Method and device for determining wireless signal intensity in area and electronic equipment

Abstract

The invention provides a method and a device for determining wireless signal intensity in an area and electronic equipment, which are used for improving the efficiency of determining signal intensity distribution in the area so as to realize the purpose of determining the signal distribution condition of a target signal source in the area in real time. The method comprises the steps of determining a target polyline corresponding to an obstacle in a target area in a polar coordinate system taking a target signal source as a pole based on size information of the obstacle in the target area, and determining target information that a propagation path of a target signal passes through the target polyline; wherein the target information comprises the number of the pixel points on the propagation path penetrating through the obstacle and the polar coordinates of the pixel points; based on the target information, determining signal intensity information of the pixel points in the target area; wherein the signal intensity information comprises the position information of the pixel points and the signal intensity on the pixel points.

Description

Technical Field

[0001] The present application relates to the field of wireless network communication technology, and in particular to a method, device and electronic device for determining wireless signal strength within a region. Background Art

[0002] With the popularization of the Internet, the Internet has become a daily necessity for people, which has put forward higher requirements for the use of the Internet, that is, the signal of radio waves. Radio wave signals are always affected by buildings, especially walls with reinforced concrete as the skeleton. Therefore, the evaluation of the distribution of signal strength of radio waves in its expected signal coverage area has become an important task.

[0003] There are currently two main methods for evaluating the distribution of radio wave signal strength. The first method is to write the media extension data for each polyline in the campus model or building model in the 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 of the intersection passing through the polyline; for example, the location of the wall. This method has the problem of low efficiency due to the large amount of calculation and many steps.

[0004] The second method is to set up the network environment in advance in the park or indoors, and then use the detection equipment to measure the signal strength at N pre-selected detection points, and then perform simulation calculations based on the signal strength of the N points to obtain the signal strength of the remaining locations. Therefore, this method also has the problem of low efficiency because it requires manual arrival at the pre-selected points in advance to measure the signal strength. Summary of the invention

[0005] The present invention provides a method, device and electronic device for determining wireless signal strength in an area, so as to improve the efficiency of determining the signal strength distribution in the area, thereby achieving the purpose of determining the signal distribution of a target signal source in the area in real time.

[0006] In a first aspect, an embodiment of the present application provides a method for determining wireless signal strength within an area, including:

[0007] Based on the size information of the obstacle in the target area, in a polar coordinate system with the target signal source as the pole, a target polyline corresponding to the obstacle in the target area is determined, and target information of the propagation path of the target signal passing through the target polyline is determined; wherein the target information includes the number of pixel points on the propagation path passing through the obstacle and the polar coordinates of the pixel points;

[0008] Based on the target information, the signal strength information of the pixel point in the target area is determined; wherein the signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

[0009] In a possible implementation manner, determining the signal strength information of the pixel points in the target area based on the target information includes:

[0010] 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;

[0011] 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.

[0012] 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 emitted 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.

[0013] In a possible implementation manner, the location information includes polar coordinates and rectangular coordinates;

[0014] Then, determining the signal strength information of the pixel points in the target area based on the target information includes:

[0015] 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 abscissa and the ordinate of the pixel coordinates are both integers;

[0016] 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;

[0017] Based on the pixel color, assigning color to the pixel point in the rectangular coordinate system to obtain a color signal intensity distribution map;

[0018] Based on the color signal intensity distribution diagram, the signal intensity information of the pixel point is read.

[0019] In this implementation, after efficiently determining the signal strength of the pixel points in the target area in the polar coordinate system, the signal strength of the pixel points in the target area is further represented in the rectangular coordinate system through rectangular coordinate transformation, thereby enhancing the readability of the signal strength distribution in the target area. In addition, color mapping in the rectangular coordinate system is implemented to obtain a color signal strength distribution map—efficiently performing heat map rendering, which allows the signal strength distribution in the target area to be more intuitively displayed to the user.

[0020] In a possible implementation manner, the polar coordinates of the pixel point are transformed into rectangular coordinates to obtain the rectangular coordinates of the pixel point in a rectangular coordinate system and the pixel coordinates corresponding to the rectangular coordinates, including:

[0021] 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;

[0022] In response to the abscissa and the ordinate in the rectangular coordinate being both integers, determining the rectangular coordinate to be the pixel coordinate; or,

[0023] 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.

[0024] In a possible implementation manner, determining the pixel color corresponding to the pixel point on the pixel coordinate in the rectangular coordinate system based on the first mapping relationship between the color and the signal strength interval includes:

[0025] Based on a second mapping relationship between the image resolution and the filter window, a target size of the filter window is determined, and the signal strength of the pixel is processed by sliding the filter window of the target size in the target area, so that the noise of the signal strength of the pixel in the filter window of the target size is less than a preset threshold, thereby obtaining denoised signal strength information;

[0026] The pixel color corresponding to the pixel is determined based on the first mapping relationship and the signal strength of the pixel in the denoised signal strength information.

[0027] In a possible implementation manner, the number of the 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 a preset signal coverage range of the target signal source;

[0028] Then, determining the signal strength information of the pixel points in the target area based on the target information includes:

[0029] In response to the number of the signal strengths at the pixel being greater than 1, the signal strength with the largest value is determined as the signal strength of the pixel.

[0030] In a possible implementation manner, the size information of the obstacle includes the type and size of the obstacle; the size information of the obstacle is obtained by the following method:

[0031] Inputting a building image containing the target area into a pre-trained semantic segmentation model to obtain the type of the obstacle;

[0032] The size of the obstacle is determined based on the ratio of the pixel distance between the pixel points in the building image to the actual distance between the pixel points; the type and the size constitute the size information of the obstacle.

[0033] In a second aspect, an embodiment of the present application provides a device for determining wireless signal strength in an area, including:

[0034] A target unit, for determining, based on the size information of the obstacles in the target area, a target polyline corresponding to the obstacles in the target area in a polar coordinate system with the target signal source as the pole, and determining the target information of the propagation path of the target signal passing through the target polyline; wherein the target information includes the number of obstacles passed through by the propagation path and the polar coordinates of the pixel points;

[0035] The strength unit is used to determine the signal strength information of the pixel point in the target area based on the target information; wherein the signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

[0036] In one possible implementation, the intensity unit 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.

[0037] In a possible implementation manner, the position information includes polar coordinates and rectangular coordinates; the intensity unit is also used 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, and the pixel coordinates corresponding to the rectangular coordinates; wherein the horizontal and vertical coordinates of the pixel coordinates are both integers; based on a 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.

[0038] In a possible implementation manner, the intensity unit is further used 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; in response to the horizontal coordinate and the vertical coordinate in the rectangular coordinate being integers, the rectangular coordinate is determined to be the pixel coordinate; or, in response to the horizontal coordinate and / or the vertical coordinate in the rectangular coordinate being non-integer, the target pixel coordinate closest to the rectangular coordinate is determined to be the pixel coordinate.

[0039] In a possible implementation manner, the intensity unit is also used to determine the target size of the filtering window based on a second mapping relationship between the image resolution and the filtering window, and to process the signal intensity of the pixel by sliding the filtering window of the target size in the target area so that the noise of the signal intensity of the pixel within the filtering window of the target size is less than a preset threshold, thereby obtaining denoised signal intensity information; and to determine the pixel color corresponding to the pixel based on the first mapping relationship and the signal intensity of the pixel in the denoised signal intensity information.

[0040] In a possible implementation manner, 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 a preset signal coverage range of the target signal source; and the intensity unit is further used to determine, in response to the number of signal intensities at the pixel point being greater than 1, the signal intensity with the largest value as the signal intensity of the pixel point.

[0041] In a possible implementation manner, the size information of the obstacle includes the type and size of the obstacle; the device further includes an information unit, and the information unit 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;

[0042] The size of the obstacle is determined based on the ratio of the pixel distance between the pixel points in the building image to the actual distance between the pixel points; the type and the size constitute the size information of the obstacle.

[0043] In a third aspect, an embodiment of the present application further provides a readable storage medium, including:

[0044] Memory,

[0045] The memory is used to store a computer program. When the computer program is executed by the processor, the device including the readable storage medium completes the method described in the first aspect and any possible implementation manner.

[0046] In a fourth aspect, an embodiment of the present application provides an electronic device, including:

[0047] Memory, used to store computer programs;

[0048] The processor is used to execute the computer program stored in the memory to implement the method described in the first aspect and any possible implementation manner.

[0049] One or more technical solutions in the embodiments of the present invention have at least the following technical effects:

[0050] First, the method provided in the embodiment of the present application sets the signal source as the pole of the polar coordinate system and performs polar coordinate transformation on the size information of the obstacle (for example, a wall, etc.). The position of the obstacle can be directly determined by the polar coordinates of the pixel point in the polar coordinates, and the number of obstacles passed by the signal on the propagation path where the pixel point is located can be determined by the polar diameter of the polar coordinates, 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.

[0051] Secondly, by determining the signal strength of each pixel point in the target area in the 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 the y-axis, the position of the pixel point on the propagation path first needs to be calculated by the square root of its horizontal coordinate and vertical coordinate. More importantly, when determining the number of obstacles passed through on the propagation path, for the rectangular coordinate system whose minimum size unit is the same as the polar coordinate system, which is 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 a rectangular coordinate system. 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.

[0052] Finally, after determining the signal strength of the pixel point at each position in the polar coordinate system, the polar coordinate inverse transformation (i.e., rectangular coordinate transformation) is performed 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 the millisecond-level signal simulation coverage heat map.

[0053] Other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purposes and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. It should be understood that the above general description and the detailed description below are only exemplary and explanatory and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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.

[0055] Figure 1 A flowchart of a method for determining wireless signal strength within an area provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of directly determining the number of wall-penetrating signals at pixel points in a target area after polar coordinate transformation provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of a method for obtaining a thermal map within a target area provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of the structure of a device for determining wireless signal strength within an area provided in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] In response to the problem that the current method for determining the signal distribution in an area is inefficient, an embodiment of the present application provides a method for determining the wireless signal strength in an area. By taking 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 the obstacles are represented in the same polar coordinate system, thereby directly counting the number of obstacles passing through the same signal propagation direction, and directly calculating the signal strength attenuation based on this, thereby efficiently determining the signal strength of the pixel points on the propagation path.

[0061] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0062] The terms "first" and "second" in the specification and claims of the present 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 their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising 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 the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

[0063] Please refer to Figure 1 The embodiment of the present application provides a method for determining the strength of wireless signals in an area, so as to improve the efficiency of the current method for determining the signal distribution in an area. The method specifically includes the following implementation steps:

[0064] 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.

[0065] The size in the polar coordinates is expressed in pixels; the polar diameter of any point in the polar coordinate system, that is, the distance between any point and the pole, is expressed in pixels. For example, in the polar coordinates (ρ, θ), ρ can be 2 pixels, indicating the distance between the current pixel and the pole-target signal source; θ indicates the propagation direction of the current signal.

[0066] The target information includes the number of obstacles that the propagation path passes through and the polar coordinates of the pixel point. The target signal indicates the signal emitted by the target signal source. The target polyline indicates the continuous line converted according to the size information of the aforementioned obstacle, such as the starting position, the end position, the shape information, etc. The continuous line can be an arc, a line segment, or a combination of an arc and a line segment.

[0067] Specifically, the target signal source is 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.

[0068] 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.

[0069] The above obstacles are mainly buildings, and in addition to distance, the factors that cause signal attenuation in buildings also include obstacles such as walls. In the polar coordinate system, coordinates are represented by a combination of polar diameter and polar angle. Therefore, after the obstacles such as walls in the rectangular coordinate system are converted into polar coordinates, the information of each propagation path of the target signal source passing through obstacles can be intuitively obtained. The information of passing through obstacles can be used to determine the attenuation of the signal emitted by the target signal source.

[0070] The information about passing through obstacles includes the distance between each point on the propagation path and the target signal source (ie, the pole), the position of passing through obstacles, the number of passing through obstacles, etc.

[0071] Since the polar coordinate system in the embodiment of the present application uses 1 pixel as the minimum size unit, each point on the above propagation path is a pixel point. The distance between each point and the target signal source (i.e., the pole) is the polar diameter in the polar coordinates of the pixel point. The position of the obstacle is the polar coordinate of the intersection of the propagation path and the obstacle. The number of obstacles passed indicates the number of obstacles passed before the signal is transmitted along the propagation path and reaches the pixel point.

[0072] The number of obstacles passed through is determined by sliding a sliding window with a sliding step of 1 pixel from the pole along the polar radius to the pixel point. Before the sliding window slides to the pixel point, when the sliding window slides to the intersection point, the polar coordinates of the intersection point can be directly read and the number of obstacles passed through + 1 is added until the pixel point is reached; then the number of obstacles passed through corresponding to the pixel point and the corresponding position of the obstacle passed through can be determined.

[0073] In some embodiments, the obstacle is a wall, and the information about passing through the obstacle is the wall-penetrating information. The wall-penetrating information includes the distance between the specified pixel point on the corresponding propagation path and the target signal source (i.e., the pole point), the wall-penetrating position (i.e., the polar coordinates of the wall-penetrating pixel point), and the number of wall-penetratings.

[0074] Figure 2 This is a schematic diagram of a wall after polar coordinate conversion provided in an embodiment of the present application. Figure 2As shown, the area inside the dotted circle is the target area, the solid circle is the target polyline, and the vector OM is a propagation path in the θ1 direction. Point A is the wall penetration position. According to the polar coordinates of point A, the number of wall penetrations before the wall penetration point A in the θ1 direction is 0, and the number of wall penetrations after position A is 1.

[0075] In this way, the target information of the pixel points on 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 wall penetrations is 1, and the position of pixel point B is marked by polar coordinates (ρ2, θ2) with a polar radius of ρ2 and a polar angle of θ2.

[0076] The following is an example of the size information of the obstacle, taking the obstacle as a wall:

[0077] 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.

[0078] 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 size data indicating size information of obstacles in the target area. The size data may be vector data.

[0079] The building map may only contain a plan view of the target area, or may be a plan view of the target area as a part thereof and also include other areas. When there is more than one target area in the building map, when the building area is input into the pre-trained segmentation model, it is also necessary to input the area data for indicating the pre-trained semantic segmentation model to select the target area, so that the pre-trained semantic segmentation model can select the target area in the building map, and identify the type, size, and position of the wall to obtain obstacle information including obstacle size data. That is, the obstacle information may include the starting point, end point, thickness of the wall, and the wall type used to determine / obtain the medium attenuation coefficient.

[0080] 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.

[0081] Furthermore, the pre-trained semantic segmentation model is described below:

[0082] First, obtain a training atlas. The training atlas includes multiple original building images and corresponding data augmentation images. Each image in the training atlas contains a label corresponding to each image, and the label includes the type of obstacle in the image and the size of the obstacle. The obstacle type can be, for example, a window, door, wall, etc. The obstacle size can be, for example, the starting point and end point in the length direction, the thickness in the width direction, and can also include the height.

[0083] The original building drawing may be a CAD floor plan or a 3D bird's-eye view building drawing. The data enhancement graph may directly perform data enhancement processing such as black-and-white conversion, random erasing, and cropping on the original building drawing with labels to obtain a data enhancement graph corresponding to the original building drawing and a label of the data enhancement graph corresponding to the original building drawing.

[0084] Then, the training atlas is input into the semantic segmentation model to be trained to obtain obstacle type information.

[0085] Next, based on the labels corresponding to each image in the training atlas, a first error between a first type of obstacle type indicated 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 type of obstacle type indicated by the semantic segmentation model to be trained.

[0086] 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.

[0087] Therefore, when it is necessary to determine the wireless signal strength in an area, the building image containing the target area can be input into the above pre-trained semantic segmentation model to obtain the types of obstacles in the target area, such as walls, doors, and windows.

[0088] In some embodiments, the type granularity of obstacles in the labels in 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.

[0089] Step 102: Based on the target information, determine the signal strength information of the pixel points in the target area.

[0090] The signal strength information includes the location information of the pixel point and the signal strength at the pixel point.

[0091] Specifically, the location 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.

[0092] Among them, the medium attenuation indicates the value of the signal strength drop caused by the obstacle. The distance attenuation indicates the value of the signal strength drop at the pixel caused by the distance between the current pixel and the target signal source. Since the above-mentioned polar diameter is determined by the architectural drawing, and the architectural drawing is obtained by scaling according to the actual size, when using the distance to calculate the medium attenuation and natural attenuation, it is also necessary to restore the distance according to the scaling ratio of the architectural drawing, and use the actual distance value obtained thereby to calculate the medium attenuation and natural attenuation. This distance restoration can also be obtained through the aforementioned pre-trained semantic segmentation model.

[0093] 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, and the signal strength of the pixel can be determined accordingly, that is, the signal strength of the pixel is obtained by subtracting the total attenuation from the signal strength of the target signal source. The polar coordinates and signal strength of the pixel are determined as the signal strength information of the pixel.

[0094] The above-mentioned total attenuation A can be calculated according to the following formula:

[0095] A=20log(d)+m*g+20log(f)+20log(4π / c)–G;

[0096] Among them, 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 represents the antenna gain, m represents the number of obstacles passed through, and g represents the medium attenuation coefficient corresponding to the obstacle type.

[0097] In the above formula of the total attenuation A, 20log(d) indicates the attenuation of signal strength as the distance changes, that is, distance attenuation; m*g indicates the attenuation of signal strength caused by the signal passing through an obstacle, that is, medium attenuation; 20log(f)+20log(4π / c) represents the inverse of the signal penetration ability.

[0098] Furthermore, if the size of the target area is no 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 introducing signals from distant signal sources.

[0099] When the preset signal coverage ranges between signal sources overlap, their respective propagation paths and target areas may overlap. In some embodiments, the number of signal sources is N, and N is an integer greater than 1. In response to the number of signal strengths at a pixel being 1, it means that there is no overlap of signals from multiple signal sources at the pixel. Alternatively, in response to the number of signal strengths 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 strength with the largest value is determined to be the signal strength of the pixel.

[0100] Furthermore, the above-mentioned location information includes polar coordinates and rectangular coordinates. In order to facilitate the user to obtain the distribution of signal strength in the target area, the signal strength information determined based on the polar coordinate system, especially the polar coordinates in the signal strength information, can be subjected to polar coordinate inverse transformation to obtain the signal strength information of the pixel point in the polar coordinate system in the rectangular coordinate system, that is, the coordinates and signal strength in the rectangular coordinate system corresponding to the pixel point in the polar coordinate system.

[0101] The signal strength of a pixel in the polar coordinate system is equal to the signal strength of the corresponding pixel in the rectangular coordinate system.

[0102] The position in the rectangular coordinate system includes the rectangular coordinates obtained by transforming the polar coordinates of the pixel point. 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 integers, and after the polar coordinates whose polar axes are integers are converted from the polar coordinate system to the rectangular coordinate system, the corresponding rectangular coordinates (horizontal coordinates and / or vertical coordinates) will be non-integer. Therefore, in order to establish the corresponding relationship between the polar coordinates and the rectangular coordinate system before and after the conversion, the rectangular coordinates can be aligned to obtain pixel coordinates whose horizontal coordinates and vertical coordinates are both integers. Specifically, the rectangular coordinates of the pixel point can be processed as follows: in response to the horizontal coordinates and vertical coordinates in the rectangular coordinates being integers, the rectangular coordinates are determined to be pixel coordinates, that is, the two are equal. Alternatively, in response to the horizontal coordinates and / or vertical coordinates in the rectangular coordinates being non-integers, the target pixel coordinates closest to the rectangular coordinates are determined to be the pixel coordinates.

[0103] The target pixel coordinates are the horizontal and vertical coordinates of the original pixel point in the rectangular coordinate system, so 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.

[0104] In some embodiments, after obtaining the rectangular coordinates of the pixel points, the rectangular coordinates can be processed using the nearest neighbor interpolation method so that the horizontal coordinates and vertical coordinates of the processed pixel coordinates are both integers. Thus, the pixel point coordinates in the rectangular coordinate system include rectangular coordinates and pixel coordinates.

[0105] In this way, the signal strength information of each pixel point in the target area in the rectangular coordinate system can be obtained.

[0106] Next, the pixel color corresponding to each pixel in the rectangular coordinate system can be determined based on the first mapping relationship between the color and signal strength interval, 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 colored to obtain a color signal strength distribution map.

[0107] Finally, the signal strength information of the pixel points can be read based on the color signal strength distribution diagram.

[0108] 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.

[0109] In some embodiments, based on the second mapping relationship between the image resolution and the filter window, the target size of the filter window is determined according to the resolution of the image in the 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 in the target area in the rectangular coordinate system, and the signal intensity of the pixel point is processed to remove noise, so that the noise of the signal intensity of the pixel point in the sliding filter window of the target size is less than a preset threshold. The resolution of the image is determined according to 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 the user setting.

[0110] Specifically, a dynamic filtering algorithm is used to slide from any vertex of the target area. For example, the shape of the target area is a rectangle, and the filter window starts to slide from the vertex of the upper left corner of the rectangle. Each slide determines the average or median of the signal strength of each pixel in the filter window. When the difference between the signal strength of the pixel at the center of the filter window and the average or median exceeds a preset threshold, it indicates that the signal strength noise of the pixel at the center of the filter window is too large, so the signal strength of the pixel at the center of the filter window is adjusted so that the aforementioned difference is within the preset threshold. The signal strength of the pixel at the center of the filter window is adjusted here without limitation in the embodiment of the present application. For example, the signal strength of the pixel at the center of the filter window can be set to the aforementioned average or median. For example, the signal strength of the pixel at the center of the filter window can be correspondingly reduced or increased so that the difference between the modified signal strength and the aforementioned average or median is just less than the aforementioned preset threshold.

[0111] 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 pixel in the target area is less than the preset threshold, thereby making the signal strength transition of each pixel in the target area smooth.

[0112] 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. The pixel in the target area can be further colored based on the corresponding relationship between each pixel and the pixel color to obtain a color signal strength distribution map.

[0113] Based on the method for determining the wireless signal strength in the area described in steps 101-102, the following takes the target signal source as an AP, and there is no signal from other wireless signal sources within the signal coverage range of the AP as an example to illustrate how to obtain the heat map. Please refer to Figure 3 .

[0114] 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.

[0115] Then, the building map is calibrated to obtain the size information of obstacles including but not limited to walls, windows, and doors, as well as the actual distance between adjacent pixels in the building map. And, based on the size information of the obstacle, a target polyline corresponding to the shape and direction of the obstacle is drawn in a polar coordinate system with the AP as the pole. An attention shielding mechanism is introduced: the target area corresponding to the AP signal coverage range is determined only in the polar coordinate system. Therefore, the length of the propagation path does not exceed the target area. Generally, the preset signal coverage range of the target signal source is expressed as a circle, then the length of the propagation path in the target area is less than or equal to the radius of the preset signal coverage range of the target signal source.

[0116] In the target area, based on the actual distance between adjacent pixels in the building map output by the pre-trained semantic segmentation model, and the number of obstacles that each pixel obtained by reading the map in the polar coordinate system passes through in its propagation direction, the signal attenuation and signal strength at the pixel are determined. Thus, the polar coordinates and signal strength of the pixel constitute the signal strength information of the pixel.

[0117] Next, the polar coordinates are inversely transformed based on the polar coordinates, and the rectangular coordinates are aligned using the nearest neighbor difference method, and the signal strength of the pixel point at the corresponding position in the rectangular coordinate system is obtained.

[0118] Next, the signal strength of the pixel points on each pixel coordinate in the rectangular coordinate system is processed by dynamic filtering method to deal with noise. And gradient color mapping is performed: different colors are used to represent the signal strength of different signal strength intervals, so as to efficiently obtain the signal strength distribution in the target area, so that users can intuitively obtain the signal strength distribution of each area in the target area in the rectangular coordinate system.

[0119] 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. Figure 1 The method for determining the wireless signal strength in the area shown in the figure corresponds to the method for determining the wireless signal strength in the area. The specific implementation of the device can refer to the description of the above method embodiment part, and the repeated parts will not be repeated. Figure 4 , the device comprises:

[0120] The target unit 401 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.

[0121] The target information includes the number of obstacles that the propagation path passes through and the polar coordinates of the pixel points.

[0122] The strength unit 402 is used to determine the signal strength information of the pixel points in the target area based on the target information.

[0123] The signal strength information includes the location information of the pixel point and the signal strength at the pixel point.

[0124] The intensity unit 402 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; determine the signal strength of the signal of the target signal source at the pixel point based on the medium attenuation and the natural attenuation, and determine the polar coordinates of the pixel point and the signal strength as the signal strength information.

[0125] The position information includes polar coordinates and rectangular coordinates; the intensity unit 402 is also used to perform a 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.

[0126] Furthermore, the intensity unit 402 is also used 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;

[0127] In response to the abscissa and the ordinate in the rectangular coordinate being both integers, determining the rectangular coordinate to be the pixel coordinate; or,

[0128] 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.

[0129] The intensity unit 402 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, and obtain 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.

[0130] 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 402 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 the signal intensity at the pixel point being greater than 1.

[0131] 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 pixel points in the building map to the actual distance between the pixel points, the size of the obstacle is determined; the type and the size constitute the size information of the obstacle.

[0132] Based on the same inventive concept, the embodiment of the present application further provides a readable storage medium, including:

[0133] Memory,

[0134] The memory is used to store a computer program. When the computer program is executed by the processor, the device including the readable storage medium performs the method for determining the wireless signal strength within an area as described above.

[0135] Based on the same inventive concept as the above method for determining the strength of wireless signals in an area, an electronic device is also provided in an embodiment of the present application, and the electronic device can implement the function of the above method for determining the strength of wireless signals in an area, please refer to Figure 5 , the electronic device comprises:

[0136] At least one processor 501, and a memory 502 connected to the at least one processor 501. The specific connection medium between the processor 501 and the memory 502 is not limited in the embodiment of the present application. Figure 5 In the example, the processor 501 and the memory 502 are connected via a bus 500. The bus 500 is Figure 5The connections between other components are shown in bold lines, and are not intended to be limiting. The bus 500 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 501 can also be called a controller, and there is no limitation on the name.

[0137] In the embodiment of the present application, the memory 502 stores instructions that can be executed by at least one processor 501. The at least one processor 501 can execute the method for determining the wireless signal strength in the area discussed above by executing the instructions stored in the memory 502. The processor 501 can implement Figure 4 The functions of each module in the device shown.

[0138] Among them, the processor 501 is the control center of the device, and can use various interfaces and lines to connect the various parts of the entire control device. By running or executing instructions stored in the memory 502 and calling data stored in the memory 502, the various functions of the device and processing data, the device can be monitored as a whole.

[0139] In one possible design, the processor 501 may include one or more processing units, and the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 501. In some embodiments, the processor 501 and the memory 502 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0140] The processor 501 may 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 may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method for determining the strength of wireless signals in an area disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0141] The memory 502 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 502 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 502 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 502 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.

[0142] By programming the processor 501, the code corresponding to the method for determining the wireless signal strength in the area described in the above embodiment can be fixed into the chip, so that the chip can execute the code when running. Figure 1 The steps of the method for determining the wireless signal strength in the area are shown. How to design and program the processor 501 is a technology well known to those skilled in the art and will not be described in detail here.

[0143] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0144] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, 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.

[0145] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0147] 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 to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform 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 (Universal Serial Bus flash disk), a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a disk or an optical disk, and other media that can store program codes.

[0148] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations 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.

Claims

1. A method for determining wireless signal strength in an area, characterized in that: include: Based on the size information of the obstacles in the target area, in a polar coordinate system with the target signal source as the pole, a target polyline corresponding to the obstacles in the target area is determined, and target information of the propagation path of the target signal passing through the target polyline is determined; wherein the target information includes the number of obstacles passed through by the propagation path and the polar coordinates of the pixel points; Based on the target information, the signal strength information of the pixel point in the target area is determined; wherein the signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

2. The method according to claim 1, characterized in that The determining, based on the target information, signal strength information of the pixel points in the target area includes: 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, 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.

3. The method according to claim 1 or 2, characterized in that The position information includes polar coordinates and rectangular coordinates; Then, determining the signal strength information of the pixel points in the target area based on the target information includes: 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 abscissa and the ordinate of the pixel coordinates are both integers; 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; Based on the pixel color, assigning color to the pixel point in the rectangular coordinate system to obtain a color signal intensity distribution map; Based on the color signal intensity distribution diagram, the signal intensity information of the pixel point is read.

4. The method according to claim 3, characterized in that The performing 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 includes: 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; In response to the abscissa and the ordinate in the rectangular coordinate being both integers, determining the rectangular coordinate to be the pixel coordinate; or, 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.

5. The method according to claim 3, characterized in that The determining, based on the first mapping relationship between the color and the signal strength interval, the pixel color corresponding to the pixel point on the pixel coordinate in the rectangular coordinate system includes: Based on a second mapping relationship between the image resolution and the filter window, a target size of the filter window is determined, and the signal strength of the pixel is processed by sliding the filter window of the target size in the target area, so that the noise of the signal strength of the pixel in the filter window of the target size is less than a preset threshold, thereby obtaining denoised signal strength information; The pixel color corresponding to the pixel is determined based on the first mapping relationship and the signal strength of the pixel in the denoised signal strength information.

6. The method according to any one of claims 1-2, 4-5, characterized in that: The number of the 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, determining the signal strength information of the pixel points in the target area based on the target information includes: In response to the number of the signal strengths at the pixel being greater than 1, the signal strength with the largest value is determined as the signal strength of the pixel.

7. The method according to claim 1, characterized in that The size information of the obstacle includes the type and size of the obstacle; the size information of the obstacle is obtained by the following method: Inputting a building image containing the target area into a pre-trained semantic segmentation model to obtain the type of the obstacle; The size of the obstacle is determined based on the ratio of the pixel distance between the pixel points in the building image to the actual distance between the pixel points; the type and the size constitute the size information of the obstacle.

8. A device for determining wireless signal strength in an area, characterized in that: include: A target unit, for determining, based on the size information of the obstacles in the target area, a target polyline corresponding to the obstacles in the target area in a polar coordinate system with the target signal source as the pole, and determining the target information of the propagation path of the target signal passing through the target polyline; wherein the target information includes the number of obstacles passed through by the propagation path and the polar coordinates of the pixel points; The strength unit is used to determine the signal strength information of the pixel point in the target area based on the target information; wherein the signal strength information includes the position information of the pixel point and the signal strength at the pixel point.

9. A readable storage medium, characterized in that: include, Memory, The memory is used to store a computer program. When the computer program is executed by the processor, the device including the readable storage medium implements the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute a computer program stored in the memory to implement a method as claimed in any one of claims 1 to 7.

Images