CN113048950A - Base station antenna inclination angle measuring method and device, storage medium and computer equipment - Google Patents
Base station antenna inclination angle measuring method and device, storage medium and computer equipment Download PDFInfo
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C9/00—Measuring inclination, e.g. by clinometers, by levels
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Abstract
In the technical scheme of the method, the device, the storage medium and the computer equipment for measuring the inclination angle of the base station antenna, the three-dimensional point cloud model of the base station is generated by three-dimensional modeling of the acquired base station main body image, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds, an antenna point cloud envelope is formed by selecting any antenna point in the antenna point clouds as an expansion point, dimension reduction is carried out on the antenna point cloud envelope, the maximum inclined plane of the antenna point cloud envelope is calculated, an antenna plane normal vector is calculated according to the maximum inclined plane and the acquired point cloud space data, so that the numerical value of the inclination angle and the numerical value of the azimuth angle of the antenna are calculated through the normal vector, the north plane normal vector and the normal vector of the antenna plane, the three-dimensional model is formed through the base station main body image, and the problem that the three-dimensional space coordinate of the antenna cannot be obtained due to weather, the accuracy of antenna measurement is promoted.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of wireless mobile communication, in particular to a method and a device for measuring the inclination angle of a base station antenna, a storage medium and computer equipment.
[ background of the invention ]
In the related technology, the measurement of the inclination angle of the antenna of the base station is mainly divided into two types, one is that the measurement is carried out by adopting a pure physical means, namely, the antenna is directly measured by an unmanned aerial vehicle or a manual work; and secondly, the antenna is indirectly measured by combining unmanned aerial vehicle shooting and a specific model algorithm. The first mode is a pure physical measurement mode, which consumes large manpower and material resources, and the effect cannot be guaranteed. Can solve through the inconvenience that the measurement brought through pure physics means through the second kind of mode to combine unmanned aerial vehicle to shoot with the means of relevant model algorithm, not only can effectual reduce cost, reduce because of the personnel safety problem that the measurement antenna brought, the effect of simultaneous measurement also can obtain effectual guarantee.
However, the pictures shot by the unmanned aerial vehicle are directly operated, so that the shooting conditions are greatly limited, and the available pictures can be obtained only by needing better weather conditions; meanwhile, in the related technical scheme, the model algorithm calculates the downtilt angle in the antenna data mainly according to the position information and other prior knowledge of the unmanned aerial vehicle, so that in the second scheme, the measured angle is easy to deviate due to the fact that the model algorithm is easy to be influenced by image distortion and shooting conditions.
[ summary of the invention ]
In view of the above, the invention provides a method and a device for measuring a base station antenna inclination angle, a storage medium and a computer device, which form a three-dimensional model based on a picture shot by an unmanned aerial vehicle, solve the problem that the three-dimensional space coordinate of an antenna cannot be obtained due to the limitation of weather conditions, and improve the accuracy of antenna measurement.
In one aspect, an embodiment of the present invention provides a method for measuring a tilt angle of a base station antenna, including:
the method comprises the steps that an acquired base station aerial image is divided into a base station main body image and a base station background image through an image recognition algorithm, wherein the base station main body image comprises an antenna image;
performing three-dimensional modeling on the base station main body image to generate a three-dimensional point cloud model of the base station, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image;
selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points;
reducing the dimension of the antenna point cloud envelope, and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground;
calculating an antenna plane normal vector according to the maximum inclined plane perpendicular to the ground direction and the acquired point cloud space data;
and calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image according to the normal vector of the antenna plane, the acquired north plane normal vector and the acquired ground plane normal vector.
Optionally, the segmenting the base station aerial image into a base station main body image and a base station background image through an image recognition algorithm, where the base station main body image includes an antenna image, includes:
performing frame selection on an image including a base station main body in the base station aerial image to generate initial base station main body data;
taking the initial base station main body data as a training set, and training through an image recognition algorithm to generate a recognition model of a base station main body;
and identifying the aerial image of the base station according to the identification model of the base station main body, and segmenting the aerial image into a base station main body image and a base station background image.
Optionally, the selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points, includes:
selecting any antenna point in the antenna point cloud in the three-dimensional point cloud model of the base station, and taking the antenna point as an initial expansion point of an antenna;
and based on a point cloud near point searching algorithm, taking the initial expansion point as a central point, and expanding outwards to form an antenna point cloud envelope.
Optionally, the method for searching based on a point cloud near point expands outward to form an antenna point cloud envelope with the initial expansion point as a central point, and includes:
calculating the point cloud density of the antenna point cloud in the three-dimensional point cloud model of the base station;
setting a proximity search range according to the point cloud density based on a point cloud proximity point searching method, and acquiring a proximity point of the initial expansion point;
and taking a regular cube formed by enveloping the adjacent points of the initial expansion points as the antenna point cloud envelope.
Optionally, after the regular cube formed by the envelope of the nearby points of the initial expansion point is used as the envelope of the antenna point cloud, the method further includes:
and acquiring point cloud space data of each antenna point cloud according to the antenna point cloud envelope.
Optionally, the three-dimensional point cloud model of the base station includes a base station point cloud corresponding to the base station main body image;
after the three-dimensional modeling is performed on the base station main body image to generate a three-dimensional point cloud model of the base station, the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image, the method further comprises the following steps:
eliminating invalid points of base station point clouds in the three-dimensional point cloud model of the base station;
clustering the antenna points in the antenna point cloud to form a set of a plurality of antenna points;
and if the set of the antenna points is judged to be smaller than a preset threshold value, rejecting the set of the antenna points.
And rejecting the miscellaneous points in the base station point cloud through a down-sampling algorithm.
Optionally, before the segmenting the acquired base station aerial image into a base station main body image and a base station background image by using an image recognition algorithm, the method further includes:
shooting a base station through an unmanned aerial vehicle to obtain an initial base station aerial image;
and screening the base station aerial image from the initial base station aerial image.
In another aspect, an embodiment of the present invention provides a base station antenna tilt angle measuring apparatus, where the apparatus includes:
the segmentation module is used for segmenting the acquired aerial image of the base station into a main image of the base station and a background image of the base station through an image recognition algorithm, wherein the main image of the base station comprises an antenna image;
the generating module is used for carrying out three-dimensional modeling on the base station main body image and generating a three-dimensional point cloud model of the base station, and the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image; selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points;
the calculation module is used for reducing the dimension of the antenna point cloud envelope and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground; calculating an antenna plane normal vector according to the maximum inclined plane perpendicular to the ground direction and the acquired point cloud space data; and calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image according to the normal vector of the antenna plane, the acquired north plane normal vector and the acquired ground plane normal vector.
On the other hand, an embodiment of the present invention provides a storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute the above-mentioned method for measuring an antenna tilt angle of a base station.
In another aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, where the memory is used to store information including program instructions, and the processor is used to control execution of the program instructions, and the program instructions are loaded by the processor and executed to perform the steps of the above-mentioned base station antenna tilt angle measurement method.
In the technical scheme provided by the embodiment of the invention, a three-dimensional point cloud model of a base station is generated by performing three-dimensional modeling on an acquired base station main body image, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds, an antenna point cloud envelope is formed by selecting any antenna point in the antenna point clouds as an expansion point, the antenna point cloud envelope is subjected to dimensionality reduction, the maximum inclined plane of the antenna point cloud envelope is calculated, an antenna plane normal vector is calculated according to the maximum inclined plane and the acquired point cloud spatial data, so that the numerical value of the downward inclination angle and the numerical value of the azimuth angle of an antenna are calculated through the normal vector of the antenna plane, the north plane normal vector and the ground plane normal vector, the three-dimensional model is formed through the base station main body image, and the problem that the three-dimensional space coordinate of the antenna cannot be, the accuracy of antenna measurement is promoted.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a flowchart of a method for measuring a tilt angle of a base station antenna according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for measuring a tilt angle of a base station antenna according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of a base station antenna tilt angle measuring apparatus according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a computer device according to an embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely one type of associative relationship that describes an associated object, meaning that three types of relationships may exist, e.g., A and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 is a flowchart of a method for measuring a tilt angle of a base station antenna according to an embodiment of the present invention, as shown in fig. 1, the method includes:
102, carrying out three-dimensional modeling on the base station main body image to generate a three-dimensional point cloud model of the base station, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna images.
103, selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points.
And 104, reducing the dimension of the antenna point cloud envelope, and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground.
And 105, calculating an antenna plane normal vector according to the maximum inclined plane vertical to the ground direction and the acquired point cloud space data.
And step 106, calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image through the normal vector of the antenna plane, the acquired north plane normal vector and the acquired ground plane normal vector.
In the technical scheme provided by the embodiment of the invention, the three-dimensional point cloud model of the base station is generated by three-dimensional modeling of the acquired base station main body image, wherein, the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds, an antenna point cloud envelope is formed by selecting any antenna point in the antenna point clouds as an expansion point, reducing the dimension of the antenna point cloud envelope, calculating the maximum slope of the antenna point cloud envelope, calculating the normal vector of the antenna plane according to the maximum slope and the acquired point cloud space data, thereby calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna through the normal vector of the plane of the antenna, the normal vector of the north plane and the normal vector of the ground plane, a three-dimensional model is formed through the base station main body image, the problem that the three-dimensional space coordinate of the antenna cannot be obtained due to weather condition limitation is solved, and the accuracy of antenna measurement is improved.
Fig. 2 is a flowchart of a method for measuring a tilt angle of a base station antenna according to another embodiment of the present invention, as shown in fig. 2, the method includes:
The unmanned aerial vehicle aerial photography uses an unmanned aerial vehicle as an aerial platform, uses airborne remote sensing equipment such as a high-resolution CCD digital camera, a light optical camera, an infrared scanner, a laser scanner, a magnetic measuring instrument and the like to acquire information, processes image information by using a computer, and makes the image according to certain precision requirements. The unmanned aerial vehicle aerial photography system has the outstanding characteristics in the aspects of design and optimal combination, and is a novel application technology integrating high-altitude shooting, remote control, a remote measuring technology, video image microwave transmission and computer image information processing.
In the embodiment of the invention, the acquired aerial image of the initial base station can have high resolution on the basis that the unmanned aerial vehicle carries out 360-degree surrounding aerial photography around the base station, so that the coordinate data of the main body characteristics of the base station under a pixel coordinate system can be acquired according to the aerial image of the initial base station, and the main body image of the base station can be conveniently subjected to three-dimensional modeling based on the pixel coordinate and the internal and external parameters of the camera.
In the embodiment of the invention, for example, the initial base station aerial image does not include the main part of the base station, so that the initial base station aerial image needs to be removed, and the base station aerial image including the main part of the base station is screened out, so that the base station main body image can be conveniently subjected to three-dimensional modeling. The mode of rejecting can comprise manual rejecting or machine identification rejecting. The mode of machine identification rejection, accessible earlier stage manual work mark the characteristic of base station main part to make the machine can discern the characteristic of base station main part, thereby reject the image of the main part that does not include the base station in the initial base station aerial image, thereby screen out the base station aerial image of the main part including the base station.
And step 203, performing frame selection on the image including the base station main body in the base station aerial image to generate initial base station main body data.
In the embodiment of the invention, the image of the base station main body including Labellmg can be framed and selected in an artificial labeling mode in the earlier stage, so that the identification model of the base station main body generated in the subsequent step 204 can learn the capability, and then the image of the base station main body in the aerial image of the base station is automatically framed and selected. In step 203, an image including the base station body can be further divided. For example, the base station body size in the base station aerial image occupies one tenth of the base station aerial image, and the base station body size in the image of the base station body after the framing occupies four fifths of the image of the base station body, and initial base station body data is generated. The initial base station main body data comprises an initial base station main body image and an initial base station main body file. The initial base station main body image comprises an image of a base station main body, and the initial base station main body file comprises annotation information generated after the initial base station main body image is framed.
And 204, training the initial base station main body data serving as a training set through an image recognition algorithm to generate a recognition model of the base station main body.
In the embodiment of the invention, the image recognition algorithm refers to a technology for processing, analyzing and understanding an image by using computer equipment so as to recognize various targets and objects in different modes. The image recognition algorithm may include an SSD image recognition algorithm, and may also include other image recognition algorithms, which are not limited in this respect.
And step 205, identifying the aerial image of the base station according to the identification model of the base station main body, and segmenting the aerial image into a base station main body image and a base station background image, wherein the base station main body image comprises an antenna image.
In computer vision, a segmented image is a region that distinguishes between different segmentations. When using semantic segmentation, it divides the image into semantically meaningful parts, and then semantically labels each part as one of the predefined classes, thereby identifying objects within the different image data.
In the embodiment of the invention, after the base station aerial image is identified through the identification model of the base station main body, the base station main body and the base station background can be segmented into the base station main body image and the base station background image, the base station main body image is used as the foreground of the base station aerial image, and the base station background image is used as the background of the base station aerial image.
And step 206, performing three-dimensional modeling on the base station main body image to generate a three-dimensional point cloud model of the base station, wherein the three-dimensional point cloud model of the base station comprises a base station point cloud corresponding to the base station main body image and a plurality of antenna point clouds corresponding to the antenna images.
In the embodiment of the invention, the base station main body image can be subjected to three-dimensional modeling through a Structure From Motion algorithm (SFM algorithm for short), wherein the SFM algorithm is an off-line algorithm for carrying out three-dimensional reconstruction based on various collected disordered pictures, the space and the set relation of a target are determined through the movement of a camera, and the SFM algorithm is a common method for three-dimensional reconstruction.
For example, the three-dimensional modeling process mainly obtains a group of sequences of base station main body images through multi-angle shooting or video extraction, and takes the sequences of the base station main body images as the input of the whole system; in a multi-view base station main body image, sparse feature points (called point clouds) are extracted according to features of a base station main body, camera positions and parameters are estimated through the feature points, and dense base station point clouds are obtained after camera parameters are obtained and feature point matching is completed.
In the embodiment of the invention, the three-dimensional point cloud model of the base station comprises a base station point cloud corresponding to the base station main body image and a plurality of antenna point clouds corresponding to the antenna images. The antenna point cloud and the base station point cloud are collectively referred to as a three-dimensional point cloud in a three-dimensional point cloud model of the base station.
And step 207, eliminating invalid points of the base station point cloud in the three-dimensional point cloud model of the base station.
In the embodiment of the present invention, after step 206, since there is a noise point in the three-dimensional point cloud model of the generated base station, the three-dimensional point cloud needs to be denoised in steps 207 to 210, so as to achieve the purpose of optimizing the three-dimensional point cloud model.
In the embodiment of the invention, the invalid points in the base station point cloud of the base station can be removed through a Kmeans algorithm, and in other embodiments of the invention, the invalid points in the three-dimensional point cloud model of the base station can also be removed through other algorithms, which is not limited by the invention. For example, the invalid point can be removed by obtaining features of outliers in advance, for example, the features of the outliers include point cloud density smaller than a preset density, and when the point cloud density of a base station point cloud in the three-dimensional point cloud is detected to be smaller than the preset density, the three-dimensional point (base station) in the base station point cloud is determined to be the invalid point, so that the invalid point is removed. For example, in the manner of removing the invalid points, the distance from each three-dimensional point to the base point cloud may be calculated to form a gaussian distribution, and three-dimensional points outside the preset mean and variance may be determined as the invalid points by presetting the mean and variance, so as to remove the invalid points. In other embodiments, the three-dimensional points may be denoised in other manners, for example, by using a KDTree algorithm, and invalid points in the three-dimensional point cloud model of the base station are eliminated, which is not limited in the present invention.
And step 208, clustering the antenna points in the antenna point cloud to form a set of a plurality of antenna points.
In the embodiment of the invention, a three-dimensional point cloud model of a base station comprises a plurality of antenna point clouds corresponding to antenna images, and antenna points in the antenna point clouds are clustered through a Kmeans clustering algorithm, wherein the K-means clustering algorithm (Kmeans clustering algorithm for short) is an iterative solution clustering analysis algorithm and comprises the steps of randomly selecting K objects as initial clustering centers, then calculating the distance between each object and each seed clustering center, and allocating each object to the nearest clustering center. In the embodiment of the invention, the K antenna points are randomly selected as the initial clustering centers, then the distance between each antenna point and each seed clustering center is calculated, and the base station antenna point is distributed to the nearest clustering center, thereby forming a set of a plurality of antenna points.
And 209, if the set of the antenna points is judged to be smaller than the preset threshold value, rejecting the set of the antenna points.
In the embodiment of the invention, the preset threshold value can be set according to an empirical value or an actual requirement, the method is not limited to the above, and the antenna point cloud can be denoised by removing the set of the antenna points smaller than the preset threshold value, so that the purpose of optimizing the three-dimensional point cloud model is achieved.
And step 210, removing the miscellaneous points in the base station point cloud through a down-sampling algorithm.
In the embodiment of the present invention, for example, the state of the base station point cloud in the generated three-dimensional point cloud model of the base station is in a dense state, for example, the point cloud forming the antenna includes 60000 points, wherein 60000 point clouds include a plurality of miscellaneous points, which may result in a large amount of calculation in subsequent calculation and an increased calculation load, and therefore the miscellaneous points in the base station point cloud need to be removed by a down-sampling algorithm. For example, after the miscellaneous points in the base station point cloud are eliminated, the point cloud forming the antenna only comprises 6000 points, so that the calculation difficulty is reduced.
In the embodiment of the present invention, on the basis of step 207 and step 209, the three-dimensional point cloud model of the base station is further optimized by removing the noise of the point cloud near the base station in the three-dimensional point cloud model through a down-sampling manner, wherein in the field of digital signal processing, down-sampling and down-sampling are performed, and the method is a multi-rate digital signal processing technology or a process for reducing a signal sampling rate, and is generally used for reducing a data transmission rate or a data size.
And step 211, selecting any antenna point in the antenna point cloud in the three-dimensional point cloud model of the base station, and taking the antenna point as an initial expansion point of the antenna.
In the embodiment of the invention, any antenna point in the antenna point cloud can be selected in a manual point selection mode, and the antenna point is used as an initial expansion point of the antenna in the antenna point cloud.
And step 212, calculating the point cloud density of the antenna point cloud in the three-dimensional point cloud model of the base station.
In the embodiment of the invention, the point cloud density is the number of point clouds in a unit volume. The three-dimensional point cloud model comprises a plurality of antenna point clouds, and the point cloud density of the antenna point clouds can be calculated by calculating the number of the antenna point clouds in a unit volume.
In the embodiment of the invention, the adjacent point of the initial expansion point can be obtained by a point cloud adjacent point searching method of FLANN. Other algorithms may be adopted in other embodiments of the present invention to obtain the proximity point of the initial expansion point, which is not limited in the present invention.
In the embodiment of the present invention, after the point cloud density of the antenna point cloud is calculated in step 212, the proximity search range is automatically set according to the point cloud density, so that the antenna point cloud in the proximity search range is used as the proximity point of the initial expansion point. The searching range is smaller when the point cloud density is larger, and the searching range is larger when the point cloud density is smaller.
And 214, taking a regular cube formed by the envelope of the adjacent points of the initial expansion points as the envelope of the antenna point cloud.
In an embodiment of the present invention, the regular cube may include a rectangular parallelepiped. Through the antenna point cloud envelope formed in step 214, the antenna image can be stripped from the base station image, so that the numerical value of the antenna downward inclination angle and the numerical value of the azimuth angle corresponding to the antenna image can be calculated subsequently.
In the embodiment of the present invention, after step 214, further, the method further includes: and enveloping the antenna point clouds to obtain point cloud space data of each antenna point cloud.
The point cloud space data comprises three-dimensional space data, ordinal number and other information. According to the invention, only in step 211, any point in the antenna point cloud is manually clicked, so that the antenna point cloud envelope can be formed through self-adaptive expansion, and information such as three-dimensional space data and ordinal number of the corresponding antenna point cloud is extracted according to the antenna point cloud envelope, so that the method is more convenient and faster compared with the related technology, and has higher efficiency.
And 215, reducing the dimension of the antenna point cloud envelope, and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground.
In the embodiment of the invention, the antenna point cloud envelope can be subjected to dimensionality reduction by a Principal Component Analysis (PCA) technology. The antenna point cloud envelope is mapped into a two-dimensional space from a three-dimensional space by utilizing a PCA (principal component analysis) technology, and then the maximum section of the antenna point cloud envelope is obtained by a Singular Value Decomposition (SVD) method, wherein the maximum section of the antenna point cloud envelope is the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground. In other embodiments, other dimension reduction algorithms may also be used, which is not limited in the present invention.
And step 216, calculating an antenna plane normal vector according to the maximum inclined plane perpendicular to the ground direction and the acquired point cloud space data.
In the embodiment of the invention, the point cloud space data of the three-dimensional point cloud can be acquired from the three-dimensional point cloud model, wherein the three-dimensional point cloud comprises the earth surface point cloud, the base station point cloud, the antenna point cloud and the like, so that the point cloud space data acquired from the three-dimensional point cloud model can comprise the point cloud space data of the earth surface point cloud, the point cloud space data of the base station point cloud and the point cloud space data of the antenna point cloud.
In the embodiment of the invention, the point cloud space data of the antenna point cloud in the maximum inclined plane in the three-dimensional space is obtained from the three-dimensional point cloud model, so that the normal vector perpendicular to the maximum inclined plane is calculated, and the normal vector on the plane is equal everywhere.
And step 217, calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image through the normal vector of the antenna plane, the acquired normal vector of the north plane and the acquired normal vector of the ground plane.
In this embodiment of the present invention, step 217 may specifically include:
and 217a, calculating a cosine value of the downtilt angle through the acquired ground plane normal vector and the antenna plane normal vector, and determining a numerical value of the downtilt angle according to the cosine value of the downtilt angle.
In the embodiment of the present invention, the downtilt is used to indicate the downtilt of the antenna in the vertical direction.
The obtaining method of the normal vector of the ground plane may include: acquiring point cloud space data of ground surface point cloud from the point cloud space data; and calculating a ground plane normal vector according to the point cloud space data of the ground point cloud by a dimension reduction algorithm.
And step 217b, calculating a cosine value of the azimuth angle through the acquired normal vector of the north plane and the normal vector of the antenna plane, and determining a numerical value of the azimuth angle according to the cosine value of the azimuth angle.
In an embodiment of the invention, the azimuth angle is used to indicate the azimuth angle of the antenna plane relative to the north plane.
The obtaining method of the north plane normal vector may include: obtaining the space coordinate of the north pole; determining a plane formed by the space coordinates of the north pole and any two points in the vertical direction of the base station as a north plane; and calculating a north plane normal vector corresponding to the north plane according to the north plane.
In the technical scheme provided by the embodiment of the invention, the three-dimensional point cloud model of the base station is generated by three-dimensional modeling of the acquired base station main body image, wherein, the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds, an antenna point cloud envelope is formed by selecting any antenna point in the antenna point clouds as an expansion point, reducing the dimension of the antenna point cloud envelope, calculating the maximum slope of the antenna point cloud envelope, calculating the normal vector of the antenna plane according to the maximum slope and the acquired point cloud space data, thereby calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna through the normal vector of the plane of the antenna, the normal vector of the north plane and the normal vector of the ground plane, a three-dimensional model is formed through the base station main body image, the problem that the three-dimensional space coordinate of the antenna cannot be obtained due to weather condition limitation is solved, and the accuracy of antenna measurement is improved.
Fig. 3 is a schematic structural diagram of a base station antenna tilt angle measuring apparatus according to an embodiment of the present invention, and as shown in fig. 3, the apparatus includes: a segmentation module 11, a generation module 12 and a calculation module 13.
The segmentation module 11 is configured to segment the acquired base station aerial image into a base station main body image and a base station background image through an image recognition algorithm, where the base station main body image includes an antenna image.
The generating module 12 is configured to perform three-dimensional modeling on the base station main body image, and generate a three-dimensional point cloud model of the base station, where the three-dimensional point cloud model of the base station includes a plurality of antenna point clouds corresponding to the antenna images.
The generating module 12 is further configured to select any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and form an antenna point cloud envelope by expanding the antenna points.
The calculation module 13 is configured to perform dimension reduction on the antenna point cloud envelope, and calculate a maximum slope of the antenna point cloud envelope in a direction perpendicular to the ground.
The calculation module 13 is further configured to calculate an antenna plane normal vector according to the maximum slope in the direction perpendicular to the ground and the acquired point cloud spatial data.
The calculation module 13 is further configured to calculate a numerical value of a downtilt angle and a numerical value of an azimuth angle of the antenna according to the normal vector of the antenna plane, the acquired north-plane normal vector, and the acquired ground-plane normal vector.
In this embodiment of the present invention, the dividing module 11 of the apparatus specifically includes: a generation sub-module 111 and a segmentation sub-module 112.
The generation submodule 111 is configured to perform framing on an image including a base station main body in the base station aerial image, and generate initial base station main body data.
The generating submodule 111 is further configured to train the initial base station main body data as a training set through an image recognition algorithm, so as to generate a recognition model of the base station main body.
The segmentation submodule 112 is configured to identify the base station aerial image according to the identification model of the base station main body, and segment the base station aerial image into a base station main body image and a base station background image.
In the embodiment of the present invention, the generating module 12 of the apparatus specifically includes: an acquisition submodule 121, a calculation submodule 122 and a generation submodule 123.
The obtaining submodule 121 is configured to select any antenna point in the antenna point cloud in the three-dimensional point cloud model of the base station, and use the antenna point as an initial expansion point of an antenna.
The calculation submodule 122 is configured to calculate a point cloud density of the antenna point cloud in the three-dimensional point cloud model of the base station.
The obtaining sub-module 121 is further configured to set a proximity search range according to the point cloud density based on a point cloud proximity point searching method, and obtain a proximity point of the initial expansion point.
The generating submodule 123 is configured to use a regular cube formed by enveloping the near points of the initial expansion points as an antenna point cloud envelope.
In the embodiment of the present invention, the apparatus further includes: an acquisition module 14.
The obtaining module 14 is configured to obtain point cloud space data of each antenna point cloud according to the antenna point cloud envelope.
In the embodiment of the invention, the three-dimensional point cloud model of the base station comprises a base station point cloud corresponding to the base station main body image;
the device also includes: and a culling module 15.
The eliminating module 15 is used for eliminating the invalid points of the base station point cloud in the three-dimensional point cloud model of the base station.
The generating module 12 is further configured to cluster the antenna points in the antenna point cloud to form a set of multiple antenna points.
The rejecting module 15 is further configured to reject the set of antenna points if it is determined that the set of antenna points is smaller than a preset threshold.
The eliminating module 15 is further configured to eliminate the miscellaneous points in the base station point cloud through a downsampling algorithm.
In the embodiment of the present invention, the apparatus further includes: a shooting module 16 and a selecting module 17.
The shooting module 16 is used for shooting the base station through the unmanned aerial vehicle to acquire an initial base station aerial image.
The selection module 17 is configured to screen the base station aerial image from the initial base station aerial image.
In the technical scheme provided by the embodiment of the invention, a three-dimensional point cloud model of a base station is generated by performing three-dimensional modeling on an acquired base station main body image, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds, an antenna point cloud envelope is formed by selecting any antenna point in the antenna point clouds as an expansion point, the antenna point cloud envelope is subjected to dimensionality reduction, the maximum inclined plane of the antenna point cloud envelope is calculated, an antenna plane normal vector is calculated according to the maximum inclined plane and the acquired point cloud spatial data, so that the numerical value of the downward inclination angle and the numerical value of the azimuth angle of an antenna are calculated through the normal vector of the antenna plane, the north plane normal vector and the ground plane normal vector, the three-dimensional model is formed through the base station main body image, and the problem that the three-dimensional space coordinate of the antenna cannot be, the accuracy of antenna measurement is promoted.
An embodiment of the present invention provides a storage medium, where the storage medium includes a stored program, where, when the program runs, a device on which the storage medium is located is controlled to execute each step of the above-described embodiment of the method for measuring an antenna tilt angle of a base station, and for specific description, reference may be made to the above-described embodiment of the method for measuring an antenna tilt angle of a base station.
An embodiment of the present invention provides a computer device, which includes a memory and a processor, where the memory is used to store information including program instructions, and the processor is used to control execution of the program instructions, and the program instructions are loaded and executed by the processor to implement the steps of the above-mentioned base station antenna tilt angle measurement method. For a detailed description, reference may be made to the above-mentioned embodiments of the method for measuring the tilt angle of the base station antenna.
Fig. 4 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 4, the computer device 4 of this embodiment includes: a processor 41, a memory 42, and a computer program 43 stored in the memory 42 and capable of running on the processor 41, wherein the computer program 43 is executed by the processor 41 to implement the method applied to the measurement of the tilt angle of the base station antenna in the embodiment, and for avoiding repetition, details are not repeated herein. Alternatively, the computer program is executed by the processor 41 to implement the functions of the models/units applied to the base station antenna tilt angle measurement apparatus in the embodiments, which are not repeated herein to avoid repetition.
The computer device 4 includes, but is not limited to, a processor 41, a memory 42. Those skilled in the art will appreciate that fig. 4 is merely an example of a computing device 4 and is not intended to limit computing device 4 and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., computing device 4 may also include input output devices, network access devices, buses, etc.
The Processor 41 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 42 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. The memory 42 may also be an external storage device of the computer device 4, such as a plug-in hard disk provided on the computer device 4, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 42 may also include both internal storage units of the computer device 4 and external storage devices. The memory 42 is used for storing computer programs and other programs and data required by the computer device 4. The memory 42 may also be used to temporarily store data that has been output or is to be output.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for measuring the inclination angle of a base station antenna is characterized by comprising the following steps:
the method comprises the steps that an acquired base station aerial image is divided into a base station main body image and a base station background image through an image recognition algorithm, wherein the base station main body image comprises an antenna image;
performing three-dimensional modeling on the base station main body image to generate a three-dimensional point cloud model of the base station, wherein the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image;
selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points;
reducing the dimension of the antenna point cloud envelope, and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground;
calculating an antenna plane normal vector according to the maximum inclined plane perpendicular to the ground direction and the acquired point cloud space data;
and calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image according to the normal vector of the antenna plane, the acquired north plane normal vector and the acquired ground plane normal vector.
2. The method of claim 1, wherein the segmenting the base station aerial image into a base station subject image and a base station background image by an image recognition algorithm, the base station subject image comprising an antenna image, comprises:
performing frame selection on an image including a base station main body in the base station aerial image to generate initial base station main body data;
taking the initial base station main body data as a training set, and training through an image recognition algorithm to generate a recognition model of a base station main body;
and identifying the aerial image of the base station according to the identification model of the base station main body, and segmenting the aerial image into a base station main body image and a base station background image.
3. The method of claim 1, wherein selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station and forming an antenna point cloud envelope by expanding the antenna points comprises:
selecting any antenna point in the antenna point cloud in the three-dimensional point cloud model of the base station, and taking the antenna point as an initial expansion point of an antenna;
and based on a point cloud near point searching algorithm, taking the initial expansion point as a central point, and expanding outwards to form an antenna point cloud envelope.
4. The method of claim 3, wherein the point cloud near point search method, with the initial expansion point as a central point, expands outward to form an antenna point cloud envelope, comprising:
calculating the point cloud density of the antenna point cloud in the three-dimensional point cloud model of the base station;
setting a proximity search range according to the point cloud density based on a point cloud proximity point searching method, and acquiring a proximity point of the initial expansion point;
and taking a regular cube formed by enveloping the adjacent points of the initial expansion points as the antenna point cloud envelope.
5. The method of claim 4, further comprising, after the forming a regular cube of the envelope of the nearby points of the initial expansion point as an envelope of the antenna point cloud:
and acquiring point cloud space data of each antenna point cloud according to the antenna point cloud envelope.
6. The method of claim 1, wherein the three-dimensional point cloud model of the base station comprises a point cloud of the base station corresponding to the base station subject image;
after the three-dimensional modeling is performed on the base station main body image to generate a three-dimensional point cloud model of the base station, the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image, the method further comprises the following steps:
eliminating invalid points of base station point clouds in the three-dimensional point cloud model of the base station;
clustering the antenna points in the antenna point cloud to form a set of a plurality of antenna points;
and if the set of the antenna points is judged to be smaller than a preset threshold value, rejecting the set of the antenna points.
And rejecting the miscellaneous points in the base station point cloud through a down-sampling algorithm.
7. The method of claim 1, wherein before the segmenting the acquired aerial image of the base station into the image of the base station body including the antenna image and the background image of the base station by the image recognition algorithm, further comprising:
shooting a base station through an unmanned aerial vehicle to obtain an initial base station aerial image;
and screening the base station aerial image from the initial base station aerial image.
8. A base station antenna tilt angle measurement apparatus, the apparatus comprising:
the segmentation module is used for segmenting the acquired aerial image of the base station into a main image of the base station and a background image of the base station through an image recognition algorithm, wherein the main image of the base station comprises an antenna image;
the generating module is used for carrying out three-dimensional modeling on the base station main body image and generating a three-dimensional point cloud model of the base station, and the three-dimensional point cloud model of the base station comprises a plurality of antenna point clouds corresponding to the antenna image; selecting any antenna point in the antenna point cloud from the three-dimensional point cloud model of the base station, and forming an antenna point cloud envelope by expanding the antenna points;
the calculation module is used for reducing the dimension of the antenna point cloud envelope and calculating the maximum inclined plane of the antenna point cloud envelope in the direction vertical to the ground; calculating an antenna plane normal vector according to the maximum inclined plane perpendicular to the ground direction and the acquired point cloud space data; and calculating the numerical value of the downward inclination angle and the numerical value of the azimuth angle of the antenna corresponding to the antenna image according to the normal vector of the antenna plane, the acquired north plane normal vector and the acquired ground plane normal vector.
9. A storage medium, characterized in that the storage medium comprises a stored program, wherein when the program runs, the storage medium is controlled to execute the method for measuring the inclination angle of the antenna of the base station according to any one of claims 1 to 7.
10. A computer device comprising a memory for storing information including program instructions and a processor for controlling the execution of the program instructions, characterized in that the program instructions are loaded and executed by the processor to implement the steps of the method of measuring the tilt angle of a base station antenna according to any one of claims 1 to 7.
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| CN114531700A (en) * | 2022-02-18 | 2022-05-24 | 北京航空航天大学云南创新研究院 | Non-artificial base station antenna work parameter acquisition system and method |
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