CN109640271B - Method for identifying block characteristic fingerprint - Google Patents
Method for identifying block characteristic fingerprint Download PDFInfo
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- CN109640271B CN109640271B CN201811550838.2A CN201811550838A CN109640271B CN 109640271 B CN109640271 B CN 109640271B CN 201811550838 A CN201811550838 A CN 201811550838A CN 109640271 B CN109640271 B CN 109640271B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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Abstract
The invention relates to the technical field of data analysis, in particular to a block characteristic fingerprint identification method. The method comprises the following steps: s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider; s2: calculating the coverage surface of the base station according to the base station engineering parameters; s3: and calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form the characteristic fingerprint of the geographic entity. The invention matches the position relation of each geographical block entity and the base station by combining the base station engineering parameters with the actual position coordinate point set of the geographical entity to form the characteristic fingerprint of the geographical entity. The existing grid type positioning mode is thoroughly abandoned, accurate identification of which specific geographic block entity a mobile phone user is located at a certain moment is facilitated, and powerful support is provided for subsequent analysis.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a block characteristic fingerprint identification method.
Background
With the improvement of the living standard of people, the mobile phone becomes a living necessity of everyone, and the mobile phone can be carried with everywhere. The mobile phone is required to realize the networking function and is inevitably communicated with the nearest base station, when the mobile phone moves from the coverage area of one base station to the coverage area of another base station, the mobile phone is automatically switched to be connected with the other base station, and therefore, the motion trail of a person carrying the mobile phone can be known by observing the motion trail of the mobile phone. However, since the coverage area of the base station is one surface, only the presence of the handset in the coverage area of the base station can be known, but the specific location of the presence is unknown.
Currently, there are several ways to perform positioning by using data of a communication operator:
1. MR signaling data fingerprinting: and training MR data containing the position information into a fingerprint library, and performing fingerprint matching on the MR without the position according to the characteristics to form the position information.
2. MR signaling multilateration: and calculating the distance according to the signal receiving field intensity and the path loss formula of the cell and at least the adjacent cell and the transceiving time difference.
The positioning results for the user in the above manner are typically presented in a 100 x 100 meter grid. The map is divided into grid-type squares of 100 × 100 meters according to the longitude and latitude, and the user is positioned in the grid mode, and only the user in which grid is located is known, but the specific position of the user is not known. Meanwhile, when the grid of 100 x 100 meters is positioned, the artificially divided grid has no representative meaning and has no reference value. Meanwhile, the positioning result of rasterization is difficult to match with a specific geographic position, and the commercial value is low. Therefore, the existing rough map block identification method is changed, accurate positioning of mobile phone users is facilitated, and the problem to be solved urgently is solved.
Disclosure of Invention
The invention provides a block characteristic fingerprint identification method, which solves the problem that in the prior art, the positioning result of a user can only be presented in a grid mode.
The technical scheme adopted by the invention is as follows:
a method for block feature fingerprint identification comprises the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form a geographic entity characteristic fingerprint;
the calculation method for calculating the matching relationship between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity comprises the following steps:
s301: according to the coverage range of the geographic entity and the coverage surface of the base station, calculating to obtain the cross area S covered by the geographic entity and the base station through an gis space calculation engine; the coverage area of the geographic entity is as follows: connecting every two actual position coordinate points of the geographic entity provided by a map service provider to form a closed coverage area, namely a geographic entity coverage area;
s302: calculating the coverage area Sb of the base station according to the engineering parameters of the base station;
s303: calculating a spatial relationship coefficient alpha of the geographic entity and the base station through an equation according to the coverage area Sb and the cross area S of the base station, wherein the calculation equation is as follows: α ═ S ÷ Sb;
s304: outputting a relationship of a geographic entity and a base station covering the geographic entity:
{B,{Lc1,α},{Lc2,α}{Lc3,α}..{Lcn,α}}
and B is a geographic entity, and Lc1, Lc2, Lc3 and Lcn are base station numbers.
Preferably, the base station engineering parameters include a regional area code, a base station identifier, a network type, an antenna azimuth, a base station coverage type, a base station antenna position longitude coordinate, and a base station antenna position latitude coordinate.
Preferably, the coverage type of the base station includes an indoor type and a non-indoor type.
Preferably, in the above aspect, a coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient.
Preferably, in the above aspect, the specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
Preferably, the antenna types include an omni-directional antenna and a directional antenna.
Preferably, in the above technical solution, the method for calculating the coverage area of the omni-directional antenna base station includes: and taking the longitude and latitude of the antenna as a central point, extending the length of the coverage radius R of the base station outwards every 45 degrees to respectively obtain eight coordinate points, and connecting every two adjacent coordinate points by using straight lines to form a closed base station coverage area, namely obtaining the coverage surface of the omnidirectional antenna base station.
Preferably, in the above technical solution, the method for calculating the coverage area of the directional antenna base station includes: taking the longitude and latitude of the antenna as a central point, respectively extending the length of a coverage radius R of the base station outwards according to angles of A, A + H/6, A + H/3, A + H/2, A-H/6, A-H/3 and A + H/2 to obtain seven coordinate points, connecting every two adjacent coordinate points with straight lines, and respectively connecting the two coordinate points at the two ends with the longitude and latitude points of the antenna to form a closed base station coverage area, namely obtaining a coverage surface of the omnidirectional antenna base station; the angle A is the antenna azimuth angle, and the angle H is the horizontal lobe angle.
Preferably, in the above technical solution, the horizontal lobe angle is calculated by 180 degrees if the number of directional antennas of the base station is less than or equal to 2, and otherwise, 120 degrees.
The invention has the beneficial effects that:
the invention matches the position relation of each geographical block entity and the base station by combining the base station engineering parameters with the actual position coordinate point set of the geographical entity to form the characteristic fingerprint of the geographical entity. The existing grid type positioning mode is thoroughly abandoned, accurate identification of which specific geographic block entity a mobile phone user is located at a certain moment is facilitated, and powerful support is provided for subsequent analysis.
Detailed Description
The present invention will be described in detail below.
The invention will be further illustrated by means of specific examples. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. Specific structural and functional details disclosed herein are merely illustrative of example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, B exists alone, and A and B exist at the same time, and the term "/and" is used herein to describe another association object relationship, which means that two relationships may exist, for example, A/and B, may mean: a alone, and both a and B alone, and further, the character "/" in this document generally means that the former and latter associated objects are in an "or" relationship.
It will be understood that when an element is referred to as being "connected," "connected," or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. In contrast, when an element is referred to as being "directly adjacent" or "directly coupled" to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between … …" versus "directly between … …", "adjacent" versus "directly adjacent", etc.).
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order. For example, the functions/acts may in fact be performed substantially concurrently or may sometimes be performed in the reverse order, depending upon the functionality/acts involved.
In the following description, specific details are provided to facilitate a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring example embodiments.
Example 1:
the embodiment provides a block characteristic fingerprint identification method, which comprises the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: and calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form the characteristic fingerprint of the geographic entity.
The calculation method for calculating the matching relationship between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity comprises the following steps:
s301: according to the coverage range of the geographic entity and the coverage surface of the base station, calculating to obtain the cross area S covered by the geographic entity and the base station through an gis space calculation engine; the coverage area of the geographic entity is as follows: connecting every two actual position coordinate points of the geographic entity provided by a map service provider to form a closed coverage area, namely a geographic entity coverage area;
s302: calculating the coverage area Sb of the base station according to the engineering parameters of the base station;
s303: calculating a spatial relationship coefficient alpha of the geographic entity and the base station through an equation according to the coverage area Sb and the cross area S of the base station, wherein the calculation equation is as follows: α ═ S ÷ Sb;
s304: outputting a relationship of a geographic entity and a base station covering the geographic entity:
{B,{Lc1,α},{Lc2,α}{Lc3,α}..{Lcn,α}}
and B is a geographic entity, and Lc1, Lc2, Lc3 and Lcn are base station numbers.
The base station engineering parameters comprise a regional area code, a base station identification code, a network system, an antenna type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate.
The base station coverage type includes an indoor type and a non-indoor type.
The coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient.
The specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
The antenna types include omni-directional antennas and directional antennas.
The method for calculating the coverage area of the base station of the omnidirectional antenna comprises the following steps: and taking the longitude and latitude of the antenna as a central point, extending the length of the coverage radius R of the base station outwards every 45 degrees to respectively obtain eight coordinate points, and connecting every two adjacent coordinate points by using straight lines to form a closed base station coverage area, namely obtaining the coverage surface of the omnidirectional antenna base station.
The method for calculating the coverage area of the directional antenna base station comprises the following steps: taking the longitude and latitude of the antenna as a central point, respectively extending the length of a coverage radius R of the base station outwards according to angles of A, A + H/6, A + H/3, A + H/2, A-H/6, A-H/3 and A + H/2 to obtain seven coordinate points, connecting every two adjacent coordinate points with straight lines, and respectively connecting the two coordinate points at the two ends with the longitude and latitude points of the antenna to form a closed base station coverage area, namely obtaining a coverage surface of the omnidirectional antenna base station; the angle A is the antenna azimuth angle, and the angle H is the horizontal lobe angle.
The horizontal lobe angle calculation method is that if the number of the directional antennas of the base station is less than or equal to 2, the angle is 180 degrees, otherwise, the angle is 120 degrees.
Example 2:
the embodiment provides a block characteristic fingerprint identification method, which comprises the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: and calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form the characteristic fingerprint of the geographic entity.
The invention matches the position relation of each geographical block entity and the base station by combining the base station engineering parameters with the actual position coordinate point set of the geographical entity to form the characteristic fingerprint of the geographical entity. The existing grid type positioning mode is thoroughly abandoned, accurate identification of which specific geographic block entity a mobile phone user is located at a certain moment is facilitated, and powerful support is provided for subsequent analysis.
Example 3:
the embodiment provides a space-time big data analysis system supporting the invention, which comprises a calculation layer and a service layer, wherein:
the calculation layer is used for calculating a track chain of each mobile phone user every day according to base station engineering parameters, mobile service signaling data and a coordinate point set of an actual position of a space block, wherein the base station engineering parameters, the mobile service signaling data and the coordinate point set are provided by a map service provider, and labeling is carried out on each mobile phone user;
and the service layer extracts different data in the calculation layer according to different business requirements, and obtains corresponding business model data after counting the extracted data.
The tag content includes occupation, work and residence attributes of the mobile phone user.
The base station engineering parameters comprise a regional area code, a base station identification code, a network type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate; the mobile service signaling data comprises time, user numbers and base station numbers.
The coverage type of the base station comprises an indoor type and a non-indoor type; the antenna types comprise an omnidirectional antenna and a directional antenna; the coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient. The specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
The service layer converts the obtained business model data into one or more of API, SDK and visual components for the third-party software to call.
And the computing layer and the service layer are both provided with system detection modules, the system detection modules are used for detecting whether the operation of each module in the system is normal or not, and if the system operation state is found to be abnormal, alarm information is sent out.
The computation layer includes:
the track library is used for storing a track chain of each mobile phone user every day;
the population library is used for storing each mobile phone user label;
the basic database is used for storing the acquired base station engineering parameters, mobile service signaling data and a set of spatial block actual position coordinate points provided by a map service provider;
and the model library is used for storing an algorithm module, and the algorithm module is used for obtaining a track library and a population library according to the content of the basic database.
The service layer comprises:
the service DB is used for storing data read in a track library and a population library of the computing layer according to different service requirements;
the third-party data access/acquisition module is used for receiving the service data input by a third party or actively acquiring the third-party service data;
and the business service module is used for counting the data stored in the business DB according to business needs to obtain corresponding business model data.
The mode of actively collecting the third-party service data is to read the required information in the search engine through a web crawler.
The service layer also comprises a user management module, and the user management module is used for user registration and user authority management; the user management module is respectively connected with a user library and an operation and maintenance library in a data mode, the user library is used for storing registered user information, and the operation and maintenance library is used for storing system operation data and operation logs.
The service layer also comprises a charging module, and the charging module is used for charging the user and managing the balance according to the consumption condition of the user. After the user recharges, the charging module records the balance after the user recharges, when the user accesses the data in the calculation layer, the charging is carried out according to the population number, the geographical area range, the geographical precision, the service use duration, the label use type and the use depth of the tracking data included in the user access data, the fee is deducted from the balance in real time, and the deducted balance is displayed.
Example 4:
the embodiment provides a comprehensive charging method of space-time big data based on the invention, which comprises the following steps:
s1, the calculation layer calculates the track chain of each mobile phone user every day according to the base station engineering parameters provided by the communication operator, the mobile service signaling data and the coordinate point set of the actual position of the space block provided by the map service provider, and marks each mobile phone user with a label; storing the obtained track chain in a track library, and storing the obtained mobile phone user tag in a population library; the label content comprises the occupation, work and residence attributes of the mobile phone user;
s2, after the user registers the account number in the service layer and charges, the data stored in the calculation layer can be accessed, after the user charges, the charging module records the balance of the user after charging, when the user accesses the data in the calculation layer, the charging is carried out according to the content of the data accessed by the user, the fee is deducted from the balance in real time, and the deducted balance is displayed.
In step S2, the content of the user access data includes one or more of population, geographic area, geographic accuracy, service usage duration, tracking data usage depth and tag usage type.
The computation layer includes:
the track library is used for storing a track chain of each mobile phone user every day;
the population library is used for storing each mobile phone user label;
the basic database is used for storing the acquired base station engineering parameters, mobile service signaling data and a set of spatial block actual position coordinate points provided by a map service provider;
a model base for storing algorithm modules for obtaining a track base and a population base according to the contents of the basic database
The service layer comprises:
the service DB is used for storing data read in a track library and a population library of the computing layer according to different service requirements;
the third-party data access/acquisition module is used for receiving the service data input by a third party or actively acquiring the third-party service data;
and the business service module is used for counting the data stored in the business DB according to business needs to obtain corresponding business model data. The mode of actively collecting the third-party service data is to read the required information in the search engine through a web crawler.
The service layer also comprises a user management module, and the user management module is used for user registration and user authority management; the user management module is respectively connected with a user library and an operation and maintenance library in a data mode, the user library is used for storing registered user information, and the operation and maintenance library is used for storing system operation data and operation logs.
The service layer also comprises a charging module, and the charging module is used for charging the user and managing the balance according to the consumption condition of the user. After the user recharges, the charging module records the balance after the user recharges, when the user accesses the data in the calculation layer, the charging is carried out according to the population number, the geographical area range, the geographical precision, the service use duration, the label use type and the use depth of the tracking data included in the user access data, the fee is deducted from the balance in real time, and the deducted balance is displayed.
And the computing layer and the service layer are both provided with system detection modules, the system detection modules are used for detecting whether the operation of each module in the system is normal or not, and if the system operation state is found to be abnormal, alarm information is sent out.
And when the balance of the user is lower than the preset value, the charging module provides the recharging reminding information for the user in time.
The base station engineering parameters comprise a regional area code, a base station identification code, a network type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate; the mobile service signaling data comprises time, user numbers and base station numbers.
The coverage type of the base station comprises an indoor type and a non-indoor type; the antenna types comprise an omnidirectional antenna and a directional antenna; the coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient. The specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
A space-time big data analysis system supporting the method comprises a calculation layer and a service layer, wherein:
the calculation layer is used for calculating a track chain of each mobile phone user every day according to base station engineering parameters, mobile service signaling data and a coordinate point set of an actual position of a space block, wherein the base station engineering parameters, the mobile service signaling data and the coordinate point set are provided by a map service provider, and labeling is carried out on each mobile phone user;
and the service layer extracts different data in the calculation layer according to different business requirements, and obtains corresponding business model data after counting the extracted data.
The tag content includes occupation, work and residence attributes of the mobile phone user.
The base station engineering parameters comprise a regional area code, a base station identification code, a network type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate; the mobile service signaling data comprises time, user numbers and base station numbers.
The coverage type of the base station comprises an indoor type and a non-indoor type; the antenna types comprise an omnidirectional antenna and a directional antenna; the coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient. The specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
The service layer converts the obtained business model data into one or more of API, SDK and visual components for the third-party software to call.
And the computing layer and the service layer are both provided with system detection modules, the system detection modules are used for detecting whether the operation of each module in the system is normal or not, and if the system operation state is found to be abnormal, alarm information is sent out.
The computation layer includes:
the track library is used for storing a track chain of each mobile phone user every day;
the population library is used for storing each mobile phone user label;
the basic database is used for storing the acquired base station engineering parameters, mobile service signaling data and a set of spatial block actual position coordinate points provided by a map service provider;
and the model library is used for storing an algorithm module, and the algorithm module is used for obtaining a track library and a population library according to the content of the basic database.
The service layer comprises:
the service DB is used for storing data read in a track library and a population library of the computing layer according to different service requirements;
the third-party data access/acquisition module is used for receiving the service data input by a third party or actively acquiring the third-party service data;
and the business service module is used for counting the data stored in the business DB according to business needs to obtain corresponding business model data.
The mode of actively collecting the third-party service data is to read the required information in the search engine through a web crawler.
The service layer also comprises a user management module, and the user management module is used for user registration and user authority management; the user management module is respectively connected with a user library and an operation and maintenance library in a data mode, the user library is used for storing registered user information, and the operation and maintenance library is used for storing system operation data and operation logs.
The service layer also comprises a charging module, and the charging module is used for charging the user and managing the balance according to the consumption condition of the user. After the user recharges, the charging module records the balance after the user recharges, when the user accesses the data in the calculation layer, the charging is carried out according to the population number, the geographical area range, the geographical precision, the service use duration, the label use type and the use depth of the tracking data included in the user access data, the fee is deducted from the balance in real time, and the deducted balance is displayed.
Example 4:
the embodiment provides a block characteristic fingerprint identification method, which is characterized by comprising the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: and calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form the characteristic fingerprint of the geographic entity.
The calculation method for calculating the matching relationship between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity comprises the following steps:
s301: according to the coverage range of the geographic entity and the coverage surface of the base station, calculating to obtain the cross area S covered by the geographic entity and the base station through an gis space calculation engine;
s302: calculating the coverage area Sb of the base station according to the engineering parameters of the base station;
s303: calculating a spatial relationship coefficient alpha of the geographic entity and the base station through an equation according to the coverage area Sb and the cross area S of the base station, wherein the calculation equation is as follows: α ═ S ÷ Sb;
s304: outputting a relationship of a geographic entity and a base station covering the geographic entity:
{B,{Lc1,α},{Lc2,α}{Lc3,α}..{Lcn,α}}
and B is a geographic entity, and Lc1, Lc2, Lc3 and Lcn are base station numbers.
Example 5:
the embodiment provides a block characteristic fingerprint identification method, which comprises the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: and calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the actual position coordinate point set of the space block to form the characteristic fingerprint of the geographic entity.
The calculation method for calculating the matching relationship between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity comprises the following steps:
s301: according to the coverage range of the geographic entity and the coverage surface of the base station, calculating to obtain the cross area S covered by the geographic entity and the base station through an gis space calculation engine;
s302: calculating the coverage area Sb of the base station according to the engineering parameters of the base station;
s303: calculating a spatial relationship coefficient alpha of the geographic entity and the base station through an equation according to the coverage area Sb and the cross area S of the base station, wherein the calculation equation is as follows: α ═ S ÷ Sb;
s304: outputting a relationship of a geographic entity and a base station covering the geographic entity:
{B,{Lc1,α},{Lc2,α}{Lc3,α}..{Lcn,α}}
and B is a geographic entity, and Lc1, Lc2, Lc3 and Lcn are base station numbers.
The base station engineering parameters comprise a regional area code, a base station identification code, a network system, an antenna type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate.
The base station coverage type includes an indoor type and a non-indoor type.
The coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient.
The antenna types include omni-directional antennas and directional antennas.
The method for calculating the coverage area of the base station of the omnidirectional antenna comprises the following steps: and taking the longitude and latitude of the antenna as a central point, extending the length of the coverage radius R of the base station outwards every 45 degrees to respectively obtain eight coordinate points, and connecting every two adjacent coordinate points by using straight lines to form a closed base station coverage area, namely obtaining the coverage surface of the omnidirectional antenna base station.
The present invention is not limited to the above-described alternative embodiments, and various other forms of products can be obtained by anyone in light of the present invention. The above detailed description should not be taken as limiting the scope of the invention, which is defined in the claims, and which the description is intended to be interpreted accordingly.
Claims (9)
1. A method for block feature fingerprint identification is characterized by comprising the following steps:
s1: acquiring base station engineering parameters provided by a communication operator and a geographical entity actual position coordinate point set provided by a map service provider;
s2: calculating the coverage surface of the base station according to the base station engineering parameters;
s3: calculating the matching relation between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity to form a characteristic fingerprint of the geographic entity;
the calculation method for calculating the matching relationship between the geographic entity and the base station according to the coverage surface of the base station and the coordinate point set of the actual position of the geographic entity comprises the following steps:
s301: according to the coverage range of the geographic entity and the coverage surface of the base station, calculating to obtain the cross area S covered by the geographic entity and the base station through an gis space calculation engine;
s302: calculating the coverage area Sb of the base station according to the engineering parameters of the base station;
s303: calculating a spatial relationship coefficient alpha of the geographic entity and the base station through an equation according to the coverage area Sb and the cross area S of the base station, wherein the calculation equation is as follows: α ═ S ÷ Sb;
s304: outputting a relationship of a geographic entity and a base station covering the geographic entity:
{B,{Lc1,α},{Lc2,α}{Lc3,α}..{Lcn,α}}
and B is a geographic entity, and Lc1, Lc2, Lc3 and Lcn are base station numbers.
2. The method of block feature fingerprinting of claim 1, wherein: the base station engineering parameters comprise a regional area code, a base station identification code, a network system, an antenna type, an antenna azimuth angle, a base station coverage type, a base station antenna position longitude coordinate and a base station antenna position latitude coordinate.
3. The method of block feature fingerprinting of claim 2, wherein: the base station coverage type includes an indoor type and a non-indoor type.
4. The method of block feature fingerprinting of claim 3, wherein: the coverage radius R of the indoor base station is a fixed value; the coverage radius R of the non-indoor base station is the product of the longitude and latitude coordinates of the base station antenna and the average distance of the nearest three non-indoor base stations and a specific coefficient.
5. The method of block feature fingerprinting of claim 4, wherein: the specific coefficient is 1.6; the coverage radius R of the indoor base station is 400 meters by default.
6. The method of block feature fingerprinting of claim 4, wherein: the antenna types include omni-directional antennas and directional antennas.
7. The method of claim 6, wherein the omni-directional antenna base station coverage is calculated by: and taking the longitude and latitude of the antenna as a central point, extending the length of the coverage radius R of the base station outwards every 45 degrees to respectively obtain eight coordinate points, and connecting every two adjacent coordinate points by using straight lines to form a closed base station coverage area, namely obtaining the coverage surface of the omnidirectional antenna base station.
8. The method of claim 6, wherein the coverage area of the directional antenna base station is calculated by: taking the longitude and latitude of the antenna as a central point, respectively extending the length of a coverage radius R of the base station outwards according to angles of A, A + H/6, A + H/3, A + H/2, A-H/6, A-H/3 and A + H/2 to obtain seven coordinate points, connecting every two adjacent coordinate points with straight lines, and respectively connecting the two coordinate points at the two ends with the longitude and latitude points of the antenna to form a closed base station coverage area, namely obtaining a coverage surface of the omnidirectional antenna base station; the angle A is the antenna azimuth angle, and the angle H is the horizontal lobe angle.
9. The method of block feature fingerprinting of claim 8, wherein: the horizontal lobe angle calculation method is that if the number of the directional antennas of the base station is less than or equal to 2, the angle is 180 degrees, otherwise, the angle is 120 degrees.
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| CN107426685A (en) * | 2017-04-20 | 2017-12-01 | 北京邮电大学 | A kind of method and apparatus for obtaining multimode location fingerprint data storehouse |
| CN108243495A (en) * | 2016-12-23 | 2018-07-03 | 亿阳信通股份有限公司 | A kind of location fingerprint database building method, device and method of locating terminal |
| CN108882174A (en) * | 2018-07-03 | 2018-11-23 | 北京三快在线科技有限公司 | Mobile terminal locating method, device, electronic equipment and storage medium |
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| CN108243495A (en) * | 2016-12-23 | 2018-07-03 | 亿阳信通股份有限公司 | A kind of location fingerprint database building method, device and method of locating terminal |
| CN107426685A (en) * | 2017-04-20 | 2017-12-01 | 北京邮电大学 | A kind of method and apparatus for obtaining multimode location fingerprint data storehouse |
| CN108882174A (en) * | 2018-07-03 | 2018-11-23 | 北京三快在线科技有限公司 | Mobile terminal locating method, device, electronic equipment and storage medium |
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