Signal distribution prediction method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a signal distribution prediction method and device, equipment, a storage medium and a program product, and the method comprises the steps: determining a target prediction model in a plurality of prediction models according to the angle of a signal incidence pitch angle of an emission source relative to a preset region and a preset threshold value, the target prediction model is used for predicting signal distribution of the emission source in a preset area; determining a plurality of calculation sections in the preset area according to the angle of the azimuth angle of signal incidence, the boundary information of the preset area and the coordinates of the central point; and according to the source parameters of the emission source and the plurality of calculation sections, predicting the prediction signal distribution of the plurality of calculation sections through the target prediction model, and according to the prediction signal distribution of the plurality of calculation sections, determining the prediction signal distribution of the preset area. The method is used for accurately predicting the prediction signal distribution of the preset area.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of wireless communication technology, and in particular, to a signal distribution prediction method, apparatus, device, storage medium, and program product. Background Art

[0002] During the signal propagation process of the transmitting source, it is necessary to predict the signal distribution of the transmitting source in a preset area in order to deploy various signal receiving devices on the ground.

[0003] In the related art, a preset area may be divided into a plurality of calculation grids, and the signal of each calculation grid may be calculated one by one to obtain the signal distribution of the entire preset area.

[0004] However, there may be an area calculated based on multiple calculation grids that exceeds the range of the preset area, resulting in a low accuracy of the calculated signal distribution of the preset area. Summary of the invention

[0005] The embodiments of the present application provide a signal distribution prediction method, apparatus, device, storage medium and program product to solve the technical problem in the related art that the area calculated based on multiple computing grids exceeds the scope of the preset area, resulting in low accuracy of the calculated signal distribution of the preset area.

[0006] In a first aspect, an embodiment of the present application provides a signal distribution prediction method, the method comprising:

[0007] Determine a target prediction model from a plurality of prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold, wherein the target prediction model is used to predict the signal distribution of the transmitting source in the preset area;

[0008] Determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area, and the coordinates of the center point;

[0009] According to the source parameters of the emission source and the multiple calculation sections, the predicted signal distribution of the multiple calculation sections is predicted by the target prediction model, and according to the predicted signal distribution of the multiple calculation sections, the predicted signal distribution of the preset area is determined.

[0010] In a possible implementation, determining a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area, and the coordinates of the center point includes:

[0011] Determine an equation of a first straight line passing through the center point according to the angle of the azimuth and the coordinates of the center point;

[0012] Determine equations of a plurality of second straight lines according to the coordinates of a plurality of vertices of the preset area, the equation of the first straight line, a preset spacing, the coordinates of the center point, and the angle of the azimuth;

[0013] The plurality of calculated cross sections are determined according to the equation of the first straight line, the equations of the plurality of second straight lines and the boundary information of the preset area.

[0014] In a possible implementation, determining the equations of the plurality of second lines according to the coordinates of the plurality of vertices of the preset area, the equation of the first line, the preset spacing, the coordinates of the center point, and the angle of the azimuth includes:

[0015] Determine the length of a first perpendicular line segment from each vertex to the first straight line according to the coordinates of each vertex of the preset area and the equation of the first straight line, and obtain the lengths of multiple first perpendicular line segments;

[0016] Determine a target first vertical line segment among the plurality of first vertical line segments, wherein the target first vertical line segment is the first vertical line segment with the longest length among the plurality of first vertical line segments;

[0017] Determining the lengths of a plurality of second vertical line segments passing through the center point according to the target first vertical line segment and the preset spacing;

[0018] The equations of the plurality of second straight lines are determined according to the coordinates of the central point, the lengths of the plurality of second vertical line segments and the angles of the azimuth angles.

[0019] In a possible implementation, the multiple calculation sections include an initial calculation section and a step calculation section; and predicting the predicted signal distribution of the multiple calculation sections by the target prediction model according to the source parameters of the emission source and the multiple calculation sections, comprises:

[0020] Obtaining geographical parameters and meteorological parameters of the preset area;

[0021] Predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameters, the geographic parameters and the meteorological parameters;

[0022] The predicted signal distribution of the step-by-step calculation section is predicted based on the predicted signal distribution of the initial calculation section, the source parameters, the geographical parameters and the meteorological parameters.

[0023] In a possible implementation, predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameter, the geographic parameter and the meteorological parameter includes:

[0024] Determining the initial signal strength of the transmitting source in the initial calculation cross section according to the source parameter, the geographical parameter and the meteorological parameter;

[0025] Dividing the initial calculation section into a plurality of calculation grids according to a preset grid size;

[0026] According to the source parameter, the initial signal strength, the geographic parameter and the meteorological parameter, predicting the predicted signal strength of each calculation grid in the initial calculation section by the target prediction model;

[0027] The predicted signal distribution of the initial calculation section is determined according to the predicted signal strength of each calculation grid in the initial calculation section.

[0028] In a possible implementation, predicting the predicted signal distribution of the step calculation section according to the predicted signal distribution of the initial calculation section, the source parameter, the geographical parameter, and the meteorological parameter includes:

[0029] Dividing the step calculation section into a plurality of calculation grids according to a preset grid size;

[0030] Determining a first computing grid and a second computing grid among the plurality of computing grids;

[0031] Predicting the predicted signal strength of the first computing grid by the target prediction model according to the predicted signal distribution of the initial computing cross section, the source parameter, the geographic parameter and the meteorological parameter;

[0032] According to the source parameters, predicting the predicted signal strength of the second computing grid by a free space propagation model;

[0033] The predicted signal distribution of the step calculation section is determined according to the predicted signal strength of the first calculation grid and the predicted signal strength of the second calculation grid.

[0034] In a possible implementation manner, determining a first computing grid and a second computing grid from the multiple computing grids includes:

[0035] Determining a blind spot height according to the pitch angle and a distance between the initial calculation section and the step calculation section;

[0036] Determine a computing grid whose height is less than or equal to the blind spot height among the multiple computing grids as a first computing grid;

[0037] A calculation grid whose height among the multiple calculation grids is greater than the height of the blind area is determined as the second calculation grid.

[0038] In a possible implementation, the multiple prediction models include a first prediction model and a second prediction model; determining a target prediction model from the multiple prediction models according to an elevation angle of a signal incident from a transmitting source relative to a preset area and a preset threshold value, including:

[0039] If the pitch angle is less than the preset threshold, determining the first prediction model as the target prediction model;

[0040] If the pitch angle is greater than or equal to the preset threshold, the second prediction model is determined as the target prediction model.

[0041] In a second aspect, an embodiment of the present application provides a signal distribution prediction device, comprising:

[0042] The determination module is used to determine a target prediction model from multiple prediction models according to the pitch angle of the signal incident from the transmitting source relative to the preset area and a preset threshold, wherein the target prediction model is used to predict the signal distribution of the transmitting source in the preset area;

[0043] The determination module is further used to determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area and the coordinates of the center point;

[0044] A prediction module, configured to predict the predicted signal distribution of the multiple calculation cross sections through the target prediction model according to the source parameters of the emission source and the multiple calculation cross sections;

[0045] The determination module is further used to determine the predicted signal distribution of the preset area according to the predicted signal distribution of the multiple calculation sections.

[0046] In a possible implementation manner, the determining module is specifically configured to:

[0047] Determine an equation of a first straight line passing through the center point according to the angle of the azimuth and the coordinates of the center point;

[0048] Determine equations of a plurality of second straight lines according to the coordinates of a plurality of vertices of the preset area, the equation of the first straight line, a preset spacing, the coordinates of the center point, and the angle of the azimuth;

[0049] The plurality of calculated cross sections are determined according to the equation of the first straight line, the equations of the plurality of second straight lines and the boundary information of the preset area.

[0050] In a possible implementation manner, the determining module is further configured to:

[0051] Determine the length of a first perpendicular line segment from each vertex to the first straight line according to the coordinates of each vertex of the preset area and the equation of the first straight line, and obtain the lengths of multiple first perpendicular line segments;

[0052] Determine a target first vertical line segment among the plurality of first vertical line segments, wherein the target first vertical line segment is the first vertical line segment with the longest length among the plurality of first vertical line segments;

[0053] Determining the lengths of a plurality of second vertical line segments passing through the center point according to the target first vertical line segment and the preset spacing;

[0054] The equations of the plurality of second straight lines are determined according to the coordinates of the central point, the lengths of the plurality of second vertical line segments and the angles of the azimuth angles.

[0055] In a possible implementation, the multiple calculation sections include an initial calculation section and a step calculation section; and the prediction module is specifically used to:

[0056] Obtaining geographical parameters and meteorological parameters of the preset area;

[0057] Predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameters, the geographic parameters and the meteorological parameters;

[0058] The predicted signal distribution of the step-by-step calculation section is predicted based on the predicted signal distribution of the initial calculation section, the source parameters, the geographical parameters and the meteorological parameters.

[0059] In a possible implementation, the prediction module is further configured to:

[0060] Determining the initial signal strength of the transmitting source in the initial calculation cross section according to the source parameter, the geographical parameter and the meteorological parameter;

[0061] Dividing the initial calculation section into a plurality of calculation grids according to a preset grid size;

[0062] According to the source parameter, the initial signal strength, the geographic parameter and the meteorological parameter, predicting the predicted signal strength of each calculation grid in the initial calculation section by the target prediction model;

[0063] The predicted signal distribution of the initial calculation section is determined according to the predicted signal strength of each calculation grid in the initial calculation section.

[0064] In a possible implementation, the prediction module is further configured to:

[0065] Dividing the step calculation section into a plurality of calculation grids according to a preset grid size;

[0066] Determining a first computing grid and a second computing grid among the plurality of computing grids;

[0067] Predicting the predicted signal strength of the first computing grid by the target prediction model according to the predicted signal distribution of the initial computing cross section, the source parameter, the geographic parameter and the meteorological parameter;

[0068] According to the source parameters, predicting the predicted signal strength of the second computing grid by a free space propagation model;

[0069] The predicted signal distribution of the step calculation section is determined according to the predicted signal strength of the first calculation grid and the predicted signal strength of the second calculation grid.

[0070] In a possible implementation, the prediction module is further configured to:

[0071] Determining a blind spot height according to the pitch angle and a distance between the initial calculation section and the step calculation section;

[0072] Determine a computing grid whose height is less than or equal to the blind spot height among the multiple computing grids as a first computing grid;

[0073] A calculation grid whose height among the multiple calculation grids is greater than the height of the blind area is determined as the second calculation grid.

[0074] In a possible implementation manner, the multiple prediction models include a first prediction model and a second prediction model; and the determination module is further configured to:

[0075] If the pitch angle is less than the preset threshold, determining the first prediction model as the target prediction model;

[0076] If the pitch angle is greater than or equal to the preset threshold, the second prediction model is determined as the target prediction model.

[0077] In a third aspect, an embodiment of the present application provides a signal distribution prediction device, including:

[0078] at least one processor; and

[0079] a memory communicatively connected to the at least one processor; wherein,

[0080] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform any method described in the first aspect.

[0081] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in any one of the first aspects.

[0082] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements any method in the first aspect when executed by a processor.

[0083] The signal distribution prediction method, device, equipment, storage medium and program product provided by the embodiment of the present application, the method determines a target prediction model in multiple prediction models according to the angle of the pitch angle of the signal incident from the transmitting source relative to the preset area and the preset threshold; determines multiple calculation sections in the preset area according to the angle of the azimuth angle of the signal incident and the coordinates of the center point of the preset area; predicts the predicted signal distribution of multiple calculation sections through the target prediction model according to the source parameters of the transmitting source and the multiple calculation sections, and determines the predicted signal distribution of the preset area according to the predicted signal distribution of the multiple calculation sections. The method can adaptively determine multiple calculation sections in the preset area based on the angle of the azimuth angle of the signal incident and the coordinates of the center point of the preset area to avoid the problem of the calculation area exceeding the preset area during the calculation process; and also determines a suitable target prediction model based on the angle of the pitch angle of the signal incident and the preset threshold, so as to accurately predict the predicted signal distribution of the preset area according to the target prediction model and the multiple calculation sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0085] Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application;

[0086] Figure 2 One of the flow charts of the signal distribution prediction method provided in the embodiment of the present application;

[0087] Figure 3 A schematic diagram of an incident azimuth angle and a pitch angle from a transmitting source to a ground receiving source provided in an embodiment of the present application;

[0088] Figure 4 A schematic diagram of a calculated cross section in a preset area provided in an embodiment of the present application;

[0089] Figure 5 The second flowchart of the signal distribution prediction method provided in the embodiment of the present application;

[0090] Figure 6 A schematic diagram of a first straight line and a second straight line of a preset area provided in an embodiment of the present application;

[0091] Figure 7 The third flowchart of the signal distribution prediction method provided in the embodiment of the present application;

[0092] Figure 8 A schematic diagram of a two-way propagation process of a signal provided in an embodiment of the present application;

[0093] Fig. 9 One of the blind area schematic diagrams of the plane wave calculation of the parabolic equation provided in the embodiment of the present application;

[0094] Fig.10 The second schematic diagram of the blind area of ​​the plane wave calculation of the parabolic equation provided in the embodiment of the present application;

[0095] Fig.11 A schematic diagram of the structure of a signal distribution prediction device provided in an embodiment of the present application;

[0096] Fig.12 A schematic diagram of the structure of a signal distribution prediction device provided in an embodiment of the present application.

[0097] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0098] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0099] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0100] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of data and other information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0101] It should be noted that the signal distribution prediction method, device, equipment, storage medium and program product provided in the present application can be used in the field of wireless communications, and can also be used in any field other than the field of wireless communications, for example, electromagnetism and other fields. The present application does not limit the application field of the signal distribution prediction method, device, equipment, storage medium and program product.

[0102] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0103] In order to facilitate understanding of the technical solutions of the embodiments of the present application, the application scenarios of the embodiments of the present application are introduced below.

[0104] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present application. Figure 1 , a receiving source is included in a preset area on the ground, and the transmitting source and the receiving source can communicate based on signals. In some examples, the transmitting source can be a satellite, the preset area can be a suburb, and the receiving source can be a terminal, a base station or other signal receiving device.

[0105] In the related art, the preset area can be divided into multiple calculation grids, and the signal of each calculation grid is calculated one by one to obtain the signal distribution of the entire preset area. However, there may be an area calculated based on multiple calculation grids that exceeds the range of the preset area, resulting in a low accuracy of the calculated signal distribution of the preset area.

[0106] In view of this, an embodiment of the present application provides a signal distribution prediction method, which includes: determining a target prediction model from multiple prediction models according to the angle of the pitch angle of the signal incident from the transmitting source relative to the preset area and a preset threshold; determining multiple calculation sections in the preset area according to the angle of the azimuth angle of the signal incident and the coordinates of the center point of the preset area; predicting the predicted signal distribution of the multiple calculation sections through the target prediction model according to the source parameters of the transmitting source and the multiple calculation sections, and determining the predicted signal distribution of the preset area according to the predicted signal distribution of the multiple calculation sections. The method can adaptively determine multiple calculation sections in the preset area based on the angle of the azimuth angle of the signal incident and the coordinates of the center point of the preset area to avoid the problem of the calculation area exceeding the preset area during the calculation process; and, based on the angle of the pitch angle of the signal incident and the preset threshold, determine a suitable target prediction model to accurately predict the predicted signal distribution of the preset area according to the target prediction model and the multiple calculation sections.

[0107] The method shown in the present application is described below through specific embodiments. It should be noted that the following embodiments can exist independently or in combination with each other, and the same or similar contents will not be described repeatedly in different embodiments.

[0108] Figure 2 One of the flow charts of the signal distribution prediction method provided in the embodiment of the present application. The method can be executed by a signal distribution prediction device, or it can also be executed by a signal distribution prediction device in a signal distribution prediction device, and the signal distribution prediction device can be implemented by software or by a combination of software and hardware.

[0109] See also Figure 2 , the method may include the following steps:

[0110] S201. Determine a target prediction model from multiple prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold.

[0111] The transmitting source may be a transmitting source in an outer space region. For example, the transmitting source may be a low-orbit satellite, such as a communication satellite, a remote sensing satellite, and an earth observation satellite.

[0112] The target prediction model is used to predict the signal distribution of the transmitting source in a preset area.

[0113] The preset area may be determined based on configuration information input by a user.

[0114] During the signal propagation process of the transmitting source, the wave equation can be used to predict the signal distribution in the preset area. Assuming that the signal propagates along the +x axis, the wave equation can satisfy the following formula:

[0115]

[0116] Where k0 is the propagation constant of the signal in a vacuum; x represents the propagation distance of the signal in the x-axis direction; z represents the propagation distance of the signal in the z-axis direction; u(x,z) represents the signal distribution in the plane formed by x and z; i represents the imaginary unit; if the signal is a horizontally polarized wave, ψ(x,z) corresponds to E y (x,z),E y (x,z) is a non-zero electric field component; if the signal is a vertically polarized wave, then ψ(x,z) corresponds to H y (x,z),H y (x,z) is a non-zero magnetic field component.

[0117] However, in the signal propagation process of the transmitting source, the geographical environment and the meteorological environment have a great influence on the signal propagation, and the parabolic equation model derived from the wave equation, when predicting the signal propagation process of the transmitting source, not only takes into account the refraction and diffraction effects of signal propagation, but also takes into account the influence of the geographical and meteorological environment on signal propagation, and has a fast calculation speed, making it more applicable in determining the field distribution of the signal propagation process of the transmitting source. Therefore, in some embodiments, the parabolic equation model can be used to simulate the signal distribution of the transmitting source in a preset area.

[0118] In some embodiments, the plurality of prediction models and the target prediction model may include a parabolic equation model.

[0119] When the parabolic equation model is used to predict signal distribution, it has the following characteristics: when the signal propagates forward in the positive direction of the x-axis, if the calculated elevation angle of the parabolic equation is less than 45°, the ground's retroreflection effect on the signal is small, and there is no need to consider the ground's retroreflection effect on the signal; if the calculated elevation angle of the parabolic equation is greater than or equal to 45°, the ground's retroreflection effect on the signal is large, and at this time, it is necessary to consider the ground's retroreflection effect on the signal. In view of this, the signal distribution prediction method provided in the embodiment of the present application, when the target prediction model selected is the parabolic equation model, also considers the relationship between the pitch angle and the preset threshold value, so as to further determine a more suitable target prediction model, so as to improve the accuracy of the target prediction model in predicting the signal distribution of the preset area.

[0120] Exemplarily, the preset threshold can be set to 45°.

[0121] S202: Determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, boundary information of the preset area, and coordinates of the center point.

[0122] It should be noted that in this method, the difference between the maximum and minimum angles of the pitch angle of the transmitting source in the preset area needs to be less than or equal to the preset difference; the difference between the maximum and minimum angles of the azimuth angle of the transmitting source in the preset area needs to be less than or equal to the preset difference. In this case, a point can be selected in advance in the preset area to set the receiving source. For example, the receiving source can be located at the center point of the ground in the preset area.

[0123] Exemplarily, the receiving source may be a terminal, a base station or other signal receiving equipment.

[0124] For ease of understanding, below, combined Figure 3 , explain the azimuth and elevation angles.

[0125] Figure 3 A schematic diagram of the incident azimuth and elevation angle from a transmitting source to a receiving source provided in an embodiment of the present application. Figure 3 , assuming that the coordinates of the transmitting source are (x0, y0, z0), and there is a receiving source in the preset area, and the coordinates of the receiving source are (x1, y1, z1), then the pitch angle of the signal from the transmitting source incident on the receiving source is and azimuth angle θ satisfy the following formulas respectively:

[0126]

[0127] θ=atan2(y1-y0,x1-x0)

[0128] In some embodiments, the multiple calculation cross sections may be parallel to each other. By determining multiple parallel calculation cross sections, the target prediction model is more convenient in predicting the signal distribution of the multiple calculation interfaces.

[0129] Exemplarily, the boundary information of the preset area may include coordinates of each boundary point of the preset area.

[0130] Figure 4 For a schematic diagram of the calculation cross section in the preset area provided in the embodiment of the present application, please refer to Figure 4 The preset area includes multiple calculation sections, which are parallel to each other and perpendicular to the xy plane of the preset area.

[0131] It should be noted that the process of determining multiple calculation sections in the preset area will be Figure 5 The details are described in the examples.

[0132] S203. Predicting predicted signal distributions of the multiple calculation sections using a target prediction model according to source parameters of the emission source and the multiple calculation sections, and determining predicted signal distributions of a preset area according to the predicted signal distributions of the multiple calculation sections.

[0133] The source parameters may include, but are not limited to: coordinates of the transmitting source, signal parameters and direction parameters.

[0134] Exemplarily, the signal parameters may include the transmission frequency and transmission field strength of the transmission source.

[0135] In some embodiments, the transmission frequency may also be referred to as a “carrier frequency”, and the transmission frequency may be the frequency at which the transmission source sends electromagnetic waves.

[0136] The emission field strength may be the electric field strength of the electromagnetic wave generated by the emission source at the emission point.

[0137] Directional parameters may include, but are not limited to: antenna pattern, azimuth angle, and elevation angle.

[0138] In some embodiments, the signal distribution prediction device may provide a data interface externally, and a user may input source parameters of a transmission source into the signal distribution prediction device through the data interface.

[0139] In some embodiments, the predicted signal distribution of multiple calculation sections can be determined in a step-by-step manner. Assuming that the number of multiple calculation sections is N, an initial calculation section can be determined among the N calculation sections; the initial signal strength of the signal emitted by the emission source propagating to the initial calculation section can be obtained; and the predicted signal distribution of the initial calculation section is predicted by the target prediction model according to the source parameters, the initial signal strength and the preset boundary conditions of the target prediction model; the initial calculation section is determined as the first calculation section, and the i-th calculation section to be stepped is determined among the remaining N-1 calculation sections, and the predicted signal distribution of the i-th calculation section to be stepped is predicted by the target prediction model according to the predicted signal distribution of the i-1 calculation section and the source parameters; wherein i is successively 2, 3, ..., N, until the predicted signal distribution of the N calculation sections is obtained, and the predicted signal distribution of the N calculation sections can be superimposed to obtain the predicted signal distribution of the preset area.

[0140] It should be noted that the process of predicting the distribution of prediction signals for multiple calculation cross sections will be Figure 7 The details are described in the examples.

[0141] The signal distribution prediction method provided in the embodiment of the present application can adaptively determine multiple calculation sections in the preset area based on the azimuth angle of the signal incidence and the coordinates of the center point of the preset area, so as to avoid the problem of the calculation area exceeding the preset area during the calculation process; and, based on the pitch angle of the signal incidence and the preset threshold, determine a suitable target prediction model to accurately predict the predicted signal distribution of the preset area based on the target prediction model and multiple calculation sections.

[0142] The above embodiment relates to the process of determining multiple calculation sections in a preset area. Figure 5 , the process of determining multiple calculation sections is explained in detail.

[0143] Figure 5 This is a flow chart of the signal distribution prediction method provided in the embodiment of the present application. Figure 5 , the method may include the following steps:

[0144] S501. Determine the equation of the first straight line passing through the center point according to the azimuth angle and the coordinates of the center point.

[0145] In some embodiments, it is assumed that the coordinates of the center point of the preset area are (x c ,y c ), the azimuth is θ, the equation of the first straight line can be determined by the following calculation formula:

[0146] y=kx+b

[0147] Where k = tanθ, b = kx c -y c , x and y are the x variable and y variable of the first straight line equation respectively, k is the slope of the first straight line equation, and b is the constant of the first straight line equation.

[0148] In some embodiments, the following steps S502 to S505 may be performed to determine the equations of multiple second lines based on the coordinates of multiple vertices of a preset area, the equation of the first line, the preset spacing, the coordinates of the center point, and the azimuth angle.

[0149] S502: Determine the length of a first perpendicular line segment from each vertex to the first straight line according to the coordinates of each vertex of the preset area and the equation of the first straight line, and obtain the lengths of multiple first perpendicular line segments.

[0150] Assume that there are n vertices in the preset area, and the coordinates of any vertex are set to (x i ,y i ), where i is 1, 2, ..., n in sequence. For any vertex among the n vertices, the length d of the first perpendicular line segment from the vertex to the first straight line can be calculated using the following formula: i :

[0151]

[0152] S503: Determine a target first vertical line segment from multiple first vertical line segments.

[0153] The target first vertical line segment may be the first vertical line segment with the longest length among the plurality of first vertical line segments.

[0154] In some embodiments, the length of the target first vertical line segment may satisfy the following formula:

[0155] d max =max(d1, d2, ..., d n )

[0156] Among them, d1, d2, and d n Respectively represent the length of the first perpendicular line segment from the 1st, 2nd and nth vertex to the first straight line, d max Indicates the length of the first perpendicular line segment of the target.

[0157] S504: Determine the lengths of multiple second vertical line segments passing through the center point according to the target first vertical line segment and the preset spacing.

[0158] In some embodiments, the length d of the first vertical line segment of the target may be max and the preset spacing Δd, the number n of the second vertical line segments is obtained:

[0159]

[0160] Figure 6 A schematic diagram of a first straight line and a second straight line of a preset area provided in an embodiment of the present application. Figure 6 , the preset area may include n straight lines, and the distance between any two straight lines is Δd. The n straight lines include 1 first straight line and n-1 second straight lines, where the first straight line passes through the center point (x c ,y c ).

[0161] In some embodiments, for any second straight line l j , the following formula can be used to calculate the two straight lines l j With the center point (x c ,y c ) is the length of the second perpendicular segment between:

[0162]

[0163] Among them, j is 1, 2, ..., n respectively.

[0164] S505: Determine equations of multiple second straight lines according to the coordinates of the center point, the lengths of multiple second vertical line segments, and the angles of the azimuths.

[0165] The second straight line may be parallel to the first straight line.

[0166] For any second straight line l j According to the second straight line l j The length d of the second perpendicular line segment between the center point of the preset areaj , the coordinates of the center point (x c ,y c ) and the angle of azimuth θ, the following formula is used to calculate the second perpendicular line segment on the second straight line l j The vertical intersection coordinates (x j ,y j ):

[0167] x j =x c -d j sinθ;

[0168] y j =d j cosθ

[0169] According to the coordinates of the vertical intersection point (x j ,y j ) and the angle of azimuth θ, the second straight line l is calculated using the following formula j The equation is:

[0170] y=kx+b j

[0171] Among them, b j =kx j -y j , x, y are the equations of the second straight line j The x variables and y variables.

[0172] The signal distribution prediction method provided in the embodiment of the present application can quickly determine the equations of multiple second straight lines in the preset area based on the coordinates of multiple vertices of the preset area, the equation of the first straight line, the preset spacing, the coordinates of the center point and the azimuth angle, so as to facilitate the subsequent accurate determination of multiple calculation sections in the preset area based on the equation of the first straight line and the equations of the multiple second straight lines.

[0173] S506: Determine a plurality of calculation sections according to the equation of the first straight line, the equations of the plurality of second straight lines, and the boundary information of the preset area.

[0174] Optionally, the intersection point between the equation of the first straight line and the boundary of the preset area and the intersection point between the equation of each second straight line and the boundary of the preset area may be determined according to the boundary information of the preset area.

[0175] The starting point coordinates and the end point coordinates of the equation of the first straight line in the preset area can be determined according to the intersection of the equation of the first straight line and the boundary of the preset area, and the signal propagation direction, and the maximum step distance of the calculation section corresponding to the equation of the first straight line can be determined according to the starting point coordinates and the end point coordinates of the equation of the first straight line in the preset area. Figure 6There are two intersection points between the equation of the first straight line and the preset area, namely the vertex at the lower left corner and the vertex at the upper right corner of the preset area. Since the signal propagation direction is from the vertex at the lower left corner to the vertex at the lower right corner, the coordinates of the vertex at the lower left corner can be determined as the starting coordinates of the equation of the first straight line in the preset area, and the coordinates of the vertex at the lower right corner can be determined as the ending coordinates of the equation of the first straight line in the preset area.

[0176] Similarly, the starting point coordinates and the end point coordinates of the equation of the second straight line in the preset area can be determined based on the intersection of the equation of the second straight line with the boundary of the preset area and the signal propagation direction, and the maximum step distance of the calculation section corresponding to the equation of the second straight line can be determined based on the starting point coordinates and the end point coordinates of the equation of the second straight line in the preset area.

[0177] The signal distribution prediction method provided in the embodiment of the present application can adaptively divide the preset area into multiple calculation sections based on the azimuth angle of the signal incident from the transmitting source relative to the preset area and the coordinates of the center point of the preset area, so as to avoid the problem of the calculation area exceeding the preset area during the calculation process, which is conducive to improving the accuracy of predicting the signal distribution of the preset area.

[0178] The above embodiment involves a process of predicting the distribution of prediction signals of multiple calculation sections by using a target prediction model according to source parameters and multiple calculation sections. Figure 7 , a detailed description is given of predicting the distribution of prediction signals of multiple calculation sections by a target prediction model based on source parameters and multiple calculation sections.

[0179] Figure 7 This is a flowchart of the signal distribution prediction method provided in the embodiment of the present application. Figure 7 , the method may include the following steps:

[0180] S701: Determine, according to source parameters of a transmitting source, an elevation angle and an azimuth angle of a signal incident on a preset area of ​​the transmitting source.

[0181] In some embodiments, the position information of the transmitting source can be determined based on the source parameters of the transmitting source, and the pitch angle and the azimuth angle can be determined based on the position information of the transmitting source and the position information of the ground receiving source set in a preset area.

[0182] It should be noted that the calculation formula for the pitch angle and the azimuth angle in step S701 may refer to the calculation formula for the pitch angle and the azimuth angle in step S201, and will not be described in detail here.

[0183] S702: Determine whether the pitch angle is less than a preset threshold.

[0184] If so, it means that the pitch angle is less than the preset threshold, and step S703 is executed; if not, it means that the pitch angle is greater than or equal to the preset threshold, and step S704 is executed.

[0185] Exemplarily, the preset threshold may be set to 45°.

[0186] S703: Determine the first prediction model as the target prediction model.

[0187] The first prediction model may be a forward parabolic equation model, which may be a Feit-Fleck type forward parabolic equation model, which may also be called a forward "Wide-Angle Parabolic Equation (WAPE)" model, which may satisfy the following formula:

[0188]

[0189] Where n is the refractive index of the medium, and n(x,z) represents the refractive index of the medium at the plane formed by x and z.

[0190] Since the forward WAPE model includes a square root term, it is not suitable to be solved by the finite difference (FD) method. The forward WAPE model can be solved by the split-step Fourier transform (SSFT) method. The SSFT solution of the forward WAPE model is:

[0191]

[0192] Where △x is the horizontal step size of the computational grid for signal propagation in the horizontal (x-axis) direction; u(x+△x,z) represents the signal distribution in the plane composed of x+△x and z; represents the inverse Fourier transform; p is a frequency domain variable, which can also be called the vertical wave number or spatial frequency, p = k0 sinθ, θ is the grazing angle of the signal horizontally with the ground; U(x,p) represents the p-domain field value during the forward propagation of the signal.

[0193] It can be understood that before calculating the SSFT solution of the forward WAPE model, the boundary conditions and initial fields of the forward WAPE model need to be clarified.

[0194] The forward WAPE model includes an upper boundary and a surface boundary, where:

[0195] The upper boundary of the forward WAPE model is the absorption boundary, which is mainly used to truncate the calculation domain of SSFT. Optionally, a window function can be used to truncate the calculation domain of SSFT, and the window function can satisfy the following formula:

[0196]

[0197] Where W(z) is the window function, Z max is the maximum calculated height of the WAPE model.

[0198] The surface boundary of the forward WAPE model is an impedance boundary. The surface boundary of finite impedance can be described by the following impedance boundary condition, expressed as:

[0199]

[0200] Among them, β is used to reflect the impedance characteristics on the boundary surface, and β can satisfy the following formula:

[0201]

[0202] Among them, ε r ′ is the relative complex permittivity of the boundary surface, ε r ′=ε r +i160σλ,ε r is the relative dielectric constant of the surface medium, σ is the conductivity of the surface medium; a j is the grazing angle on the jth stepping surface.

[0203] The initial field of the forward WAPE model can satisfy the following formula:

[0204]

[0205] Where u(x0,z) represents the initial field of the signal at the initial plane formed by x0 and z, α represents the antenna elevation angle, A(α) represents the antenna pattern function, and R ∥or⊥ Indicates the horizontal or vertical reflection coefficient of the ground, H i Set the height for the antenna.

[0206] S704: Determine the second prediction model as the target prediction model.

[0207] The second prediction model can be a two-way parabolic equation model. The two-way parabolic equation model is based on the traditional forward parabolic equation model. The propagation field of the signal in the preset area is divided into two parts: the forward propagation field and the backward propagation field. The backward propagation field accumulated at each reflection point is added to the forward field according to the distance step, so as to obtain the propagation field of the signal in the preset area.

[0208] Assume that the wave equation of the signal along the +x direction is Among them, ψ F (x,z) is the forward propagation field of the signal along the +x direction; the wave equation of the signal along the -x direction is Among them, ψ B (x,z) is the backward propagation field of the signal along the -x direction. On the wave propagation path, for multiple calculation sections, the signal distribution in each calculation section during forward propagation is first calculated according to the forward parabolic equation. The reflection boundary of the signal can be determined according to the geographic elevation information of the preset area. The reflected signal is calculated using the backward parabolic equation. Finally, the signal distribution in the forward propagation process in each calculation section is superimposed with the calculation results of the signal distribution in the backward propagation process to obtain the predicted signal distribution in the preset area. The calculation formula for the superimposed propagation field is: ψ T (x,z)=ψ F (x,z)+ψ B (x,z).

[0209] The second model may include a forward parabolic equation model and a backward parabolic equation model, and u can be solved by the forward parabolic equation model. F (x,z), solve u through the backward parabolic equation model B (x,z).

[0210] The backward parabolic equation model may be a Feit-Fleck backward parabolic equation model, and the Feit-Fleck backward parabolic equation model may satisfy the following formula:

[0211]

[0212] The SSFT solution of the Feit-Fleck type backward parabolic equation model is:

[0213]

[0214] It is understandable that before calculating the SSFT solution of the Feit-Fleck backward parabolic equation model, the boundary conditions and initial fields of the Feit-Fleck backward parabolic equation model need to be clarified. It should be noted that the boundary conditions and initial fields of the Feit-Fleck backward parabolic equation model can be calculated by referring to the boundary conditions and initial fields of the Feit-Fleck forward parabolic equation model in step S703.

[0215] For ease of understanding, below, combined Figure 8 The forward propagation and backward propagation processes are explained.

[0216] Figure 8 A schematic diagram of a two-way propagation process of a signal provided in an embodiment of the present application. Figure 8 , assuming there are 3 calculation sections, the third calculation section is the reflection surface.

[0217] During the forward propagation process, the forward signal distribution when the signal propagates to the first calculation section is calculated by the forward parabolic equation model according to the initial forward signal distribution of the signal at the first calculation section; the forward signal distribution when the signal propagates to the second calculation section is calculated step by step by the forward parabolic equation model according to the forward signal distribution at the first calculation section; and the forward signal distribution when the signal propagates to the third calculation section is calculated step by step by the forward parabolic equation model according to the signal distribution at the second calculation section.

[0218] During the backward propagation process, the forward signal distribution of the signal at the third calculation section during the forward propagation process is taken as the initial signal distribution, and the backward signal distribution when the signal propagates to the third calculation section is calculated by the backward parabolic equation model; based on the backward signal distribution at the third calculation section, the backward signal distribution when the signal propagates to the second calculation section is step-calculated by the backward parabolic equation model; and based on the backward signal distribution at the second calculation section, the backward signal distribution when the signal propagates to the first calculation section is step-calculated by the backward parabolic equation model.

[0219] For any calculation section, the forward signal distribution and backward signal distribution of each calculation section are superimposed to obtain the predicted signal distribution of the calculation section. According to the predicted signal distribution of each calculation interface, the predicted signal distribution of the preset area is obtained.

[0220] It should be noted that the embodiment of the present application is described using three calculation sections as an example. In some embodiments, the number of calculation sections can also be any value greater than 1. For example, the calculation sections can also be 2, 4, ...

[0221] In an embodiment of the present application, the pitch angle of the transmitting source relative to the preset area can be divided into a large angle (≥45°) and a small angle (<45°) based on a preset threshold, and when the transmitting source is incident at a large angle, the reflection effect of the ground on the signal is taken into account, and a bidirectional parabolic equation model is selected to predict the predicted signal distribution of the transmitting source in the preset area, so that the predicted predicted signal distribution is more accurate.

[0222] S705 . Determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area, and the coordinates of the center point.

[0223] The multiple calculation sections may include initial calculation sections and step calculation sections.

[0224] It should be noted that the specific execution process of step S705 can refer to Figure 5The specific implementation process of the embodiment will not be described in detail here.

[0225] S706: Obtain geographic parameters and meteorological parameters of a preset area.

[0226] The shape of the preset area may be a regular polygon, for example, the preset area may be a rectangular area.

[0227] It is understandable that, during the signal propagation process, when the terrain in the preset area has different undulation heights, the degree of influence of reflection and diffraction on the signal propagation process is different. In addition, the types of media on the surface are relatively complex and diverse. For example, the types of media on the surface may include forest types, river types, and building types. The dielectric constants of different media types vary greatly, so that the media type has a greater impact on the calculation of the surface reflection coefficient and signal propagation.

[0228] Therefore, considering the influence of the elevation data and medium type of the preset area on the signal propagation process of the preset area, in order to more accurately predict the signal propagation process, the geographic parameters selected in the embodiment of the present application may include elevation data and electromagnetic parameters of the medium.

[0229] Elevation data may include information such as geographic coordinates and undulating heights of complex terrain, which may be used to indicate terrain with large undulations and irregular shapes.

[0230] The medium may include forests, rivers, ground, buildings, etc. The electromagnetic parameters of the medium may be used to indicate the propagation characteristics of the signal in the medium. The electromagnetic parameters of the medium may include the dielectric constant, conductivity, and complex dielectric constant of the medium, etc.

[0231] In some embodiments, the elevation data of a preset area can be determined in the following manner: obtain a digital elevation map in GeoTIFF format; determine the complex terrain of the preset area based on the digital elevation map in GeoTIFF format according to the positioning information of the preset area, and extract the geographic coordinates and undulating height information of the complex terrain.

[0232] In some embodiments, the medium type of the surface environment in a preset area may be determined based on the geographic image map in combination with the GlobeLand30 dataset, and the electromagnetic parameters of the medium corresponding to the preset area may be determined based on the medium type.

[0233] Meteorological parameters may include, but are not limited to, the refractive index of air.

[0234] In some embodiments, meteorological information of a preset area may be obtained, and the meteorological information may include but is not limited to the air temperature, humidity, and air pressure of the preset area. After obtaining the meteorological information of the preset area, the meteorological information may be substituted into the empirical formula of the air dielectric constant to calculate the air dielectric constant corresponding to the preset area, and the refractive index of the air in the preset area may be determined based on the air dielectric constant.

[0235] S707. Predict the distribution of prediction signals of the initial calculation section through the target prediction model according to the source parameters, geographic parameters and meteorological parameters.

[0236] In some embodiments, the predicted signal distribution of the initial calculation interface can be determined in the following manner: determine the initial signal strength of the transmitting source in the initial calculation section based on source parameters, geographical parameters and meteorological parameters; divide the initial calculation section into multiple calculation grids according to a preset grid size; predict the predicted signal strength of each calculation grid in the initial calculation section through a target prediction model based on source parameters, initial signal strength, geographical parameters and meteorological parameters; determine the predicted signal distribution of the initial calculation section based on the predicted signal strength of each calculation grid in the initial calculation section.

[0237] In the area between the transmitting source and the ground, since there are fewer factors affecting signal propagation, the signal propagation process can be approximated to free space propagation. The following free space propagation loss calculation formula can be used to calculate the propagation loss of the signal from the transmitting source to the initial calculation section:

[0238] PL = 32.4 + 20lg (f) + 20lg (d)

[0239] Wherein, PL is the free space propagation loss of the signal, f is the transmission frequency of the signal of the transmitting source, in MHz; d is the signal propagation distance, in km.

[0240] According to the transmission signal strength and propagation loss of the transmitting source, the propagation signal strength of the transmitting source propagating to the initial calculation cross section is determined.

[0241] According to the propagation signal strength, boundary conditions, source parameters, meteorological parameters and geographical parameters, the following formula can be used to determine the initial signal strength of the transmitting source in the initial calculation section:

[0242]

[0243] Where u(x0,z) represents the initial signal strength at the initial calculation section composed of x0 and z, α represents the antenna elevation angle, A(α) represents the antenna pattern function, and R ∥or⊥ Indicates the horizontal or vertical reflection coefficient of the ground, H i Set the height for the antenna.

[0244] S708. Predict the prediction signal distribution of the step calculation section according to the prediction signal distribution, source parameters, geographic parameters and meteorological parameters of the initial calculation section.

[0245] In some embodiments, the predicted signal distribution of the step calculation section can be determined in the following manner: according to a preset grid size, the step calculation section is divided into multiple calculation grids; a first calculation grid and a second calculation grid are determined among the multiple calculation grids; according to the predicted signal distribution of the initial calculation section, source parameters, geographical parameters and the meteorological parameters, the predicted signal strength of the first calculation grid is predicted by the target prediction model; according to the transmission source parameters, the predicted signal strength of the second calculation grid is predicted by the free space propagation model; according to the predicted signal strength of the first calculation grid and the predicted signal strength of the second calculation grid, the predicted signal distribution of the step calculation section is determined.

[0246] The propagation process of the signal from the transmitting source near the ground can be approximated as the propagation process of a plane wave. During the propagation of the plane wave, when the parabolic equation is used to step from the initial calculation section to the step calculation section, a blind area of ​​the plane wave field propagation will appear, such as Fig. 9 shown.

[0247] Fig. 9 This is one of the blind area diagrams of the plane wave calculation of the parabolic equation provided in the embodiment of the present application. Fig. 9 When the parabolic equation is iteratively calculated from the initial calculation section to the step calculation section, there is a height difference between the initial calculation section and the step calculation section due to the pitch angle of signal propagation. As a result, when the parabolic equation is iteratively calculated from the initial calculation section to the step calculation section, there are three types of areas in the step calculation section: calculation blind area, parabolic equation calculation area and redundant area, among which: the calculation grids in the calculation blind area need to be blinded; the calculation grids in the parabolic equation calculation area can use the target prediction model to calculate the signal distribution of each calculation grid; the calculation grids in the redundant area can be discarded.

[0248] In some embodiments, the blind spot height can be determined based on the pitch angle and the spacing between the initial calculation section and the step calculation section; a calculation grid whose height is less than or equal to the blind spot height among multiple calculation grids is determined as the first calculation grid; a calculation grid whose height is greater than the blind spot height among multiple calculation grids is determined as the second calculation grid.

[0249] The free space propagation model can be used to predict the signal distribution of a signal propagating in free space. The free space propagation model can be any model used to predict the signal distribution of a signal (or electromagnetic wave) propagating in free space. This application does not limit the type of the free space propagation model.

[0250] Next, combine Fig.10 , the process of determining the blind spot height is explained.

[0251] Fig.10 The second schematic diagram of the blind area of ​​the plane wave calculation of the parabolic equation provided in the embodiment of the present application. Fig.10 When the parabolic equation is iteratively calculated from the initial calculation section to the step calculation section, there is a coverage blind area, and the blind area height of the coverage blind area is h. The height h of the coverage blind area can satisfy the following formula:

[0252]

[0253] Where h is the height of the coverage blind area, and Δx is the distance between the initial calculation section and the step calculation section.

[0254] For the second calculation grid in the coverage blind area, ignoring the influence of the geographical parameters and meteorological parameters of the preset area on signal propagation, the signal distribution of each second calculation grid is approximately calculated using the free space propagation model. The height range of the blind spot is: N z ·Δz-h~N z ·Δz, where N z is the number of grids divided along the z direction for the parabolic equation, and Δz is the grid step size along the z direction for the parabolic equation.

[0255] It can be understood that when stepping from the initial calculation section to the step calculation section, according to the distance Δx between the two calculation sections and the angle of the signal pitch angle Determine the height h of the coverage blind area, and perform blind filling processing on the area. Through blind filling processing, it is possible to avoid missing the signal strength of the coverage blind area when calculating the field of the step calculation section, which is conducive to improving the accuracy of calculating the signal strength of the step calculation section.

[0256] It can be understood that the number of step calculation sections can be multiple. The predicted signal distribution, source parameters, geographic parameters and meteorological parameters of the current step calculation section can be used, and the predicted signal distribution of the next step calculation section to be stepped can be predicted with reference to the method of step S708, and so on, until the predicted signal distribution of all step calculation sections is obtained.

[0257] The signal distribution prediction method provided in the embodiment of the present application can divide the pitch angle of the transmitting source relative to the preset area into large angles (≥45°) and small angles (<45°) based on a preset threshold, and when the transmitting source is incident at a large angle, considering the reflection effect of the ground on the signal, select a two-way parabolic equation model to predict the predicted signal distribution of the transmitting source in the preset area, so that the predicted predicted signal distribution is more accurate. It is also possible to adaptively divide the preset area into multiple calculation sections, and adaptively divide the grids of each calculation section; and use a segmented (free space propagation and near-ground propagation) calculation method to determine the predicted signal distribution of each calculation section, so that the predicted signal distribution of the predicted preset area is more accurate.

[0258] Fig.11 This is a schematic diagram of the structure of a signal distribution prediction device provided in an embodiment of the present application. The data processing device can be a chip or a chip module. Fig.11 , the signal distribution prediction device 10 comprises:

[0259] A determination module 11, configured to determine a target prediction model from a plurality of prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold, wherein the target prediction model is used to predict a signal distribution of the transmitting source in the preset area;

[0260] The determination module 11 is further used to determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area and the coordinates of the center point;

[0261] A prediction module 12, configured to predict the predicted signal distribution of the plurality of calculation sections by using the target prediction model according to the source parameters of the emission source and the plurality of calculation sections;

[0262] The determination module 11 is further configured to determine the predicted signal distribution of the preset area according to the predicted signal distributions of the multiple calculation sections.

[0263] In a possible implementation, the determining module 11 is specifically configured to:

[0264] Determine an equation of a first straight line passing through the center point according to the angle of the azimuth and the coordinates of the center point;

[0265] Determine equations of a plurality of second straight lines according to the coordinates of a plurality of vertices of the preset area, the equation of the first straight line, a preset spacing, the coordinates of the center point, and the angle of the azimuth;

[0266] The plurality of calculated cross sections are determined according to the equation of the first straight line, the equations of the plurality of second straight lines and the boundary information of the preset area.

[0267] In a possible implementation manner, the determining module 11 is further configured to:

[0268] Determine the length of a first perpendicular line segment from each vertex to the first straight line according to the coordinates of each vertex of the preset area and the equation of the first straight line, and obtain the lengths of multiple first perpendicular line segments;

[0269] Determine a target first vertical line segment among the plurality of first vertical line segments, wherein the target first vertical line segment is the first vertical line segment with the longest length among the plurality of first vertical line segments;

[0270] Determining the lengths of a plurality of second vertical line segments passing through the center point according to the target first vertical line segment and the preset spacing;

[0271] The equations of the plurality of second straight lines are determined according to the coordinates of the central point, the lengths of the plurality of second vertical line segments and the angles of the azimuth angles.

[0272] In a possible implementation, the multiple calculation sections include an initial calculation section and a step calculation section; the prediction module 12 is specifically used to:

[0273] Obtaining geographical parameters and meteorological parameters of the preset area;

[0274] Predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameters, the geographic parameters and the meteorological parameters;

[0275] The predicted signal distribution of the step-by-step calculation section is predicted based on the predicted signal distribution of the initial calculation section, the source parameters, the geographical parameters and the meteorological parameters.

[0276] In a possible implementation, the prediction module 12 is further configured to:

[0277] Determining the initial signal strength of the transmitting source in the initial calculation cross section according to the source parameter, the geographical parameter and the meteorological parameter;

[0278] Dividing the initial calculation section into a plurality of calculation grids according to a preset grid size;

[0279] According to the source parameter, the initial signal strength, the geographic parameter and the meteorological parameter, predicting the predicted signal strength of each calculation grid in the initial calculation section by the target prediction model;

[0280] The predicted signal distribution of the initial calculation section is determined according to the predicted signal strength of each calculation grid in the initial calculation section.

[0281] In a possible implementation, the prediction module 12 is further configured to:

[0282] Dividing the step calculation section into a plurality of calculation grids according to a preset grid size;

[0283] Determining a first computing grid and a second computing grid among the plurality of computing grids;

[0284] Predicting the predicted signal strength of the first computing grid by the target prediction model according to the predicted signal distribution of the initial computing cross section, the source parameter, the geographic parameter and the meteorological parameter;

[0285] According to the source parameters, predicting the predicted signal strength of the second computing grid by a free space propagation model;

[0286] The predicted signal distribution of the step calculation section is determined according to the predicted signal strength of the first calculation grid and the predicted signal strength of the second calculation grid.

[0287] In a possible implementation, the prediction module 12 is further configured to:

[0288] Determining a blind spot height according to the pitch angle and a distance between the initial calculation section and the step calculation section;

[0289] Determine a computing grid whose height is less than or equal to the blind spot height among the multiple computing grids as a first computing grid;

[0290] A calculation grid whose height among the multiple calculation grids is greater than the height of the blind area is determined as the second calculation grid.

[0291] In a possible implementation, the multiple prediction models include a first prediction model and a second prediction model; the determination module 11 is further configured to:

[0292] If the pitch angle is less than the preset threshold, determining the first prediction model as the target prediction model;

[0293] If the pitch angle is greater than or equal to the preset threshold, the second prediction model is determined as the target prediction model.

[0294] The signal distribution prediction device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0295] Fig.12 This is a schematic diagram of the structure of the signal distribution prediction device provided in the embodiment of the present application. Fig.12The signal distribution prediction device 20 may include: a memory 21 and a processor 22. Exemplarily, the memory 21 and the processor 22 are interconnected via a bus 23.

[0296] The memory 21 is used to store program instructions;

[0297] The processor 22 is used to execute the program instructions stored in the memory, so as to enable the signal distribution prediction device 20 to execute the method shown in the above method embodiment.

[0298] It is understandable that the signal distribution prediction device 20 may include at least one processor and a memory connected to the at least one processor in communication. The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method shown in the above embodiment.

[0299] The signal distribution prediction device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0300] An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above-mentioned signal distribution prediction method.

[0301] The embodiment of the present application may also provide a computer program product, including a computer program, which, when executed by a processor, can implement the above-mentioned signal distribution prediction method.

[0302] All or part of the steps of the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a readable memory. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned memory (storage medium) includes: read-only memory (ROM), random access memory (RAM), flash memory, hard disk, solid state drive, magnetic tape, floppy disk, optical disc and any combination thereof.

[0303] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable signal distribution prediction device to generate a machine, so that the instructions executed by the processing unit of the computer or other programmable signal distribution prediction device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0304] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable signal distribution prediction device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0305] These computer program instructions can also be loaded onto a computer or other programmable signal distribution prediction device so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0306] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0307] In the present application, the term "include" and its variations may refer to non-restrictive inclusion; the term "or" and its variations may refer to "and / or". The terms "first", "second", etc. in the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. In the present application, "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previously associated objects are in an "or" relationship.

Claims

1. A signal distribution prediction method, characterized in that: The method comprises: Determine a target prediction model from a plurality of prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold, wherein the target prediction model is used to predict the signal distribution of the transmitting source in the preset area; Determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area, and the coordinates of the center point; According to the source parameters of the emission source and the multiple calculation sections, the predicted signal distribution of the multiple calculation sections is predicted by the target prediction model, and according to the predicted signal distribution of the multiple calculation sections, the predicted signal distribution of the preset area is determined.

2. The method according to claim 1, characterized in that: According to the angle of the azimuth angle of the signal incident, the boundary information of the preset area and the coordinates of the center point, a plurality of calculation sections are determined in the preset area, including: Determine an equation of a first straight line passing through the center point according to the angle of the azimuth and the coordinates of the center point; Determine equations of a plurality of second straight lines according to the coordinates of a plurality of vertices of the preset area, the equation of the first straight line, a preset spacing, the coordinates of the center point, and the angle of the azimuth; The plurality of calculated cross sections are determined according to the equation of the first straight line, the equations of the plurality of second straight lines and the boundary information of the preset area.

3. The method according to claim 2, characterized in that Determining equations of a plurality of second lines according to the coordinates of a plurality of vertices of the preset area, the equation of the first line, a preset spacing, the coordinates of the center point, and the angle of the azimuth, comprises: Determine the length of a first perpendicular line segment from each vertex to the first straight line according to the coordinates of each vertex of the preset area and the equation of the first straight line, and obtain the lengths of multiple first perpendicular line segments; Determine a target first vertical line segment among the plurality of first vertical line segments, wherein the target first vertical line segment is the first vertical line segment with the longest length among the plurality of first vertical line segments; Determining the lengths of a plurality of second vertical line segments passing through the center point according to the target first vertical line segment and the preset spacing; The equations of the plurality of second straight lines are determined according to the coordinates of the central point, the lengths of the plurality of second vertical line segments and the angles of the azimuth angles.

4. The method according to any one of claims 1 to 3, characterized in that: The multiple calculation sections include an initial calculation section and a step calculation section; Predicting the predicted signal distribution of the multiple calculation cross sections by the target prediction model according to the source parameters of the emission source and the multiple calculation cross sections includes: Obtaining geographical parameters and meteorological parameters of the preset area; Predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameters, the geographic parameters and the meteorological parameters; The predicted signal distribution of the step-by-step calculation section is predicted based on the predicted signal distribution of the initial calculation section, the source parameters, the geographical parameters and the meteorological parameters.

5. The method according to claim 4, characterized in that Predicting the distribution of prediction signals of the initial calculation cross section by the target prediction model according to the source parameter, the geographic parameter and the meteorological parameter, comprises: Determining the initial signal strength of the transmitting source in the initial calculation cross section according to the source parameter, the geographical parameter and the meteorological parameter; Dividing the initial calculation section into a plurality of calculation grids according to a preset grid size; According to the source parameter, the initial signal strength, the geographic parameter and the meteorological parameter, predicting the predicted signal strength of each calculation grid in the initial calculation section by the target prediction model; The predicted signal distribution of the initial calculation section is determined according to the predicted signal strength of each calculation grid in the initial calculation section.

6. The method according to claim 4 or 5, characterized in that: Predicting the predicted signal distribution of the step calculation section according to the predicted signal distribution of the initial calculation section, the source parameter, the geographical parameter and the meteorological parameter, comprises: Dividing the step calculation section into a plurality of calculation grids according to a preset grid size; Determining a first computing grid and a second computing grid among the plurality of computing grids; Predicting the predicted signal strength of the first computing grid by the target prediction model according to the predicted signal distribution of the initial computing cross section, the source parameter, the geographic parameter and the meteorological parameter; According to the source parameters, predicting the predicted signal strength of the second computing grid by a free space propagation model; The predicted signal distribution of the step calculation section is determined according to the predicted signal strength of the first calculation grid and the predicted signal strength of the second calculation grid.

7. The method according to claim 6, characterized in that Determining a first computing grid and a second computing grid from among the plurality of computing grids comprises: Determining a blind spot height according to the pitch angle and a distance between the initial calculation section and the step calculation section; Determine a computing grid whose height is less than or equal to the blind spot height among the multiple computing grids as a first computing grid; A calculation grid whose height among the multiple calculation grids is greater than the height of the blind area is determined as the second calculation grid.

8. The method according to any one of claims 1 to 7, characterized in that: The multiple prediction models include a first prediction model and a second prediction model; determining a target prediction model from the multiple prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold, including: If the pitch angle is less than the preset threshold, determining the first prediction model as the target prediction model; If the pitch angle is greater than or equal to the preset threshold, the second prediction model is determined as the target prediction model.

9. A signal distribution prediction device, characterized in that: include: A determination module, configured to determine a target prediction model from a plurality of prediction models according to a pitch angle of a signal incident from a transmitting source relative to a preset area and a preset threshold, wherein the target prediction model is used to predict a signal distribution of the transmitting source in the preset area; The determination module is further used to determine a plurality of calculation sections in the preset area according to the azimuth angle of the incident signal, the boundary information of the preset area and the coordinates of the center point; A prediction module, configured to predict the predicted signal distribution of the multiple calculation cross sections through the target prediction model according to the source parameters of the emission source and the multiple calculation cross sections; The determination module is further used to determine the predicted signal distribution of the preset area according to the predicted signal distribution of the multiple calculation sections.

10. A signal distribution prediction device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when the computer-executable instructions are executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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