CN117202344A - Positioning method, positioning device, terminal equipment and storage medium - Google Patents

Abstract

The application discloses a positioning method, a positioning device, terminal equipment and a storage medium, wherein the positioning method comprises the following steps: acquiring measurement report MR data to be positioned; matching MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid units. Based on the scheme of the application, the grid units in the positioning fingerprint database are provided with the signal fingerprint feature vectors, and the corresponding actual geographic positions are associated. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

Description

Positioning method, positioning device, terminal equipment and storage medium

Technical Field

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

Background

The MR (Measurement Report ) data is network original data measured by UE (User Equipment), the MR data carries related information of uplink and downlink wireless links, is the most common data source in the mobile network optimization work, and has important application significance for positioning the MR data.

The MR data does not directly carry position information, and a simulation positioning method based on a signal propagation model is mostly adopted to position the MR data to be positioned at present, but the precision of the simulation positioning method is not high,

disclosure of Invention

The application mainly aims to provide a positioning method, a positioning device, a terminal device and a storage medium, which aim to solve or improve the problem of low positioning accuracy of MR data.

In order to achieve the above object, the present application provides a positioning method, including:

acquiring measurement report MR data to be positioned;

matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units;

and determining the position corresponding to the MR data to be positioned according to the matched grid unit.

Optionally, the positioning fingerprint database comprises a grid unit constructed based on measurement report MR data samples of networking terminals corresponding to broadband devices in the building object;

the step of matching the MR data to be located with the grid units in the location fingerprint database to obtain matched grid units includes:

And matching the MR data to be positioned with the grid units in the positioning fingerprint database based on a preset normalized Euclidean distance algorithm to obtain the matched grid units.

Optionally, before the step of matching the MR data to be located with the grid cells in the location fingerprint database, the method further includes:

acquiring position information of a building object, and acquiring an MR data sample of a networking terminal corresponding to broadband equipment in the building object;

combining the position information and the MR data sample to obtain a target data sample;

and constructing a grid unit of the positioning fingerprint database based on the target data sample.

Optionally, the step of acquiring the position information of the building object includes:

acquiring the use address information of a broadband account corresponding to broadband equipment in the building object;

resolving the using address information into normalized address information meeting preset specifications;

obtaining optimized position information of the building object according to the normalized address information;

the step of combining the position information and the MR data samples to obtain a target data sample comprises:

And combining the optimized position information and the MR data sample to obtain the target data sample.

Optionally, after the step of obtaining the optimized position information of the building object according to the normalized address information, before the step of combining the optimized position information and the MR data sample to obtain the target data sample, the method further includes:

acquiring initialization position information corresponding to broadband equipment in the building object;

calculating distance information according to the initialized position information and the optimized position information;

screening the broadband equipment according to the distance information to determine effective broadband equipment;

calculating to obtain the position information of the building object after secondary optimization based on a preset clustering algorithm and the initialized position information corresponding to the effective broadband equipment;

the step of combining the optimized position information and the MR data samples to obtain the target data samples includes:

and combining the position information after the secondary optimization with the MR data sample to obtain the target data sample.

Optionally, the step of acquiring MR data samples of a networking terminal corresponding to the broadband device in the building object includes:

Acquiring an MR data sample of a networking terminal in a preset range, wherein the building object is positioned in the preset range;

and screening the MR data samples of the networking terminals in the preset range, and reserving the MR data samples of the networking terminals corresponding to the broadband equipment in the building object.

Optionally, before the step of acquiring the MR data samples of the networking terminal in the preset range, the method further includes:

detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively;

determining a target time period from among the plurality of time periods according to the terminal networking state;

the steps are performed at least once within the target time period: and acquiring MR data samples of the networking terminal in a preset range.

The embodiment of the application also provides a positioning device, which comprises:

the acquisition module is used for acquiring MR data to be positioned;

the matching module is used for matching the MR data to be positioned with the grid units in the positioning fingerprint database to obtain matched grid units;

and the positioning module is used for determining the position corresponding to the MR data to be positioned according to the matched grid units.

The embodiment of the application also provides a terminal device, which comprises a memory, a processor and a positioning program stored in the memory and capable of running on the processor, wherein the positioning program realizes the steps of the positioning method when being executed by the processor.

The embodiment of the application also provides a computer readable storage medium, wherein a positioning program is stored on the computer readable storage medium, and the positioning program realizes the steps of the positioning method when being executed by a processor.

The positioning method, the positioning device, the terminal equipment and the storage medium provided by the embodiment of the application are used for acquiring the MR data of the measurement report to be positioned; matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid unit. Based on the scheme of the application, the grid units in the positioning fingerprint database are provided with the signal fingerprint feature vectors, and the corresponding actual geographic positions are associated. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

Drawings

FIG. 1 is a schematic diagram of functional modules of a terminal device to which a positioning device of the present application belongs;

FIG. 2 is a flow chart of a first exemplary embodiment of a positioning method according to the present application;

FIG. 3 is a flow chart of a second exemplary embodiment of a positioning method according to the present application;

FIG. 4 is a flow chart of a third exemplary embodiment of a positioning method according to the present application;

FIG. 5 is a flow chart of a fourth exemplary embodiment of a positioning method according to the present application;

FIG. 6 is a flow chart of a fifth exemplary embodiment of a positioning method according to the present application;

FIG. 7 is a flowchart of a sixth exemplary embodiment of a positioning method according to the present application;

fig. 8 is a flowchart of a seventh exemplary embodiment of the positioning method of the present application.

The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

The main solutions of the embodiments of the present application are: acquiring measurement report MR data to be positioned; matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid unit. Based on the scheme of the application, the grid units in the positioning fingerprint database are provided with the signal fingerprint feature vectors, and the corresponding actual geographic positions are associated. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

Specifically, referring to fig. 1, fig. 1 is a schematic diagram of functional modules of a terminal device to which a positioning device of the present application belongs. The positioning device may be a device independent of the terminal device, which is capable of positioning, and which may be carried on the terminal device in the form of hardware or software. The terminal equipment can be an intelligent mobile terminal with a data processing function such as a mobile phone and a tablet personal computer, and can also be a fixed terminal equipment or a server with a data processing function.

In this embodiment, the terminal device to which the positioning device belongs at least includes an output module 110, a processor 120, a memory 130, and a communication module 140.

The memory 130 stores an operating system and a positioning program, and the positioning device can acquire measurement report MR data to be positioned; matching MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and storing the determined information such as the position corresponding to the MR data to be positioned in the memory 130 according to the matched grid unit; the output module 110 may be a display screen or the like. The communication module 140 may include a WIFI module, a mobile communication module, a bluetooth module, and the like, and communicates with an external device or a server through the communication module 140.

Wherein the positioning program in the memory 130 when executed by the processor performs the steps of:

acquiring measurement report MR data to be positioned;

matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units;

and determining the position corresponding to the MR data to be positioned according to the matched grid unit.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

and matching the MR data to be positioned with the grid units in the positioning fingerprint database based on a preset normalized Euclidean distance algorithm to obtain the matched grid units.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

acquiring position information of a building object, and acquiring an MR data sample of a networking terminal corresponding to broadband equipment in the building object;

combining the position information and the MR data sample to obtain a target data sample;

and constructing a grid unit of the positioning fingerprint database based on the target data sample.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

Acquiring the use address information of a broadband account corresponding to broadband equipment in the building object;

resolving the using address information into normalized address information meeting preset specifications;

obtaining optimized position information of the building object according to the normalized address information;

further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

and combining the optimized position information and the MR data sample to obtain the target data sample.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

acquiring initialization position information corresponding to broadband equipment in the building object;

calculating distance information according to the initialized position information and the optimized position information;

screening the broadband equipment according to the distance information to determine effective broadband equipment;

calculating to obtain the position information of the building object after secondary optimization based on a preset clustering algorithm and the initialized position information corresponding to the effective broadband equipment;

further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

And combining the position information after the secondary optimization with the MR data sample to obtain the target data sample.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

acquiring an MR data sample of a networking terminal in a preset range, wherein the building object is positioned in the preset range;

and screening the MR data samples of the networking terminals in the preset range, and reserving the MR data samples of the networking terminals corresponding to the broadband equipment in the building object.

Further, the positioning program in the memory 130, when executed by the processor, further performs the steps of:

detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively;

determining a target time period from among the plurality of time periods according to the terminal networking state;

the steps are performed at least once within the target time period: and acquiring MR data samples of the networking terminal in a preset range.

According to the embodiment, through the scheme, the MR data of the measurement report to be positioned is obtained; matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid unit. In this embodiment, the grid unit in the positioning fingerprint database has the signal fingerprint feature vector, and correlates the corresponding actual geographic position. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

Referring to fig. 2, a first embodiment of a positioning method according to the present application provides a flowchart, where the positioning method includes:

step S10, acquiring measurement report MR data to be located.

In particular, MR data to be located, which may come from one or more terminal devices, may be acquired by means of a dedicated measurement device. For example, for a mobile network operator, MR data from a UE to be located may be acquired by a base station or network device.

The MR data to be located does not itself directly comprise position information, but it mainly contains various information about signal propagation and device measurements, such as signal strength, frequency, time delay, neighbor cell information, etc.

It is noted that erroneous MR data may exist among the acquired plurality of MR data to be located, and that unsatisfactory erroneous MR data needs to be excluded. The way to exclude erroneous MR data includes: data consistency check, data outlier detection, data consistency comparison, actual scene comparison, data quality assessment indexes, data visualization analysis and the like.

And step S20, matching the MR data to be positioned with the grid units in the positioning fingerprint database to obtain matched grid units.

Specifically, the localization data fingerprint database is a database that can be used for MR localization, and includes a grid unit constructed based on at least one of DT (Drive Test) data, MDT (Minimization of Drive Tests, minimization of Drive Test) data, OTT (Top of The present) data, and analog MDT data, which provide various application services to users via The internet. The simulated MDT data refers to target data samples obtained by combining MR data samples of networking terminals corresponding to broadband equipment in a building object based on position information of the building object.

It will be appreciated that the number of grid cells in the location data fingerprint library is plural, each grid cell having a corresponding signal fingerprint feature vector and location.

Regarding signal fingerprint feature vectors: because the factors such as wireless environment quality, base station antennas, topography, buildings and the like can influence the change of signal intensity, the UE can observe a group of signal intensity sample values of cells at each position, the RSRP (Reference Signal Received Power ) sample values of the group of cells received at different positions are different, and signal fingerprint feature vectors can be obtained based on the RSRP. Similarly, the signal fingerprint feature vector may also be obtained based on RSRQ (Reference Signal Received Quality ) or other information that characterizes the signal fingerprint, without limitation. The MR data to be located carries the corresponding signal fingerprint feature vector.

And matching the MR data to be positioned with the grid units in the fingerprint database of the positioning data, wherein the grid unit closest to the signal fingerprint feature vector of the MR data to be positioned is searched in the matching process. Then, the closest grid cell to the signal fingerprint feature vector of the MR data to be located is taken as the matching grid cell.

Step S30, determining the position corresponding to the MR data to be positioned according to the matched grid units.

Specifically, since the signal fingerprint feature vector of the matched grid unit is closest to the signal fingerprint feature vector of the MR data to be positioned, and the position corresponding to the matched grid unit is determined in advance, the position corresponding to the matched grid unit can be further determined as the position corresponding to the MR data to be positioned, and the position information corresponding to the MR data to be positioned is obtained. Thus, the localization of the MR data to be localized is completed.

According to the scheme, the method and the device specifically obtain measurement report MR data to be positioned; matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid unit. In this embodiment, the grid unit in the positioning fingerprint database has the signal fingerprint feature vector, and correlates the corresponding actual geographic position. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

Further, referring to fig. 3, a second embodiment of the positioning method of the present application provides a flowchart, based on the embodiment shown in fig. 2, the positioning fingerprint database includes a grid unit constructed based on location information of a building object and measurement report MR data samples of networking terminals corresponding to broadband devices in the building object; step S20, matching the MR data to be located with the grid units in the location fingerprint database, to obtain further refinement of the matched grid units, including:

step S21, based on a preset normalized Euclidean distance algorithm, the MR data to be positioned is matched with the grid units in the positioning fingerprint database, and the matched grid units are obtained.

In particular, in order to find the grid unit closest to the signal fingerprint feature vector of the MR data to be located, the matching may be performed based on a preset normalized euclidean distance algorithm. Firstly, corresponding Euclidean distances are calculated respectively aiming at the signal fingerprint feature vector of MR data to be positioned and the signal fingerprint feature vector of each grid unit. It will be appreciated that the grid elements and euclidean distance are in a one-to-one relationship.

Further, the calculated Euclidean distance is normalized to obtain a normalized Euclidean distance so as to eliminate the influence of different feature dimensions, and thus, the distance value which is relatively consistent under the different feature dimensions can be ensured.

Further, in the normalized Euclidean distances of all the grid units, finding the normalized Euclidean distance with the smallest value, and determining the grid unit corresponding to the normalized Euclidean distance with the smallest value as the matched grid unit. It will be appreciated that the matching grid elements match the signal fingerprint feature vector of the MR data to be located to the highest degree.

According to the scheme, the MR data to be positioned is matched with the grid units in the positioning fingerprint database based on a preset normalized Euclidean distance algorithm, and the matched grid units are obtained. In the embodiment, the influence of different feature dimensions is fully considered, the normalization Euclidean distance algorithm is adopted for matching, the difference between the different feature dimensions can be eliminated, the feature dimensions play a more balanced role in matching, and finally a more proper matched grid unit is obtained.

Further, referring to fig. 4, a flowchart is provided in a third embodiment of the positioning method according to the present application, based on the embodiment shown in fig. 2, step S20 includes, before matching the MR data to be positioned with the grid cells in the positioning fingerprint database:

and S01, acquiring position information of a building object and MR data samples of networking terminals corresponding to broadband equipment in the building object.

Specifically, the positioning data fingerprint database is a database for MR positioning, and generally comprises grid units constructed based on at least one of DT data, MDT data and OTT data, wherein the acquisition coverage of the DT data, the MDT data and the OTT data directly affects the effective data volume of the positioning data fingerprint database. Currently, the three data are limited in terms of acquisition coverage: the coverage of DT data is only aimed at a trunk road, the testing workload is large, and the data timeliness is poor; OTT data need to read URI (Uniform Resource Identifier ) of HTTP (Hypertext Transfer Protocol, hypertext transfer protocol) protocol header from information sent by mobile terminal APP, thereby obtaining longitude and latitude information of the corresponding terminal, but if the data are encrypted, the data cannot be obtained, resulting in few samples of OTT data; the MDT data requires the user terminal to start the GPS (Global Positioning System ) and support the MDT function, the data acquisition requirement is higher, the user coordination degree willingness degree is low, and the number of terminals supporting the MDT function is small at present. Therefore, the acquisition coverage of DT data, MDT data and OTT data has a large limitation, and the effective data volume of the positioning data fingerprint database can not meet the MR positioning requirements of a large range and high precision.

In summary, supplementing the localization data fingerprint database with more valid data is one of the core approaches to enhance MR localization. For this reason, this embodiment proposes to construct a grid unit based on a kind of simulated MDT data, so as to increase the effective data volume of the positioning data fingerprint database, and enhance MR positioning based on the positioning data fingerprint database.

The "building object" according to the present embodiment refers to the whole building or a specific area or floor within the building, such as a building, a room, a corridor, a floor, or other divided units of the building. A corresponding at least one broadband device is installed within the building object, which can be a home broadband device, an enterprise broadband device, or other type of broadband device. Taking Home Gateway as an example, a Home Gateway refers to an integrated network device for providing broadband access and connecting various devices in a Home environment, and it generally combines various functions of a modem, a router, a switch, a wireless access point, etc., and is a common Home broadband device.

The data entered into the localization fingerprint database needs to include MR data samples, as well as location information corresponding to the MR data samples. For this reason, the present embodiment needs to acquire the location information of the building object and MR data samples of the networking terminals corresponding to the broadband devices in the building object. The position information is longitude and latitude information and is used for representing the specific geographic position of the building object; networking terminals refer to terminals that are connected to the broadband device through a corresponding broadband device, such as a Personal Computer (PC), a smart phone, a tablet computer, and other smart devices connected to the broadband device through wired or wireless connection; MR data samples refer to measurement data collected and recorded in a wireless communication system regarding signal and network parameters.

And step S02, combining the position information and the MR data sample to obtain a target data sample.

Specifically, after obtaining the location information of the building object and the MR data sample of the networking terminal corresponding to the broadband device in the building object, the location information and the MR data sample may be further combined to obtain the target data sample.

In addition, the MDT data refers to minimization of drive test data, and the collection process involves an automatic drive test technology introduced by 3G UMTS (Universal Mobile Telecommunications System )/4G LTE (Long-Term Evolution)/5 NR (New Radio), wherein the automatic drive test technology is used for collecting, reporting and preprocessing measurement data by configuring a common user/commercial terminal through a network. The user terminal can automatically report MDT data containing user position information to the base station only by starting the GPS and supporting the MDT function. The MDT is similar to the MR, and comprises fields such as RSRP (Reference Signal Received Power ), RSRQ (Reference Signal Received Quality, reference signal received quality) and the like, and comprises longitude and latitude information based on GPS, so that the MDT can be used for big data analysis. In short, the MDT data covers information such as "time identifier", "user identifier", "cell identifier", "longitude and latitude", "RSRP".

The format of the target data sample related to the application is similar to the MDT data format, so that the target data sample is matched with a positioning data fingerprint database based on MDT data and can be incorporated into the positioning data fingerprint database. That is, the target data sample may be considered as a type of simulated MDT data.

And step S03, constructing a grid unit of the positioning fingerprint database based on the target data sample.

Specifically, after the target data sample is obtained, a grid unit for positioning the fingerprint database can be directly constructed based on the target data sample; or one or more of data cleaning, abnormal value removal, correction, standardized data format and the like can be performed on the target data sample, so that the consistency and the accuracy of the target data sample are ensured, and then a grid unit of the positioning fingerprint database is constructed based on the processed target data sample, so that the safety and the accessibility of the positioning fingerprint database are ensured.

For a location fingerprint database containing grid cells constructed from target data samples, data verification and calibration may also be performed to ensure accuracy and reliability of the grid cells of the location fingerprint database, which may include comparison with known locations, verification of the correctness of the corresponding locations of the grid cells of the location fingerprint database, and mutual calibration with other reference data to ensure data consistency.

It should be noted that, in order to ensure the instantaneity and adaptability of the positioning fingerprint database and reflect the change and evolution of the network environment, the positioning fingerprint database can be updated according to the above steps when the new broadband device/broadband account number of the building object or the wireless network environment changes, and the new target data sample is utilized to construct the grid unit of the positioning fingerprint database.

It can be appreciated that the embodiment adds the simulated MDT data which is different from the DT data, the MDT data and the OTT data, and can improve the acquisition coverage of the positioning fingerprint database. On this basis, a spatial grid set of finer granularity (e.g., 20 m x 20 m grid) can be constructed. In constructing a finer granularity spatial grid set, the resolution of the grid, i.e. the actual spatial extent size represented by each grid cell, may be predefined, which depends on the actual application requirements and the characteristics of the target data sample. A grid cell table may then be created in the location fingerprint database, which grid cell table should contain unique identifiers of grid cells and spatial geometric columns (e.g., points, lines, or polygons) for representing the boundaries of the grid cells. Further, grid cells in the grid cell table are constructed based on one or more of DT data, MDT data, OTT data, simulated MDT data.

The embodiment is equivalent to supplementing the data of the positioning fingerprint database, so that the positioning fingerprint database comprises more effective grid units, the MR positioning range and accuracy supported by the positioning fingerprint database can be effectively improved, and the positioning fingerprint database can be used for scenes such as smart cities, advertising marketing, smart transportation, infrastructure and business matching planning, emergency disaster relief, environmental protection and the like, and has higher practical value.

It will be appreciated that the third embodiment of the positioning method of the present application may be combined with the fourth embodiment to form a new embodiment.

According to the scheme, the position information of the building object and the MR data sample of the networking terminal corresponding to the broadband equipment in the building object are obtained; combining the position information and the MR data sample to obtain a target data sample; and constructing a grid unit of the positioning fingerprint database based on the target data sample. In this embodiment, the location information of the building object and the MR data sample of the networking terminal corresponding to the broadband device in the building object are obtained and combined, so that the target data sample meeting the requirements of the positioning fingerprint database can be obtained, and the target data sample can be used for constructing a grid unit of the positioning fingerprint database to perform data supplementation on the positioning fingerprint database. Therefore, the data acquisition coverage can be effectively improved, and the positioning fingerprint database can support the MR positioning with a larger range and higher precision.

Further, referring to fig. 5, a flowchart is provided in a fourth embodiment of the positioning method according to the present application, based on the embodiment shown in fig. 4, step S01, obtaining the position information of the building object is further refined, which includes:

and step S011, obtaining the use address information of the broadband account corresponding to the broadband equipment in the building object.

In particular, the broadband account number corresponding to the broadband device is generally associated with an address, and when the user applies for the home broadband service/enterprise broadband service, the service provider may require the user to provide an installation address or a residence address as a target address for providing the service, i.e., use address information.

Step S012, resolving the using address information into normalized address information meeting preset specifications.

In particular, many internet map service providers provide address query functions that allow corresponding latitude and longitude coordinates to be obtained by inputting address information. However, the usage address information may adopt a non-standardized expression mode, and cannot meet the query requirement of the internet map, so that the usage address information needs to be resolved into standardized address information meeting the preset specification, namely the query specification of the internet map.

For example, the address information of the use of the broadband account corresponding to the home broadband device in a certain residential building is analyzed as: the H number of the G unit of the F building of the E district of the D street in the C district of the A province is normalized address information, and meets the query specification of the Internet map.

And step S013, obtaining the optimized position information of the building object according to the normalized address information.

Specifically, a query request can be submitted to the internet map service based on the normalized address information, so as to query and obtain longitude and latitude information corresponding to the normalized address information of the broadband device, and further, optimized position information is calculated and obtained based on the longitude and latitude information corresponding to the normalized address information of the broadband device.

Step S02, combining the position information and the MR data sample to obtain a target data sample for further refinement, including:

and step S021, combining the optimized position information with the MR data sample to obtain the target data sample.

Specifically, after obtaining the optimized position information of the building object and the MR data sample of the networking terminal corresponding to the broadband device in the building object, the optimized position information and the MR data sample may be further combined to obtain the target data sample.

According to the scheme, the use address information of the broadband account corresponding to the broadband equipment in the building object is obtained; resolving the using address information into normalized address information meeting preset specifications; obtaining optimized position information of the building object according to the normalized address information; and combining the optimized position information and the MR data sample to obtain the target data sample. In this embodiment, the usage address information of the broadband account is resolved into normalized address information, and further, optimized position information is obtained according to the normalized address information, where the optimized position information can more accurately represent the position of the building object, and meets the requirement of high-precision target data sample collection.

Further, referring to fig. 6, a flowchart is provided in a fifth embodiment of the positioning method according to the present application, based on the embodiment shown in fig. 5, step S013, after obtaining the optimized position information of the building object according to the normalized address information, further includes:

step S014, acquiring initialization position information corresponding to the broadband device in the building object.

Specifically, because the optimized location information is obtained by querying the internet map service based on the normalized address of the broadband account, there may be a problem of lower accuracy, or the actual distance between the optimized location information and the broadband device in the building object is far.

In order to make the optimized location information closer to the actual location of the broadband device within the building object, a secondary optimization of the optimized location information is required. More specifically, the secondary optimization process needs to acquire latitude and longitude information, i.e. initialization position information, obtained when the broadband device in the building object is installed.

Step S015, calculating distance information according to the initialized location information and the optimized location information.

Specifically, since the initialized location information and the optimized location information belong to latitude and longitude information, a related formula or algorithm can be used to calculate a distance between the initialized location information and the optimized location information, that is, a distance between an initialized location of the broadband device in the building object when the broadband device is installed and an optimized location of the building object, so as to obtain corresponding distance information.

For example, a haverine formula (Haversine formula) may be used to calculate a great circle distance between two latitude and longitude coordinates, i.e., a straight line distance between two latitude and longitude coordinates.

If there are multiple broadband devices in the building object, the multiple broadband devices have respective initialization position information, and the distance information corresponding to each of the multiple broadband devices is obtained through calculation.

And step S016, screening the broadband equipment according to the distance information to determine effective broadband equipment.

Specifically, the initialization position information of the broadband device at the time of installation is not necessarily accurate because of human input errors or system reasons. Broadband devices with accurate initialization location information can be considered valid broadband devices, and broadband devices with inaccurate initialization location information can be considered invalid broadband devices.

In order to distinguish between active broadband devices and inactive broadband devices, a plurality of broadband devices may be screened based on preset thresholds and distance information. If the distance information corresponding to a certain broadband device is smaller than (or equal to or smaller than) a threshold value, the broadband device can be determined to be an effective broadband device; if the distance information corresponding to a certain wideband device is greater than or equal to (or greater than) a threshold value, the wideband device may be determined as an invalid wideband device.

Further, the invalid broadband device and associated initialization location information do not participate in subsequent computing steps.

And step S017, calculating the secondarily optimized position information of the building object based on a preset clustering algorithm and the initialized position information corresponding to the effective broadband equipment.

Specifically, the number of the effective broadband devices can be multiple, and the K value is set to be 1 by adopting a K-Means clustering algorithm, so that the position closest to the initialization position of each effective broadband device, namely the position information of the building object after secondary optimization, can be further calculated.

It is understood that the location information after the secondary optimization is longitude and latitude information. In addition, other clustering algorithms besides the K-Means clustering algorithm can be adopted to realize the calculation process.

Step S021, combining the optimized position information and the MR data sample to obtain the target data sample for further refinement, including:

step S0211, combining the position information after the secondary optimization with the MR data sample to obtain the target data sample.

Specifically, after obtaining the secondarily optimized position information of the building object and the MR data sample of the networking terminal corresponding to the broadband device in the building object, the secondarily optimized position information and the MR data sample may be further combined to obtain the target data sample.

According to the scheme, the initialization position information corresponding to the broadband equipment in the building object is obtained; calculating distance information according to the initialized position information and the optimized position information; screening the broadband equipment according to the distance information to determine effective broadband equipment; calculating to obtain the position information of the building object after secondary optimization based on a preset clustering algorithm and the initialized position information corresponding to the effective broadband equipment; and combining the position information after the secondary optimization with the MR data sample to obtain the target data sample. In this embodiment, after the broadband device is screened according to the distance information, the secondarily-optimized position information of the building object is further calculated based on the clustering algorithm, and the secondarily-optimized position information can more accurately represent the position of the building object, so as to meet the requirement of acquiring the target data sample with higher precision.

Further, referring to fig. 7, a flowchart is provided in a sixth embodiment of the positioning method according to the present application, based on the embodiment shown in fig. 4, step S01, further refines an MR data sample of a networking terminal corresponding to a broadband device in the building object, including:

Step S018, acquiring an MR data sample of a networking terminal in a preset range, wherein the building object is located in the preset range.

Specifically, one or more MR signal strength measurements may be initiated to obtain MR data samples for a preset range of networked terminals. The preset range refers to a range of the building object and the vicinity thereof, and the acquired MR data samples of the networking terminals in the preset range include not only the MR data samples of the networking terminals corresponding to the broadband devices in the building object, but also the MR data samples of the networking terminals in the vicinity of the building object.

And step S019, screening the MR data samples of the networking terminals in the preset range, and reserving the MR data samples of the networking terminals corresponding to the broadband equipment in the building object.

In particular, for the procedure of supplementing the localization fingerprint database of the present embodiment, MR data samples of networked terminals in the vicinity of the building object belong to redundant data. Therefore, MR data samples of the networking terminals in a preset range need to be screened, and MR data samples of the networking terminals corresponding to the broadband devices in the building object are reserved.

According to the scheme, the MR data sample of the networking terminal in the preset range is obtained, wherein the building object is located in the preset range; and screening the MR data samples of the networking terminals in the preset range, and reserving the MR data samples of the networking terminals corresponding to the broadband equipment in the building object. In this embodiment, MR data samples of the building object and surrounding networking terminals thereof may be obtained, MR data samples of networking terminals corresponding to broadband devices in the building object may be further screened and reserved, MR data sample collection is completed pertinently, and data resources are provided for supplementing the positioning fingerprint database.

Further, referring to fig. 8, a flowchart is provided in a seventh embodiment of the positioning method according to the present application, based on the embodiment shown in fig. 7, step S018, before obtaining an MR data sample of a networking terminal in a preset range, further includes:

and step S0110, detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively.

Specifically, the number of networked terminals within a building object is different in different time periods, for example, the number of networked terminals of a residential building is generally greater during weekday and night than during weekday and day. The acquisition coverage of the target data sample will also be higher when the number of networked terminals within the building object is greater.

In order to increase the acquisition coverage of the target data samples as much as possible, several time periods may be preset, for example 8 to 12 pm, 9 to 12 am, 14 to 18 pm. And detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively, wherein the terminal networking state at least reflects the number of networking terminals of the broadband equipment and can also carry the identification of the networking terminals of the broadband equipment on the basis.

And step S0111, determining a target time period from the plurality of time periods according to the terminal networking state.

Specifically, after detecting the terminal networking states corresponding to the time periods, the target time period may be determined from among the time periods further according to the terminal networking states. For example, the time period in which the number of networking terminals is the largest is determined as the target time period, or the time period in which the number of broadband devices to which networking terminals are connected (i.e., the broadband devices to which corresponding networking terminals are connected are online) is the largest is determined as the target time period. In addition, the target time period may be determined according to the actual requirement, and is not limited to the two modes.

It is understood that the time span of the target time period and the preset number of time periods may not be equivalent. For example, the predetermined period of time is 8 to 12 pm, and the target period of time is 9 to 11 pm, and the target period of time is within the predetermined period of time, but is not completely equivalent.

Step S0112, in the target period, performing the steps at least once: and acquiring MR data samples of the networking terminal in a preset range.

Specifically, one or more MR signal intensity measurements may be initiated within a target time period to obtain MR data samples for a preset range of networked terminals. If one MR signal strength measurement is initiated, then a time may be selected for initiation during the target time period; if multiple MR signal strength measurements are activated, the activation can be performed according to a preset activation frequency for a target period of time.

According to the scheme, the terminal networking state of the broadband equipment in the building object is detected in a preset plurality of time periods; determining a target time period from among the plurality of time periods according to the terminal networking state; the steps are performed at least once within the target time period: and acquiring MR data samples of the networking terminal in a preset range. In this embodiment, by detecting the terminal networking states in different time periods, a suitable target time period can be determined, and the MR data sample is acquired in the target time period, so that the acquisition coverage of the MR data sample can be effectively improved.

In addition, the embodiment of the application also provides a positioning device, which comprises:

the acquisition module is used for acquiring MR data to be positioned;

the matching module is used for matching the MR data to be positioned with the grid units in the positioning fingerprint database to obtain matched grid units;

the positioning module is used for determining the position corresponding to the MR data to be positioned according to the matched grid units;

the positioning fingerprint database comprises a grid unit constructed based on measurement report MR data samples of networking terminals corresponding to broadband equipment in a building object; the matching module comprises a matching unit; the matching unit is used for matching the MR data to be positioned with the grid units in the positioning fingerprint database based on a preset normalized Euclidean distance algorithm to obtain the matched grid units;

The positioning device further comprises a first acquisition unit, a first combination unit and a first construction unit; the first acquisition unit is used for acquiring the position information of the building object and MR data samples of networking terminals corresponding to broadband equipment in the building object; the first combination unit is configured to combine the position information and the MR data sample to obtain a target data sample; the first construction unit is used for constructing a grid unit of the positioning fingerprint database based on the target data sample;

the first acquisition unit comprises a second acquisition unit, an analysis unit and a first optimization unit; the second obtaining unit is used for obtaining the using address information of the broadband account corresponding to the broadband equipment in the building object; the analyzing unit is used for analyzing the using address information into normalized address information meeting preset specifications; the first optimizing unit is used for obtaining optimized position information of the building object according to the normalized address information; the first combination unit comprises a second combination unit; the second combination unit is configured to combine the optimized position information and the MR data sample to obtain the target data sample;

The first acquisition unit further comprises a third acquisition unit, a calculation unit, a first screening unit and a second optimization unit; the third obtaining unit is used for obtaining initialization position information corresponding to broadband equipment in the building object; the calculating unit is used for calculating distance information according to the initialized position information and the optimized position information; the first screening unit is used for screening the broadband equipment according to the distance information and determining effective broadband equipment; the second optimizing unit is used for calculating and obtaining the position information of the building object after secondary optimization based on a preset clustering algorithm and the initialization position information corresponding to the effective broadband equipment; the second combination unit comprises a third combination unit; the third combination unit is configured to combine the second optimized position information and the MR data sample to obtain the target data sample;

the first acquisition unit further comprises a fourth acquisition unit and a second screening unit; the fourth obtaining unit is configured to obtain an MR data sample of a networking terminal in a preset range, where the building object is located in the preset range; the second screening unit is configured to screen MR data samples of the networking terminal in the preset range, and reserve MR data samples of the networking terminal corresponding to the broadband device in the building object;

The first acquisition unit further comprises a detection unit, a determination unit and an execution unit; the detection unit is used for detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively; the determining unit is used for determining a target time period from the time periods according to the terminal networking state; the execution unit is configured to execute, at least once, the steps in the target time period: and acquiring MR data samples of the networking terminal in a preset range.

The positioning principle and implementation process are implemented in this embodiment, please refer to the above embodiments, and are not repeated herein.

In addition, the embodiment of the application also provides a terminal device, which comprises a memory, a processor and a positioning program stored in the memory and capable of running on the processor, wherein the positioning program realizes the steps of the positioning method when being executed by the processor.

Because the positioning program is executed by the processor and adopts all the technical schemes of all the embodiments, the positioning program has at least all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.

In addition, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a positioning program, and the positioning program realizes the steps of the positioning method when being executed by a processor.

Because the positioning program is executed by the processor and adopts all the technical schemes of all the embodiments, the positioning program has at least all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.

Compared with the prior art, the positioning method, the positioning device, the terminal equipment and the storage medium provided by the embodiment of the application are characterized in that the MR data of the measurement report to be positioned is obtained; matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units; and determining the position corresponding to the MR data to be positioned according to the matched grid unit. Based on the scheme of the application, the grid units in the positioning fingerprint database are provided with the signal fingerprint feature vectors, and the corresponding actual geographic positions are associated. By matching the MR data to be located with the grid cells, the position of the MR data to be located can be determined from the position of the matched grid cells. Therefore, the positioning method based on the positioning fingerprint database can effectively improve the positioning accuracy of MR data.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.

The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) to perform the method of each embodiment of the present application.

The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.

Claims (10)

1. A positioning method, characterized in that the positioning method comprises:

acquiring measurement report MR data to be positioned;

matching the MR data to be positioned with grid units in a positioning fingerprint database to obtain matched grid units;

and determining the position corresponding to the MR data to be positioned according to the matched grid unit.

2. The positioning method according to claim 1, wherein the positioning fingerprint database includes a grid unit constructed based on position information of a building object and measurement report MR data samples of networking terminals corresponding to broadband devices within the building object;

the step of matching the MR data to be located with the grid units in the location fingerprint database to obtain matched grid units includes:

and matching the MR data to be positioned with the grid units in the positioning fingerprint database based on a preset normalized Euclidean distance algorithm to obtain the matched grid units.

3. The positioning method of claim 1, wherein prior to the step of matching the MR data to be positioned with grid cells in the positioning fingerprint database, further comprising:

acquiring position information of a building object, and acquiring an MR data sample of a networking terminal corresponding to broadband equipment in the building object;

combining the position information and the MR data sample to obtain a target data sample;

and constructing a grid unit of the positioning fingerprint database based on the target data sample.

4. A positioning method as set forth in claim 3, wherein the step of acquiring the position information of the building object includes:

acquiring the use address information of a broadband account corresponding to broadband equipment in the building object;

resolving the using address information into normalized address information meeting preset specifications;

obtaining optimized position information of the building object according to the normalized address information;

the step of combining the position information and the MR data samples to obtain a target data sample comprises:

and combining the optimized position information and the MR data sample to obtain the target data sample.

5. The positioning method of claim 4, wherein after the step of obtaining the optimized position information of the building object based on the normalized address information, the step of combining the optimized position information with the MR data samples to obtain the target data samples is preceded by the step of:

acquiring initialization position information corresponding to broadband equipment in the building object;

calculating distance information according to the initialized position information and the optimized position information;

screening the broadband equipment according to the distance information to determine effective broadband equipment;

calculating to obtain the position information of the building object after secondary optimization based on a preset clustering algorithm and the initialized position information corresponding to the effective broadband equipment;

the step of combining the optimized position information and the MR data samples to obtain the target data samples includes:

and combining the position information after the secondary optimization with the MR data sample to obtain the target data sample.

6. A positioning method as claimed in claim 3, wherein the step of obtaining MR data samples of a networked terminal corresponding to a broadband device within the building object comprises:

Acquiring an MR data sample of a networking terminal in a preset range, wherein the building object is positioned in the preset range;

and screening the MR data samples of the networking terminals in the preset range, and reserving the MR data samples of the networking terminals corresponding to the broadband equipment in the building object.

7. The positioning method of claim 6, wherein prior to the step of acquiring MR data samples for a predetermined range of networked terminals, further comprising:

detecting the terminal networking state of the broadband equipment in the building object in a preset plurality of time periods respectively;

determining a target time period from among the plurality of time periods according to the terminal networking state;

the steps are performed at least once within the target time period: and acquiring MR data samples of the networking terminal in a preset range.

8. A positioning device, the positioning device comprising:

the acquisition module is used for acquiring MR data to be positioned;

the matching module is used for matching the MR data to be positioned with the grid units in the positioning fingerprint database to obtain matched grid units;

and the positioning module is used for determining the position corresponding to the MR data to be positioned according to the matched grid units.

9. A terminal device, characterized in that it comprises a memory, a processor and a positioning program stored on the memory and executable on the processor, which positioning program, when executed by the processor, implements the steps of the positioning method according to any of claims 1-7.

10. A computer readable storage medium, characterized in that it has stored thereon a positioning program, which when executed by a processor, implements the steps of the positioning method according to any of claims 1-7.