Method and apparatus for determining wireless signal strength in region, storage medium, and electronic device

Abstract

The present application provides a method and apparatus for determining a wireless signal strength in a region, a computer-readable storage medium, and an electronic device. The method comprises: acquiring building diagram information, the building diagram information comprising the position of a target signal source, a target region corresponding to the target signal source, dimension information of one or more obstacles in the target region, and type information and image calibration information of the one or more obstacles; transforming the building diagram information into a polar coordinate system, the position of the target signal source being a pole of the polar coordinate system; on the basis of the dimension information, the type information, the image calibration information, and a propagation path, in the polar coordinate system, of a target signal transmitted by the target signal source and propagated to a target pixel in the region, determining an attenuation amount of the target pixel, the propagation path passing through at least part of the one or more obstacles; and on the basis of the signal strength of the target signal source and the attenuation amount of the target pixel, determining the signal strength at the target pixel.

Description

Method, device, storage medium and electronic device for determining wireless signal strength in an area

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on July 17, 2023, with application number 202310875603.5 and application name “Method, device and electronic device for determining wireless signal strength in an area”, the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present application relates to the field of wireless network communication technology, and in particular to a method, device, computer-readable storage medium, and electronic device for determining wireless signal strength within a region. Background Art

[0004] With the widespread adoption of the internet, it has become a daily necessity. This has placed higher demands on internet usage, and therefore on radio wave signals. Radio wave signals are often affected by buildings, particularly reinforced concrete walls. Therefore, assessing the distribution of radio wave signal strength within the intended coverage area has become a crucial task.

[0005] Summary of the Invention

[0006] The present application provides a method, apparatus, computer-readable storage medium, and electronic device for determining wireless signal strength within an area.

[0007] In a first aspect, each exemplary embodiment of the present application provides a method for determining the wireless signal strength within an area, comprising: obtaining building drawing information, the building drawing information including the position of a target signal source, a target area corresponding to the target signal source, size information of one or more obstacles within the target area, type information of the one or more obstacles, and image calibration information; converting the building drawing information into a polar coordinate system, wherein the position of the target signal source is a pole of the polar coordinate system; determining the attenuation of the target pixel point based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system from the target signal emitted by the target signal source to the target pixel point within the target area, wherein the propagation path passes through at least part of the one or more obstacles; and determining the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation of the target pixel point.

[0008] In this embodiment, by setting the signal source as the pole of the polar coordinate system and performing polar coordinate transformation on the size information of the obstacle (for example, a wall, etc.), its position can be directly determined by the polar coordinates of the pixel point in the polar coordinates, and the polar diameter of the polar coordinates can be used to determine the number of obstacles passed by the signal on the propagation path where the pixel point is located, so as to efficiently determine the signal strength at the pixel point, thereby improving the efficiency of determining the signal distribution in the target area, thereby achieving the purpose of real-time determination of the signal distribution of the target signal source in the area.

[0009] In one embodiment, the attenuation includes a medium attenuation, which indicates a decrease in the signal strength caused by the target signal passing through at least a portion of the one or more obstacles; and the attenuation of the target pixel point is determined based on the size information, the type information, the image calibration information, and the propagation path, including: when the propagation path passes through at least a portion of the one or more obstacles, the medium attenuation is determined based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information and the type information.

[0010] In one embodiment, when the propagation path passes through at least a portion of the one or more obstacles, the medium attenuation is determined based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information and the type information, including: determining one or more target polylines corresponding to the one or more obstacles based on the size information; and when the propagation path passes through the one or more target polylines, the medium attenuation is determined based on the number of times the propagation path passes through the one or more obstacles, the size information and the type information.

[0011] In one embodiment, determining the one or more target polylines corresponding to the one or more obstacles based on the size information includes: mapping the one or more obstacles to the corresponding one or more target polylines according to the center lines of the one or more obstacles, wherein the one or more target polylines include thickness information of the one or more obstacles.

[0012] In one embodiment, the attenuation also includes a distance attenuation, which indicates a decrease in the signal strength caused by the path length of the target pixel point; and the attenuation of the target pixel point is determined based on the size information, the type information, the image calibration information, and the propagation path of the target signal emitted by the target signal source to the target pixel point in the area in the polar coordinate system, and also includes: determining the distance attenuation based on the image calibration information and the path length of the target pixel point.

[0013] In one embodiment, the attenuation is calculated by the following formula: A=20log(d)+m*g+20log(f)+20log(4π / c)-G;

[0014] Wherein, A represents the attenuation of the target pixel point, d represents the polar diameter of the target pixel point, f represents the frequency of the target signal, c represents the speed of light, G represents the antenna gain of the target signal source, m is the number of times passing through at least part of the one or more obstacles, and g is the medium attenuation coefficient corresponding to at least part of the one or more obstacles.

[0015] In one embodiment, when the propagation path passes through at least a portion of the one or more obstacles, the medium attenuation is determined based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information, and the type information, including: determining the size information, type information, and the number of times the propagation path passes through at least a portion of the one or more obstacles based on the intersection pixel points of the propagation path and at least a portion of the one or more obstacles; and determining the medium attenuation based on the size information, type information, and the number of times the propagation path passes through at least a portion of the one or more obstacles.

[0016] In this embodiment, by determining the signal strength of each pixel point in the target area in a polar coordinate system, the position of the signal passing through the obstacle in the rectangular coordinate system can be directly located, avoiding the problem of reduced efficiency caused by the need for multiple simultaneous equations to calculate the intersection between the signal and the obstacle on each propagation path when directly determining the signal strength at each position in the rectangular coordinate system. At the same time, the coordinates in the rectangular coordinate system are represented by the distance between the corresponding pixel point and the y-axis (i.e., the horizontal coordinate) and the distance between the pixel point and the x-axis (i.e., the vertical coordinate). When the propagation path is not parallel to the x-axis or y-axis, the position of the pixel point on the propagation path first needs to be calculated by the square root of the sum of its horizontal and vertical coordinates.

[0017] In one embodiment, before determining the size information, the type information and the number of times the propagation path passes through at least a portion of the one or more obstacles based on the intersecting pixel points of the propagation path and at least a portion of the one or more obstacles, the method further includes: determining the intersecting pixel point by sliding a sliding window from the pole along the extension direction of the propagation path toward the target pixel point.

[0018] In one embodiment, after determining the intersecting pixel points by sliding a sliding window from the pole along the extension direction of the propagation path toward the target pixel point, the method further includes: determining the number of times the at least part of the one or more obstacles are passed through based on the number of intersecting pixel points determined.

[0019] In this embodiment, when determining the number of obstacles passed through on the propagation path, for a rectangular coordinate system whose minimum size unit is the same as that of a polar coordinate system, namely a pixel, it is difficult to reasonably set the sliding step size to ensure that all points on the propagation path from the origin to the pixel point that pass through the obstacle are determined. Therefore, the method provided in the embodiment of the present application also avoids determining the number of obstacles passed through by the propagation path where the pixel point is located in the rectangular coordinate system, and when the propagation path is not parallel to the coordinate axis (i.e., the x-axis or the y-axis), it is difficult to set the sliding step size to determine the number of obstacles passed along the propagation path.

[0020] In one embodiment, after determining the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation amount of the target pixel point, the method further includes: converting the building drawing information from the polar coordinate system to a rectangular coordinate system to obtain pixel coordinates corresponding to the target pixel point, wherein the horizontal coordinate and the vertical coordinate of the pixel coordinate are both integers; determining the pixel color corresponding to the pixel coordinate based on a first mapping relationship between pixel color and signal strength interval, the signal strength of the target pixel point, and the signal strength interval corresponding to the signal strength; and assigning color to the target pixel point in the rectangular coordinate system based on the pixel color.

[0021] In one embodiment, converting the building drawing information from the polar coordinate system to the rectangular coordinate system to obtain the pixel coordinates corresponding to the target pixel point includes: performing a rectangular coordinate transformation on the polar coordinates of the target pixel point to obtain the rectangular coordinates of the target pixel point in the rectangular coordinate system; and in response to the horizontal coordinate and / or the vertical coordinate in the rectangular coordinate being a non-integer, determining the target pixel coordinates closest to the rectangular coordinates as the pixel coordinates.

[0022] In one embodiment, before determining the pixel color corresponding to the pixel coordinate based on the first mapping relationship between the pixel color and the signal intensity interval, the signal intensity of the target pixel point, and the signal intensity interval corresponding to the signal intensity, the method also includes: determining the target size of the filtering window based on the second mapping relationship between the image resolution of the building drawing information and the size of the filtering window, and processing the signal intensity of the target pixel point by sliding the filtering window of the target size in the target area to obtain the noise-reduced signal intensity of the target pixel point; and determining the pixel color corresponding to the pixel coordinate based on the first mapping relationship between the pixel color and the signal intensity interval, the signal intensity of the target pixel point, and the signal intensity interval corresponding to the signal intensity, includes: determining the pixel color corresponding to the pixel coordinate based on the first mapping relationship, the noise-reduced signal intensity, and the signal intensity interval corresponding to the signal intensity.

[0023] In this embodiment, after determining the signal strength of the pixel points at each position in the polar coordinate system, the polar coordinates are inversely transformed (i.e., rectangular coordinate transformation) to map the pixel points in the polar coordinate system to the rectangular coordinate system, so as to perform color gradient mapping corresponding to the signal strength on each pixel point in the rectangular coordinate system, thereby realizing a millisecond-level signal simulation coverage heat map.

[0024] In one embodiment, the target signal source includes a first target signal source and a second target signal source, and the target pixel point is located within the target area corresponding to the first target signal source and the second target signal source; and determining the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation amount of the target pixel point includes: determining the signal strength of the target pixel point based on the maximum value of the first signal strength of the first target signal source at the target pixel point and the second signal strength of the second target signal source at the target pixel point.

[0025] In one embodiment, the size information and type information of the one or more obstacles are obtained by the following steps: inputting the building image information containing the target area into a pre-trained semantic segmentation model to obtain the type information of the one or more obstacles; and determining the size information of the one or more obstacles based on the image calibration information in the building image information.

[0026] In a second aspect, each exemplary embodiment of the present application provides a method for determining wireless signal strength within an area, including:

[0027] Based on the size information of the obstacle in the target area, determining, in a polar coordinate system with the target signal source as the pole, a target polyline corresponding to the obstacle in the target area, and determining target information of the target signal propagation path passing through the target polyline; wherein the target information includes the number of pixels on the propagation path that pass through the obstacle and the polar coordinates of the pixels; and

[0028] Based on the target information, signal strength information of the pixel points in the target area is determined; wherein the signal strength information includes position information of the pixel points and signal strength at the pixel points.

[0029] In one embodiment, determining the signal strength information of the pixel points in the target area based on the target information includes:

[0030] Determining, based on the polar coordinates of the pixel point and the number of obstacles passed through, a dielectric attenuation and a natural attenuation of the signal of the target signal source along the propagation path to the pixel point; and

[0031] Based on the medium attenuation and the natural attenuation, the signal strength of the signal of the target signal source at the pixel point is determined, and the polar coordinates of the pixel point and the signal strength are determined as the signal strength information.

[0032] In this embodiment, the distance between any pixel point and the target signal source can be directly read through the polar diameter of the polar coordinates of the pixel point, and the attenuation of the signal from the target signal source when it is transmitted to the position of the pixel point can be determined through the aforementioned distance and the number of obstacles passed through, thereby achieving the purpose of efficiently determining the signal strength information at the pixel point.

[0033] In one embodiment, the position information includes polar coordinates and rectangular coordinates;

[0034] The determining, based on the target information, signal strength information of the pixel points within the target area includes:

[0035] Performing a rectangular coordinate transformation on the polar coordinates of the pixel point to obtain the rectangular coordinates of the pixel point in a rectangular coordinate system and the pixel coordinates corresponding to the rectangular coordinates; wherein the horizontal coordinate and the vertical coordinate of the pixel coordinate are both integers;

[0036] Determining a pixel color corresponding to a pixel point on the pixel coordinates in a rectangular coordinate system based on a first mapping relationship between color and the signal strength interval;

[0037] assigning colors to the pixels in the rectangular coordinate system based on the pixel colors to obtain a color signal intensity distribution map; and

[0038] Based on the color signal intensity distribution diagram, signal intensity information of the pixel points is read.

[0039] This implementation efficiently determines the signal strength of pixels within the target area using polar coordinates, then further transforms them into rectangular coordinates to represent the signal strength within the target area in a rectangular coordinate system. This enhances the readability of the signal strength distribution within the target area. Furthermore, color mapping within the rectangular coordinate system is implemented to produce a colored signal strength distribution map—efficiently rendering a heat map. This allows for a more intuitive display of the signal strength distribution within the target area to the user.

[0040] In a third aspect, each exemplary embodiment of the present application provides a device for determining wireless signal strength within an area, including:

[0041] a target unit configured to obtain building map information, the building map information including a position of a target signal source, a target area corresponding to the target signal source, size information of one or more obstacles within the target area, type information of the one or more obstacles, and image calibration information; convert the building map information into a polar coordinate system, wherein the position of the target signal source is a pole of the polar coordinate system; and

[0042] An intensity unit is configured to determine the attenuation of the target pixel point based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system from the target signal emitted by the target signal source to the target pixel point within the area, wherein the propagation path passes through at least a portion of the one or more obstacles; and determine the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation of the target pixel point.

[0043] In a fourth aspect, each exemplary embodiment of the present application further provides a readable storage medium having instructions stored thereon, wherein when the instructions are executed by a processor, the processor is enabled to execute the method described in each exemplary embodiment.

[0044] In a fifth aspect, each exemplary embodiment of the present application provides an electronic device, including:

[0045] Memory for storing computer programs;

[0046] The processor is configured to execute the computer program stored in the memory to implement the method described in the first aspect and any possible implementation manner.

[0047] Other features and advantages of the present application will be described in the following description and, in part, will become apparent from the description or may be learned through practice of the present application. The objectives and other advantages of the present application may be achieved and obtained through the structures particularly pointed out in the written description, claims, and drawings. It should be understood that the above general description and the detailed description that follow are merely exemplary and explanatory and do not limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0049] FIG1 is a flow chart of a method for determining wireless signal strength within an area provided by an embodiment of the present application;

[0050] FIG2 is a flow chart of a method for determining wireless signal strength within an area provided by another embodiment of the present application;

[0051] FIG3 is a schematic diagram of directly determining the number of wall-penetrating signals at pixel points in a target area after polar coordinate transformation according to an embodiment of the present application;

[0052] FIG4 is a schematic diagram of a method for obtaining a thermal map within a target area provided by an embodiment of the present application;

[0053] FIG5 is a schematic structural diagram of an apparatus for determining wireless signal strength within an area provided by an embodiment of the present application;

[0054] FIG6 is a schematic structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. Unless there is a conflict, the embodiments in the present application and the features in the embodiments can be combined with each other in any way. In addition, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be performed in an order different from that here.

[0056] The terms "first" and "second" in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of its variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in this application can mean at least two, for example, two, three or more, and the embodiments of this application are not limited thereto.

[0057] Currently, there are two main methods for evaluating the distribution of radio wave signal strength. The first is to write the media extension data for each polyline in the campus model or building model in the Computer Aided Design (CAD) drawing, and write the signal attenuation values ​​of different frequency bands one by one. Then, the intersections between the signal and the polyline objects are calculated one by one, and the number of intersections in each grid is calculated to determine the information where the intersection passes through the polyline, such as the wall penetration position. This method has the problem of low efficiency due to the large amount of calculation and many steps.

[0058] The second method involves setting up a network environment in advance within a campus or indoor environment. Then, using testing equipment, the signal strength is measured at N pre-selected test points. Simulation calculations are then performed based on the signal strength at these N points to determine the signal strength at the remaining locations. However, this method also suffers from inefficiency because it requires manual labor to reach the pre-selected test points in advance to perform signal strength measurements.

[0059] To address the low efficiency of current methods for determining signal distribution within an area, an embodiment of the present application provides a method for determining wireless signal strength within an area. By using the wireless signal source as the pole, the obstacles in the target area are converted into polar coordinates, so that the wireless signal source and obstacles are represented in the same polar coordinate system. This achieves the direct counting of the number of obstacles passing through the same signal propagation direction, and based on this, directly calculates the signal strength attenuation, thereby efficiently determining the signal strength of the pixel points on the propagation path.

[0060] Please refer to Figure 1. An embodiment of the present application provides a method for determining the wireless signal strength in an area. The method specifically includes the following implementation steps.

[0061] Step 101: Based on the size information of the obstacles in the target area, determine the target polyline corresponding to the obstacles in the target area in a polar coordinate system with the wireless signal source as the pole, and determine the target information of the propagation path of the target signal passing through the obstacle area.

[0062] Specifically, the dimensions in the polar coordinates can be expressed in pixels. The polar diameter of any point in the polar coordinate system, that is, the distance between any point and the pole, can be expressed in pixels. For example, in the polar coordinates (ρ, θ), ρ represents the polar diameter of the corresponding pixel point, that is, the distance between the corresponding pixel point and the pole (i.e., the target signal source), which can be, for example, 2 pixels, and θ represents the polar angle, that is, the propagation direction of the current signal of the target signal source, which can be, for example, 50°.

[0063] Target information can include the number of obstacles the target signal propagation path passes through and the polar coordinates of the pixel. The target signal indicator is the signal emitted by the target signal source. The target polyline indicator is a continuous line derived from the obstacle's dimensional information, such as its starting and ending positions, and its shape. This continuous line can be an arc, a straight line segment, or a combination of arcs and straight line segments.

[0064] Specifically, the target signal source may be a wireless signal source, such as a wireless router, a wireless access point (AP), a base station, etc. The signal sent by the target signal source is the target signal.

[0065] Correspondingly, the radio waves emitted by the wireless signal source may be WiFi (Wireless Fidelity) signals or base station electromagnetic wave signals. The target area is the coverage area of ​​the target signal centered on the target signal source.

[0066] The above-mentioned obstacle may be a building or a part of a building. Factors causing signal attenuation in a building or a part of a building include, in addition to the distance between the wireless signal source and the obstacle, factors such as the type of obstacle, such as a wall.

[0067] Because polar coordinates represent coordinates as a combination of polar diameters and polar angles, by converting obstacles like walls from rectangular coordinates to polar coordinates, we can intuitively obtain information about the target signal source's propagation paths through obstacles. This information can be used to determine the attenuation of the signal transmitted by the target signal source.

[0068] The information about the obstacles passed through includes the distance between each point on the propagation path and the target signal source (ie, the pole), the position of the obstacle passed through, the number (or number of times) of obstacles passed through, etc.

[0069] In some embodiments, information about obstacles passed through may also include the emission angle of the target signal source, i.e., the polar angle of the polar coordinates of the target pixel corresponding to the propagation path. In this embodiment, the polar coordinates of the target pixel (i.e., the polar diameter (related to the propagation path) and the polar angle (related to the emission angle of the target signal source)), as well as the location of the obstacle passed through and the number of times the obstacle was passed through, can more quickly obtain the attenuation amount, thereby determining the signal strength within the area.

[0070] Since the polar coordinate system in this application uses a pixel as the smallest unit of size, each point on the propagation path is a pixel. The distance between each point and the target signal source (i.e., the pole) is the polar diameter of the pixel in polar coordinates. The location of the obstacle is the polar coordinate of the intersection of the propagation path and the obstacle. The number of obstacles crossed indicates the number of obstacles the signal passes through before reaching the pixel along the propagation path.

[0071] The number of obstacles crossed is determined by sliding a window with a step size of 1 pixel from the pole along the extension direction of the polar radius toward the pixel. Before the window reaches the pixel, when it reaches the intersection, the polar coordinates of the intersection are directly read and added to the number of obstacles crossed + 1 until the pixel is reached. This determines the number of obstacles crossed corresponding to the pixel and the corresponding location of the obstacle crossed.

[0072] In some embodiments, if the obstacle is a wall, the information about the obstacle passing through is called wall-penetration information. This wall-penetration information includes the distance between a specified pixel point on the corresponding propagation path and the target signal source (i.e., the polar point), the wall-penetration position (i.e., the polar coordinates of the pixel point passing through the wall), and the number of walls passed through.

[0073] FIG2 is a flow chart of a method for determining wireless signal strength within an area provided by another embodiment of the present application, which specifically includes the following steps.

[0074] Step 201: Acquire building map information, which includes the location of a target signal source, a target area corresponding to the target signal source, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information.

[0075] The target area may be a preset range area that can be covered by the signal emitted by the target signal source.

[0076] In this embodiment, the number of target signal sources is 1. In other embodiments, the number of target signal sources may be multiple, which will be described in detail in the following embodiments.

[0077] The size information of the obstacle may include the thickness, height, and surface roughness of the obstacle.

[0078] The type information of the obstacle indicates the type of the obstacle, for example, it may be a brick wall, a wooden wall, a glass wall, a window, a door, etc.

[0079] The image calibration information indicates a ratio relationship between pixel distances between pixels in the architectural image information and distances between corresponding actual positions in reality.

[0080] The architectural drawing information can be a CAD architectural plan file or other types of files, which is not specifically limited in this application. The architectural drawing information can be used for indoor architectural drawings or outdoor architectural drawings, which is not specifically limited in this application.

[0081] Step 202: convert the building drawing information into a polar coordinate system, wherein the position of the target signal source is a pole of the polar coordinate system.

[0082] Step 203: Determine the attenuation of the target pixel point based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system from the target signal emitted by the target signal source to the target pixel point within the target area, wherein the propagation path passes through at least a portion of the one or more obstacles.

[0083] The target pixel point indicates a mapped pixel point in the building map information at an actual position of the signal strength to be confirmed.

[0084] At least a portion of one or more obstacles may refer to one or more obstacles among the one or more obstacles, and may also refer to a specific portion of a single obstacle among the one or more obstacles.

[0085] Step 204 : Determine the signal strength of the target pixel based on the signal strength of the target signal source and the attenuation of the target pixel.

[0086] Figure 3 is a schematic diagram of a wall after polar coordinate conversion, provided in an embodiment of the present application. As shown in Figure 3, the area within the dashed circle is the target area, and the solid circle is the target polyline. Vector OM represents a propagation path in the θ1 direction. Point A is the wall penetration location. Based on the polar coordinates of point A, the number of wall penetrations before point A in the θ1 direction is 0, and the number of wall penetrations after point A is 1.

[0087] In this way, the target information of the pixel points along the propagation path of the target signal at each angle can be obtained from the polar coordinate system. For example, the wall penetration information of point B includes: the number of walls penetrated is 1, and the position of pixel point B is identified by the polar coordinates (ρ2, θ2) with a polar radius of ρ2 and a polar angle of θ2.

[0088] The size information of the obstacle is described below by taking a wall as an example.

[0089] The size information of the obstacle includes at least the starting position and the ending position of the wall along the length direction, and the thickness along the width direction.

[0090] In some embodiments, a building image containing a target area is input into a pre-trained semantic segmentation model, so that the semantic segmentation model identifies obstacles in the building image and obtains dimension data indicating the size information of the obstacles in the target area. The dimension data may be vector data.

[0091] The building map may contain only a plan view of the target area, or it may be a plan view that includes a portion of the target area and also includes other areas. When the building map contains more than one target area, the building area is input into the pre-trained segmentation model along with region data indicating that the pre-trained semantic segmentation model should select the target area. This allows the pre-trained semantic segmentation model to select the target area in the building map and identify the type, size, and location of the wall to obtain obstacle information including obstacle size data. Specifically, this obstacle information may include the wall's starting point, end point, thickness, and wall type for determining / obtaining the medium attenuation coefficient.

[0092] The above-mentioned area data may be, for example, the shape of the target area, the coordinates of the center position of the target area, and the coordinates of key points on the edge of the target area.

[0093] Furthermore, the above-mentioned pre-trained semantic segmentation model is described below.

[0094] First, a training atlas is obtained. This training atlas includes multiple original building images and their corresponding data augmentation images. Each image in the training atlas is labeled with a corresponding obstacle type and size. Obstacle types can include windows, doors, walls, etc. Obstacle sizes can include starting and ending points in the length direction, thickness in the width direction, and may also include height.

[0095] The original architectural drawing can be a CAD floor plan or a 3D bird's-eye view. The data augmentation graph can directly perform data augmentation processing on the labeled original architectural drawing, such as black-and-white conversion, random erasing, and cropping, to obtain a data augmentation graph corresponding to the original architectural drawing and a label for the data augmentation graph corresponding to the original architectural drawing.

[0096] Then, the training atlas is input into the semantic segmentation model to be trained to obtain obstacle type information.

[0097] Next, based on the labels corresponding to each image in the training atlas, the first error between the first type indicating the obstacle type output by the semantic segmentation model to be trained and the obstacle type of the label corresponding to the image is determined, as well as the first error between the first type indicating the obstacle type output by the semantic segmentation model to be trained and the obstacle type of the label corresponding to the image.

[0098] The cross entropy function is used as the loss function, and the parameters of the semantic segmentation model to be trained are adjusted inversely until the loss function converges to the optimal value to obtain the trained semantic segmentation model.

[0099] Therefore, when determining the wireless signal strength within an area, a building image containing the target area can be input into the pre-trained semantic segmentation model to obtain the types of obstacles within the target area, such as walls, doors, and windows.

[0100] In some embodiments, the type granularity of obstacles in the labels during the training phase can be further refined, for example, walls can be refined into solid walls, hollow walls, etc., to achieve fine-grained identification of obstacle types in the target area.

[0101] Step 102: Based on the target information, determine the signal strength information of the pixels within the target area.

[0102] The signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

[0103] Specifically, the position information of the pixel point can be directly determined by its polar coordinates: polar diameter and polar angle. The medium attenuation and natural attenuation of the signal from the target signal source along the propagation path to the pixel point can also be determined by the polar diameter, polar angle, and the number of obstacles passed through.

[0104] The medium attenuation indicates the drop in signal strength caused by the target signal passing through an obstacle. The distance attenuation (i.e., natural attenuation) indicates the drop in signal strength at the pixel due to the distance between the current pixel and the target signal source.

[0105] Because the polar diameters are determined by architectural drawings, which are scaled to actual dimensions, when using distance to calculate dielectric attenuation and natural attenuation, it is also necessary to perform distance restoration based on the architectural drawing's scale and use the resulting actual distance values ​​to calculate dielectric attenuation and natural attenuation. This distance restoration can also be achieved using the pre-trained semantic segmentation model described above.

[0106] Next, the total attenuation of the target signal source when it reaches the pixel can be determined based on the medium attenuation and natural attenuation. The signal strength of the pixel can be determined based on this attenuation. This is done by subtracting the total attenuation from the target signal source's signal strength. The polar coordinates and signal strength of the pixel are then used as the signal strength information for the pixel.

[0107] The total attenuation A can be calculated according to the following formula: A = 20log(d) + m*g + 20log(f) + 20log(4π / c) - G;

[0108] Among them, A represents the attenuation of the pixel point, d represents the polar diameter of the pixel point (i.e., the transmission distance), f represents the frequency of the signal, c represents the speed of light, G is the antenna gain, m is the number of obstacles passed through, and g is the medium attenuation coefficient corresponding to the obstacle type.

[0109] In the above formula for the total attenuation A, 20log(d) indicates the signal strength attenuation as the signal changes with distance, that is, distance attenuation; m*g indicates the signal strength attenuation caused by the signal passing through an obstacle, that is, medium attenuation; and 20log(f)+20log(4π / c) represents the inverse of the signal penetration ability.

[0110] Furthermore, if the size of the above-mentioned target area is not larger than the signal coverage range of the target signal source, then in the target area, the length of the propagation path of the signal of the target signal source is less than or equal to the radius of the preset signal coverage range of the target signal source, thereby avoiding the problem of decreased efficiency in determining signal strength caused by the introduction of signals from distant signal sources.

[0111] When the preset signal coverage ranges of signal sources overlap, their respective propagation paths and target areas may overlap. In some embodiments, the number of target signal sources is N, where N is an integer greater than 1. In response to the number of signal intensities at a pixel being 1, it indicates that there is no overlap of signals from multiple signal sources at the pixel. Alternatively, in response to the number of signal intensities at a pixel being greater than 1, it means that there is overlap of signals from multiple signal sources at the pixel, and the signal intensity with the largest value is determined to be the signal intensity of the pixel.

[0112] Furthermore, the aforementioned location information includes polar coordinates and rectangular coordinates. To facilitate the user's acquisition of the distribution of signal strength in the target area, the signal strength information determined based on the polar coordinate system, particularly the polar coordinates in the signal strength information, may be subjected to an inverse polar coordinate transformation to obtain the signal strength information of the pixel in the polar coordinate system in the rectangular coordinate system, i.e., the coordinates in the rectangular coordinate system corresponding to the pixel in the polar coordinate system and the signal strength.

[0113] The signal intensity of a pixel in the polar coordinate system is equal to the signal intensity of the corresponding pixel in the rectangular coordinate system.

[0114] The position in the rectangular coordinate system includes the rectangular coordinates obtained by transforming the polar coordinates of the pixel points. Both the polar coordinate system and the rectangular coordinate system use pixels as the minimum size unit, so the polar axes in the polar coordinates are all integers, and after the polar coordinates whose units of some polar axes are integers are converted from the polar coordinate system to the rectangular coordinate system, the corresponding rectangular coordinates (abscissa and / or ordinate) will be non-integer. Therefore, in order to establish a corresponding relationship before and after the conversion of the polar coordinates and the rectangular coordinate system, the rectangular coordinates can be aligned to obtain pixel coordinates whose abscissa and ordinate are both integers. Specifically, the rectangular coordinates of the pixel point can be processed as follows: in response to the abscissa and ordinate in the rectangular coordinates being both integers, the rectangular coordinates are determined to be pixel coordinates, that is, the two are equal. Alternatively, in response to the abscissa and / or ordinate in the rectangular coordinates being non-integers, the target pixel coordinates closest to the rectangular coordinates are determined to be the pixel coordinates.

[0115] The target pixel coordinates are the horizontal and vertical coordinates of the original pixel point in the rectangular coordinate system. Therefore, the horizontal and vertical coordinates in the target pixel coordinates are both integers. The original pixel point may or may not coincide with the rectangular coordinates obtained by converting any pixel point in the polar coordinate system.

[0116] In some embodiments, after obtaining the rectangular coordinates of the pixel points, the rectangular coordinates can be processed using a nearest neighbor interpolation method so that the horizontal and vertical coordinates of the processed pixel coordinates are both integers. Thus, the pixel coordinates in the rectangular coordinate system include rectangular coordinates and pixel coordinates.

[0117] In this way, the signal strength information of each pixel in the target area in the rectangular coordinate system can be obtained.

[0118] Next, the pixel color corresponding to each pixel in the rectangular coordinate system can be determined based on the first mapping relationship between color and signal strength intervals, the pixel coordinates of the pixel, and the signal strength of the pixel. Based on the pixel color of the pixel, the pixel in the rectangular coordinate system is assigned a color to obtain a color signal strength distribution map.

[0119] Finally, the signal strength information of the pixel points can be read based on the color signal strength distribution map.

[0120] Furthermore, in order to improve the visual effect and reduce the noise (ie, signal strength noise) caused by the aforementioned coordinate alignment or calculation errors, a filtering algorithm may be used to remove the noise.

[0121] In some embodiments, based on a second mapping relationship between image resolution and the filter window, a target size of the filter window is determined according to the resolution of the image in a rectangular coordinate system. The target size of the filter window is inversely proportional to the resolution. The filter window of the target size is slid across the target area in the rectangular coordinate system, and the signal intensity of the pixels is processed to remove noise, so that the noise of the signal intensity of the pixels within the sliding filter window of the target size is less than a preset threshold. The resolution of the image is determined by the ratio between the pixel distance and the actual distance between two points in the image, and the image resolution can be changed according to user settings.

[0122] Specifically, a dynamic filtering algorithm is used to slide from any vertex of the target area. For example, the target area is in the shape of a rectangle, and the filter window starts to slide from the upper left vertex of the rectangle. Each slide determines the average or median of the signal intensity of each pixel in the filter window. When the difference between the signal intensity of the pixel at the center of the filter window and the average or median exceeds a preset threshold, it indicates that the signal intensity noise of the pixel at the center of the filter window is too large, so the signal intensity of the pixel at the center of the filter window is adjusted so that the aforementioned difference is within the preset threshold. The embodiment of the present application does not limit the adjustment of the signal intensity of the pixel at the center of the filter window. For example, the signal intensity of the pixel at the center of the filter window can be set to the aforementioned average or median. For example, the signal intensity of the pixel at the center of the filter window can be correspondingly reduced or increased so that the difference between the modified signal intensity and the aforementioned average or median is just less than the aforementioned preset threshold.

[0123] In this way, as the filter window slides, the signal strength of each pixel can be processed one by one, so that the signal strength noise of the pixels in the target area is less than the preset threshold, thereby making the signal strength transition of each pixel in the target area smooth.

[0124] Thus, the pixel color corresponding to the pixel can be determined based on the aforementioned first mapping relationship and the signal strength of the pixel in the denoised signal strength information. Furthermore, based on the correspondence between each pixel and its color, the pixels in the target area can be assigned a color to obtain a color signal strength distribution map.

[0125] Based on the method for determining the wireless signal strength within the area described in steps 101 to 102, the following describes how to obtain a heat map, taking the target signal source as an AP and the AP's signal coverage area as an example, with no other wireless signal sources present. Please refer to FIG4 .

[0126] First, the acquired building image is input into the pre-trained semantic segmentation model to identify the types of obstacles that cause signal attenuation in the building image.

[0127] The architectural image is then calibrated based on the image calibration information to obtain the dimensions of obstacles, including but not limited to walls, windows, and doors, as well as the actual distances between adjacent pixels in the architectural image. This image calibration information indicates the ratio between the distances between pixels in the architectural image and the corresponding distances between actual locations in real space.

[0128] Based on the obstacle's dimensions, a target polyline corresponding to the obstacle's shape and orientation is drawn in a polar coordinate system with the AP as the pole. An attention masking mechanism is introduced: only the target area corresponding to the AP's signal coverage is determined in the polar coordinate system. Therefore, the propagation path length does not exceed the target area. Generally, if the target signal source's predetermined signal coverage area is circular, the propagation path length within the target area is less than or equal to the radius of the target signal source's predetermined signal coverage area.

[0129] Within the target area, the signal attenuation and signal strength at each pixel are determined based on the actual distances between adjacent pixels in the building image output by the pre-trained semantic segmentation model and the number of obstacles each pixel passes through in its propagation direction, as determined by reading the polar coordinate system. The polar coordinates and signal strength of each pixel thus constitute the pixel's signal strength information.

[0130] Next, an inverse polar coordinate transformation is performed based on the polar coordinates, and the rectangular coordinates are aligned using the nearest neighbor difference method, and the integer is rounded to obtain the signal intensity of the pixel point at the corresponding position in the rectangular coordinate system.

[0131] Next, the signal strength of each pixel at each rectangular coordinate system is subjected to dynamic filtering to remove noise. Gradient color mapping is then performed: different colors represent signal strength in different signal strength ranges, effectively obtaining the signal strength distribution within the target area. This allows users to intuitively understand the signal strength distribution of each area within the target area in the rectangular coordinate system.

[0132] Based on the same inventive concept, an embodiment of the present application provides a device for determining the strength of wireless signals in an area. The device corresponds to the method for determining the strength of wireless signals in an area shown in Figure 1 above. The specific implementation of the device can be found in the description of the embodiment of the above method. The repeated parts will not be repeated. Referring to Figure 5, the device includes a target unit 501 and a strength unit 502.

[0133] The target unit 501 is used to determine the target polyline corresponding to the obstacle in the target area in a polar coordinate system with the target signal source as the pole based on the size information of the obstacle in the target area, and determine the target information that the propagation path of the target signal passes through the target polyline.

[0134] The target information includes the number of obstacles passed by the propagation path and the polar coordinates of the pixel points.

[0135] The strength unit 502 is configured to determine signal strength information of the pixel points within the target area based on the target information.

[0136] The signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

[0137] The intensity unit 502 is specifically used to determine the medium attenuation and natural attenuation of the signal of the target signal source along the propagation path to the pixel point based on the polar coordinates of the pixel point and the number of obstacles passed through; based on the medium attenuation and the natural attenuation, determine the signal strength of the signal of the target signal source at the pixel point, and determine the polar coordinates of the pixel point and the signal strength as the signal strength information.

[0138] The position information includes polar coordinates and rectangular coordinates; the intensity unit 502 is also used to perform rectangular coordinate transformation on the polar coordinates of the pixel point to obtain the rectangular coordinates of the pixel point in the rectangular coordinate system, and the pixel coordinates corresponding to the rectangular coordinates; wherein the horizontal coordinate and the vertical coordinate of the pixel coordinate are both integers; based on the first mapping relationship between color and the signal intensity interval, the pixel color corresponding to the pixel point on the pixel coordinate in the rectangular coordinate system is determined; based on the pixel color, the pixel point in the rectangular coordinate system is colored to obtain a color signal intensity distribution map; based on the color signal intensity distribution map, the signal intensity information of the pixel point is read.

[0139] Furthermore, the intensity unit 502 is further configured to perform a rectangular coordinate transformation on the polar coordinates of the pixel point to obtain the rectangular coordinates of the pixel point in a rectangular coordinate system;

[0140] In response to the abscissa and the ordinate in the rectangular coordinate being integers, determining the rectangular coordinate to be the pixel coordinate; or,

[0141] In response to the abscissa and / or the ordinate in the rectangular coordinate being a non-integer, the target pixel coordinates closest to the rectangular coordinates are determined as the pixel coordinates.

[0142] The intensity unit 502 is also used to determine the target size of the filtering window based on the second mapping relationship between the image resolution and the filtering window, and process the signal intensity of the pixel point by sliding the filtering window of the target size in the target area, so that the noise of the signal intensity of the pixel point in the filtering window of the target size is less than a preset threshold, thereby obtaining denoised signal intensity information; based on the first mapping relationship and the signal intensity of the pixel point in the denoised signal intensity information, determine the pixel color corresponding to the pixel point.

[0143] Furthermore, the number of target signal sources is N, where N is an integer greater than 1; in the target area, the length of the propagation path is less than or equal to the radius of the preset signal coverage range of the target signal source; then the intensity unit 502 is also used to determine that the signal intensity with the largest value is the signal intensity of the pixel point in response to the number of signal intensities on the pixel point being greater than 1.

[0144] Furthermore, the size information of the obstacle includes the type and size of the obstacle; the above-mentioned device for determining the wireless signal strength in the area also includes an information unit, which is specifically used to input a building map containing the target area into a pre-trained semantic segmentation model to obtain the type of the obstacle; based on the ratio of the pixel distance between pixels in the building map to the actual distance between the pixels, the size of the obstacle is determined; the type and size constitute the size information of the obstacle.

[0145] Based on the same inventive concept, an embodiment of the present application further provides a readable storage medium having instructions stored thereon, wherein when the instructions are executed by a processor, the processor is enabled to execute the methods described in each exemplary embodiment.

[0146] Based on the same inventive concept as the above-mentioned method for determining the strength of wireless signals within an area, an embodiment of the present application further provides an electronic device, which can implement the functions of the above-mentioned method for determining the strength of wireless signals within an area. Referring to FIG. 6 , the electronic device includes:

[0147] At least one processor 601, and a memory 602 connected to at least one processor 601. In the embodiments of the present application, the specific connection medium between the processor 601 and the memory 602 is not limited. FIG6 takes the connection between the processor 601 and the memory 602 via the bus 600 as an example. The bus 600 is represented by a bold line in FIG6. The connection method between other components is only for schematic illustration and is not intended to be limiting. The bus 600 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, FIG6 only uses a bold line to represent it, but this does not mean that there is only one bus or one type of bus. Alternatively, the processor 601 can also be called a controller, and there is no limitation on the name.

[0148] In this embodiment of the present application, memory 602 stores instructions executable by at least one processor 601. At least one processor 601 can execute the method for determining wireless signal strength within an area discussed above by executing the instructions stored in memory 602. Processor 601 can implement the functions of each module in the apparatus shown in FIG5 .

[0149] Among them, the processor 601 is the control center of the device, which can use various interfaces and lines to connect the various parts of the entire control device, and monitor the device as a whole by running or executing instructions stored in the memory 602 and calling data stored in the memory 602, the various functions of the device and processing data.

[0150] In one possible design, processor 601 may include one or more processing units. Processor 601 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily processes wireless communications. It is understood that the modem processor may not be integrated into processor 601. In some embodiments, processor 601 and memory 602 may be implemented on the same chip. In some embodiments, they may also be implemented on separate chips.

[0151] The processor 601 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method for determining the wireless signal strength within an area disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0152] The memory 602 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 602 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 602 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 602 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0153] By designing and programming processor 601, the code corresponding to the method for determining wireless signal strength within an area described in the aforementioned embodiment can be embedded within the chip, enabling the chip to execute the steps of the method for determining wireless signal strength within an area shown in FIG1 during operation. Designing and programming processor 601 is well known to those skilled in the art and will not be further described here.

[0154] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0155] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0156] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0157] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0158] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a universal serial bus flash disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0159] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for determining wireless signal strength in an area, comprising: Acquire building map information, where the building map information includes a location of a target signal source, a target area corresponding to the target signal source, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information; Converting the architectural drawing information into a polar coordinate system, wherein the position of the target signal source is a pole of the polar coordinate system; determining an attenuation amount of the target pixel point based on the size information, the type information, the image calibration information, and a propagation path of a target signal emitted by the target signal source to a target pixel point in the target area in the polar coordinate system, wherein the propagation path passes through at least a portion of the one or more obstacles; and The signal strength of the target pixel point is determined based on the signal strength of the target signal source and the attenuation of the target pixel point.

2. The method of claim 1, wherein: The attenuation includes a medium attenuation, wherein the medium attenuation indicates a decrease in the signal strength caused by the target signal passing through at least a portion of the one or more obstacles; as well as Determining the attenuation of the target pixel based on the size information, the type information, the image calibration information, and the propagation path includes: When the propagation path passes through at least a portion of the one or more obstacles, the medium attenuation amount is determined based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information, and the type information.

3. The method of claim 2, wherein: When the propagation path passes through at least a portion of the one or more obstacles, determining the medium attenuation based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information, and the type information, comprises: Based on the size information, determining one or more target polylines corresponding to the one or more obstacles; and When the propagation path passes through the one or more target polylines, the medium attenuation is determined based on the number of times the one or more obstacles are passed through, the size information, and the type information.

4. The method of claim 3, wherein: The step of determining the one or more target polylines corresponding to the one or more obstacles based on the size information includes: The one or more obstacles are mapped to the corresponding one or more target polylines according to the center lines of the one or more obstacles, wherein the one or more target polylines include thickness information of the one or more obstacles.

5. The method of claim 2, wherein: The attenuation further includes a distance attenuation, where the distance attenuation indicates a decrease in the signal strength caused by a path length of the target pixel point; and The determining the attenuation of the target pixel point based on the size information, the type information, the image calibration information, and the propagation path of the target signal emitted by the target signal source to the target pixel point in the area in the polar coordinate system, further includes: Determine the distance attenuation based on the image calibration information and the path length of the target pixel point Reduction.

6. The method of claim 5, wherein: The attenuation is calculated by the following formula: A = 20log(d) + m*g + 20log(f) + 20log(4π / c) - G; Among them, A represents the attenuation of the target pixel point, d represents the polar diameter of the target pixel point, f represents the frequency of the target signal, c represents the speed of light, G represents the antenna gain of the target signal source, m is the number of times passing through at least part of the one or more obstacles, and g is the medium attenuation coefficient corresponding to at least part of the one or more obstacles.

7. The method of claim 2, wherein: When the propagation path passes through at least a portion of the one or more obstacles, determining the medium attenuation based on the number of times the propagation path passes through at least a portion of the one or more obstacles, the size information, and the type information, comprises: Determining size information, type information, and the number of times of passing through at least a portion of the one or more obstacles of at least a portion of the one or more obstacles according to intersection pixels of the propagation path and at least a portion of the one or more obstacles; and The medium attenuation is determined based on size information of at least a portion of the one or more obstacles, type information, and a number of times of passing through at least a portion of the one or more obstacles.

8. The method of claim 7, wherein: Before determining the size information, the type information, and the number of times of passing through at least a portion of the one or more obstacles according to the intersection pixel points of the propagation path and at least a portion of the one or more obstacles, the method further includes: The intersection pixel point is determined by sliding a sliding window from the pole along the extension direction of the propagation path toward the target pixel point.

9. The method of claim 8, wherein: After determining the intersecting pixel point by sliding a sliding window from the pole along the extension direction of the propagation path toward the target pixel point, the method further includes: The number of times the at least part of the one or more obstacles are passed through is determined based on the number of the intersecting pixels.

10. The method of claim 1, wherein: After determining the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation of the target pixel point, the method further includes: Convert the building drawing information from the polar coordinate system to a rectangular coordinate system to obtain pixel coordinates corresponding to the target pixel point, wherein the horizontal coordinate and the vertical coordinate of the pixel coordinate are both integers; Determining the pixel color corresponding to the pixel coordinate based on a first mapping relationship between pixel color and signal strength interval, the signal strength of the target pixel point, and the signal strength interval corresponding to the signal strength; and Based on the pixel color, the target pixel point in the rectangular coordinate system is assigned a color.

11. The method of claim 10, wherein: The converting the building drawing information from the polar coordinate system to the rectangular coordinate system to obtain the pixel coordinates corresponding to the target pixel point includes: Performing a rectangular coordinate transformation on the polar coordinates of the target pixel point to obtain the rectangular coordinates of the target pixel point in a rectangular coordinate system; and In response to the abscissa and / or the ordinate in the rectangular coordinate being non-integer, the target pixel coordinates closest to the rectangular coordinates are determined as the pixel coordinates.

12. The method of claim 10, wherein: Before determining the pixel color corresponding to the pixel coordinate based on the first mapping relationship between the pixel color and the signal strength interval, the signal strength of the target pixel point, and the signal strength interval corresponding to the signal strength, the method further includes: Determine a target size of the filtering window based on a second mapping relationship between the image resolution of the building drawing information and the size of the filtering window, and process the signal strength of the target pixel by sliding the filtering window of the target size in the target area to obtain the signal strength of the target pixel after noise reduction; and The determining the pixel color corresponding to the pixel coordinate based on the first mapping relationship between the pixel color and the signal strength interval, the signal strength of the target pixel point, and the signal strength interval corresponding to the signal strength includes: The pixel color corresponding to the pixel coordinate is determined based on the first mapping relationship, the signal strength after noise reduction, and the signal strength interval corresponding to the signal strength.

13. The method according to any one of claims 1 to 12, wherein: The target signal source includes a first target signal source and a second target signal source, and the target pixel point is located in a target area corresponding to the first target signal source and the second target signal source; as well as The determining the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation amount of the target pixel point includes: The signal strength of the target pixel is determined based on a maximum value of a first signal strength of the first target signal source at the target pixel and a second signal strength of the second target signal source at the target pixel.

14. The method according to any one of claims 1 to 13, wherein: The size information and type information of the one or more obstacles are obtained by the following steps: Inputting the building image information including the target area into a pre-trained semantic segmentation model to obtain type information of the one or more obstacles; as well as Based on the image calibration information in the building drawing information, the size information of the one or more obstacles is determined.

15. A device for determining wireless signal strength in an area, comprising: a target unit configured to obtain building map information, the building map information including a position of a target signal source, a target area corresponding to the target signal source, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information; Converting the architectural drawing information into a polar coordinate system, wherein the position of the target signal source is a pole of the polar coordinate system; as well as The intensity unit is configured to determine the attenuation of the target pixel point based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system from the target signal emitted by the target signal source to the target pixel point in the area, wherein the propagation path passes through at least part of the one or more obstacles; and determine the signal strength of the target pixel point based on the signal strength of the target signal source and the attenuation of the target pixel point.

16. A computer-readable storage medium having instructions stored thereon, wherein: When the instructions are executed by a processor, the processor is enabled to perform the method according to any one of claims 1 to 14.

17. An electronic device comprising: Memory for storing computer programs; as well as A processor, configured to implement the method according to any one of claims 1 to 14 when executing the computer program stored in the memory.

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