CN111901750B

CN111901750B - Positioning method, positioning device, electronic equipment and storage medium

Info

Publication number: CN111901750B
Application number: CN202010951340.8A
Authority: CN
Inventors: 孙宏; 兰婷; 王栩然; 王瑜
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2020-09-11
Filing date: 2020-09-11
Publication date: 2022-06-17
Anticipated expiration: 2040-09-11
Also published as: CN111901750A

Abstract

The application provides a positioning method, a positioning device, an electronic device and a storage medium, wherein a preset correction model is utilized to determine correction work parameter data according to acquired MDT data and cell work parameter data within a preset time, then resident position information of a user terminal is determined according to the correction work parameter data, the MDT data and XDR data, and finally positioning information of the user terminal is determined according to the resident position information and acquired real-time MR data of the user terminal by utilizing a mode matching algorithm. The technical problem that the judgment accuracy of the indoor resident position of the user is not high due to the fact that the positioning information of the MR data and the position of the base station in the cell parameter data are inaccurate in the prior art is solved, and the technical effect that the cell parameter data are corrected by utilizing the MDT data so as to establish the accurate positioning fingerprint information of the user to achieve the high-accuracy positioning of the indoor and outdoor positions of the user is achieved.

Description

Positioning method, positioning device, electronic equipment and storage medium

Technical Field

The present application relates to the field of mobile communications, and in particular, to a positioning method, an apparatus, an electronic device, and a storage medium.

Background

At present, the mobile communication technology has been widely applied, and with the gradual maturity of internet big data analysis, big data behavior analysis is performed on users, so that intelligent and information-based services become a direction of the current internet technology development.

The big data analysis is carried out on the user, intelligent and information-based services are realized, and the omnibearing behavior data acquisition and analysis can be naturally and rarely carried out on the user. However, in the prior art, user behavior positioning analysis is performed based on mobile communication interaction data of a user, so that the problem of inaccurate positioning exists, and particularly, for whether the user is located indoors or outdoors, due to reasons such as signal drift and discontinuity of data sent by a mobile phone terminal in the prior art, the problem that the indoor and outdoor positioning of the user is difficult to accurately judge is caused.

Therefore, the prior art has the technical problem that whether the user is located indoors or outdoors cannot be accurately positioned.

Disclosure of Invention

The application provides a positioning method, a positioning device, electronic equipment and a storage medium, which are used for solving the technical problem that a user cannot be accurately positioned indoors or outdoors in the prior art.

In a first aspect, the present application provides a positioning method, including:

determining correction working parameter data according to acquired MDT data and cell working parameter data within a preset time length by using a preset correction model, wherein the cell working parameter data comprise communication data of a cell corresponding to a covered traffic area;

determining resident position information of the user terminal according to the corrected parameter data, the MDT data and the external data report XDR data;

and determining the positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time measurement report MR data of the user terminal by using a pattern matching algorithm.

In a possible design, the determining, by using a preset modification model, modified working parameter data according to the acquired MDT data within a preset duration and the cell working parameter data includes:

acquiring MR data reported by the user terminal within a preset time length, wherein the MR data comprises MDT data, each MR data corresponds to a sampling point, and the MDT data comprises position information of the sampling point;

according to the position information, performing geographic rasterization grouping on the MR data to determine a sampling grid, wherein the sampling grid comprises at least one sampling point;

and adjusting data related to the position of a base station in the cell parameter data according to the sampling grid to determine the corrected parameter data.

In one possible design, the adjusting data related to a base station location in the cell parameter data according to the sampling grid to determine the modified parameter data includes:

adding an intra-domain identifier to the sampling points in the sampling grid according to the position of the base station, wherein the intra-domain identifier is used for indicating whether the sampling points are in a preset region corresponding to the position of the base station;

determining a first conformity between the sampling point and a base station according to the intra-domain identifier;

determining a corrected position of the base station according to the first conformity and the sampling grid;

and determining the corrected parameter data according to the corrected position.

Optionally, the determining, according to the intra-domain identifier, a first conformity between the sampling point and a base station includes:

and determining the proportion of the number of the sampling points in the preset area to the total number of the sampling points according to the intra-domain identifier, wherein the first conformity is the proportion.

In one possible design, the determining the revised position of the base station based on the first conformity and the sampling grid includes:

if the conformity is lower than a first threshold value and the number of sampling points of the sampling grid is lower than a preset number, determining the base station as a station to be evaluated;

determining an initial correction position according to the station to be evaluated and a TA (time advance) value corresponding to the sampling grid by using a preset central position algorithm;

and determining the correction position by using an adjustment algorithm in a preset adjustment area by taking the initial correction position as a center.

In a possible design, the determining an initial correction position according to the TA value corresponding to the site to be evaluated and the sampling grid by using a preset center position algorithm includes:

selecting a first sampling point, corresponding to the site to be evaluated, of which the TA value is smaller than a first preset TA threshold value from the sampling grid;

and determining the geometric centers of all the first sampling points according to the position information of the first sampling points by using a geometric center algorithm, wherein the initial correction position is the geometric center.

In one possible design, the determining the corrected position by using an adjustment algorithm in a preset adjustment region with the initial corrected position as the center includes:

randomly selecting one of the position points in the preset adjusting area, and calculating second conformity between all the sampling points in the sampling grid and the position points, wherein the second conformity is used for expressing the proportion of the sampling points in the preset area corresponding to the position points to the total number of the sampling points;

if the second conformity degree is greater than or equal to a preset conformity degree threshold value, determining the position point as a position point to be selected;

selecting the position point with the largest second coincidence value from all the position points to be selected as the corrected position;

and if the position points with the second conformity greater than the preset conformity threshold value do not exist in all the position points, selecting a second sampling point with the TA value smaller than a second preset TA threshold value corresponding to the station to be evaluated from the sampling grid again so as to determine the corrected position again.

In a possible design, the preset area includes a preset first sub-area and a preset second sub-area, the first sub-area corresponds to a first TA value, the second sub-area corresponds to a second TA value, correspondingly, the area identifier includes a first sub-area identifier, a second sub-area identifier and a non-corresponding identifier, if the TA value and the position of the sampling point both correspond to the first sub-area or the second sub-area, the first sub-area identifier or the second sub-area identifier is added to the sampling point, otherwise, the non-corresponding identifier is added to the sampling point, according to the in-area identifier, the first conformity of the sampling point and the base station is determined, including:

and determining the first conformity according to the first sub-domain identifier, the second sub-domain identifier, the non-corresponding identifier and the corresponding weight.

In a second aspect, the present application provides a positioning device comprising:

the acquisition module is used for acquiring MDT data, cell parameter data, external data report XDR data and real-time measurement report MR data in a preset time length;

the preprocessing module is used for determining correction working parameter data according to acquired MDT data and cell working parameter data within preset time by using a preset correction model, wherein the cell working parameter data comprise communication data of a cell corresponding to a covered traffic area;

the preprocessing module is further configured to determine resident location information of the user terminal according to the corrected parameter data, the MDT data, and the external data report XDR data;

and the positioning module is used for determining the positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time measurement report MR data of the user terminal by using a pattern matching algorithm.

In a possible design, the preprocessing module is configured to determine, by using a preset modification model, modified power management parameter data according to the acquired MDT data of the minimization of drive test and the cell power management parameter data within a preset time duration, and includes:

the acquisition module is used for acquiring MR data reported by the user terminal within a preset time length, wherein the MR data comprise MDT data, each MR data corresponds to a sampling point, and the MDT data comprise position information of the sampling point;

the preprocessing module is used for performing geographic rasterization grouping on the MR data according to the position information to determine a sampling grid, and the sampling grid comprises at least one sampling point;

the preprocessing module is further configured to adjust data related to a base station location in the cell parameter data according to the sampling grid, so as to determine the corrected parameter data.

In one possible design, the preprocessing module is further configured to adjust data related to a base station location in the cell parameter data according to the sampling grid to determine the modified parameter data, and includes:

the preprocessing module is further configured to add an intra-domain identifier to the sampling point in the sampling grid according to the base station position, where the intra-domain identifier is used to indicate whether the sampling point is in a preset region corresponding to the base station position;

the preprocessing module is further configured to determine a first conformity between the sampling point and a base station according to the intra-domain identifier;

the preprocessing module is further configured to determine a corrected position of the base station according to the first conformity and the sampling grid; and determining the corrected parameter data according to the corrected position.

Optionally, the preprocessing module is further configured to determine a first coincidence degree of the sampling point with a base station according to the intra-domain identifier, and includes:

the preprocessing module is further configured to determine, according to the intra-domain identifier, a ratio of the number of the sampling points to a total number of sampling points in the preset region, where the first conformity is the ratio.

In one possible design, the preprocessing module is further configured to determine a revised position of the base station according to the first conformity and the sampling grid, and includes:

the preprocessing module is further configured to determine that the base station is a station to be evaluated if the first conformity is lower than a first threshold value and the number of sampling points of the sampling grid is lower than a preset number;

the preprocessing module is further configured to determine an initial correction position according to the site to be evaluated and a Time Advance (TA) value corresponding to the sampling grid by using a preset central position algorithm;

the preprocessing module is further configured to determine the correction position by using an adjustment algorithm in a preset adjustment region with the initial correction position as a center.

In a possible design, the preprocessing module is further configured to determine an initial correction position according to the station to be evaluated and a time advance TA value corresponding to the sampling grid by using a preset center position algorithm, and includes:

the preprocessing module is further configured to select a first sampling point, corresponding to the site to be evaluated, of which the TA value is smaller than a first preset TA threshold from the sampling grid;

the preprocessing module is further configured to determine geometric centers of all the first sampling points according to the position information of the first sampling points by using a geometric center algorithm, where the initial correction position is the geometric center.

In one possible design, the preprocessing module is further configured to determine the corrected position by using an adjustment algorithm in a preset adjustment region with the initial corrected position as a center, and includes:

the preprocessing module is further configured to randomly select one of the position points in the preset adjustment region, and calculate a second conformity between all the sampling points in the sampling grid and the position points, where the second conformity is used to indicate a proportion of the sampling points included in the preset region corresponding to the position points to a total number of the sampling points;

the preprocessing module is further configured to determine that the location point is a candidate location point if the second conformity is greater than or equal to a preset conformity threshold;

the preprocessing module is further configured to select, from all the position points to be selected, a position point with the largest second coincidence value as the corrected position;

the preprocessing module is further configured to reselect a second sampling point, corresponding to the to-be-evaluated site, from the sampling grid, where the TA value is smaller than a second preset TA threshold, if there is no location point in all the location points where the second conformity is greater than the preset conformity threshold, so as to re-determine the corrected location.

In a possible design, the preset region includes a preset first sub-region and a preset second sub-region, the first sub-region corresponds to a first TA value, the second sub-region corresponds to a second TA value, and correspondingly, the region identifier includes a first sub-region identifier, a second sub-region identifier, and a non-corresponding identifier, and correspondingly, the preprocessing module is further configured to add the first sub-region identifier or the second sub-region identifier to the sampling point if the TA value and the position of the sampling point both correspond to the first sub-region or the second sub-region, and otherwise add the non-corresponding identifier to the sampling point;

the preprocessing module is further configured to determine a first conformity between the sampling point and a base station according to the intra-domain identifier, and includes:

the preprocessing module is further configured to determine the first compliance according to the first sub-domain identifier, the second sub-domain identifier, the non-corresponding identifier, and the corresponding weight.

In a third aspect, the present application provides an electronic device comprising:

a memory for storing program instructions;

and the processor is used for calling and executing the program instructions in the memory to execute any one of the possible positioning methods provided by the first aspect.

In a fourth aspect, the present application provides a storage medium, in which a computer program is stored, the computer program being configured to execute any one of the possible positioning methods provided in the first aspect.

Drawings

In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, 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 schematic view of an application scenario of a positioning method provided in the present application;

fig. 2 is a schematic flow chart of a positioning method provided in the present application;

fig. 3a to 3d are schematic diagrams illustrating a base station location correction principle provided in the embodiment of the present application;

fig. 4 is a schematic flowchart of another positioning method according to an embodiment of the present application;

fig. 5a to 5d are schematic diagrams illustrating another base station location correction principle provided in the embodiment of the present application;

FIG. 6 is a schematic structural diagram of a positioning device provided herein;

fig. 7 is a schematic structural diagram of an electronic device provided in the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, including but not limited to combinations of embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any inventive step are within the scope of the present application.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings (if any) are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The following explains and describes terms related to embodiments of the present application.

MR (Measurement Report) data: meaning that the information is sent once every 480ms on the traffic channel (470 ms on the signaling channel). The MR measurement report is completed by an MS (Mobile Station) and a BTS (Base Transceiver Station), the MS executes and reports the downlink level intensity, quality and TA (Time Advanced) of a GSM (Global System for Mobile Communications) cell, and the BTS executes and reports the measurement of the reception level intensity and quality of the uplink MS. The processing of the measurement report is usually completed in a BSC (Base Station Controller) (when a BTS preprocessing mode is adopted, the measurement report processing can be completed by moving to the BTS), and basic functions such as filtering and interpolation are provided, so as to provide basic input for a subsequent handover decision algorithm, which is the basis of the handover decision algorithm, the power control algorithm, and the like.

MDT (Minimization Drive Test) data, whose basic principle is based on an automatic reported measurement Report of a commercial terminal, requires supporting support of a terminal of version R10, and the terminal needs to have the capability of wireless environment measurement (such as RSRP (Reference Signal Receiving Power), RSRQ (Reference Signal Receiving Quality), PHR (Power Headroom Report)), typical event measurement, and location information measurement. The MDT data provides possibility for an operator to collect a dynamic fluctuation process of a wireless network through a commercial terminal, provides a comprehensive reference view for network optimization, analysis and diagnosis processes, and can partially replace manual drive tests. The information required by MDT provided by the report of the terminal LOG LOG comprises the following steps: positioning information, idle state information, information of not being in a service area, a serving cell signal lower threshold report, a terminal transmission power margin lower threshold report, an access failure report, a paging channel failure report, a broadcast channel failure report, and a radio link failure report.

The TA (Time Advanced) value is the difference between the actual Time when the mobile station signal arrives at the base station and the Time when the mobile station signal arrives at the base station assuming that the distance between the mobile station and the base station is 0. In the GSM system, during communication, if the mobile station moves away from the base station during a call, messages from the base station will arrive at the mobile station with increasing delay. At the same time, the mobile station's reply message will arrive at the base station with increasing delay, which can lead to a situation: the message sent by the mobile station in the time slot received by the base station is overlapped with another call message received by the base station in the next time slot to cause interference, so that a Time Adjustment (TA) measure is introduced. The time delay situation of the information can be judged through the TA value.

At present, based on a big data full network analysis platform, the transformation of future big data operation is realized by paying attention to the combination of services and wireless through hundreds of millions of user behavior information, and multi-dimensional, massive and efficient data processing and integration are realized on the basis of integrated analysis thinking through 'big data' and 'accurate positioning', so that the transformation is used for transferring accurate services and pushing preferential information, and the transformation becomes an important development trend of new internet economy. In order to realize big data analysis, the judgment and identification of the behavior information of the user become very critical basic data. Especially, the positioning identification problem of whether the user is located indoors or outdoors is more critical.

However, in the prior art, the position of the user is generally determined by using the MR data only, and the amount of the non-traffic data of the MR data is too low, which results in that the collected sampling points cannot support the increasing high-precision positioning requirement for the position of the user. The signal drift or the user moving around the building or staying in the building can cause misjudgment.

Fig. 1 is a schematic view of an application scenario of the positioning method provided in the present application. As shown in fig. 1, a road map of a certain area is geographically rasterized to obtain a geographic sampling grid with a certain grid size, for example, the side length is 5km, a plurality of base stations 111 are distributed on the map, each base station corresponds to a plurality of communication cells, generally, one base station corresponds to at least 3 communication cells, and basic data of all the communication cells in the map form cell engineering parameter data. It should be noted that in the present application, in order to extract data of a user terminal moving at a high speed, for example, when the user is on a high-speed rail, a subway or a car driving on an expressway, the user may have a long time of idle time to browse information, which requires that a covered cell of a traffic area corresponding to the expressway 12 (including a subway, an expressway, and a high-speed rail line) shown in fig. 1 is extracted and marked, and added to cell engineering parameter data. In addition, the road information can be used for eliminating the drifting data sampling points in the subsequent positioning process so as to more accurately position the position of the user terminal.

Fig. 2 is a schematic flow chart of a positioning method provided in the present application. As shown in fig. 2, the positioning method provided in the embodiment of the present application includes the specific steps of:

s201, determining corrected working parameter data according to the acquired MDT data and the cell working parameter data within the preset time length by using a preset correction model.

In this step, the cell parameter data includes communication data of a cell corresponding to the covered traffic area, and the correction parameter data is cell data obtained by correcting the position of the base station in the cell parameter data.

Specifically, firstly, MR data reported by the user terminal within a preset time length is obtained, the MR data includes MDT data, each MR data corresponds to a sampling point, and the MDT data includes position information of the sampling point. If the user terminal equipment is connected with the WIFI when the user is indoors, the user terminal cannot send MR data to the operator server at the moment, which is one of the reasons that the data quantity of the non-communication service information contained in the MR data is too small, so that data loss of indoor position positioning is caused, the MDT data can be contained in the MR data and sent to the operator server through the user terminal, and even when the user is connected with the WIFI indoors, the operator server can still receive the data. Therefore, the positioning information of the MR data is effectively supplemented by the MDT data, so that the basic data quantity of the historical behavior information acquisition of the user is improved, and the indoor or outdoor positioning judgment result of the user is obtained more carefully and accurately.

Secondly, according to the position information, geographic rasterization grouping is carried out on the MR data to determine a sampling grid, and the sampling grid comprises at least one sampling point. As shown in fig. 1, after the map is rasterized, the MR data sampling points reported by the user terminal fall into sampling grids 11 that are geographically rasterized one by one, each sampling grid 11 is numbered, and then the number of the sampling grid to which the MR data corresponding to each sampling point belongs is added to the MR data corresponding to each sampling point, so that the MR data of each sampling point can be geographically rasterized and grouped.

And then, adjusting data related to the position of the base station in the cell parameter data according to the sampling grid to determine the corrected parameter data. The sampling grid comprises a plurality of sampling points, MDT data corresponding to the sampling points can be compared with standard communication data determined by the geographical position of the base station in the cell engineering parameter data to obtain a difference value between the standard communication data and the MDT data of the sampling points, and then the longitude and latitude of the base station in the cell engineering parameter data, namely the position of the base station, can be corrected by using a correction algorithm according to the difference value.

firstly, adding an intra-domain identifier to the sampling point in the sampling grid according to the position of the base station, wherein the intra-domain identifier is used for indicating whether the sampling point is in a preset region corresponding to the position of the base station.

For ease of understanding, the following description is made in conjunction with fig. 3.

Fig. 3a to 3d are schematic diagrams illustrating a base station location correction principle provided in the embodiment of the present application. As shown in fig. 3a, fig. 3a is a schematic diagram of a certain sampling grid 11 in fig. 1 after being amplified, and a theoretical area coverage 31 corresponding to a communication signal parameter is obtained according to the communication signal parameter, such as a TA value, a signal strength, or a signal quality value, in cell parameter data, with a base station position 311 in the cell parameter data as a center. It is understood that the theoretical area coverage 31 is not limited to the circular area in fig. 3a, and in a specific application scenario, the shape of the obtained theoretical area coverage 31 may also vary according to the selection of the communication signal parameters, and may be any shape, and may even be an area formed by combining several discontinuous areas, and the application does not limit the specific shape of the theoretical area coverage 31. The sampling points 32 represent MDT data or MR data uploaded by a certain user terminal at a certain time.

As shown in fig. 3b, the sampling points 32 can be divided into sampling points 321 within the theoretical coverage area 31, and different intra-domain identifiers can be added to the sampling points 321 and the sampling points 322 from the sampling points 322 outside the theoretical coverage area 31, for example, 1 and 0 are used to identify the sampling points 321 and the sampling points 322 inside and outside the theoretical coverage area 31.

Secondly, according to the intra-domain identifier, determining a first conformity between the sampling point and a base station.

In this step, the first conformity is used to evaluate the matching degree between the communication data of the sampling point and the theoretical value of the base station, and it can be evaluated whether the position data of the base station needs to be corrected or not through the first conformity.

In a possible design, a ratio of the number of sampling points to a total number of sampling points in the preset area is determined according to the intra-domain identifier, and the first conformity is the ratio.

Specifically, the first conformity may be defined as a ratio of all sampling points in the domain identified as "1", i.e., in the theoretical coverage area 31.

In another possible design, the sampling points marked as "0" in the domain may be eliminated, and then the first conformity is determined according to the communication data of the sampling points marked as "1" in the domain and the standard communication data of the base station according to a preset algorithm. If the difference between the distance between the position of the sampling point with the TA value of 2-8 and the position of the base station and the preset distance is used as the first conformity after normalization processing.

And then, determining the corrected position of the base station according to the first conformity and the sampling grid.

Specifically, in one possible design, the method includes:

determining an initial correction position according to the site to be evaluated and the TA value of the time advance corresponding to the sampling grid by using a preset central position algorithm;

For ease of understanding, the following description is made in conjunction with fig. 3 c.

And when the conformity of the sampling point corresponding to a certain base station is lower than a first threshold value, such as 60%, determining the base station as the station to be evaluated. Then, as shown in fig. 3c, sampling points with TA values less than or equal to 5 are taken, and the geometric center position of each sampling point, i.e., the initial corrected position 312, is calculated by using a preset center position algorithm.

And finally, determining the corrected parameter data according to the corrected position.

As shown in fig. 3d, after the initial corrected position is obtained, the matching degrees of all the sampling points are compared with the preset coverage range corresponding to the initial corrected position, and if the matching degree is lower than the preset threshold, for example, 80%, the initial corrected position 312 is adjusted in the preset adjustment region 33 corresponding to the initial corrected position, for example, within the range of radius R in fig. 3d, so that the matching degrees of all the sampling points reach the preset threshold, and the corrected position 323 is obtained. As shown in fig. 3d, the sampling point 321 is a sampling point located within the adjusted theoretical coverage range 32, and the sampling point 322 is located outside the theoretical coverage range 32, and the modified position 323 makes more sampling points fall within the theoretical coverage range 32. It should be noted that the theoretical coverage is not limited to the circular range with the circle center 323 in fig. 3d, and those skilled in the art can change the specific shape of the theoretical coverage according to actual needs.

S202, determining resident position information of the user terminal according to the corrected working parameter data, the MDT data and the XDR data.

In this step, it specifically includes:

converging the XDR data in the preset time length according to the preset converging time length to determine XDR converging data;

determining a cell coverage table and MDT fingerprint data according to the MDT data and the converged XDR data;

performing fingerprint database positioning analysis according to the MR data within the preset time length corresponding to the MDT data and the MDT fingerprint data, and determining a positioning result of the MR data;

determining a seed user table according to the positioning result, the XDR convergence data and the correction tool parameter data;

determining user fingerprint data according to the seed user table and the XDR convergence data;

and determining the resident position information according to the user fingerprint data by utilizing an analysis model.

Specifically, for example: firstly, calculating the duration and the times of residence of each user in each service cell within one hour, calculating the moving speed of the user, and judging whether the user is a high-speed moving user or not according to the position of the work parameters and whether the cell in the work parameters is a high-speed rail subway cell or not; secondly, performing day-level convergence on the residence time of each user in the main service cell according to the day and night, and screening the first ten cells with the longest residence time of each user in the day and the night, wherein the residence time of each user in the day and the night is 10-17 points in the day and 22-5 points in the night; and then, carrying out weekly aggregation on the resident time of each user in the main service cell according to the day and night, screening out data of which each user resides in the same main service cell for more than three days in one week and the resident time per day is more than the preset time, and sequencing according to the resident days of the users and the average resident time per day to obtain XDR aggregated data. The XDR aggregated data can generate a cell coverage table and MDT fingerprint data by combining with the MDT data according to the aggregation result of the same time level, and preparation is made for generating subsequent user-level fingerprints. Then, the MR data of the current network in nearly half a month is obtained, the MDT fingerprint data is used for fingerprint database positioning analysis to obtain the positioning result of the MR data, the positioning result is collected according to the imsi and the time, the result is combined with the XDR aggregation data and the corrected parameter data after MDT calibration to generate a seed user table, then the XDR aggregation data, namely the cell coverage table and the MDT fingerprint data, and the TA table and the adjacent table are combined with the multi-level time positioning information of the XDR aggregation data to finally generate the fingerprint data of the user level, and finally the resident position information of the single user obtained according to the half-month data analysis can be obtained by analyzing the fingerprint data. It should be noted that, those skilled in the art may select an analysis model of fingerprint data according to a time situation, and the application is not limited thereto.

S203, determining the positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time MR data of the user terminal by using a pattern matching algorithm.

Through the preprocessing work of S201-S202, the corrected parameters data and the neighbor cell table which pass the MDT calibration, the MDT fingerprint data and the resident location information of the user are obtained, and the data are used as a static table to participate in the positioning operation of the step.

Specifically, the method includes the steps of acquiring real-time MR data of the whole network, using a neural network fingerprint positioning algorithm as a pattern matching algorithm, obtaining a positioning analysis result of each sampling point, collecting all positioning results according to IMSI and time, analyzing the mobility of a user, defining sampling point data operating a certain moving range and moving speed as outdoor positioning results, matching static and low-speed moving sampling points according to user-level resident position fingerprints, and recording the matching results as indoor user sampling points, wherein the sampling points which are not matched are marked as outdoor user sampling points.

It should be noted that, the positioning method of the present embodiment may establish the positioning fingerprint library by using the existing MDT data without additional test data, and establish the resident user fingerprint library by analyzing the resident user behavior and performing the correlation analysis of the MR/XDR data. Further, although the fingerprint library has high accuracy, the fingerprint library cannot guarantee that all areas are tested due to limitations of fingerprint acquisition (for example, an ATU is only on a road, and CQTs are limited by the number of test points); the model training utilizes a local fingerprint library to train the propagation model to obtain the propagation model which is most approximate to the real wireless environment, and then the model is utilized to calculate the intensity of each cell in all grids of 50 x 50 meters.

It should be further noted that the pattern matching algorithm may be a knn (knorestneighborwood) algorithm, the user location information is extracted through the feature data matching algorithm, the multi-cell level feature value judgment algorithm is used to determine the longitude and latitude coordinates of the sampling point, the level of the user MR, and the MR is subjected to fingerprint matching according to the neural network positioning algorithm to accurately position the location longitude and latitude information of the MR.

In a possible design, the MDT fingerprint database and the resident fingerprint database corresponding to the resident location information need to be updated periodically. The resident users have large data size to analyze, the time consumption of one round of analysis is long, and most of the resident positions of the users are fixed, and the resident users can process the data once every quarter or every half year according to the platform processing capacity. The calculation amount of the correction parameter data of the MDT fingerprint database updating and the MDT calibration is relatively small, and the correlation with the positioning precision is higher, so that the data updating of the MDT related static table can be performed once every month.

In the positioning method provided in this embodiment, a preset correction model is used to determine correction parameter data according to the acquired MDT data and cell parameter data within a preset duration, then resident location information of the user terminal is determined according to the correction parameter data, the MDT data, and the XDR data, and finally a mode matching algorithm is used to determine positioning information of the user terminal according to the resident location information and the acquired real-time MR data of the user terminal. The technical problem that the judgment accuracy of the indoor resident position of the user is not high due to the fact that the positioning information of the MR data and the position of the base station in the cell parameter data are inaccurate in the prior art is solved, and the technical effect that the cell parameter data are corrected by utilizing the MDT data so as to establish the accurate positioning fingerprint information of the user to achieve the high-accuracy positioning of the indoor and outdoor positions of the user is achieved.

Fig. 4 is a schematic flowchart of another positioning method according to an embodiment of the present application. As shown in fig. 4, the positioning method specifically includes the steps of:

s401, MR data reported by the user terminal within a preset time length is obtained.

In this step, the MR data includes MDT data, each of the MR data corresponds to one sampling point, and the MDT data includes position information of the sampling point.

S402, performing geographical rasterization grouping on the MR data according to the position information of the sampling points to determine a sampling grid.

In this step, the sampling grid contains at least one of the sampling points. For example, the map is divided into 5km by 5km grids as shown in fig. 1, so that each grid may contain a plurality of sampling points.

And S403, adding an intra-domain identifier to the sampling points in the sampling grid according to the position of the base station.

In this step, the intra-domain identifier is used to indicate whether the sampling point is in a preset region corresponding to the base station location. The preset area comprises a preset first sub area and a preset second sub area, the first sub area corresponds to a first TA value, the second sub area corresponds to a second TA value, and the first sub area corresponds to the second TA value, the area identifier comprises a first sub area identifier, a second sub area identifier and a non-corresponding identifier, if the TA value and the position of the sampling point correspond to the first sub area or the second sub area, the first sub area identifier or the second sub area identifier is added to the sampling point, otherwise, the non-corresponding identifier is added to the sampling point.

For ease of understanding, reference is now made to fig. 5a-5 b.

Fig. 5a to 5d are schematic diagrams illustrating another base station location correction principle provided in the embodiment of the present application. As shown in fig. 5a, for the single sampling grid 11, the location point 511 recorded in the database by the base station, and the first TA value corresponding to the base station, such as TA1 ═ 0,3], the corresponding preset first sub-area 512 is a circular area, the second TA value corresponding to the base station, such as TA2 ═ 3,10], the corresponding preset second sub-area 513 is an annular area, the sampling point 521 is a sampling point whose TA value is within the first TA value range, and the sampling point 522 is a sampling point within the second TA value range.

As shown in fig. 5b, if the position of the sampling point 521 is located in the first sub-region 512, a first sub-region identifier 524 is added to the sampling point 521, if the first sub-region identifier is "1", otherwise, a non-corresponding identifier 523 is added, if the non-corresponding identifier is "0"; if the position of the sampling point 522 is located in the second sub-region 513, a second sub-region identifier 525 is added, if the second sub-region identifier is "2", otherwise, a non-corresponding identifier 523, if the non-corresponding identifier is "0", is added.

It should be noted that the preset area corresponding to each TA value may also be a coverage area corresponding to a TA value drawn by the latest drive test data and used for the communication between the ue and the base station, and the coverage area may be a complete banded area or an area group consisting of a plurality of unconnected areas.

It should be further noted that only two TA threshold ranges are given in this embodiment, actually, those skilled in the art may divide the TA values into multiple levels to form a TA value coverage area with multiple annuli, and the TA value area of each level corresponds to a different weight. Therefore, the base station position can be more accurately calibrated according to different TA values and the TA value corresponding to the MR data of the target user.

S404, determining a first conformity according to the first subdomain identification, the second subdomain identification, the non-corresponding identification and the corresponding weight.

In this step, the first conformity is an evaluation index for evaluating whether the existing base station position coordinates are accurate. In the present embodiment, the first conformity may be calculated by equation (1), where equation (1) is as follows:

wherein, P₁Is the first conformity, N₁Identifying the number, N, for the first sub-field₂Identifying the number, N, for the second sub-field₃Is a non-corresponding identification number, N is the total number of sampling points in the sampling grid, mu₁Identifying a corresponding weight, μ, for the first sub-field₂Identifying a corresponding weight, μ, for the second subfield₃Corresponding weights are identified for the non-correspondences.

In one possible design, the first conformity may also be calculated using equation (2), equation (2) being as follows:

wherein, P₁Is the first conformity, N₁Is the number of sampling points whose TA values are within a first TA value range, n₁Identifying the number, N, for the first sub-field₂Is the number of sampling points whose TA values are within a second range of TA values, n₂Identifying the number, N, for the second sub-field₃Is a non-corresponding identification number, N is the total number of sampling points in the sampling grid, mu₁Is as followsA subfield identifying the corresponding weight, mu₂Identifying a corresponding weight, μ, for the second sub-field₃Corresponding weights are identified for the non-correspondences.

It should be noted that, a person skilled in the art may select a calculation algorithm of the first conformity according to the actual situation, and the application is not limited.

It should be further noted that the weight values may be dynamically adjusted according to different geographical ranges or different sampling grids, so as to meet the requirement of high-precision identification of different geographical position ranges.

S405, if the first conformity is lower than a first threshold value and the number of sampling points of the sampling grid is lower than a preset number, determining the base station as a station to be evaluated.

In this step, a large number of base stations are distributed in a geographic location range such as a city, and during the deployment and later maintenance of the base stations, the locations of some base stations are shifted due to historical reasons, or the operation of some base stations is temporarily stopped due to the need of temporary construction, and other some complex situations. However, the data of these base stations are not updated in time, which results in a large deviation in the positioning analysis of the user's resident location realized by the cell parameters of these base stations, and therefore it is necessary to judge whether the data such as the longitude and latitude location of the base station needs to be updated by the first conformity.

In this embodiment, a base station with a first conformity lower than 60% is selected as a station to be evaluated, and the position of the station to be evaluated is corrected.

S406, selecting first sampling points, corresponding to the to-be-evaluated station, of which the TA values are smaller than a first preset TA threshold value from the sampling grids, and determining the geometric centers of all the first sampling points according to the position information of the first sampling points by using a geometric center algorithm, namely the initial correction positions.

As shown in fig. 5c, if the first predetermined TA threshold is 5, the first sampling point with a TA value less than 5 is selected, the square blocks of different filling patterns in fig. 5c are the first sampling points with different TA values, and the non-filled square blocks are the sampling points with a TA value greater than or equal to 5. Different TA values correspond to different position weights, the smaller the TA value is, the larger the position weight is, and the initial correction position 53 of the base station can be calculated by using a geometric center algorithm according to the position information of the first sampling point and the corresponding weight. The specific implementation manner of the geometric center algorithm can be selected by a person skilled in the art according to actual situations, and the present application is not limited.

S407, randomly selecting one of the position points in the preset adjusting area, and calculating second conformity between all sampling points in the sampling grid and the position points.

In this step, the second conformity is used to indicate a proportion of the sampling points included in the preset region corresponding to the location point to a total number of sampling points.

In order to make the latitude and longitude positioning position of the base station more accurate, and thereby improve the accuracy of subsequent user positioning, fine adjustment of the initial corrected position 53 obtained in the previous step is also required. In the present embodiment, as shown in fig. 5d, the initial correction position is adjusted within the preset adjustment region 55 with the radius R being 300M and the initial correction position 53 as a center, so that the preset region 54 corresponding to the initial correction position can cover as many sampling points as possible. The ratio of the number of sampling points in the predetermined area 54 to the total number of sampling points is used as the second conformity.

S408, if the second conformity degree is greater than or equal to the preset conformity degree threshold value, determining the position point as a position point to be selected; and selecting the position point with the largest second coincidence value as a correction position from all the position points to be selected.

In this embodiment, the preset conformity threshold is set to be 80%, and when a position point with the second conformity degree greater than or equal to 80% exists in the preset adjustment region 55, the position point with the maximum second conformity degree is taken as the corrected position 56.

And S409, if the position points with the second conformity greater than the preset conformity threshold do not exist in all the position points, re-selecting a second sampling point with a TA value smaller than the second preset TA threshold corresponding to the station to be evaluated from the sampling grid so as to re-determine the corrected position.

In this embodiment, when there is no position point within the preset adjustment area 55 where the second conformity degree is greater than or equal to 80%, the first preset TA threshold in S406 is enlarged to the second preset TA threshold, for example, the second preset TA threshold is set to 8, and then steps S406-S408 are repeated to determine the corrected position 56.

In one possible design, the second predetermined TA value is obtained by multiplying the first predetermined TA value by the adjustment factor, and steps S406-S408 may be repeated until the modified position 56 satisfying the condition is found.

Further alternatively, a threshold of the number of times of loop may be set, and when the number of times of repeatedly performing steps S406 to S408 reaches the threshold of the number of times of loop, for example, 4 times, the calculation of the corrected position is stopped, and the base station is deleted from the user positioning fingerprint database, or a manual correction request is issued to prompt the operator to correct the position of the base station by means of reacquiring the drive test data, and the like.

And S410, determining resident position information of the user terminal according to the corrected working parameter data, the MDT data and the XDR data.

S411, determining the positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time MR data of the user terminal by using a pattern matching algorithm.

The principles and noun explanations of steps S410-S411 are referred to in S202-S203, and will not be described herein again.

In the positioning method provided in this embodiment, a preset correction model is used to determine correction parameter data according to the acquired MDT data and cell parameter data within a preset duration, then resident location information of the user terminal is determined according to the correction parameter data, the MDT data, and the XDR data, and finally a mode matching algorithm is used to determine positioning information of the user terminal according to the resident location information and the acquired real-time MR data of the user terminal. The technical problem that the judgment accuracy of the indoor resident position of the user is not high due to the fact that the positioning information of the MR data and the position of the base station in the cell working parameter data are inaccurate in the prior art is solved, and the technical effect that the cell working parameter data are corrected by using the MDT data so as to establish the accurate positioning fingerprint information of the user to achieve the high-accuracy positioning of the indoor position and the outdoor position of the user is achieved.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments can be implemented by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps including the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Fig. 6 is a schematic structural diagram of a positioning device provided in the present application. The positioning means may be implemented by software, hardware or a combination of both.

As shown in fig. 6, the positioning apparatus 600 includes:

an obtaining module 601, configured to obtain MDT data of minimization of drive tests, cell parameter data, XDR data of external data reports, and MR data of real-time measurement reports within a preset time duration;

a preprocessing module 602, configured to determine, by using a preset correction model, correction power parameter data according to acquired Minimization of Drive Test (MDT) data within a preset time and cell power parameter data, where the cell power parameter data includes communication data of a cell corresponding to a covered traffic area;

the preprocessing module 602 is further configured to determine resident location information of the user terminal according to the corrected parameter data, the MDT data, and the external data report XDR data;

a positioning module 603, configured to determine, by using a pattern matching algorithm, positioning information of the user terminal according to the corrected parameter data, the resident location information, and the acquired real-time measurement report MR data of the user terminal.

In a possible design, the preprocessing module 602 is configured to determine, by using a preset modification model, modified MDT data according to acquired MDT data of minimization of drive test within a preset time and cell parameter data, and includes:

the obtaining module 601 is configured to obtain MR data reported by the user terminal within a preset time duration, where the MR data includes MDT data, each MR data corresponds to a sampling point, and the MDT data includes position information of the sampling point;

the preprocessing module 602 is configured to perform geographic rasterization grouping on the MR data according to the location information to determine a sampling grid, where the sampling grid includes at least one sampling point;

the preprocessing module 602 is further configured to adjust data related to a base station location in the cell parameter data according to the sampling grid, so as to determine the modified parameter data.

In one possible design, the preprocessing module 602 is further configured to adjust data related to a base station location in the cell parameter data according to the sampling grid to determine the modified parameter data, and includes:

the preprocessing module 602 is further configured to add an intra-domain identifier to the sampling point in the sampling grid according to the base station location, where the intra-domain identifier is used to indicate whether the sampling point is in a preset region corresponding to the base station location;

the preprocessing module 602 is further configured to determine a first coincidence degree of the sampling point with a base station according to the intra-domain identifier;

the preprocessing module 602 is further configured to determine a corrected position of the base station according to the first conformity and the sampling grid; and determining the corrected parameter data according to the corrected position.

Optionally, the preprocessing module 602 is further configured to determine a first coincidence degree of the sampling point with the base station according to the intra-domain identifier, and includes:

the preprocessing module 602 is further configured to determine, according to the intra-domain identifier, a ratio between the number of sampling points in the preset region and a total number of sampling points, where the first conformity is the ratio.

In one possible design, the preprocessing module 602 is further configured to determine a revised position of the base station according to the first conformity and the sampling grid, and includes:

the preprocessing module 602 is further configured to determine that the base station is a station to be evaluated if the first conformity is lower than a first threshold and the number of sampling points of the sampling grid is lower than a preset number;

the preprocessing module 602 is further configured to determine an initial correction position according to the site to be evaluated and a time advance TA value corresponding to the sampling grid by using a preset center position algorithm;

the preprocessing module 602 is further configured to determine the correction position by using an adjustment algorithm in a preset adjustment area with the initial correction position as a center.

In a possible design, the preprocessing module 602 is further configured to determine an initial correction position according to the station to be evaluated and a time advance TA value corresponding to the sampling grid by using a preset center position algorithm, where the method includes:

the preprocessing module 602 is further configured to select, from the sampling grid, a first sampling point whose TA value corresponding to the station to be evaluated is smaller than a first preset TA threshold;

the preprocessing module 602 is further configured to determine geometric centers of all the first sampling points according to the position information of the first sampling points by using a geometric center algorithm, where the initial corrected position is the geometric center.

In one possible design, the preprocessing module 602 is further configured to determine the corrected position by using an adjustment algorithm in a preset adjustment region, with the initial corrected position as a center, and includes:

the preprocessing module 602 is further configured to randomly select one of the position points in the preset adjustment region, and calculate a second conformity between all the sampling points in the sampling grid and the position points, where the second conformity is used to indicate a proportion of the sampling points included in the preset region corresponding to the position points to a total number of the sampling points;

the preprocessing module 602 is further configured to determine that the location point is a candidate location point if the second conformity is greater than or equal to a preset conformity threshold;

the preprocessing module 602 is further configured to select, from all the position points to be selected, a position point with a largest second coincidence value as the corrected position;

the preprocessing module 602 is further configured to reselect a second sampling point, corresponding to the to-be-evaluated site, where the TA value is smaller than a second preset TA threshold from the sampling grid, if there is no location point in all the location points where the second conformity is greater than the preset conformity threshold, so as to re-determine the corrected location.

In a possible design, the preset region includes a preset first sub-region and a preset second sub-region, the first sub-region corresponds to a first TA value, the second sub-region corresponds to a second TA value, and correspondingly, the region identifier includes a first sub-region identifier, a second sub-region identifier, and a non-corresponding identifier, and correspondingly, the preprocessing module 602 is further configured to add the first sub-region identifier or the second sub-region identifier to the sampling point if the TA value and the position of the sampling point both correspond to the first sub-region or the second sub-region, and otherwise add the non-corresponding identifier to the sampling point;

the preprocessing module 602 is further configured to determine a first conformity between the sampling point and a base station according to the intra-domain identifier, and includes:

the preprocessing module 602 is further configured to determine the first compliance according to the first sub-domain identifier, the second sub-domain identifier, the non-corresponding identifier, and the corresponding weight.

It should be noted that the positioning apparatus provided in the embodiment shown in fig. 6 can execute the method provided in any of the above method embodiments, and the specific implementation principle, technical features, technical term explanations, and technical effects thereof are similar and will not be described herein again.

Fig. 7 is a schematic structural diagram of an electronic device provided in the present application. As shown in fig. 7, the electronic device 700 may include: at least one processor 701 and a memory 702. Fig. 7 shows an electronic device as an example of a processor.

The memory 702 stores programs. In particular, the program may include program code including computer operating instructions.

The memory 702 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The processor 701 is configured to execute computer-executable instructions stored by the memory 702 to implement the methods described in the method embodiments above.

The processor 701 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

Alternatively, the memory 702 may be separate or integrated with the processor 701. When the memory 702 is a device independent from the processor 701, the electronic device 700 may further include:

a bus 703 for connecting the processor 701 and the memory 702. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. Buses may be classified as address buses, data buses, control buses, etc., but do not represent only one bus or type of bus.

Alternatively, in a specific implementation, if the memory 702 and the processor 701 are implemented by being integrated on one chip, the memory 702 and the processor 701 may complete communication through an internal interface.

The present application also provides a computer-readable storage medium, which may include: various media that can store 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, and in particular, the computer-readable storage medium stores program instructions that are used for the positioning method in the foregoing embodiments.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of positioning, comprising:

determining corrected power parameters according to MDT data and cell power parameters in the acquired preset duration by using a preset correction model, wherein the cell power parameters comprise communication data of a cell corresponding to a covered traffic area;

determining the positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time measurement report MR data of the user terminal by using a pattern matching algorithm;

the determining the modified power parameters data according to the acquired MDT data and the cell power parameters data within the preset time by using the preset modification model comprises the following steps:

2. The method of claim 1, wherein the determining the first degree of coincidence of the sampling point with the base station according to the intra-domain identity comprises:

3. The method of claim 1, wherein determining the revised position of the base station based on the first conformity and the sampling grid comprises:

if the first conformity is lower than a first threshold value and the number of sampling points of the sampling grid is lower than a preset number, determining the base station as a station to be evaluated;

4. The positioning method according to claim 3, wherein the determining an initial correction position according to the TA values corresponding to the site to be evaluated and the sampling grid by using a preset center position algorithm comprises:

5. The method according to claim 4, wherein the determining the corrected position by using an adjustment algorithm in a preset adjustment region with the initial corrected position as a center comprises:

selecting the position point with the maximum second coincidence value from all the position points to be selected as the correction position;

6. The positioning method according to any one of claims 1 and 3-5, wherein the preset region includes a preset first sub-region and a preset second sub-region, the first sub-region corresponds to a first TA value, the second sub-region corresponds to a second TA value, and the in-domain identifier includes a first sub-region identifier, a second sub-region identifier, and a non-corresponding identifier, if the TA value and the position of the sampling point both correspond to the first sub-region or the second sub-region, the first sub-region identifier or the second sub-region identifier is added to the sampling point, otherwise, the non-corresponding identifier is added to the sampling point, and the determining the first degree of matching between the sampling point and the base station according to the in-domain identifier includes:

7. A positioning device, comprising:

the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for determining correction work parameter data according to MDT data and cell work parameter data within the acquired preset time length by using a preset correction model, and the cell work parameter data comprises communication data of a cell corresponding to a covered traffic area;

the positioning module is used for determining positioning information of the user terminal according to the corrected working parameter data, the resident position information and the acquired real-time measurement report MR data of the user terminal by using a pattern matching algorithm;

the determining of the modified working parameter data according to the acquired MDT data and the cell working parameter data within the preset time by using the preset modification model includes:

8. An electronic device, comprising:

a processor; and the number of the first and second groups,

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform a positioning method of any of claims 1 to 6 via execution of the executable instructions.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the positioning method according to any one of claims 1 to 6.