A simulation method for medium-wave broadcast coverage based on medium-wave analysis technology

Abstract

This invention discloses a medium-wave broadcast coverage simulation method based on medium-wave analysis technology, belonging to the field of signal propagation simulation technology. It addresses the problems of limited dimensions and lack of spatiotemporal dynamic characteristics in the assessment of propagation impact factors during medium-wave broadcasting under existing technologies. By constructing a simulation environment database and setting simulation datasets covering several spatial regions, medium-wave propagation analysis models for different time periods are established, and propagation paths for each time period are constructed. The simulation datasets are used as interference sources for simulation to obtain the propagation path loss of medium-wave broadcasting in any time period and spatial region. The propagation path loss of all spatial regions along the propagation path in the same time period is statistically analyzed. The propagation paths of different time periods in the same spatial region are superimposed to obtain the broadcast coverage intensity of each spatial region. The broadcast coverage intensity of all spatial regions is then labeled onto the entire simulation area to generate a broadcast coverage effect view characterizing the broadcast reception quality.

Description

Technical Field

[0001] This invention relates to the field of signal propagation simulation technology, and more specifically to a method for simulating medium-wave broadcast coverage based on medium-wave analysis technology. Background Technology

[0002] In existing technologies, medium-wave broadcast coverage prediction methods mostly rely on simplified propagation models or data analysis of a single time period, failing to fully integrate the multi-dimensional environmental factors that affect signal propagation. Traditional methods usually do not fully consider the synergistic effects of digital elevation, the ground feature structure formed by land point clouds, and spatial geoelectric distribution on signal attenuation, and lack dynamic modeling of the differences in the propagation mechanisms of ground waves and sky waves at different time periods.

[0003] This leads to discrepancies between simulation results and actual broadcast coverage, making it difficult to accurately reflect signal strength distribution under complex terrain and spatiotemporal changes. Consequently, it fails to effectively support the precise planning and optimization of broadcast networks, resulting in the failure to promptly detect and address coverage blind spots or interference areas. Summary of the Invention

[0004] The purpose of this invention is to provide a medium-wave broadcast coverage simulation method based on medium-wave analysis technology to address the shortcomings in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a mid-wave broadcast coverage simulation method based on mid-wave analysis technology, comprising the following steps:

[0006] Step S1: Construct a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information, and set up a simulation dataset covering several spatial regions based on the simulation environment database.

[0007] Step S2: Establish medium wave propagation analysis models for different time periods, construct the propagation and diffusion paths of the medium wave propagation analysis models for each time period, use the simulation dataset as the interference source on the propagation and diffusion path for simulation, and then obtain the diffusion path loss of medium wave broadcasting in any time period and spatial region.

[0008] Step S3: Calculate the diffusion path loss of all spatial regions on the propagation path during the same time period, and add up the diffusion path loss corresponding to the propagation path of the same spatial region at different time periods to obtain the broadcast coverage strength of each spatial region.

[0009] Step S4: Mark the broadcast coverage intensity of all spatial areas onto the entire simulation area where medium wave broadcasting is carried out, and generate a broadcast coverage effect view to characterize the broadcast reception quality.

[0010] In a preferred embodiment, the process of constructing a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information includes:

[0011] The simulation area is set to cover several map-defined spaces. Simulation nodes are created for each map-defined space, identification credentials are established for each simulation node, a central database is deployed, and a data communication channel is established between each simulation node and the central database. Each simulation node can acquire digital elevation parameters, land point cloud data, and spatial geoelectric distribution information within its own spatial area.

[0012] Each simulation node generates its own data storage package, which is used to package and store all the data obtained by the simulation node in the spatial area. The identification credentials of each simulation node are associated with its own data storage package as retrieval entries.

[0013] Create a database storage area in the central database that is the same number of data storage packages. Create an external retrieval area in the data communication channel corresponding to each simulation node. The database storage area is used to store data storage packages, and the external retrieval area is used to securely retrieve the data storage packages of each simulation node and the information communication environment within the data communication channel.

[0014] Once the security check is successful, the data storage package of each simulation node is stored in the corresponding storage area of ​​the central database through its respective data communication channel. If the check fails, the corresponding simulation node is subjected to security checks until the security check is successfully completed and the data storage package is stored. When the data storage packages of all simulation nodes in the simulation area are stored in the central database, the central database is synchronously converted into the simulation environment database.

[0015] In a preferred embodiment, the process of setting a simulation dataset covering several spatial regions based on a simulation environment database includes:

[0016] Based on historical simulation data, a set of effective data fields for simulating the simulation area is obtained. A bag-of-words model is deployed for each storage area in the library. The data storage packages of each storage area in the library are analyzed by the bag-of-words model to obtain several data fields for each area.

[0017] The system iterates and searches between the data fields corresponding to each data storage package and the set of valid data fields, filters out several valid data fields of each data storage package, integrates all valid data fields obtained from the data storage packages corresponding to each storage area in the simulation environment database, and sets up a simulation dataset covering the spatial area corresponding to each simulation node under the simulation area. The simulation dataset under each spatial area is used to perform simulation simulation of the current spatial area.

[0018] In a preferred embodiment, the secure retrieval process includes:

[0019] Security retrieval includes static security scanning and dynamic sandbox detection;

[0020] Perform a static security scan on the data storage packet. Obtain the hash value sequence of the data storage packet through the static security scan and compare it with the trusted sequence of the preset trusted source. If the comparison matches, the static security scan is completed; otherwise, mark the corresponding data storage packet as an abnormal data packet.

[0021] Dynamic sandbox detection is performed on the data communication channels. A sandbox space is created for each data communication channel. All access behaviors in the data communication channels are obtained and imported into their respective sandbox spaces. Several dynamic monitoring points are set up in the sandbox spaces. Each dynamic monitoring point monitors the access behaviors within a monitoring period and determines whether there are any abnormal access behaviors that pose security risks to the information communication environment during the corresponding monitoring period.

[0022] If so, the data of the dynamic monitoring points corresponding to the abnormal access behavior will be isolated to determine the abnormal source of the abnormal access behavior; otherwise, the dynamic sandbox will be used for detection.

[0023] If the data storage packet of the simulation node successfully passes the static security scan, and the information communication environment within the data communication channel corresponding to the simulation node passes the dynamic sandbox detection, then the corresponding simulation node passes the security retrieval; otherwise, the security retrieval fails.

[0024] In a preferred embodiment, the process of establishing mid-wave propagation analysis models for different time periods and constructing the propagation and diffusion paths of the mid-wave propagation analysis models for each time period includes:

[0025] Different time periods include daytime and nighttime. During the daytime, a ground wave propagation model is established, which only involves ground wave propagation. During the nighttime, a sky wave propagation model is established, which includes both ground wave and sky wave, with sky wave as the main waveform component.

[0026] Set the propagation start point and propagation end point of the medium wave propagation analysis model for different time periods. Transmit the medium wave signal from the propagation start point and receive the medium wave signal at the propagation end point. Monitor the propagation area of ​​the medium wave signal from the propagation start point to the propagation end point. Divide the propagation area into several sub-propagation areas. Locate a propagation intermediate point in each sub-propagation area and set the basic diffusion area of ​​the medium wave at each propagation intermediate point.

[0027] By binding the propagation midpoint of each sub-propagation region to the medium-wave basic diffusion region of the propagation midpoint, several diffusion path points of a medium-wave signal during propagation are obtained. By connecting several diffusion path points of different sub-propagation regions, the propagation diffusion path of the medium-wave propagation analysis model under the corresponding time period is obtained.

[0028] In a preferred embodiment, the process of simulating the propagation path loss of medium wave broadcasting at any time period and spatial region by using the simulation dataset as an interference source on the propagation path includes:

[0029] A propagation path is selected as the execution object of the simulation. Several spatial regions traversed by the propagation path are obtained. Based on the retrieval entries in the simulation environment database corresponding to each spatial region, the entire simulation dataset of the execution object is obtained and imported into the pre-deployed scene rendering engine.

[0030] A scene architecture is rendered at each spatial region traversed by the current diffusion path. The simulation dataset of each spatial region is decomposed, and the digital elevation information, obstacle information and related disturbance signals of the scene space where the scene architecture is located are analyzed. These are used as interference sources on the propagation and diffusion path, and all interference sources belonging to the same spatial region are treated as a set of interference.

[0031] In each spatial region, a target grid point is set, and the main path loss of the medium wave signal propagating from the starting point of the current spatial region to the target grid point is obtained. Several interference sources in the corresponding interference set of the spatial region are taken as signal propagation points, and the branch path loss from each signal propagation point to the target grid point is obtained. The main path loss and branch path loss under a spatial region are accumulated to obtain the diffusion path loss under any time period and spatial region.

[0032] In a preferred embodiment, the process of calculating the propagation path loss of all spatial regions along the propagation path during the same time period, and superimposing the propagation paths of the same spatial region at different time periods to obtain the broadcast coverage strength of each spatial region includes:

[0033] The diffusion path loss of different spatial regions under the same time period is accumulated to obtain the total diffusion loss for daytime and nighttime periods. For any spatial region through which the medium wave signal passes during broadcasting, the propagation diffusion path of each time period is superimposed to obtain the dynamic matrix of diffusion loss of the corresponding spatial region throughout the entire time period. The dynamic matrix of diffusion loss consists of instantaneous diffusion loss matrices at several time nodes. Each instantaneous diffusion loss matrix is ​​used to characterize the instantaneous broadcast coverage intensity at a certain moment in the spatial region, while the dynamic matrix of diffusion loss is used to characterize the changing trend of the broadcast coverage intensity of the corresponding spatial region throughout the day.

[0034] In a preferred embodiment, the process of annotating the broadcast coverage intensity of the entire spatial region onto the entire simulation area where medium-wave broadcasting is conducted, and generating a broadcast coverage effect view to characterize broadcast reception quality, includes:

[0035] Construct a spatial reference field for the entire simulation area, import the diffusion loss dynamic matrix of all spatial regions into the spatial reference field, and insert the diffusion loss dynamic matrix at the corresponding spatial region based on the position coordinates of each spatial region in the spatial reference field.

[0036] A data display axis is set for each insertion position, and several data display nodes based on time sequence are set on the data display axis. Several instantaneous diffusion loss matrices are arranged to several data display nodes based on propagation time sequence. Each data display node is used to display the broadcast coverage intensity of a certain spatial area at a certain time. Several data display nodes on the data display axis are traversed based on time sequence, and the traversal result is used to display the change of broadcast coverage intensity of a certain spatial area throughout the entire time period.

[0037] A baseline strength value is set to determine the broadcast coverage strength for different time periods and spatial areas. Different colors are used to mark the corresponding spatial areas on the spatial area baseline field, and the corresponding levels of broadcast reception quality are set based on the different colors.

[0038] A view component is set up for each data display axis on the spatial reference field. The traversal results of several data display nodes on the data display axis based on the time sequence are visualized to the corresponding view component. Each view component is used to demonstrate the color-coded changes in the broadcast coverage intensity of a corresponding spatial area in the simulation area. All view components are integrated to construct a broadcast coverage effect view.

[0039] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0040] This invention constructs a simulation environment database integrating digital elevation parameters, land point cloud data, and spatial geoelectric distribution information, and generates a simulation dataset covering multiple spatial regions based on this database. This effectively improves the accuracy and completeness of environmental modeling. By establishing a time-segmented mid-wave propagation analysis model, it simulates the propagation paths of ground waves and sky waves at different times, and incorporates the simulation dataset as an interference source into the simulation. This enables refined calculation of diffusion path loss for any time period and spatial region. By statistically analyzing and superimposing diffusion path losses in different spatiotemporal dimensions, it generates a coverage effect view reflecting broadcast reception quality, improving the reliability and visualization of mid-wave broadcast coverage prediction. This provides data support for broadcast network optimization and overcomes, to some extent, the problems of inaccurate coverage assessment and lack of spatiotemporal dynamic characteristics in existing technologies. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0042] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1, please refer to Figure 1 As shown in this embodiment, a medium-wave broadcast coverage simulation method based on medium-wave analysis technology includes the following steps:

[0045] Step S1: Construct a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information, and set up a simulation dataset covering several spatial regions based on the simulation environment database.

[0046] Step S2: Establish medium wave propagation analysis models for different time periods, construct the propagation and diffusion paths of the medium wave propagation analysis models for each time period, use the simulation dataset as the interference source on the propagation and diffusion path for simulation, and then obtain the diffusion path loss of medium wave broadcasting in any time period and spatial region.

[0047] Step S3: Calculate the diffusion path loss of all spatial regions on the propagation path during the same time period, and add up the diffusion path loss corresponding to the propagation path of the same spatial region at different time periods to obtain the broadcast coverage strength of each spatial region.

[0048] Step S4: Mark the broadcast coverage intensity of all spatial areas onto the entire simulation area where medium wave broadcasting is carried out, and generate a broadcast coverage effect view to characterize the broadcast reception quality.

[0049] It should be further explained that, in the specific implementation process, the process of constructing a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information, and setting up a simulation dataset covering several spatial regions based on the simulation environment database, includes:

[0050] A simulation area is set up, which covers several map-defined spaces representing different latitude and longitude ranges. A simulation node is created for the spatial region corresponding to each map-defined space. The boundary contour coordinates of each map-defined space in the simulation area are obtained and used as the identification credentials of the simulation node corresponding to the spatial region where the map-defined space is located.

[0051] A central database is deployed, and each simulation node in the simulation area establishes its own data communication channel with the central database. Each simulation node can acquire digital elevation parameters, land point cloud data, and spatial geoelectric distribution information within its own spatial area.

[0052] The digital elevation parameters are used to characterize the basic topographic contours and major propagation obstacles of the simulation area. They exist in the form of a digital elevation model, which is a geographic dataset representing ground elevation information. It describes the macroscopic topographic undulations along the propagation path, including mountains, hills, valleys, plains, etc., and is the most basic and important geographic factor affecting radio wave propagation.

[0053] The land point cloud data is used to characterize the concrete structures attached to the land surface, such as buildings and trees. The point cloud data is a collection of a number of three-dimensional coordinate points. These three-dimensional coordinate points are acquired through lidar technology and are used to record the geometric shape of the Earth's surface and the objects on it. By analyzing the point cloud data, the land surface type and the objects on the land surface can be classified more accurately.

[0054] The spatial geoelectric distribution information determines the magnitude of the resistance encountered by signal energy when it is transmitted on the surface. It directly controls the attenuation rate of ground wave signals and mainly includes the spatial distribution of relative permittivity and conductivity. The relative permittivity is an indicator of a material's ability to store electrical energy in an electric field, and the conductivity is an indicator of a material's ability to conduct electricity. The spatial geoelectric distribution information describes the Earth's surface's ability to conduct and absorb electromagnetic waves and is a decisive parameter for calculating ground wave propagation loss.

[0055] A corresponding data storage package is generated for each simulation node. The data storage package is used to package and store all the data obtained by the simulation node in the spatial area. The identification credentials of each simulation node are associated with its respective data storage package, which is used as the retrieval entry for the data storage package in the subsequent process.

[0056] A database storage area equal to the number of data storage packets is created at the central database. An external retrieval area is created at the data communication channel of each simulation node. The database storage area is used to store the data storage packets, and the external retrieval area is used to securely retrieve the data storage packets of each simulation node and the information communication environment within the data communication channel.

[0057] Once the security check is successful, the data storage package corresponding to each simulation node is stored in the corresponding storage area of ​​the central database through its respective data communication channel. If the security check fails, the corresponding simulation node is subjected to security checks until the simulation node passes the security check, and then the data storage package of the corresponding simulation node is stored in the central database.

[0058] The security search includes static security scanning and dynamic sandbox detection;

[0059] Static security scanning is performed on the data storage packets of each simulation node. The hash value sequence corresponding to the data storage packet is obtained through static security scanning. The obtained hash value sequence is compared with the trusted sequence corresponding to the preset trusted source. If the comparison is consistent, the static security scan of the current data storage packet is completed. Otherwise, the data storage packet of the corresponding simulation node is marked as an abnormal data packet.

[0060] Dynamic sandbox detection is performed on the data communication channels of each simulation node. A sandbox space is created for each data communication channel, and all access behaviors in the data communication channel are imported into their respective sandbox spaces. Several dynamic monitoring points are set up in the sandbox spaces, and each dynamic monitoring point monitors the access behaviors within a monitoring period, thereby determining whether there are any abnormal access behaviors that pose security risks to the information communication environment during the corresponding monitoring period.

[0061] If yes, then the dynamic monitoring points corresponding to the abnormal access behavior in the sandbox space are isolated to determine the abnormal source of the abnormal access behavior, and the abnormal source is associated with the corresponding dynamic monitoring point. An index for the abnormal source is established based on the point sequence of the dynamic monitoring point, and the corresponding abnormal source is obtained based on the index. If no, then the dynamic sandbox is used for detection.

[0062] The location sequence is obtained by binary serializing the start timestamp of the monitoring period corresponding to the dynamic monitoring point. The location sequence serves as a unique identity authentication identifier for each dynamic monitoring point and is used as a retrieval index for subsequent searching of the abnormal source of the dynamic monitoring point with abnormal access behavior.

[0063] If a simulation node's data storage packet successfully passes the static security scan and the information communication environment within the corresponding data communication channel of the simulation node passes the dynamic sandbox detection, then the corresponding simulation node passes the security retrieval; otherwise, the security retrieval fails.

[0064] When a security search is successful, the data storage package is given a "security checked" security tag and is allowed to be moved out of the external search area. When a security search fails, the data storage package is prohibited from being moved out of the external search area.

[0065] The security check process is as follows: Several anomaly sources are obtained based on the retrieval index. A check experience database is established based on historical check data. This database stores check procedures corresponding to various anomaly sources. These procedures address security risks to the information communication environment caused by the anomaly sources. All anomaly information corresponding to the obtained anomaly sources is imported into the database. All check procedures matching the current anomaly source in the database are then matched. If an anomaly source cannot be found in the database, its anomaly information is analyzed separately, and a suitable check procedure is created. By executing all matched or created check procedures, the abnormal data packets are analyzed to identify several data points with missing, redundant, or erroneous data. These data points are then filled, deleted, or modified, and the abnormal data packets are returned as normal data packets. This completes the check of the data storage packet or information communication environment corresponding to any simulation node or data communication channel.

[0066] When all data storage packages of simulation nodes under the simulation area are stored in the central database, the central database is synchronously converted into the simulation environment database. Based on historical simulation data, a set of effective data fields for simulating the simulation area is obtained. A bag-of-words model is deployed for each storage area in the database. The data storage packages of each storage area in the database are analyzed by text through the bag-of-words model to obtain several corresponding data fields.

[0067] The process of obtaining a valid set of data fields is as follows: retrieve all historical simulation data within the historical time period of the simulation database, spatially align and merge the digital elevation parameters, land point cloud data and spatial geoelectric distribution information included in the historical simulation data to form a historical simulation dataset, and clean and fill in the missing values.

[0068] Knowledge screening is conducted based on the physical principles of radio wave propagation to determine an initial set of candidate fields that are strongly correlated with path loss calculation. The initial set of candidate fields specifically includes transmitter power, transmission frequency, distance between transmitter and receiver, surface conductivity, and terrain diffraction parameters, etc.

[0069] Perform quantitative correlation analysis to calculate the Pearson correlation coefficient between each initial candidate field and the historical path loss results, eliminate weak data fields with correlation below the preset threshold, and retain the remaining initial candidate fields as valid candidate fields;

[0070] The random forest algorithm is used to perform multivariate feature importance analysis on all valid candidate fields. A pre-deployed prediction model is trained on all valid candidate fields to obtain the importance score of each valid candidate field. Valid candidate fields that meet the importance score requirements are marked as valid data fields. After integrating all valid data fields, a set of valid data fields is obtained.

[0071] The system iterates and searches between the data fields corresponding to each data storage package and the set of valid data fields to filter out the valid data fields for each data storage package. Specifically, when a data field can be found in the set of valid data fields, the corresponding data field is marked as a valid data field. The valid data field is the key data for simulation in any spatial region under the simulation area. Other data fields that are not marked as valid data fields are filtered out to avoid redundant workload in processing irrelevant data.

[0072] By integrating all valid data fields obtained from the data storage package corresponding to each storage area in the simulation environment database, a simulation dataset corresponding to the spatial area of ​​each simulation node under the simulation area is set up. The simulation dataset under each spatial area is used to perform simulation of the current spatial area.

[0073] It should be further explained that, in the specific implementation process, the process of establishing medium-wave propagation analysis models for different time periods and constructing the propagation and diffusion paths of the medium-wave propagation analysis models for each time period includes:

[0074] The different time periods include daytime and nighttime. Different types of medium wave propagation analysis models are established for daytime and nighttime respectively. Specifically, during the daytime, a ground wave propagation model is established that only propagates ground waves. During the nighttime, a sky wave propagation model is established that includes both ground waves and sky waves, with sky waves as the main waveform component.

[0075] Set the propagation start point and propagation end point of the medium wave propagation analysis model for different time periods. Transmit the medium wave signal from the propagation start point and receive the medium wave signal at the propagation end point. Monitor the propagation area of ​​the medium wave signal from the propagation start point to the propagation end point. Divide the propagation area into several sub-propagation areas. Locate a propagation intermediate point in each sub-propagation area and set the basic diffusion area of ​​the medium wave corresponding to each propagation intermediate point.

[0076] The volume of the medium-wave base diffusion region and the sub-propagation region are positively correlated; that is, the larger the volume of the sub-propagation region, the larger the volume of the medium-wave base diffusion region below the corresponding sub-propagation region. The specific volume relationship is as follows:

[0077] Define the volume of the unit propagation region and the corresponding volume of the unit diffusion region, and denot them as follows: and Several sub-propagation regions are labeled, and the labels are denoted as follows: , =1, 2, 3, ..., n, where n is a natural number greater than 0. The volume of the medium-wave fundamental diffusion region corresponding to each sub-propagation region is denoted as... The volume of each sub-propagation region is denoted as Then, the following formula can be used to express it:

[0078] ;

[0079] Among them, the regional volume of the medium-wave fundamental diffusion region Indicates the current label is The sub-propagation region corresponds to the regional diffusion volume of the medium wave signal under ideal conditions. However, because the medium wave signal is affected by various interferences during propagation, the actual regional diffusion volume will be smaller than the ideal case.

[0080] For the medium-wave propagation analysis model of the same time period, the propagation midpoint of each sub-propagation region is bound to the medium-wave basic diffusion region of the propagation midpoint, thereby obtaining several diffusion path points of a medium-wave signal in the propagation process. By connecting several diffusion path points of the medium-wave propagation analysis model in different sub-propagation regions, the propagation diffusion path of the medium-wave propagation analysis model in the corresponding time period is obtained. The propagation diffusion path represents the signal diffusion situation of the medium-wave signal in several time periods during the propagation process.

[0081] It should be further explained that, in the specific implementation process, the process of using the simulation dataset as an interference source on the propagation path to simulate and obtain the propagation path loss of medium wave broadcasting in any time period and spatial region includes:

[0082] A propagation path is selected as the execution object of the simulation. Several spatial regions traversed by the selected propagation path are obtained. Based on the retrieval entries in the simulation environment database corresponding to each spatial region, the entire simulation dataset of the current execution object is obtained. The entire simulation dataset is imported into the pre-deployed scene rendering engine, and the scene rendering engine renders all relevant interference sources for the current propagation path.

[0083] The scene rendering engine renders a scene architecture at each spatial region traversed by the current diffusion path, decomposes the simulation dataset of each spatial region, analyzes the digital elevation information, obstacle information and related disturbance signals of the scene space where the scene architecture is located, takes the digital elevation information, obstacle information and related disturbance signals as the corresponding interference sources on the propagation and diffusion path, and takes all interference sources belonging to the same spatial region as an interference set.

[0084] A target grid point is set in each spatial region. The main path loss of the medium wave signal propagating from the starting point of the current spatial region to the target grid point is denoted as . Using several interference sources in the corresponding interference set of the spatial region as signal propagation points, the branch path loss from each signal propagation point to the target grid point is obtained, and the branch path loss of each point is recorded sequentially. , ... Where m is a natural number greater than 0, the total diffusion path loss for medium wave broadcasting in the corresponding time period and spatial region is: + + +……+ And generate the corresponding diffusion path loss certificate ID based on the spatial region.

[0085] It should be noted that when a medium-wave signal is broadcast to each spatial region along its propagation path, it inherently incurs a transmission loss along the path. Ideally, this transmission loss is the total loss for the corresponding spatial region along the propagation path. However, when the medium-wave signal is transmitted as ground wave during the daytime, additional transmission losses occur due to terrain undulations rendered by digital elevation information, obstruction of the medium-wave signal by obstacles rendered by obstacle information, and interference caused by related disturbance signals along the propagation path. Accumulating these additional transmission losses with the original transmission losses yields the actual propagation path loss for each spatial region. Similarly, during the nighttime, when both ground waves and sky waves propagate, with sky waves being the dominant component, additional transmission losses also occur due to the aforementioned factors and the type of waveform components. It is also necessary to statistically analyze these additional transmission losses. Considering the transmission losses caused by each interference source in the interference set to the corresponding spatial region, a more accurate propagation path loss for each spatial region can be obtained.

[0086] It should be further explained that, in the specific implementation process, the process of calculating the propagation path loss of all spatial areas along the propagation path during the same time period, and superimposing the propagation paths of the same spatial area at different time periods to obtain the broadcast coverage strength of each spatial area includes:

[0087] Based on daytime and nighttime periods respectively, the propagation path loss in different spatial regions along the propagation path is statistically analyzed for each period. The propagation path loss in different spatial regions within the same period is then accumulated to obtain the total propagation loss for each daytime and nighttime period. The total propagation loss represents the total amount of loss along the propagation path when the medium wave signal is broadcast in the simulation area during the daytime or nighttime period.

[0088] It should be noted that the total diffusion loss along the propagation path during the daytime period represents the overall loss suffered by the medium wave signal when broadcasting within the range of several consecutive time periods represented by the daytime period. Similarly, the total diffusion loss along the propagation path during the nighttime period represents the overall loss suffered by the medium wave signal when broadcasting within the range of several consecutive time periods represented by the nighttime period.

[0089] For any spatial region that a medium-wave signal passes through during broadcasting, the propagation paths of each time period are superimposed to obtain the dynamic matrix of diffusion loss for the corresponding spatial region throughout the entire time period. The dynamic matrix of diffusion loss consists of instantaneous diffusion loss matrices corresponding to several time nodes. Each instantaneous diffusion loss matrix is ​​used to characterize the instantaneous broadcast coverage intensity at a certain moment in the spatial region. Furthermore, the dynamic matrix of diffusion loss is used to characterize the instantaneous broadcast coverage intensity at each moment in the entire time period in the corresponding spatial region, and is used to represent the changing trend of the broadcast coverage intensity throughout the day in the corresponding spatial region.

[0090] It should be further explained that, in the specific implementation process, the process of marking the broadcast coverage intensity of the entire spatial area onto the entire simulation area for medium-wave broadcasting, and generating a broadcast coverage effect view to characterize the broadcast reception quality, includes:

[0091] A spatial reference field corresponding to the entire simulation area is constructed using 3D modeling technology. The spatial reference field is used to characterize the entire scene where the simulation area is located. The diffusion loss dynamic matrix of the entire spatial area is imported into the spatial reference field.

[0092] Based on the position coordinates of each spatial region in the spatial region reference field, the diffusion loss dynamic matrix is ​​inserted at the corresponding spatial region. A data display axis is set for each insertion position, and several data display nodes based on the time sequence are set on the data display axis. Several instantaneous diffusion loss matrices corresponding to the diffusion loss dynamic matrix are arranged at several data display nodes based on the propagation time sequence.

[0093] Each data display node is used to display the broadcast coverage intensity of a certain spatial area at a certain moment. Several data display nodes on the data display axis are traversed in chronological order, and the traversal results are used to display the changes in the broadcast coverage intensity of a certain spatial area throughout the entire time period.

[0094] Set an intensity benchmark value. When the broadcast coverage intensity of a certain spatial area at a certain time is greater than or equal to the intensity benchmark value, the corresponding spatial area is marked in green on the spatial area benchmark field. When the broadcast coverage intensity of a certain spatial area at a certain time is less than the intensity benchmark value, the corresponding spatial area is marked in red on the spatial area benchmark field.

[0095] When marked in green, it indicates that the corresponding spatial area of ​​the simulation area has a good or excellent radio reception quality level; when marked in red, it indicates that the corresponding spatial area of ​​the simulation area has a poor radio reception quality level.

[0096] For each data display axis on the reference field of the spatial region corresponding to the entire simulation area, a view component is set up. The traversal results of several data display nodes on the data display axis based on the time sequence are visualized onto the corresponding view component. Each view component is used to demonstrate the color-coded changes in the broadcast coverage intensity of a corresponding spatial region in the simulation area. By integrating all view components, a broadcast coverage effect view is constructed.

[0097] The broadcast coverage effect view is used to characterize the changes in the broadcast coverage intensity of medium wave signals in any spatial area and time period within the entire simulation area. The alternating green and red colors represent the broadcast reception quality of different spatial areas. Based on preset reception quality standards, spatial areas that do not meet reception quality requirements can be screened out. Abnormal broadcast areas can be quickly located, and measures can be taken to optimize the broadcast coverage in abnormal broadcast areas. The view also allows for intuitive analysis of the changes in broadcast coverage intensity in any spatial area within the entire simulation area.

[0098] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for simulating medium-wave broadcast coverage based on medium-wave analysis technology, characterized in that, Includes the following steps: Step S1: Construct a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information, and set up a simulation dataset covering several spatial regions based on the simulation environment database. Step S2: Establish medium wave propagation analysis models for different time periods, construct the propagation and diffusion paths of the medium wave propagation analysis models for each time period, use the simulation dataset as the interference source on the propagation and diffusion path for simulation, and take all interference sources belonging to the same spatial area as an interference set. In each spatial region, a target grid point is set, and the main path loss of the medium wave signal propagating from the starting position of the current spatial region to the target grid point is obtained. Several interference sources in the corresponding interference set of the spatial region are taken as signal propagation points, and the branch path loss from each signal propagation point to the target grid point is obtained. The main path loss and branch path loss under a spatial region are accumulated to obtain the diffusion path loss under any time period and spatial region. Step S3: Calculate the diffusion path loss of all spatial regions on the propagation path during the same time period, and add up the diffusion path loss corresponding to the propagation path of the same spatial region at different time periods to obtain the broadcast coverage strength of each spatial region. Step S4: Mark the broadcast coverage intensity of all spatial areas onto the entire simulation area where medium wave broadcasting is carried out, and generate a broadcast coverage effect view to characterize the broadcast reception quality.

2. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 1, characterized in that, The process of constructing a simulation environment database based on digital elevation parameters, land point cloud data, and spatial geoelectric distribution information includes: The simulation area is set to cover several map-defined spaces. Simulation nodes are created for each map-defined space, identification credentials are established for each simulation node, a central database is deployed, and a data communication channel is established between each simulation node and the central database. Each simulation node can acquire digital elevation parameters, land point cloud data, and spatial geoelectric distribution information within its own spatial area. Each simulation node generates its own data storage package, which is used to package and store all the data obtained by the simulation node in the spatial area. The identification credentials of each simulation node are associated with its own data storage package as retrieval entries. Create a database storage area in the central database that is the same number of data storage packages. Create an external retrieval area in the data communication channel corresponding to each simulation node. The database storage area is used to store data storage packages, and the external retrieval area is used to securely retrieve the data storage packages of each simulation node and the information communication environment within the data communication channel. Once the security check is successful, the data storage package of each simulation node is stored in the corresponding storage area of ​​the central database through its respective data communication channel. If the check fails, the corresponding simulation node is subjected to security checks until the security check is successfully completed and the data storage package is stored. When the data storage packages of all simulation nodes in the simulation area are stored in the central database, the central database is synchronously converted into the simulation environment database.

3. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 2, characterized in that, The process of setting up a simulation dataset covering several spatial regions based on a simulation environment database includes: Based on historical simulation data, a set of effective data fields for simulating the simulation area is obtained. A bag-of-words model is deployed for each storage area in the library. The data storage packages of each storage area in the library are analyzed by the bag-of-words model to obtain several data fields for each area. The system iterates and searches between the data fields corresponding to each data storage package and the set of valid data fields, filters out several valid data fields of each data storage package, integrates all valid data fields obtained from the data storage packages corresponding to each storage area in the simulation environment database, and sets up a simulation dataset covering the spatial area corresponding to each simulation node under the simulation area. The simulation dataset under each spatial area is used to perform simulation simulation of the current spatial area.

4. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 3, characterized in that, The secure retrieval process includes: Security retrieval includes static security scanning and dynamic sandbox detection; Perform a static security scan on the data storage packet. Obtain the hash value sequence of the data storage packet through the static security scan and compare it with the trusted sequence of the preset trusted source. If the comparison is consistent, the static security scan is completed; otherwise, mark the corresponding data storage packet as an abnormal data packet. Dynamic sandbox detection is performed on the data communication channels. A sandbox space is created for each data communication channel. All access behaviors in the data communication channels are obtained and imported into their respective sandbox spaces. Several dynamic monitoring points are set up in the sandbox spaces. Each dynamic monitoring point monitors the access behaviors within a monitoring period and determines whether there are any abnormal access behaviors that pose security risks to the information communication environment during the corresponding monitoring period. If so, the data of the dynamic monitoring points corresponding to the abnormal access behavior will be isolated to determine the abnormal source of the abnormal access behavior; otherwise, the dynamic sandbox will be used for detection. If the data storage packet of the simulation node successfully passes the static security scan, and the information communication environment within the data communication channel corresponding to the simulation node passes the dynamic sandbox detection, then the corresponding simulation node passes the security retrieval; otherwise, the security retrieval fails.

5. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 4, characterized in that, The process of establishing mid-wave propagation analysis models for different time periods and constructing the propagation and diffusion paths of the mid-wave propagation analysis models for each time period includes: Different time periods include daytime and nighttime. During the daytime, a ground wave propagation model is established, which only involves ground wave propagation. During the nighttime, a sky wave propagation model is established, which includes both ground wave and sky wave, with sky wave as the main waveform component. Set the propagation start point and propagation end point of the medium wave propagation analysis model for different time periods. Transmit the medium wave signal from the propagation start point and receive the medium wave signal at the propagation end point. Monitor the propagation area of ​​the medium wave signal from the propagation start point to the propagation end point. Divide the propagation area into several sub-propagation areas. Locate a propagation intermediate point in each sub-propagation area and set the basic diffusion area of ​​the medium wave at each propagation intermediate point. By binding the propagation midpoint of each sub-propagation region to the medium-wave basic diffusion region of the propagation midpoint, several diffusion path points of a medium-wave signal during propagation are obtained. By connecting several diffusion path points of different sub-propagation regions, the propagation diffusion path of the medium-wave propagation analysis model under the corresponding time period is obtained.

6. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 5, characterized in that, The process of using simulation datasets as interference sources along the propagation path includes: A propagation path is selected as the execution object of the simulation. Several spatial regions traversed by the propagation path are obtained. Based on the retrieval entries in the simulation environment database corresponding to each spatial region, the entire simulation dataset of the execution object is obtained and imported into the pre-deployed scene rendering engine. A scene architecture is rendered at each spatial region traversed by the current diffusion path. The simulation dataset of each spatial region is decomposed, and the digital elevation information, obstacle information, and related disturbance signals of the scene space where the scene architecture is located are analyzed and used as interference sources on the propagation and diffusion path.

7. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 6, characterized in that, The process of calculating the propagation path loss of all spatial regions along the propagation path during the same time period, and then superimposing the propagation path losses of the same spatial region at different time periods to obtain the broadcast coverage strength of each spatial region includes: The diffusion path loss of different spatial regions under the same time period is accumulated to obtain the total diffusion loss for daytime and nighttime periods. For any spatial region through which the medium wave signal passes during broadcasting, the propagation diffusion path of each time period is superimposed to obtain the dynamic matrix of diffusion loss of the corresponding spatial region throughout the entire time period. The dynamic matrix of diffusion loss consists of instantaneous diffusion loss matrices at several time nodes. Each instantaneous diffusion loss matrix is ​​used to characterize the instantaneous broadcast coverage intensity at a certain moment in the spatial region, while the dynamic matrix of diffusion loss is used to characterize the changing trend of the broadcast coverage intensity of the corresponding spatial region throughout the day.

8. The method for simulating medium-wave broadcast coverage based on medium-wave analysis technology according to claim 7, characterized in that, The process of mapping the broadcast coverage intensity of the entire spatial region onto the entire simulation area where medium-wave broadcasting is conducted, and generating a broadcast coverage effect view to characterize the broadcast reception quality, includes: Construct a spatial reference field for the entire simulation area, import the diffusion loss dynamic matrix of all spatial regions into the spatial reference field, and insert the diffusion loss dynamic matrix at the corresponding spatial region based on the position coordinates of each spatial region in the spatial reference field. A data display axis is set for each insertion position, and several data display nodes based on time sequence are set on the data display axis. Several instantaneous diffusion loss matrices are arranged to several data display nodes based on propagation time sequence. Each data display node is used to display the broadcast coverage intensity of a certain spatial area at a certain time. Several data display nodes on the data display axis are traversed based on time sequence, and the traversal result is used to display the change of broadcast coverage intensity of a certain spatial area throughout the entire time period. A baseline strength value is set to determine the broadcast coverage strength for different time periods and spatial areas. Different colors are used to mark the corresponding spatial areas on the spatial area baseline field, and the corresponding levels of broadcast reception quality are set based on the different colors. A view component is set up for each data display axis on the spatial reference field. The traversal results of several data display nodes on the data display axis based on the time sequence are visualized to the corresponding view component. Each view component is used to demonstrate the color-coded changes in the broadcast coverage intensity of a corresponding spatial area in the simulation area. All view components are integrated to construct a broadcast coverage effect view.

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