

[0055] In this solution, the occurrence timestamp refers to the specific time at which a lightning event occurred, as recorded by the lightning detection system. This time stamp is typically expressed in high-precision UTC format, accurate to the millisecond level. This timestamp is used to align time series with other data sources to ensure temporal consistency and location accuracy.

[0056] An operation log is a file that records the operating status of a target power line tower over a specific time period, including information such as voltage, current, circuit breaker status, protection actions, and telemetry values. These logs can originate from SCADA systems, substation monitoring systems, or sensors on the equipment itself, and are used to determine whether a lightning strike has affected the equipment.

[0057] The lightning impact status refers to the physical impact or interference status of a target power line tower during a lightning event, determined based on criteria such as temporal consistency verification, spatial matching, and operational status changes. This status can be used for subsequent maintenance, risk assessment, and accident accountability.

[0058] A lightning disaster record database is a data platform dedicated to storing and managing information on various lightning events and their impacts. This includes information such as event number, occurrence time, lightning strike coordinates, affected device ID, lightning strike status, and recovery time. This information is used for historical analysis, statistical modeling, disaster review, and lightning protection optimization decision support.

[0059] The lightning location system receives lightning data collected from various ground-based lightning detection devices and extracts the timestamp of each lightning event (i.e., the standard UTC time of the lightning discharge instant, accurate to the millisecond level). The system then retrieves the operating information of target power line towers spatially adjacent to the lightning event and obtains their corresponding operation logs. These logs typically originate from SCADA systems or intelligent monitoring terminals and contain information such as time synchronization information, current and voltage waveforms, insulation state changes, arrester activation signals, and protective device tripping records. Using a time alignment algorithm, the system compares the lightning event timestamp with the times of various abnormal events recorded in the operation logs (such as voltage sags, trips, and ground current surges), determining whether they fall within a preset time window (e.g., ±2 seconds). The system further verifies the accuracy of the match by combining spatial proximity (e.g., the lightning strike point is within the tower's buffer radius). Once a target power line tower is confirmed to have exhibited an abnormal state at the time of the lightning strike and successfully matched both spatially and temporally with the lightning event, the tower is deemed to have been affected by the lightning strike. The system records this status using a standardized data structure, including tower number, lightning event ID, impact time, abnormal parameter type, severity level, and other information. This information is then written to a back-end lightning disaster record database, which supports query, statistics, report generation, and accountability analysis, ensuring that this information is traceable, accessible, and visible. This process enables precise traceability and digital registration of lightning strike impacts.

[0060] In this solution, by double-checking the temporal and spatial characteristics of lightning events, it is possible to quickly and accurately identify power line towers affected by lightning strikes and automatically enter them into the lightning disaster record database. This helps to achieve intelligent tracing, risk assessment and responsibility division of lightning disasters, improve the operation and maintenance efficiency and response speed of the power system, and reduce manual troubleshooting costs and fault missed detection rates.

[0061] Example 2 Figure 2 This is a flow chart of the lightning location method based on multi-source data fusion provided in Example 2 of this application. Figure 2 As shown, the specific steps include: S201 , obtaining a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculating an arrival time difference of each lightning event based on the first arrival time and the second arrival time.

[0062] S202 , obtaining a lightning area image corresponding to each lightning event, and determining a lightning detection distance, a lightning capture time difference, and a lightning observation angle according to the lightning area image.

[0063] S203, obtaining the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, and the equipment distance between each ground lightning detection equipment that collects each lightning event, and calculating the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection equipment that receives the lightning event based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula; wherein the number of lightning strike points is at least two.

[0064] S204: Acquire the location information of the first ground lightning detection device that receives the lightning event, and calculate the geographical coordinates of each lightning strike point according to the location information and the spatial distance.

[0065] S205 , determining spatial distribution information of key infrastructure in the lightning-affected area, and determining density of key infrastructure in the lightning-affected area based on the spatial distribution information.

[0066] Critical infrastructure refers to core projects and facilities within the lightning-affected area that have significant impacts on social operations, public safety, energy security, etc.

[0067] Spatial distribution information can refer to the two-dimensional or three-dimensional location information of critical infrastructure in geographic space.

[0068] The density of critical infrastructure can refer to the number of critical infrastructure distributed within a unit area, usually measured in units of “units / km²”.

[0069] The boundary range of the lightning-affected area can be obtained. This range can be regionally fused based on the real-time lightning strike coordinate data and radar lightning echo images provided by the meteorological lightning monitoring system to form a dynamic lightning-affected area. Then, a list of facilities that intersect with the area is extracted from the existing critical infrastructure database. The database contains spatial distribution information such as the latitude and longitude coordinates, facility type, and operation level identification of each critical infrastructure. Next, the distribution of these facilities in the area is processed using GIS spatial analysis methods, and their number per unit area is calculated, that is, the density of critical infrastructure is obtained. It can be expressed by the formula Ps=N / A, where N is the total number of facilities in the hit area and A is the area of ​​the lightning-affected area. This density value serves as an important input indicator for the subsequent normalized assessment of lightning risks and the classification of warning levels.

[0070] S206 , substituting the density of critical infrastructure into a preset normalization function to obtain a normalized density risk value of the lightning-affected area.

[0071] The pre-set normalization function can be a mathematical function that maps critical infrastructure density values ​​(e.g., the number of facilities per unit area) to a standardized risk value range (e.g., 0 to 1). This function is used to eliminate the impact of the original density values ​​in different regions, scales, or units, facilitating unified comparison and risk level calculation.

[0072] in, is the normalized density risk value; for critical infrastructure density; is the maximum value in historical data; The minimum value in the historical data.

[0073] The normalized density risk value (NDR) is a numerical value between [0, 1] or another standardized interval, representing the relative risk level of the density of critical infrastructure within a lightning-affected area. A higher NDR value indicates a dense concentration of critical infrastructure within the area, a higher potential loss from lightning, and a higher potential risk.

[0074] Based on the acquired spatial distribution information, the number of critical infrastructure within each lightning-affected grid area can be counted and divided by the area of ​​the corresponding area to calculate the critical infrastructure density (the number of facilities per unit area) for each area. Next, the maximum and minimum density values ​​within all assessment areas are collected, and the actual density value of each area is substituted into a preset normalization function to calculate the normalized density risk value corresponding to each area, ranging from 0 to 1. This standardized risk value is used in conjunction with environmental parameters to subsequently assess the lightning hazard level, ensuring density comparability and consistent risk perception across different areas. If outliers exist, preprocessing methods such as quantile truncation can be used before normalization to improve robustness.

[0075] S207, obtaining the relative humidity, wind direction angle, altitude information and historical lightning frequency of the lightning-affected area, and calculating the hazard level value of the lightning-affected area based on the radar reflectivity, electric field change rate, critical infrastructure density, normalized density risk value, relative humidity, wind direction angle, altitude information, historical lightning frequency and a preset lightning hazard calculation formula.

[0076] Relative humidity refers to the ratio of the actual water vapor content per unit volume of air to the maximum water vapor content the air can hold at that temperature, usually expressed as a percentage. In lightning impact assessments, relative humidity affects the ionization intensity of thundercloud discharges and the likelihood of lightning formation.

[0077] Wind direction refers to the angle of the wind direction relative to the north direction, with the unit of degree (°) ranging from 0° to 360°.

[0078] Altitude information refers to the vertical height of each location in the lightning-affected area relative to sea level, measured in meters (m). Areas with higher altitudes are closer to the lightning discharge layer and are more likely to be struck by lightning.

[0079] The historical lightning frequency can refer to the cumulative number of lightning events that occurred in a specific area over a period of time (such as one, five, or ten years), or the annual average number of lightning events. This metric reflects the lightning activity in a region and can serve as an important a priori factor for predicting future lightning risks.

[0080] The hazard level is a risk score representing the potential degree of lightning damage, calculated based on all of the aforementioned environmental and facility factors. It can be a continuous value (e.g., a real number between 0 and 1) or categorized into levels (e.g., low, medium, high, and very high). Its calculation relies on a pre-defined multi-factor lightning hazard calculation formula, representing the lightning threat level within the current time and space, and providing quantitative support for applications such as dynamic risk warning and emergency response.

[0081] To calculate the hazard level for a lightning-affected area, the authors first obtain the area's relative humidity (measured in %), wind direction (using a wind vane to obtain wind direction changes, measured in degrees), altitude (based on terrain height from elevation data sources such as GPS, DEM, or LiDAR), and historical lightning frequency (using a lightning monitoring network to count the number of historical lightning events in a specific area). Furthermore, these indicators are combined with previously acquired radar reflectivity (measured in dBZ, reflecting cloud intensity), electric field change rate (using a ground-based electric field meter to obtain the discharge trend of lightning activity), and critical infrastructure density (the number of facilities such as transmission towers and base stations per unit area) along with their corresponding normalized density risk value (using linear or nonlinear normalization to facilitate comparative analysis). These indicators are then substituted into a preset lightning hazard calculation formula. This formula integrates various factors and assigns appropriate weight coefficients. The resulting hazard level can be a continuous value (e.g., 0-100) or a graded result (e.g., I-IV), which can be used to assist in issuing lightning warnings, identifying risk areas, and dispatching emergency resources.

[0082] In this embodiment, it is possible to achieve fusion analysis of multi-source heterogeneous data in the lightning-affected area, comprehensively assess the potential threat level of lightning to critical infrastructure, and ultimately generate a quantitative hazard level value. This will help improve the accurate early warning capability of lightning disasters, optimize emergency response deployment, and reduce the risk of damage to critical facilities, thereby ensuring the safe and stable operation of core systems such as regional power and communications.

[0083] Based on the above technical solution, optionally, after calculating the danger level value of the lightning-affected area, the method further includes: Constructing a hazard level space mapping matrix according to the hazard level value; Determine a lightning risk heat map by overlaying the hazard level spatial mapping matrix and the preset map layer; Obtaining high-risk areas in the lightning risk heat map, and determining target areas for triggering early warning signals based on the high-risk areas; The deployment information of the lightning protection devices in the target area is obtained, the target scheduling lightning protection device is determined according to the deployment information, and the working state of the target scheduling lightning protection device is adjusted.

[0084] In this scheme, the hazard level spatial mapping matrix can refer to a two-dimensional or three-dimensional grid data structure constructed by distributing the calculated hazard level values ​​of different geographical locations in the form of spatial coordinates, reflecting the lightning risk level of each spatial unit within the lightning-affected area, and used for subsequent heat map construction and visualization analysis.

[0085] The preset map layer can refer to a digital map layer pre-loaded in the system, which contains geographic information, administrative divisions, topography, distribution of important facilities, etc., and serves as the base map for spatial overlay and display of lightning risk data.

[0086] A lightning risk heat map can be an image generated by superimposing the hazard level spatial mapping matrix with a preset map layer. It usually uses a color gradient (such as red, yellow, and green) to display the lightning risk intensity in different areas, realizing a visual expression of the risk space.

[0087] High-risk areas can refer to areas where the corresponding hazard level values ​​in the lightning risk heat map exceed the set threshold. These are locations where lightning disasters are most likely to occur and require key monitoring and early warning.

[0088] The target area can be a specific area that intersects with key facilities, densely populated areas or high-value asset areas further screened out from the high-risk areas, and measures must be taken to focus on risk prevention and control.

[0089] Lightning protection devices can refer to hardware facilities deployed in the target area to protect key equipment, buildings or lines from the impact of lightning strikes, including lightning rods, surge protectors (SPDs), grounding systems, etc.

[0090] Deployment information can refer to configuration data such as the geographical location, type, technical parameters, operating status and control authority of each lightning protection device in the target area, which is used for system scheduling and status monitoring.

[0091] Targeted scheduling of lightning protection devices can refer to a set of specific lightning protection devices that are determined by the system to require working status adjustment (such as activation, switching, power adjustment, etc.) under the current warning requirements, in order to respond to specific lightning risks and enhance regional protection capabilities.

[0092] Based on the calculated hazard level values, a spatial hazard level mapping matrix can be constructed using a regular gridding method (e.g., 0.01° latitude and longitude resolution or a specified UTM projection grid). Each grid cell represents a specific geographic area and stores its corresponding lightning hazard value, forming a two-dimensional or three-dimensional (including a time dimension) matrix structure. This hazard level spatial mapping matrix is ​​then overlaid with pre-defined map layers composed of multi-source spatial data. These layers typically include topographic maps, geographic boundaries, road networks, and critical infrastructure distribution layers to geolocate and visualize lightning hazard information, thereby generating a real-time, updated lightning risk heat map. This heat map uses a color gradient (e.g., blue-green-yellow-red) to represent different hazard levels, highlighting high-risk areas (red areas) on the map. Subsequently, based on a set risk threshold (e.g., a hazard level value > 0.75), all areas exceeding this threshold are extracted from the heat map to construct the geometric boundaries of the high-risk areas. By overlaying analysis with layers such as key urban areas, transmission line corridors, and substation coverage, the system further identifies target areas requiring attention. These areas not only have high lightning risk levels but also contain critical assets or densely populated areas, necessitating triggering of lightning warning signals. Next, the system retrieves information from the database about lightning protection devices that spatially overlap with these target areas, including lightning rods, grounding devices, surge protectors, and lightning warning devices. It then retrieves deployment information, such as device number, installation location (latitude and longitude), device type, real-time operating status, device coverage radius, and last maintenance time, to determine whether each device currently has response capabilities. Based on a combined analysis of risk level and device status, it identifies target lightning protection devices eligible for dispatch response. Finally, the system adjusts the operating status of these devices, such as adjusting the grounding continuity status, increasing the surge protector response level, enabling remote monitoring, adjusting the power isolation control logic, or sending status update commands. This enables dynamic management and precise scheduling of lightning protection resources, improving overall lightning protection efficiency and real-time response capabilities.

[0093] In this solution, by constructing a spatial mapping matrix of hazard levels and overlaying preset map layers to generate a lightning risk heat map, accurate identification of high-risk areas and automatic early warning of target areas can be achieved. Combined with the deployment information of lightning protection devices, intelligent response of target scheduling lightning protection devices can be achieved, effectively improving the spatial perception capability of lightning disasters, early warning accuracy and emergency response efficiency, and ensuring the safety of critical infrastructure and personnel.

[0094] Based on the above technical solution, an optional, preset lightning hazard calculation formula is: Among them, R is the hazard level value; is the rate of change of the electric field; for critical infrastructure density; is the radar reflectivity; z is the altitude information; is the historical frequency of lightning; is the normalized density risk value; is the wind direction angle.

[0095] Example 3 Figure 3 This is a schematic diagram of the structure of the lightning location system based on multi-source data fusion provided in Example 3 of this application. Figure 3 As shown, specifically including: The arrival time difference calculation module 301 is used to obtain the first arrival time and the second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculate the arrival time difference of each lightning event based on the first arrival time and the second arrival time; A lightning area image analysis module 302 is configured to obtain a lightning area image corresponding to each lightning event and determine a lightning detection distance, a lightning capture time difference, and a lightning observation angle based on the lightning area image; The spatial distance calculation module 303 is used to obtain the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, as well as the device distance between each ground lightning detection device that collected each lightning event. Based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, device distance, and a preset joint lightning location formula, it calculates the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that received the lightning event. The number of lightning strike points is at least two. The geographic coordinate calculation module 304 is configured to obtain the location information of the first ground lightning detection device that receives the lightning event, and calculate the geographic coordinates of each lightning strike point based on the location information and the spatial distance.

[0096] The lightning location system based on multi-source data fusion provided by the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0097] Example 4 like Figure 4 As shown, an embodiment of the present application also provides an electronic device 400, including a processor 401, a memory 402, and a program or instruction stored in the memory 402 and executable on the processor 401. When the program or instruction is executed by the processor 401, each process of the above-mentioned lightning location method embodiment based on multi-source data fusion is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0098] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0099] Example 5 An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned cable installation process based on the tension adaptive control system embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0100] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk.

[0101] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or system comprising the element. In addition, it should be noted that the scope of the methods and systems in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0102] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the existing technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of this application.

[0103] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0104] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that are possible for those skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include more other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A lightning location method based on multi-source data fusion, characterized in that: The method comprises: Obtaining a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculating an arrival time difference of each lightning event based on the first arrival time and the second arrival time; Acquire a lightning area image corresponding to each lightning event, and determine the lightning detection distance, lightning capture time difference, and lightning observation angle based on the lightning area image; Obtain the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, as well as the equipment distance between each ground lightning detection device that collected each lightning event. Calculate the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that received the lightning event based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula; the number of lightning strike points is at least two. The location information of the first ground lightning detection device that receives the lightning event is obtained, and the geographical coordinates of each lightning strike point are calculated based on the location information and the spatial distance.

2. The method according to claim 1, characterized in that in, The preset joint lightning location formula is: in, is the spatial distance; c is the speed of light; is the arrival time difference; is the preset refractive index correction coefficient; Calibrate weight coefficients for preset satellites; Lightning detection distance; is the device distance; is the lightning observation angle; Capturing time differences for thunder and lightning; is the preset electric field response weight coefficient; is the rate of change of the electric field; Correction weight coefficient for preset radar; is the radar reflectivity.

3. The method according to claim 1, characterized in that in, After calculating the geographical coordinates of each lightning strike point based on the location information and the spatial distance, the method further includes: Determining spatial distribution information of critical infrastructure in the lightning-affected area, and determining the density of critical infrastructure in the lightning-affected area based on the spatial distribution information; Substitute the density of critical infrastructure into the preset normalization function to obtain the normalized density risk value of the lightning-affected area; Obtain the relative humidity, wind direction angle, altitude information and historical frequency of lightning in the lightning-affected area, and calculate the hazard level value of the lightning-affected area based on radar reflectivity, electric field change rate, critical infrastructure density, normalized density risk value, relative humidity, wind direction angle, altitude information, historical frequency of lightning and the preset lightning hazard calculation formula.

4. The method according to claim 3, characterized in that in, After calculating the danger level value of the lightning-affected area, the method further includes: Constructing a hazard level space mapping matrix according to the hazard level value; Determine a lightning risk heat map by overlaying the hazard level spatial mapping matrix and the preset map layer; Obtaining high-risk areas in the lightning risk heat map, and determining target areas for triggering early warning signals based on the high-risk areas; The deployment information of the lightning protection devices in the target area is obtained, the target scheduling lightning protection device is determined according to the deployment information, and the working state of the target scheduling lightning protection device is adjusted.

5. The method according to claim 3, characterized in that in, The default lightning risk calculation formula is: Among them, R is the hazard level value; is the rate of change of the electric field; for critical infrastructure density; is the radar reflectivity; z is the altitude information; is the historical frequency of lightning; is the normalized density risk value; is the wind direction angle.

6. The method according to claim 1, characterized in that in, After calculating the geographical coordinates of each lightning strike point based on the location information and the spatial distance, the method further includes: Obtain the spatial positioning information of the power line tower, perform spatial buffer matching on the geographic coordinates and spatial positioning information, and determine the target power line tower that meets the spatial proximity relationship.

7. The method according to claim 6, characterized in that in, After determining the target power line tower that satisfies the spatial proximity relationship, the method further includes: Obtaining the occurrence timestamp of the lightning event and the operation log corresponding to the target power line tower, performing a time consistency check based on the occurrence timestamp and the time record of the operation log to confirm whether the lightning event corresponds to the target power line tower; If the lightning event corresponds to a target power line tower, the target power line tower is marked as being in a state of being affected by a lightning strike, and the target power line tower and the corresponding state of being affected by a lightning strike are recorded in a lightning disaster record database.

8. A lightning location system based on multi-source data fusion, characterized in that: The system comprises: an arrival time difference calculation module, configured to obtain a first arrival time and a second arrival time of each lightning event collected by each ground lightning detection device within a preset time window, and calculate an arrival time difference of each lightning event based on the first arrival time and the second arrival time; A lightning area image analysis module is used to obtain a lightning area image corresponding to each lightning event, and determine the lightning detection distance, lightning capture time difference, and lightning observation angle based on the lightning area image; A spatial distance calculation module is used to obtain the electric field change rate and radar reflectivity of the lightning area corresponding to each lightning event, as well as the equipment distance between each ground lightning detection device that collects each lightning event. Based on the arrival time difference, lightning detection distance, lightning capture time difference, lightning observation angle, electric field change rate, radar reflectivity, equipment distance, and a preset joint lightning location formula, it calculates the spatial distance between the lightning strike point of each lightning event and the first ground lightning detection device that receives the lightning event; the number of lightning strike points is at least two; The geographic coordinate calculation module is used to obtain the position information of the first ground lightning detection device that receives the lightning event, and calculate the geographic coordinates of each lightning strike point based on the position information and the spatial distance.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the lightning location method based on multi-source data fusion as described in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the lightning location method based on multi-source data fusion according to any one of claims 1 to 7 are implemented.

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