Medium-wave broadcast-based field intensity prediction method and system

Abstract

The invention relates to the technical field of field intensity prediction, in particular to a medium-wave broadcast-based field intensity prediction method and system, and the method comprises the following steps: obtaining the environment space information of an emission source for medium-wave broadcast, and constructing an environment model of the emission source based on the environment space information; rasterizing the target area of the emission source based on the prediction model to form a plurality of grid receiving points; predictive control information is configured for the emission source based on the predictive model, and the predictive control information comprises a vernier and a selection frame chain corresponding to the vernier; driving the verniers to sequentially move in the target area along the propagation direction; the field intensity value of the vernier at each position is predicted based on the selection frame chain of the vernier, the grid points meeting the preset field intensity condition are connected to form the field intensity range contour, the field intensity range and the field intensity values of the grid points in the field intensity range are output to serve as the final prediction result, and the accuracy of field intensity prediction can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of field strength prediction technology, specifically to a field strength prediction method and system based on medium-wave broadcasting. Background Technology

[0002] As an important means of information dissemination, accurate prediction of medium-wave broadcasting signal coverage is crucial for station planning, frequency allocation, interference analysis, and network optimization. Traditional field strength prediction methods, such as certain empirical or deterministic models recommended by the International Telecommunication Union (ITU), typically treat the entire service area as a whole for simulation calculations. Existing field strength prediction methods cannot dynamically adjust to complex local propagation environments (such as undulating terrain, urban building clusters, and varying surface cover). This inability to adapt to complex geographical environments negatively impacts the accuracy of field strength predictions.

[0003] To address this issue, we propose a field strength prediction method and system based on medium-wave broadcasting. Summary of the Invention

[0004] The purpose of this invention is to provide a field strength prediction method and system based on medium wave broadcasting to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a field strength prediction method and system based on medium-wave broadcasting, the method comprising the following steps: Obtain the environmental spatial information of the transmitter used for medium-wave broadcasting, and construct an environmental model of the transmitter based on the environmental spatial information; The target area of ​​the transmitter is rasterized based on the prediction model to form multiple raster receiving points; predictive control information is configured for the transmitter based on the prediction model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor; The cursor is driven to move sequentially within the target area along the propagation direction; the field strength value of the cursor at each position is predicted based on the selection box chain of the cursor; grid points that meet the preset field strength conditions are connected to form the field strength range outline; and the field strength range and the field strength values ​​of each grid point within it are output as the final prediction result.

[0006] Preferably, the step of obtaining the environmental spatial information of the transmitter used for medium-wave broadcasting and constructing an environmental model of the transmitter based on the environmental spatial information includes: Acquire multi-source environmental data of the target area where the emission source is located. The multi-source environmental data includes at least digital elevation model data, land cover type data, and building outline data. A three-dimensional terrain triangular mesh surface is generated based on the digital elevation model data; according to the land cover type data and the preset mapping table, the surface conductivity value and relative permittivity value of the mid-wave frequency band are associated with the triangular facets of the three-dimensional terrain triangular mesh surface. A three-dimensional building volumetric model is generated based on the building outline data and constructed on a three-dimensional terrain triangular mesh surface to output an environmental space model.

[0007] Preferably, the step of configuring predictive control information for the emission source based on a predictive model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor, includes: Based on the prediction model, an independent cursor is configured for each of the multiple different propagation directions originating from the emission source; Each cursor is configured with a selection box chain, which includes multiple selection boxes corresponding to multiple propagation directions.

[0008] Preferably, the driving cursor moves sequentially within the target area along the propagation direction; the step of predicting the field strength value of the cursor at each position based on the selection box chain of the cursor, and connecting grid points that meet the preset field strength conditions to form the field strength range outline includes: The current grid receiving point where the cursor is located is collected in real time, and the target selection box chain is obtained by determining the selection box chain corresponding to the current grid receiving point. The field strength value of the current grid receiving point is predicted based on the field strength value of the grid receiving point corresponding to the target selection box chain. The cursor is driven to move sequentially within the target area along the propagation direction, and multiple field strength values ​​are obtained based on multiple grid receiving points; The grid receiving points corresponding to the field strength values ​​that meet the preset field strength threshold are taken as valid grid receiving points. The boundary contour of the continuous area formed by adjacent valid grid receiving points is taken as the field strength range. The coordinates and field strength values ​​of all grid receiving points within the field strength range are taken as the field strength prediction results.

[0009] Preferably, the step of acquiring the current grid receiving point of the real-time acquisition cursor, determining the selection box chain corresponding to the cursor at the current grid receiving point to obtain the target selection box chain, and predicting the field strength value of the current grid receiving point based on the field strength value of the grid receiving point corresponding to the target selection box chain includes: Obtain the grid receiving point where the cursor is currently positioned, and use it as the current target grid. Based on a preset spatial association strategy, an initial selection frame chain corresponding to the current target grid receiving point is determined. This initial selection frame chain consists of multiple selection frames arranged sequentially along the propagation direction. Each selection frame contains one or more upstream grid receiving points with predicted field strengths. The spatial association strategy is as follows: Using the current target grid as a reference, along the reverse direction of the cursor propagation, a fixed number of adjacent grids or all predicted grids within a fixed sector area are selected by the selection box, and multiple selection boxes are connected to form the initial selection box chain. Adjust the coverage area of ​​the selection boxes in the initial selection box chain, and use the adjusted selection box chain as the target selection box chain; Based on the field strength values ​​of all associated grid receiving points within the target selection frame chain, the field strength value of the current target grid is predicted.

[0010] Preferably, the step of adjusting the coverage area of ​​the selection boxes in the initial selection box chain and using the adjusted selection box chain as the target selection box chain includes: Retrieve multiple selection boxes from the initial selection box chain; Based on the common environmental feature partitions or common field strength change patterns to which multiple selection boxes belong, the multiple selection boxes are grouped into a collaborative scaling group, and an associated adjustment operation is performed on the collaborative scaling group. When the local propagation situation information of a selection box in a collaborative scaling group differs significantly from that of other selection boxes in the group, the selection box is removed from the collaborative scaling group and its boundary is adjusted separately. Use the adjusted selection box chain as the target selection box chain.

[0011] Preferably, the step of performing the associated adjustment operation on the collaborative scaling group includes: Obtain the local propagation situation information of each selection box in the collaborative scaling group in the corresponding propagation direction. The local propagation situation information includes at least one of terrain occlusion, ground feature attenuation and signal stability. Based on the local propagation situation information, determine the boundary adjustment strategy for the collaborative scaling group; The target coverage area of ​​each selection box is determined according to the boundary adjustment strategy. The end of each selection box in the co-scaling group that is far away from the emission source in the propagation direction is fixed, and the end that is close to the emission source is moved in the direction away from or close to the emission source to adjust its boundary to the target coverage area, and resampling is performed within the new boundary range. Based on the boundary adjustment results of each collaborative scaling group, the target selection box chain is formed.

[0012] Preferably, the step of determining the boundary adjustment strategy of the collaborative scaling group based on the local propagation situation information includes: When at least one of the terrain occlusion, ground object attenuation, or signal stability is higher than a preset threshold, the boundary adjustment strategy of reducing the selection box coverage area is adopted to reduce the number of grid receiving points covered by the selection box in the propagation direction. When at least one of the terrain occlusion, ground object attenuation, or signal stability is lower than a preset threshold, the boundary adjustment strategy of the selection box coverage area is increased to increase the number of grid receiving points covered by the selection box in the propagation direction.

[0013] Preferably, the steps of determining the target coverage area of ​​each selection box according to the boundary adjustment strategy, fixing the end of each selection box in the collaborative scaling group that is away from the emission source in the propagation direction, moving the end that is closer to the emission source in a direction away from or closer to the emission source to adjust its boundary to the target coverage area, and resampling within the new boundary range include: The target coverage area is determined according to the boundary adjustment strategy; the selection box is kept fixed at the end furthest from the emission source in the propagation direction. When it is necessary to reduce the coverage area of ​​the selection box, the end closer to the emission source is moved away from the emission source; when it is necessary to increase the coverage area of ​​the selection box, the end closer to the emission source is moved closer to the emission source, so that the current coverage area of ​​the selection box is equal to the target coverage area. Resampling is performed within the adjusted selection box boundaries.

[0014] A field strength prediction system based on medium-wave broadcasting, applied to any one of the field strength prediction methods based on medium-wave broadcasting described above, includes: The module is used to acquire the environmental spatial information of the transmitter used for medium wave broadcasting, and to build an environmental model of the transmitter based on the environmental spatial information; The configuration module is used to rasterize the target area of ​​the transmitter based on the prediction model to form multiple raster receiving points; and to configure predictive control information for the transmitter based on the prediction model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor. The prediction module is used to drive the cursor to move sequentially within the target area along the propagation direction; predict the field strength value of the cursor at each position based on the selection box chain of the cursor; connect the grid points that meet the preset field strength conditions to form the field strength range outline; and output the field strength range and the field strength values ​​of each grid point within it as the final prediction result.

[0015] Compared with the prior art, the beneficial effects of the present invention are: By predicting the field strength data of the target receiving point in real time based on the environmental data of each target area and other predicted field strength data related to the current location, the accuracy of field strength prediction can be effectively improved. During the prediction process, the selection box is dynamically scaled according to the local propagation situation information. In areas with complex environment and unstable signal, the selection box range is automatically expanded to integrate more data, while in areas with simple environment and stable signal, the selection box range is automatically reduced, thereby improving the overall prediction efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the selection box chain of the present invention; Figure 3 This is a system structure block diagram of the present invention. Detailed Implementation

[0018] 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, and 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.

[0019] Example

[0020] Please see Figures 1 to 2 This invention provides a field strength prediction method and system technical solution based on medium-wave broadcasting: A field strength prediction method based on medium-wave broadcasting includes the following steps: S1: Obtain the environmental spatial information of the transmitter used for medium wave broadcasting, and construct an environmental model of the transmitter based on the environmental spatial information; The steps of acquiring environmental spatial information of the transmitter used for medium-wave broadcasting and constructing an environmental model of the transmitter based on the environmental spatial information include: acquiring multi-source environmental data of the target area where the transmitter is located, wherein the multi-source environmental data includes at least digital elevation model data, land cover type data, and building outline data; generating a three-dimensional terrain triangular mesh surface based on the digital elevation model data; associating the surface conductivity value and relative permittivity value of the medium-wave frequency band with the triangular facets of the three-dimensional terrain triangular mesh surface according to the land cover type data and a preset mapping table; generating a three-dimensional building volumetric model based on the building outline data, constructing it on the three-dimensional terrain triangular mesh surface, and outputting the environmental spatial model; Specifically, the target area refers to a continuous geographical area centered on the geographical location of the medium-wave broadcast source, with its maximum expected service radius or potential interference assessment radius as its boundary; the electromagnetic parameters associated with the triangular facets of the three-dimensional terrain triangular mesh surface are obtained by querying a preset surface type-electromagnetic parameter mapping table. This mapping table defines the correspondence between different surface cover types and the conductivity and relative permittivity values ​​of the medium-wave band. The specific implementation of associating electromagnetic parameters with triangular facets is as follows: a data structure is stored for each vertex or facet in the three-dimensional terrain triangular mesh surface. The data structure includes at least geographic coordinates, elevation values, surface type codes, electrical conductivity values, and relative permittivity fields. Digital elevation model (DEM) data is a dataset storing surface elevation in a regular raster format, used to characterize the topographic relief features of the prediction area. It provides necessary input parameters for calculating diffraction loss and terrain shading along the mid-wave propagation path. DEM data can be obtained through airborne laser scanning, generating extremely detailed DEM data with sub-meter resolution, even penetrating vegetation to generate surface models. It is mainly used when waves are blocked by obstacles such as ridges during propagation, causing diffraction. DEM data provides the necessary topographic profile information for calculating diffraction loss (e.g., using an edge-shaped diffraction model). Without DEM data, it is impossible to accurately calculate signal attenuation caused by mountains. The surface cover type data is used to distinguish surface physical materials, such as water bodies, forests, urban building complexes, and farmland. By using a mapping table, each land surface type is associated with typical electromagnetic parameters (such as conductivity and relative permittivity) in its mid-wave frequency band, thereby transforming pure geographic classification data into an electromagnetic property data layer that can be used to calculate propagation loss.

[0021] S2: Based on the prediction model, the target area of ​​the transmitter is rasterized to form multiple raster receiving points; based on the prediction model, predictive control information is configured for the transmitter, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor; The step of configuring predictive control information for a transmitter based on a predictive model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor, includes: configuring an independent cursor for multiple different propagation directions originating from the transmitter based on the predictive model; configuring a selection box chain for each cursor, wherein the selection box chain includes multiple selection boxes corresponding to the multiple propagation directions respectively; Specifically, the configuration of an independent cursor for each of the multiple propagation directions originating from the transmitting source based on the prediction model includes: determining multiple medium-wave broadcast propagation directions originating from the transmitting source; configuring an independent cursor for each propagation direction based on the prediction model; wherein each cursor is bound to its corresponding unique propagation direction and is set to move and predict field strength along that direction within a gridded coverage area; the propagation direction configured for each cursor is used to determine its movement trajectory and the search azimuth of the upstream associated grid during the prediction process; the determination of the multiple medium-wave broadcast propagation directions is based on any of the following methods: defining them according to the main lobe and side lobe directions of the antenna directivity pattern of the transmitting source; or, dividing the area evenly with the transmitting source as the center according to a preset azimuth interval; Specifically, the grid receiving points that the cursor has passed through and that have been predicted are marked as the corresponding cursor dwell points. The local situation information of the dwell points in the same propagation direction is evaluated. The selection boxes in the same propagation direction with the same local situation information are synchronously scaled. The selection boxes are issued by the cursor. The corresponding selection boxes are appropriately increased or decreased according to different propagation directions. The adjusted selection boxes are connected to obtain a selection box chain. A memory is configured for the transmitter to store multiple cursors. Independent cursors are configured according to different propagation directions. The cursors are driven to move sequentially along their propagation directions within the gridded coverage area by the prediction model. At each position of the cursor, the corresponding spatial association strategy is called to determine the selection box chain. The field strength prediction of the current position is performed based on the field strength data in the selection box chain. The spatial association strategy is used to determine the position of each selection box in the selection box chain, that is, the propagation direction corresponding to each selection box. The prediction model is set to drive multiple cursors to move and predict in parallel or alternately. Predictive control information also includes a field strength calculation strategy, which defines how to calculate the predicted field strength value at the current cursor position based on the field strength value and spatial position of the receiving points of the grids within the selection frame chain. The field strength calculation strategy is configured to: calculate the weight of the field strength value of each grid based on the propagation path loss from each grid to the current cursor position, and calculate the predicted field strength value of the current position by weighted average. S3: Drive the cursor to move sequentially within the target area along the propagation direction; predict the field strength value of the cursor at each position based on the selection box chain of the cursor, connect the grid points that meet the preset field strength conditions to form the field strength range outline, and output the field strength range and the field strength value of each grid point within it as the final prediction result. The steps of driving the cursor to move sequentially within the target area along the propagation direction, predicting the field strength value of the cursor at each position based on the selection box chain of the cursor, and connecting grid points that meet the preset field strength conditions to form the field strength range outline include: real-time acquisition of the grid receiving point where the cursor is currently located, and determining the selection box chain corresponding to the cursor at the current grid receiving point to obtain the target selection box chain; predicting the field strength value of the current grid receiving point based on the field strength value of the grid receiving point corresponding to the target selection box chain; driving the cursor to move sequentially within the target area along the propagation direction, obtaining multiple field strength values ​​based on multiple grid receiving points; taking the grid receiving point corresponding to the field strength value that meets the preset field strength threshold as the effective grid receiving point, taking the boundary outline of the continuous area formed by adjacent effective grid receiving points as the field strength range, and taking the coordinates and field strength values ​​of all grid receiving points within the field strength range as the field strength prediction result. The steps of acquiring the current grid receiving point where the cursor is located in real time, determining the selection box chain corresponding to the cursor at the current grid receiving point to obtain the target selection box chain, and predicting the field strength value of the current grid receiving point based on the field strength value of the grid receiving point corresponding to the target selection box chain include: acquiring the grid receiving point where the cursor is currently located as the current target grid; determining the initial selection box chain corresponding to the current target grid receiving point according to a preset spatial association strategy, wherein the initial selection box chain consists of multiple selection boxes arranged sequentially along the propagation direction, and each selection box contains one or more upstream grid receiving points. The associated grid receiving points with predicted field strength are defined by the following spatial association strategy: using the current target grid as a reference, along the reverse direction of the cursor propagation, a fixed number of adjacent grids or all predicted grids within a fixed sector area are selected using a selection box, and multiple selection boxes are connected to form the initial selection box chain; the coverage area of ​​the selection boxes in the initial selection box chain is adjusted, and the selection box chain composed of the adjusted selection boxes is used as the target selection box chain; based on the field strength values ​​of all associated grid receiving points within the target selection box chain, the field strength value of the current target grid is predicted. It should be noted that, based on the current target grid, along the reverse direction of the cursor propagation, a fixed number of adjacent grids or all predicted grids within a fixed sector area are selected to form the target selection frame chain: K grid receiving points directly adjacent to the current position of the cursor in the reverse direction of propagation are selected; all predicted grid receiving points within a sector area with the current position of the cursor as the vertex, opened at a specified angle in the reverse direction of propagation, and with a radius of R are selected. Specifically, the selection boxes in the selection box chain correspond to selection boxes in different propagation directions. Each selection box is a dynamic data acquisition window that communicates with the cursor and is bound to a specific propagation direction. During each step of the cursor's position movement, a set of the most relevant grid receiving points (i.e., the "associated grid set") is intelligently selected from the upstream predicted area, and its field strength data is used as input to predict the field strength value corresponding to the current grid receiving point of the cursor. It is a scalable and directional "sensor array" dispatched for the cursor. The spatial position of the selection box moves with the movement of the cursor. At each new position of the cursor, a new selection box instance is generated. All the selection boxes in different propagation directions corresponding to a certain position of the cursor are connected to form the "selection box chain" of the cursor at the current grid receiving point. The cursor is a driving pointer that moves along the propagation direction on the gridded prediction model. Starting from the emission source, it explores outward in the specified direction (such as east, south, west, and north). Wherever it moves, the prediction calculation occurs. The selection box is dispatched by it, and the propagation direction is its trajectory, dividing the entire geographic area to be predicted into the center points of uniform grid cells. The final result of field strength prediction is to obtain the field strength value at each grid point. The propagation direction to be collected may not be the same at different cursor positions. Therefore, during the cursor's movement, the positions of multiple selection boxes in the selection box chain will change accordingly (here, position refers to the propagation direction corresponding to the selection box). Since the data collected by the selection boxes comes from grid receiving points corresponding to different propagation directions, when the cursor change causes the required grid receiving points to come from different directions, it is necessary to select and discard multiple selection boxes in the selection box chain, establish communication between the selection boxes and the cursor, and adjust the needs and usage of the selection boxes according to the propagation direction affecting the prediction result of the current grid receiving point of the cursor. Automatic cursor control and selection box... The communication relationship between the selection boxes includes disconnection or connection. For disconnected selection boxes, it is not necessary to collect data in the direction of propagation. Only for connected selection boxes, the corresponding data is collected. The data collected by the selection box may be the field strength value of one grid receiving point or the field strength values ​​of multiple grid receiving points. Specifically, it is determined according to the spatial range covered by the scaled selection box in the corresponding propagation direction. The spatial range covered (i.e., the associated grid set) is not fixed, but can be intelligently scaled (enlarged or reduced) according to the "current propagation situation information". When it senses that the terrain ahead is complex (high obstruction) or the prediction uncertainty is high, it will expand its range to collect more and wider data in order to make more accurate predictions.Conversely, in flat and open areas, it narrows the scope to improve computational efficiency. A cursor, with selection boxes in all moving positions and along the same propagation direction, connected sequentially in time, forms a "selection box chain." By controlling the scaling of the selection boxes, it can comprehensively predict the field strength value for the next grid receiving point based on different situational information in different propagation directions, improving prediction accuracy. By driving dynamic scaling of the selection boxes based on local propagation situational information, it automatically expands the selection box range to integrate more data in complex environments and unstable signals, while automatically narrowing the selection box range in simple environments and stable signals. This optimizes computational resources and significantly improves overall prediction efficiency. Multiple prediction directions with similar propagation environments are merged and a unified associative scaling operation is performed for batch scaling, effectively reducing the computation time required for large-scale predictions. The specific steps for predicting the field strength value of the current target grid based on the field strength values ​​of all associated grid receiving points within the target selection frame chain are as follows: For each associated grid receiving point in the target selection frame chain, calculate the signal propagation path loss from it to the current target grid; assign a weighting coefficient to the field strength value of each associated grid receiving point based on the reciprocal of the path loss; perform a weighted average of the field strength values ​​of all associated grid receiving points within the target selection frame chain, and use the calculation result as the predicted field strength value of the current target grid; Specifically, the process of assigning a weighting coefficient to the field strength value of each associated grid receiving point involves: calculating the reciprocal of the path loss; summing the reciprocals of the path losses of all associated grid receiving points within the target selection frame chain; and dividing the reciprocal of the path loss of each associated grid receiving point by the sum to obtain its normalized weighting coefficient. When calculating the predicted field strength of a current target grid, the point is not considered in isolation, but rather a set of associated grids with known actual field strength measurements (i.e., associated grid receivers). These associated grids are selected through a predefined logical chain (target selection box chain). Associated grids that are close to the target grid and have a good propagation environment can improve the accuracy of the predicted field strength value for the current target grid. Centered on the current target grid, one or more selection boxes are determined according to preset rules (e.g., concentric squares, sector areas, etc.), forming a "chain". Each selection box in the chain contains several grids with known field strength measurements; these grids are called "associated grid receiving points". For each associated grid receiving point i in the chain, the signal propagation path loss Li from that point to the current target grid is calculated. The key improvement of this embodiment is that this calculation integrates multi-source geographic data, digital elevation model data (used to calculate diffraction loss and line-of-sight determination due to terrain undulations), land cover type data (used to determine different penetration and absorption losses based on different types such as vegetation, water bodies, cities, and farmland), and building outline data (used to determine whether the signal is blocked by buildings and calculate the corresponding diffraction loss or penetration loss); associated grid receiving points... field strength value The magnitude of the contribution to the final predicted value is determined by its weighting coefficient. The weighting coefficient is determined based on the reciprocal of path loss; that is, the smaller the path loss, the larger the weight. The basic formula is as follows: ,in, It is an adjustable attenuation factor (usually) ≥1), used to control the sensitivity of path loss to the influence of weights. The larger the value, the faster the weight decays for points with high path loss; for all points within the target selection box chain... The target grid is calculated by weighting the field strength values ​​of the receiving points of each associated grid cell. Field strength prediction value ,in, Using a weighted average ensures that measurement points with better propagation conditions have a greater influence on the results. For example, to predict the signal strength of a target grid T in a city park, three associated grid receiving points were found around it. Point A is located on an open area on the other side of the park, with line-of-sight propagation from point T. Point B is separated from point T by a dense grove of trees, and point C is separated from point T by a tall office building. For point A, the line-of-sight distance was confirmed using digital elevation model data, and the ground cover was grass with no building obstructions. The calculated path loss... The minimum (assumed to be 90 dB) for point B, at sight distance, but the land cover type data indicates "dense vegetation," adding additional absorption loss. Calculated The value is relatively large (assumed to be 110dB). For point C, the building outline data signal is completely blocked, requiring calculation of significant diffraction loss or categorization as non-line-of-sight. The calculated... Maximum (assumed to be 130dB), assign weights (Pick =1), =1 / 90≈0.0111, =1 / 110≈0.0091, =1 / 130≈0.007; Assume the measured field strengths at the three points are as follows: , . , The final predicted value of -83.8dBm is closer to the field strength of points A and B with better propagation conditions, while the influence of the field strength of point C, which is severely blocked by buildings, is suppressed by its smaller weight. When calculating signal propagation path loss, the effects of digital elevation model data, land cover type data, and building outline data on radio wave propagation are comprehensively considered. The corresponding calculation formula is: ,in, This represents the base path loss at the reference distance. Indicates the path loss index; Indicates associated grid receiving point To the current target grid The straight-line distance. This represents the diffraction loss calculated based on DEM data. The diffraction edge loss between the signal path and the terrain profile can be calculated using models such as the Egli model and the Deygout method. This indicates the additional loss based on land cover type data. It is a value obtained from a table, for example: water bodies: +0 dB, farmland: +2 dB, dense forest: +15 dB; This indicates additional loss based on building outline data. If the ray intersects with the building polygon (i.e., is blocked), a large fixed loss value (e.g., +30dB) is assigned, or the penetration loss is calculated based on the building's material and height. If it is a line-of-sight distance, then... By integrating multi-source data into the classic propagation model, the accuracy and reliability of field strength prediction in complex environments have been greatly improved.

[0022] The steps of adjusting the coverage area of ​​the selected boxes in the initial selection box chain and using the adjusted selection box chain as the target selection box chain include: obtaining multiple selected boxes in the initial selection box chain; grouping the multiple selected boxes into a collaborative scaling group based on the common environmental feature partition or common field strength variation pattern to which the multiple selected boxes belong; wherein, the common environmental feature partition is obtained by performing terrain feature clustering on the digital elevation model data of its coverage area; the common field strength variation pattern is identified by analyzing the field strength attenuation rate and fluctuation variance of the upstream predicted raster receiver points corresponding to each selected box; performing an association adjustment operation on the collaborative scaling group; when the local propagation situation information of a certain selected box in the collaborative scaling group is significantly different from that of other selected boxes in the group, the selected box is removed from the collaborative scaling group and its boundary is adjusted separately; and using the adjusted selection box chain as the target selection box chain. It should be noted that the step of grouping multiple selection boxes into a collaborative scaling group based on the common environmental feature partitions to which they belong includes: performing terrain feature clustering on the digital elevation model data of the area covered by the selection boxes to obtain multiple environmental feature partitions; grouping selection boxes belonging to the same environmental feature partition into the same collaborative scaling group; specifically, extracting terrain feature parameters from the digital elevation model data, the terrain feature parameters including at least one of elevation, slope, and aspect; using a clustering algorithm to partition the covered area based on the terrain feature parameters, dividing areas with similar terrain features into the same environmental feature partition; and grouping the multiple selection boxes into a collaborative scaling group based on the common field strength variation pattern to which they belong. The steps include: analyzing the field strength attenuation rate and fluctuation variance of the upstream predicted dwell points corresponding to each selection box; identifying selection boxes with similar field strength attenuation rates and fluctuation variances as having a common field strength change pattern; merging selection boxes with a common field strength change pattern into the same co-scaling group; when adjusting the first selection box in the initial selection box chain, its end away from the transmitter is defined as the boundary coinciding with the transmitter position; the scaling order of the selection boxes in the initial selection box chain starts from the selection box closest to the transmitter and proceeds sequentially towards the direction away from the transmitter; by adjusting the coverage area of ​​the selection box, the number of grid receiving points covered by the selection box in the corresponding propagation direction is adjusted, where the coverage area of ​​the selection box is referred to here.

[0023] Specifically, a collaborative scaling group is a group of selection boxes with different propagation directions but similar environmental characteristics (terrain) or historical signal behavior (field strength variation patterns). This allows multiple selection boxes in similar situations to form a "team." Thus, when the detection range needs adjustment, a single command can be issued to the entire team (unified adjustment), instead of issuing individual commands to each selection box, greatly improving efficiency. Local propagation situation information is a set of dynamic parameters used to quantify the signal transmission difficulty and reliability faced by a single selection box in its specific propagation direction. Boundary adjustment specifically refers to an adjustment method that fixes the far end and moves the near end. Boundary adjustment involves fixing the cursor end and then pulling or loosening the end closer to the source to change the coverage area of ​​the selection box, ensuring that the prediction always moves forward (away from the source).

[0024] Based on Digital Elevation Model (DEM) data, if the propagation path of the selected box has significant terrain undulations (high variance, steep slope), a magnification operation is triggered to capture possible diffraction paths. Land cover attenuation is based on land cover type data; if the path includes urban building clusters (high attenuation) or open water areas (low attenuation), magnification (to overcome attenuation) or reduction (to improve efficiency) operations are triggered accordingly. Signal stability is based on the field strength data of upstream predicted grids. If the field strength value fluctuates drastically (high variance), indicating high prediction uncertainty, a magnification operation is triggered to obtain more sample data and smooth the prediction results. Common terrain feature partitions correspond to the results of terrain clustering analysis. If multiple selected boxes (even with different propagation directions) are located within the same "hilly area" or "flat area" clustered from DEM data, they are associated and uniformly adjusted, treated as a whole for batch efficiency optimization, ensuring prediction accuracy in complex areas while achieving computational efficiency in uniform areas.

[0025] The steps of performing associated adjustment operations on the collaborative scaling group include: acquiring local propagation situation information of each selection box in the collaborative scaling group in the corresponding propagation direction, wherein the local propagation situation information includes at least one of terrain occlusion, ground feature attenuation, and signal stability; determining the boundary adjustment strategy of the collaborative scaling group based on the local propagation situation information; determining the target coverage area of ​​each selection box based on the boundary adjustment strategy; fixing the end of each selection box in the collaborative scaling group that is away from the emission source in the propagation direction, and moving the end that is close to the emission source in the direction away from or close to the emission source to adjust its boundary to the target coverage area, and resampling within the new boundary range; and forming the target selection box chain based on the boundary adjustment results of each collaborative scaling group. Specifically, terrain occlusion is obtained by analyzing digital elevation model data in the propagation direction and calculating the ratio of the maximum obstruction height to the path length in the path profile. This is used to characterize the degree of signal occlusion caused by terrain undulations in the propagation direction. Ground feature attenuation is obtained by identifying the land cover type in the propagation direction and querying a preset ground feature attenuation coefficient mapping table corresponding to the mid-wave frequency band. This is used to characterize the degree of signal attenuation caused by ground features in the propagation direction. Signal stability is obtained by calculating the statistical variance of the field strength values ​​of the predicted dwell points upstream of the selection box. This is used to characterize the stability of the signal in the propagation direction. The adjustment operation for the selection box includes: adjusting the number of grid receiving points associated with the selection box, or adjusting the spatial search radius of the selection box. The adjustment operation corresponding to the collaborative scaling group is: when multiple selection boxes in the initial selection box chain are grouped into the same collaborative scaling group, all selection boxes in the group are scaled using a uniform scaling factor. The step of determining the boundary adjustment strategy of the collaborative scaling group based on the local propagation situation information includes: when at least one of the terrain occlusion, ground object attenuation, or signal stability is higher than a preset threshold, reducing the boundary adjustment strategy of the selection box coverage area to reduce the number of grid receiving points covered by the selection box in the propagation direction; when at least one of the terrain occlusion, ground object attenuation, or signal stability is lower than a preset threshold, increasing the boundary adjustment strategy of the selection box coverage area to increase the number of grid receiving points covered by the selection box in the propagation direction. The steps of determining the target coverage area of ​​each selection box according to the boundary adjustment strategy, fixing the end of each selection box in the collaborative scaling group that is away from the emission source in the propagation direction, and moving the end that is close to the emission source in a direction away from or close to the emission source to adjust its boundary to the target coverage area, and resampling within the new boundary range include: determining the target coverage area according to the boundary adjustment strategy; keeping the end of the selection box away from the emission source fixed in the propagation direction; when it is necessary to reduce the coverage area of ​​the selection box, moving the end that is close to the emission source in a direction away from the emission source, and when it is necessary to increase the coverage area of ​​the selection box, moving the end that is close to the emission source in a direction close to the emission source, so that the current coverage area of ​​the selection box is equal to the target coverage area; and performing a resampling operation within the adjusted selection box boundary range. Specifically, the resampling operation involves adjusting the spatial search radius or sector angle of the selection box to ensure that the number of grid receivers it covers matches the requirements of the target coverage area. It also involves collecting the field strength values ​​corresponding to each grid receiver within the coverage area, fixing the far end to maintain the current prediction "frontline." Adjusting the near end only changes the length and range of its data source. This minimizes the interference of scaling operations on the prediction process, achieving smooth and controllable changes in coverage. Since all members within the group use the same adjustment logic (fixing the far end and moving the near end) and receive unified instructions, batch adjustments for the entire group become very simple and fast. Only the same geometric operation needs to be performed independently on each selection box, greatly improving computational efficiency.

[0026] A field strength prediction system based on medium-wave broadcasting, applied to any one of the field strength prediction methods based on medium-wave broadcasting described above, includes: The module is used to acquire the environmental spatial information of the transmitter used for medium wave broadcasting, and to build an environmental model of the transmitter based on the environmental spatial information; The configuration module is used to rasterize the target area of ​​the transmitter based on the prediction model to form multiple raster receiving points; and to configure predictive control information for the transmitter based on the prediction model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor. The prediction module is used to drive the cursor to move sequentially within the target area along the propagation direction; predict the field strength value of the cursor at each position based on the selection box chain of the cursor; connect the grid points that meet the preset field strength conditions to form the field strength range outline; and output the field strength range and the field strength values ​​of each grid point within it as the final prediction result.

[0027] This invention predicts the field strength data of the target receiving point in real time based on environmental data of each target area and other predicted field strength data related to the current location. This can effectively improve the accuracy of field strength prediction. During the prediction process, the selection box is dynamically scaled according to local propagation situation information. In areas with complex environments and unstable signals, the selection box range is automatically expanded to integrate more data, while in areas with simple environments and stable signals, the selection box range is automatically reduced, thereby improving the overall prediction efficiency.

[0028] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0029] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A field strength prediction method based on medium-wave broadcasting, characterized in that, Includes the following steps: Obtain the environmental spatial information of the transmitter used for medium-wave broadcasting, and construct an environmental model of the transmitter based on the environmental spatial information; The target area of ​​the transmitter is rasterized based on the prediction model to form multiple raster receiving points; predictive control information is configured for the transmitter based on the prediction model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor; The cursor is driven to move sequentially within the target area along the propagation direction; the field strength value of the cursor at each position is predicted based on the selection box chain of the cursor; grid points that meet the preset field strength conditions are connected to form the field strength range outline; and the field strength range and the field strength values ​​of each grid point within it are output as the final prediction result.

2. The field strength prediction method based on medium-wave broadcasting according to claim 1, characterized in that: The steps of obtaining the environmental spatial information of the transmitter used for medium-wave broadcasting and constructing an environmental model of the transmitter based on the environmental spatial information include: Acquire multi-source environmental data of the target area where the emission source is located. The multi-source environmental data includes at least digital elevation model data, land cover type data, and building outline data. A three-dimensional terrain triangular mesh surface is generated based on the digital elevation model data; according to the land cover type data and the preset mapping table, the surface conductivity value and relative permittivity value of the mid-wave frequency band are associated with the triangular facets of the three-dimensional terrain triangular mesh surface. A three-dimensional building volumetric model is generated based on the building outline data and constructed on a three-dimensional terrain triangular mesh surface to output an environmental space model.

3. The field strength prediction method based on medium-wave broadcasting according to claim 1, characterized in that: The step of configuring predictive control information for the emission source based on a predictive model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor, includes: Based on the prediction model, an independent cursor is configured for each of the multiple different propagation directions originating from the emission source; Each cursor is configured with a selection box chain, which includes multiple selection boxes corresponding to multiple propagation directions.

4. The field strength prediction method based on medium-wave broadcasting according to claim 3, characterized in that: The driving cursor moves sequentially within the target area along the propagation direction; The steps of predicting the field strength value at each position of the cursor based on the selection box chain, and connecting grid points that meet the preset field strength conditions to form the field strength range outline include: The current grid receiving point where the cursor is located is collected in real time, and the target selection box chain is obtained by determining the selection box chain corresponding to the current grid receiving point. The field strength value of the current grid receiving point is predicted based on the field strength value of the grid receiving point corresponding to the target selection box chain. The cursor is driven to move sequentially within the target area along the propagation direction, and multiple field strength values ​​are obtained based on multiple grid receiving points; The grid receiving points corresponding to the field strength values ​​that meet the preset field strength threshold are taken as valid grid receiving points. The boundary contour of the continuous area formed by adjacent valid grid receiving points is taken as the field strength range. The coordinates and field strength values ​​of all grid receiving points within the field strength range are taken as the field strength prediction results.

5. The field strength prediction method based on medium-wave broadcasting according to claim 4, characterized in that: The steps of acquiring the current grid receiving point of the real-time acquisition cursor, determining the selection box chain corresponding to the cursor at the current grid receiving point to obtain the target selection box chain, and predicting the field strength value of the current grid receiving point based on the field strength value of the grid receiving point corresponding to the target selection box chain include: Obtain the grid receiving point where the cursor is currently positioned, and use it as the current target grid. Based on a preset spatial association strategy, an initial selection frame chain corresponding to the current target grid receiving point is determined. This initial selection frame chain consists of multiple selection frames arranged sequentially along the propagation direction. Each selection frame contains one or more upstream grid receiving points with predicted field strengths. The spatial association strategy is as follows: Using the current target grid as a reference, along the reverse direction of the cursor propagation, a fixed number of adjacent grids or all predicted grids within a fixed sector area are selected by the selection box, and multiple selection boxes are connected to form the initial selection box chain. Adjust the coverage area of ​​the selection boxes in the initial selection box chain, and use the adjusted selection box chain as the target selection box chain; Based on the field strength values ​​of all associated grid receiving points within the target selection frame chain, the field strength value of the current target grid is predicted.

6. The field strength prediction method based on medium-wave broadcasting according to claim 5, characterized in that: The step of adjusting the coverage area of ​​the selection boxes in the initial selection box chain and using the adjusted selection box chain as the target selection box chain includes: Retrieve multiple selection boxes from the initial selection box chain; Based on the common environmental feature partitions or common field strength change patterns to which multiple selection boxes belong, the multiple selection boxes are grouped into a collaborative scaling group, and an associated adjustment operation is performed on the collaborative scaling group. When the local propagation situation information of a selection box in a collaborative scaling group differs significantly from that of other selection boxes in the group, the selection box is removed from the collaborative scaling group and its boundary is adjusted separately. Use the adjusted selection box chain as the target selection box chain.

7. The field strength prediction method based on medium-wave broadcasting according to claim 6, characterized in that: The step of performing the associated adjustment operation on the collaborative scaling group includes: Obtain the local propagation situation information of each selection box in the collaborative scaling group in the corresponding propagation direction. The local propagation situation information includes at least one of terrain occlusion, ground feature attenuation and signal stability. Based on the local propagation situation information, determine the boundary adjustment strategy for the collaborative scaling group; The target coverage area of ​​each selection box is determined according to the boundary adjustment strategy. The end of each selection box in the co-scaling group that is far away from the emission source in the propagation direction is fixed, and the end that is close to the emission source is moved in the direction away from or close to the emission source to adjust its boundary to the target coverage area, and resampling is performed within the new boundary range. Based on the boundary adjustment results of each collaborative scaling group, the target selection box chain is formed.

8. The field strength prediction method based on medium-wave broadcasting according to claim 7, characterized in that: The step of determining the boundary adjustment strategy of the collaborative scaling group based on the local propagation situation information includes: When at least one of the terrain occlusion, ground object attenuation, or signal stability is higher than a preset threshold, the boundary adjustment strategy of reducing the selection box coverage area is adopted to reduce the number of grid receiving points covered by the selection box in the propagation direction. When at least one of the terrain occlusion, ground object attenuation, or signal stability is lower than a preset threshold, the boundary adjustment strategy of the selection box coverage area is increased to increase the number of grid receiving points covered by the selection box in the propagation direction.

9. The field strength prediction method based on medium-wave broadcasting according to claim 7, characterized in that: The steps of determining the target coverage area of ​​each selection box according to the boundary adjustment strategy, fixing the end of each selection box in the collaborative scaling group that is away from the emission source in the propagation direction, moving the end that is closer to the emission source in the direction away from or closer to the emission source to adjust its boundary to the target coverage area, and resampling within the new boundary range include: The target coverage area is determined according to the boundary adjustment strategy; the selection box is kept fixed at the end furthest from the emission source in the propagation direction. When it is necessary to reduce the coverage area of ​​the selection box, the end closer to the emission source is moved away from the emission source; when it is necessary to increase the coverage area of ​​the selection box, the end closer to the emission source is moved closer to the emission source, so that the current coverage area of ​​the selection box is equal to the target coverage area. Resampling is performed within the adjusted selection box boundaries.

10. A field strength prediction system based on medium-wave broadcasting, applied to the field strength prediction method based on medium-wave broadcasting as described in any one of claims 1-9, characterized in that, include: The module is used to acquire the environmental spatial information of the transmitter used for medium wave broadcasting, and to build an environmental model of the transmitter based on the environmental spatial information; The configuration module is used to rasterize the target area of ​​the transmitter based on the prediction model to form multiple raster receiving points; and to configure predictive control information for the transmitter based on the prediction model, wherein the predictive control information includes a cursor and a selection box chain corresponding to the cursor. The prediction module is used to drive the cursor to move sequentially within the target area along the propagation direction; predict the field strength value of the cursor at each position based on the selection box chain of the cursor; connect the grid points that meet the preset field strength conditions to form the field strength range outline; and output the field strength range and the field strength values ​​of each grid point within it as the final prediction result.

Images