CN113207170A - Position fusion correction method based on multi-source signaling - Google Patents
Position fusion correction method based on multi-source signaling Download PDFInfo
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Abstract
The invention provides a position fusion correction method based on multi-source signaling, which belongs to the technical field of positioning and comprises the following steps: step S10, obtaining multi-source signaling data of each base station cell, reading position points carried by each multi-source signaling data, preprocessing each position point and generating a sample set; step S20, creating a grid domain through positive axis cylindrical projection and grid division; step S30, mapping each position point in the sample set to a grid domain; s40, performing density clustering on the position points mapped into the grid domain to obtain a plurality of connected point clusters; and step S50, carrying out fusion correction on the point cluster with the maximum number of the position points to obtain a corrected position. The invention has the advantages that: the accuracy of base station cell location has greatly been promoted.
Description
Technical Field
The invention relates to the technical field of positioning, in particular to a position fusion correction method based on multi-source signaling.
Background
In the field of mobile communication, a mobile station has wide application in the aspects of resident life, urban planning, government construction and the like based on the positioning information of a base station cell.
The accuracy with which a mobile station can be positioned by a signaling source of a base station cell depends on the location of the base station cell and the size of the coverage area. However, there is a certain distance between the mobile station performing signal transmission with the base station cell and the cell site; the signal coverage areas of different base station cells under the same site are different, and a longer actual distance also exists between mobile stations which carry out signal transmission with different base station cells under the same site; in the management process of the operator base station cell, the problems of position error collection, manual error introduction and the like exist, and the problems of abnormal or missing longitude and latitude storage data of the position of a part of base station cell sites and the like exist, so that the positioning precision is not high, and the requirement of correcting the positioned position is generated.
For the position correction, there is conventionally the following method:
1. and checking the position of the station of the base station cell by checking the station by the manual work on site. However, the number of base station cell groups is huge, the workload of the method is heavy, large time cost and labor cost are required to be invested, the accuracy of the checking result depends on the experience summary of the checking personnel on the engineering parameters of the base station, and the stability is poor.
2. The method comprises the steps of correcting the position of a base station cell through the signaling switching times and the spatial position relation between the base station cell and an adjacent cell, selecting a related base station cell group which is most frequently switched with signals of the base station cell to be checked, correcting the position of the base station cell to be checked through setting a position weight parameter according to the switching times, and comparing the corrected position of the base station cell with the position to be checked to judge whether the position of the base station cell to be checked is abnormal or not. However, the method has many unsuitable scenes, has a poor identification effect on abnormal base station cells to be detected with unobvious distance distribution characteristics with surrounding base station groups, is greatly influenced by the distribution density of the base station cells, and has low identification efficiency on abnormal base station cells in suburban areas.
Therefore, how to provide a position fusion correction method based on multi-source signaling to improve the accuracy of base station cell positioning becomes an urgent problem to be solved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a position fusion correction method based on multi-source signaling, so as to improve the accuracy of base station cell positioning.
The invention is realized by the following steps: a position fusion correction method based on multi-source signaling is characterized in that: the method comprises the following steps:
step S10, obtaining multi-source signaling data of each base station cell, reading position points carried by each multi-source signaling data, preprocessing each position point and generating a sample set;
step S20, creating a grid domain through positive axis cylindrical projection and grid division;
step S30, mapping each position point in the sample set to a grid domain;
s40, performing density clustering on the position points mapped into the grid domain to obtain a plurality of connected point clusters;
and step S50, carrying out fusion correction on the point cluster with the maximum number of the position points to obtain a corrected position.
Further, the step S10 is specifically:
the method comprises the steps of obtaining multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data of each base station cell, reading position points carried by each multi-source signaling data, carrying out position check on each position point, eliminating each position point with the position deviation exceeding a preset distance, and then generating a sample set based on each reserved position point.
Further, the step S20 specifically includes:
step S21, projecting the longitude and latitude lines of the earth surface onto the cylindrical surface through positive axis cylindrical projection, and after the cylindrical surface is unfolded based on the bus, obtaining a rectangular coordinate system which is vertical to each other based on the longitude and latitude lines;
step S22, four coordinate base points and a grid step length are set, where the coordinate base points are (x)min,ymin)、(xmin,ymax)、(xmax,ymin)、(xmax,ymax)；
And step S23, dividing the rectangular coordinate system based on the coordinate base points and the grid step length to obtain a grid domain.
Further, in step S30, the mapping formula for mapping the position points to the grid domain is as follows:
wherein x represents the abscissa of the location point, y represents the ordinate of the location point, xminRepresents the lower limit of the abscissa, y, of the grid domainminRepresents the lower ordinate limit of the trellis domain, Eps represents the trellis step size, and G () represents the mapping function.
Further, the step S40 specifically includes:
step S41, setting a density threshold, traversing each grid of the grid domain, sequentially judging whether the density of each grid is greater than the density threshold based on the number of the position points, and if so, adding cluster marks to the grids; if not, adding a processed mark for the grid;
and step S42, communicating the adjacent grids marked by the clusters to obtain a plurality of communicated point clusters.
Further, the step S50 is specifically:
selecting the point cluster with the largest number of the position points, and performing arithmetic mean calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
Further, the step S50 is specifically:
selecting the point cluster with the largest number of the position points, and calculating the corresponding weight based on the number of the repetitions of the longitude and the latitude of each position point in the point cluster:
using the weight wnCarrying out weighted average calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
The invention has the advantages that:
1. the method comprises the steps of reading position points carried by multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, eliminating abnormal position points of the data to generate a sample set, mapping the position points in the sample set into a created grid domain, performing density clustering on the position points to obtain a plurality of communicated point clusters, and finally performing fusion correction on the point clusters with the largest number of the position points to obtain a corrected position.
2. By fusing multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, the source of the position point is diversified, and errors caused by special samples are reduced.
3. The longitude and latitude on the earth surface are projected onto the cylindrical surface through the positive axis cylindrical projection, the cylindrical surface is unfolded based on a bus, a rectangular coordinate system which is perpendicular to each other is obtained based on the longitude and latitude, the rectangular coordinate system is divided based on a coordinate base point and a grid step length to obtain a grid domain, and then the position points are mapped into the grid domain.
4. The density clustering is carried out on the position points mapped into the grid domain to obtain a plurality of communicated point clusters, the point clusters in any shape can be found, the identification precision of the point clusters in irregular shapes is higher, and the positioning precision of the base station cell is further improved.
5. The correction position is calculated by fusing multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, time synchronization and related equipment resources are not needed, and the cost of base station cell positioning is reduced.
Drawings
The invention will be further described with reference to the following examples with reference to the accompanying drawings.
FIG. 1 is a flow chart of a position fusion correction method based on multi-source signaling according to the present invention.
FIG. 2 is a schematic diagram of the grid domain creation process of the present invention.
Fig. 3 is a schematic diagram of a trellis domain of the present invention.
FIG. 4 is a schematic illustration of the location point mapping of the present invention.
Detailed Description
The technical scheme in the embodiment of the application has the following general idea: the method comprises the steps of generating a sample set after position points with abnormal data are removed by fusing position points carried by multi-source signaling data, mapping the position points in the sample set into a created grid domain, carrying out density clustering on the position points to obtain a plurality of communicated point clusters, and finally carrying out arithmetic average solving and correcting position or weighted average solving and correcting position on the point clusters with the largest number of the position points so as to improve the accuracy of base station cell positioning.
Referring to fig. 1 to 4, a preferred embodiment of a location fusion correction method based on multi-source signaling according to the present invention includes the following steps:
step S10, obtaining multi-source signaling data of each base station cell, reading position points carried by each multi-source signaling data, preprocessing each position point and generating a sample set; removing the position points which deviate seriously;
step S20, creating a grid domain through positive axis cylindrical projection and grid division;
step S30, mapping each position point in the sample set to a grid domain based on the spatial position relation between the position point and the grid in the grid domain;
s40, performing density clustering on the position points mapped into the grid domain by using a CLIQUE clustering algorithm to obtain a plurality of connected point clusters;
and step S50, carrying out fusion correction on the point cluster with the maximum number of the position points to obtain a corrected position. For example, three point clusters are obtained, wherein the first point cluster comprises 100 position points, the second point cluster comprises 200 position points, and the third point cluster comprises 300 position points, and then the third point cluster is selected for fusion correction.
The step S10 specifically includes:
the method comprises the steps of obtaining multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data of each base station cell, reading position points carried by each multi-source signaling data, carrying out position check on each position point, eliminating each position point with the position deviation exceeding a preset distance, and then generating a sample set based on each reserved position point. The MRO data refers to data generated in the handshaking process of the user terminal and the base station; the OTT data refers to longitude and latitude coordinate information generated by a user terminal due to position request or position sending in the APP using process; the MDT data refers to a minimization of drive test technology, and related parameters required by network optimization are acquired through a measurement report reported by a mobile phone; the palm hall data refers to position data generated when the user terminal uses the palm business hall.
The step S20 specifically includes:
step S21, projecting the longitude and latitude lines of the earth surface onto the cylindrical surface through positive axis cylindrical projection, and after the cylindrical surface is unfolded based on the bus, obtaining a rectangular coordinate system which is vertical to each other based on the longitude and latitude lines;
step S22, four coordinate base points and a grid step length are set, where the coordinate base points are (x)min,ymin)、(xmin,ymax)、(xmax,ymin)、(xmax,ymax)；
And step S23, dividing the rectangular coordinate system based on the coordinate base points and the grid step length to obtain a grid domain.
In step S30, the mapping formula for mapping the position points to the grid domain is:
wherein x represents the abscissa of the location point, y represents the ordinate of the location point, xminRepresents the lower limit of the abscissa, y, of the grid domainminRepresents the lower ordinate limit of the trellis domain, Eps represents the trellis step size, and G () represents the mapping function.
The step S40 specifically includes:
step S41, setting a density threshold, traversing each grid of the grid domain, sequentially judging whether the density of each grid is greater than the density threshold based on the number of the position points, and if so, adding cluster marks to the grids; if not, adding a processed mark for the grid;
and step S42, communicating the adjacent grids marked by the clusters to obtain a plurality of communicated point clusters. I.e. only for meshes having a density greater than the density threshold.
The step S50 specifically includes:
selecting the point cluster with the largest number of the position points, and performing arithmetic mean calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
The step S50 specifically includes:
selecting the point cluster with the largest number of the position points, and calculating the corresponding weight based on the number of the repetitions of the longitude and the latitude of each position point in the point cluster:
using the weight wnCarrying out weighted average calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
In summary, the invention has the advantages that:
1. the method comprises the steps of reading position points carried by multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, eliminating abnormal position points of the data to generate a sample set, mapping the position points in the sample set into a created grid domain, performing density clustering on the position points to obtain a plurality of communicated point clusters, and finally performing fusion correction on the point clusters with the largest number of the position points to obtain a corrected position.
2. By fusing multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, the source of the position point is diversified, and errors caused by special samples are reduced.
3. The longitude and latitude on the earth surface are projected onto the cylindrical surface through the positive axis cylindrical projection, the cylindrical surface is unfolded based on a bus, a rectangular coordinate system which is perpendicular to each other is obtained based on the longitude and latitude, the rectangular coordinate system is divided based on a coordinate base point and a grid step length to obtain a grid domain, and then the position points are mapped into the grid domain.
4. The density clustering is carried out on the position points mapped into the grid domain to obtain a plurality of communicated point clusters, the point clusters in any shape can be found, the identification precision of the point clusters in irregular shapes is higher, and the positioning precision of the base station cell is further improved.
5. The correction position is calculated by fusing multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data, time synchronization and related equipment resources are not needed, and the cost of base station cell positioning is reduced.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.
Claims (7)
1. A position fusion correction method based on multi-source signaling is characterized in that: the method comprises the following steps:
step S10, obtaining multi-source signaling data of each base station cell, reading position points carried by each multi-source signaling data, preprocessing each position point and generating a sample set;
step S20, creating a grid domain through positive axis cylindrical projection and grid division;
step S30, mapping each position point in the sample set to a grid domain;
s40, performing density clustering on the position points mapped into the grid domain to obtain a plurality of connected point clusters;
and step S50, carrying out fusion correction on the point cluster with the maximum number of the position points to obtain a corrected position.
2. The multi-source signaling-based location fusion correction method of claim 1, wherein: the step S10 specifically includes:
the method comprises the steps of obtaining multi-source signaling data at least comprising MRO data, MDT data, OTT data and palm hall data of each base station cell, reading position points carried by each multi-source signaling data, carrying out position check on each position point, eliminating each position point with the position deviation exceeding a preset distance, and then generating a sample set based on each reserved position point.
3. The multi-source signaling-based location fusion correction method of claim 1, wherein: the step S20 specifically includes:
step S21, projecting the longitude and latitude lines of the earth surface onto the cylindrical surface through positive axis cylindrical projection, and after the cylindrical surface is unfolded based on the bus, obtaining a rectangular coordinate system which is vertical to each other based on the longitude and latitude lines;
step S22, four coordinate base points and a grid step length are set, where the coordinate base points are (x)min,ymin)、(xmin,ymax)、(xmax,ymin)、(xmax,ymax)；
And step S23, dividing the rectangular coordinate system based on the coordinate base points and the grid step length to obtain a grid domain.
4. The multi-source signaling-based location fusion correction method of claim 1, wherein: in step S30, the mapping formula for mapping the position points to the grid domain is:
wherein x represents the abscissa of the location point, y represents the ordinate of the location point, xminRepresents the lower limit of the abscissa, y, of the grid domainminRepresents the lower ordinate limit of the trellis domain, Eps represents the trellis step size, and G () represents the mapping function.
5. The multi-source signaling-based location fusion correction method of claim 1, wherein: the step S40 specifically includes:
step S41, setting a density threshold, traversing each grid of the grid domain, sequentially judging whether the density of each grid is greater than the density threshold based on the number of the position points, and if so, adding cluster marks to the grids; if not, adding a processed mark for the grid;
and step S42, communicating the adjacent grids marked by the clusters to obtain a plurality of communicated point clusters.
6. The multi-source signaling-based location fusion correction method of claim 1, wherein: the step S50 specifically includes:
selecting the point cluster with the largest number of the position points, and performing arithmetic mean calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
7. The multi-source signaling-based location fusion correction method of claim 1, wherein: the step S50 specifically includes:
selecting the point cluster with the largest number of the position points, and calculating the corresponding weight based on the number of the repetitions of the longitude and the latitude of each position point in the point cluster:
using the weight wnCarrying out weighted average calculation on the longitude and latitude of each position point contained in the point cluster to obtain a corrected position:
wherein xnAn abscissa representing a position point; y isnRepresents the ordinate of the position point; n represents the number of the position point and is a positive integer.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079113A (en) * | 2022-08-22 | 2022-09-20 | 国家海洋技术中心 | Ground wave radar directional diagram measuring method and system based on unmanned ship |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100178932A1 (en) * | 2008-11-25 | 2010-07-15 | Andreas Hansson | Device and Method for AGPS High Accuracy Positioning in Unknown Cell Areas |
| US20120077487A1 (en) * | 2009-06-01 | 2012-03-29 | Zte Corporation | Method, Location Service Apparatus And System For Acquiring A Cell Position And Locating A Cell |
| CN105992239A (en) * | 2015-02-04 | 2016-10-05 | 中国移动通信集团辽宁有限公司 | Method, apparatus and equipment of real-time location of pseudo base station |
| CN106547894A (en) * | 2016-11-03 | 2017-03-29 | 浙江夏农信息技术有限公司 | The system and method that location tags are lived in duty is excavated based on mobile communication signaling big data |
| CN108133001A (en) * | 2017-12-21 | 2018-06-08 | 重庆玖舆博泓科技有限公司 | MR indoor and outdoors separation method, device and medium |
| CN108417023A (en) * | 2018-05-02 | 2018-08-17 | 长安大学 | Traffic zone central point choosing method based on taxi on-board and off-board space of points cluster |
| CN108574934A (en) * | 2017-03-10 | 2018-09-25 | 中国移动通信集团福建有限公司 | A kind of pseudo-base station localization method and device |
| CN109302714A (en) * | 2018-12-07 | 2019-02-01 | 南京华苏科技有限公司 | Realize that base station location is studied and judged and area covered knows method for distinguishing based on user data |
| CN110650531A (en) * | 2019-09-24 | 2020-01-03 | 上海连尚网络科技有限公司 | Base station coordinate calibration method, system, storage medium and equipment |
| CN111277947A (en) * | 2018-12-04 | 2020-06-12 | 中兴通讯股份有限公司 | Method, device, server, base station and storage medium for predicting longitude and latitude of cell |
-
2021
- 2021-03-26 CN CN202110324652.0A patent/CN113207170B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100178932A1 (en) * | 2008-11-25 | 2010-07-15 | Andreas Hansson | Device and Method for AGPS High Accuracy Positioning in Unknown Cell Areas |
| US20120077487A1 (en) * | 2009-06-01 | 2012-03-29 | Zte Corporation | Method, Location Service Apparatus And System For Acquiring A Cell Position And Locating A Cell |
| CN105992239A (en) * | 2015-02-04 | 2016-10-05 | 中国移动通信集团辽宁有限公司 | Method, apparatus and equipment of real-time location of pseudo base station |
| CN106547894A (en) * | 2016-11-03 | 2017-03-29 | 浙江夏农信息技术有限公司 | The system and method that location tags are lived in duty is excavated based on mobile communication signaling big data |
| CN108574934A (en) * | 2017-03-10 | 2018-09-25 | 中国移动通信集团福建有限公司 | A kind of pseudo-base station localization method and device |
| CN108133001A (en) * | 2017-12-21 | 2018-06-08 | 重庆玖舆博泓科技有限公司 | MR indoor and outdoors separation method, device and medium |
| CN108417023A (en) * | 2018-05-02 | 2018-08-17 | 长安大学 | Traffic zone central point choosing method based on taxi on-board and off-board space of points cluster |
| CN111277947A (en) * | 2018-12-04 | 2020-06-12 | 中兴通讯股份有限公司 | Method, device, server, base station and storage medium for predicting longitude and latitude of cell |
| CN109302714A (en) * | 2018-12-07 | 2019-02-01 | 南京华苏科技有限公司 | Realize that base station location is studied and judged and area covered knows method for distinguishing based on user data |
| CN110650531A (en) * | 2019-09-24 | 2020-01-03 | 上海连尚网络科技有限公司 | Base station coordinate calibration method, system, storage medium and equipment |
Non-Patent Citations (2)
| Title |
|---|
| 罗伟华: ""基于MR大数据的基站小区定位方案"", 《移动通信》 * |
| 赵燕东等: ""基于北斗卫星导航系统的林区智能巡检测绘系统研究"", 《农业机械学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079113A (en) * | 2022-08-22 | 2022-09-20 | 国家海洋技术中心 | Ground wave radar directional diagram measuring method and system based on unmanned ship |
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