CN113207082A - Mobile network data positioning system and method based on traffic route position fingerprint database - Google Patents
Mobile network data positioning system and method based on traffic route position fingerprint database Download PDFInfo
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Abstract
The invention discloses a mobile network data positioning system based on a traffic route position fingerprint database, which comprises: the line basic data acquisition module automatically acquires line basic data and generates a basic information sampling point sequence according to a sampling time sequence; the circuit position fingerprint library module generates a circuit track reference point sequence with circuits having the same circuit direction and uniform position intervals, generates a circuit position fingerprint sample library according to the circuit track reference point sequence data, and automatically updates the position fingerprint sample library; the network data analysis adaptation module generates a sampling point sequence to be positioned, which contains a mobile network signal; and the terminal positioning processing module performs classification identification on the data of the sampling point to be positioned and performs fingerprint positioning on the line position of the sampling point. The system improves the construction efficiency of the position fingerprint database, the real-time performance and the effectiveness of fingerprint data are good, the position correlation and the directionality exist among fingerprint positions, and the accuracy and the effectiveness of terminal positioning by using mobile network signal data in a traffic line scene are improved.
Description
Technical Field
The invention relates to the technical field of software, in particular to a mobile network data positioning system, a mobile network data positioning method, a mobile network data positioning terminal and a mobile network data positioning medium based on a traffic route position fingerprint database.
Background
Currently, location services are increasingly widely applied in the fields of life services and specific industry applications, such as network travel services, take-out services, internet of things services, intelligent traffic scheduling and the like. The existing position positioning technology is mainly divided into two main technologies of terminal side resolving positioning and network side resolving positioning. The terminal side resolving positioning technology mainly comprises satellite navigation positioning technologies such as GPS positioning and Beidou positioning, position positioning service is provided through a satellite positioning module of the terminal equipment, the satellite positioning technology is mature and high in positioning precision, and accurate positioning service cannot be provided for the terminal equipment under the condition that no satellite positioning signal or no satellite positioning function exists; the network side resolving positioning is mainly used for positioning by adopting a geometric measurement positioning method or a position fingerprint positioning method according to wireless network positioning signal data (including wireless signal power measurement data, wireless signal time measurement data and wireless signal angle measurement data), the geometric measurement positioning method such as a triangulation positioning method generally depends on information source position information of a wireless network (wireless network information sources generally refer to base stations, WIFI equipment and other wireless signal transmitting equipment), the wireless signal position fingerprint positioning method has the advantages that effective positioning cannot be carried out under the condition that information source position information is lacked or the number of measured information sources is less than 3, a wireless signal position fingerprint database needs to be constructed, accuracy and effectiveness of data of the wireless signal position fingerprint database greatly affect positioning effects, the efficiency of constructing the wireless signal fingerprint database in a traditional manual mode is low, and instantaneity and effectiveness of fingerprint data are poor; the position fingerprint database constructed by using the network signal data automatically acquired by random positions has the defects of uneven fingerprint position distribution, lack of position correlation among fingerprint positions and influence on the positioning accuracy and effectiveness of the fingerprint positioning method. In the absence of an efficient, accurate and automatic location fingerprint database construction method, the accuracy and availability of location positioning using mobile communication data such as MR data (4G/5G terminal measurement report) are poor, and terminal positioning service cannot be provided in a large scale.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a mobile network data positioning system, a method, a terminal and a medium based on a traffic route position fingerprint library, which can improve the construction efficiency of the position fingerprint library, have good real-time performance and effectiveness of fingerprint data, have correlation and directivity among fingerprint positions, and enhance the accuracy and effectiveness of positioning the terminal by using mobile network signal data in a traffic route scene.
In a first aspect, an embodiment of the present invention provides a mobile network data positioning system based on a traffic route location fingerprint library, including: a circuit basic data acquisition module, a circuit position fingerprint library module, a network data analysis and adaptation module and a terminal positioning processing module, wherein,
the line basic data acquisition module is used for automatically acquiring line basic data of a vehicle in the advancing process and generating a basic information sampling point sequence according to the sampling time sequence;
the circuit position fingerprint library module is used for generating a circuit track reference point sequence with the same circuit direction and uniform position intervals of circuits according to the association of the acquired basic information sampling point sequence with the sampling point route names and the preset distance intervals of adjacent circuit points, generating signal fingerprint characteristics of track reference points from the circuit track reference point data, receiving and storing the circuit track reference point sequence data, generating a circuit position fingerprint sample library according to the circuit track reference point sequence data, finding out the matched circuit basic information sampling point data according to the longitude and latitude positions of the position fingerprint sample points, and automatically updating the sample point signal fingerprint characteristics of the position fingerprint sample library by using the fingerprint characteristic data generated by the matched basic information sample points;
the network data analysis adaptive module acquires and analyzes third-party network data, provides network data adaptive analysis processing according to different network data types, and generates a to-be-positioned sampling point sequence containing mobile network signals;
the terminal positioning processing module uses the data of the line position fingerprint sample library, marks type labels on the sampling points to be positioned by adopting a classification method taking the base station as a special type, processes the data of the sampling points to be positioned by using a position fingerprint positioning method, and marks matched position fingerprint labels on the sampling points to be positioned.
In a second aspect, an embodiment of the present invention provides a method for locating mobile network data based on a traffic route location fingerprint library, including the following steps:
receiving and acquiring line basic data of a vehicle in the advancing process, and generating a basic information sampling point sequence according to the sampling time sequence;
generating line track reference point sequence data with the same line direction and uniform position intervals of lines according to the acquired basic information sampling point sequence association sampling point route names and the preset distance intervals of adjacent line points, generating signal fingerprint characteristics of track reference points from the line track reference point sequence data, receiving and storing the line track reference point sequence data, generating a line position fingerprint sample base according to the line track reference point sequence data, finding out the basic information sampling point data of a matched line according to the longitude and latitude positions of the position fingerprint sample points, and automatically updating the sample point signal fingerprint characteristics of the position fingerprint sample base by using the fingerprint characteristic data generated by the matched basic information sample points;
acquiring and analyzing third-party network data, providing network data self-adaptive analysis processing according to different network data types, and generating a to-be-positioned sampling point sequence containing a mobile network signal;
and marking the sampling points to be positioned with type labels by using the data of the line position fingerprint sample library and adopting a classification method taking the base station as a special type, processing the data of the sampling points to be positioned by using a position fingerprint positioning method, and marking matched position fingerprint labels on the sampling points to be positioned.
In a third aspect, an intelligent terminal provided in an embodiment of the present invention includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the foregoing embodiment.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium is characterized by storing a computer program, where the computer program includes program instructions, and the program instructions, when executed by a processor, cause the processor to execute the method described in the foregoing embodiment.
The invention has the beneficial effects that:
according to the mobile network data positioning system, method, terminal and medium based on the traffic route position fingerprint library, the basic data of a vehicle in the advancing process is automatically collected, the route position fingerprint sample library is automatically generated, positioning processing is achieved, full-process automatic processing is achieved, manual participation is not needed, the position fingerprint library construction efficiency is improved, automatic updating of fingerprint data is conducted by using test data, real-time performance and effectiveness of the fingerprint data are good, position correlation and directionality exist among fingerprint positions, and accuracy and effectiveness of terminal positioning conducted by using mobile network signal data in a traffic route scene are improved.
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In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a block diagram illustrating a mobile network data positioning system based on a traffic route location fingerprint database according to a first embodiment of the present invention;
fig. 2 is a flowchart illustrating a mobile network data positioning method based on a traffic route location fingerprint database according to a second embodiment of the present invention;
fig. 3 shows a block diagram of an intelligent terminal according to a third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, 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, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
As shown in fig. 1, there is a block diagram illustrating a mobile network data positioning system based on a traffic route location fingerprint database according to a first embodiment of the present invention, where the system includes: the system comprises a line basic data acquisition module, a line position fingerprint library module, a network data analysis and adaptation module and a terminal positioning processing module.
The line basic data acquisition module automatically acquires line basic data in the advancing process of vehicles, high-speed rails and light rails, and generates a basic information sampling point sequence according to the sampling time sequence, wherein the basic information sampling points comprise data contents such as sampling types, sampling time, longitude and latitude, a mobile network signal list and the like, and the basic information sampling point sequence is preferably provided for the line position fingerprint database module through a real-time data acquisition interface.
The line position fingerprint library module comprises a position fingerprint generating unit, wherein the position fingerprint generating unit acquires the area information and the line name of a basic information sampling point according to map data by using the sampling type and the longitude and latitude of the line basic information sampling point, for example: road name, subway line name, high-speed rail line name, light rail line name. Due to the continuity and the directionality of the traffic route track, the continuous route basic information sampling points with the same route name and the same movement direction in the route basic information sampling point sequence can be divided into the same route sampling point paragraph based on the route name, the longitude and the latitude and the movement route direction of the sampling points, and the sampling points in the route sampling point paragraph have the same route name and the same route direction and are arranged according to the route sequence. According to the sequence of the sampling points in the line sampling point section, calculating the cumulative distance from each sampling point to the first sampling point and the total length of the line sampling point section, and accumulating the distances DIS [ i ], DIS [ i ] ═
DIS [ i-1] + d (i, i-1), where d (i, i-1) is the straight-line distance between two points between adjacent sampling points i and i-1, the accumulated distance DIS [ n ] from the last sampling point n to the first sampling point is also the total length of line sampling point segments, the distance interval parameter MDIS between adjacent line points is preset, a line track reference point sequence is generated according to the preset distance interval MDIS between adjacent line points and the line sampling point segments, the line track reference point sequence is composed of a series of line track reference points with linked positions and uniform intervals according to the line sequence, and the line track reference point data includes: the method comprises the following steps of taking a first sampling point of a path sampling point paragraph as a point in a path reference point sequence, generating a path track reference point j at intervals of MDIS from the first sampling point, and mapping and interpolating the path reference point j to a straight line segment between two adjacent path sampling points k and k +1 according to a position interpolation algorithm by using the longitude and latitude of the path sampling point paragraph according to a position interpolation algorithm, wherein the longitude and latitude coordinates of the path track reference point j are calculated, and the distance relationship between the path track reference point j and the path sampling points k and k +1 needs to be satisfied: DIS [ k ] < ═ Ref [ j ] < ═ DIS [ k +1], according to the preset wireless signal fingerprint distance parameter DFPRINT, searching the basic information sampling point in the distance range DFPRINT with the longitude and latitude position of the line track reference point j in the line base information sampling point sequence, adding the mobile network signal list data of the basic information sampling point meeting the condition to the mobile network reference signal list of the line track reference point j, and adding the line track reference point j to the line track reference point sequence in sequence, and transmitting the generated line track reference point sequence data to the line position fingerprint sample library module to generate the line position fingerprint sample library.
The line position fingerprint library module comprises a line position fingerprint sample library unit, the line position fingerprint sample library unit receives and stores line track reference point sequence data, and a line position fingerprint sample library is generated according to the line track reference point sequence data. The method specifically comprises the following steps: generating a reference point j network signal fingerprint feature list according to the mobile network reference signal list data of the line track reference point j, wherein the network signal fingerprint feature fields selectable in the list are not limited to: base station identification, base station type, signal strength mean, signal strength variance, signal strength maximum, signal strength minimum. Presetting location similarity distance parameters DCFM, comparing location similarity of a line track reference point j and location fingerprint sample points in the same line direction in a line location fingerprint sample library according to a reference point sequence in the sequence, judging whether a distance interval is in a set range of the similarity distance DCFM, if so, marking the line track reference point as location similarity, if not, marking the line track reference point as location dissimilarity, and generating line location fingerprint sample point data by marking the line track reference point j as the dissimilarity, wherein the line location fingerprint sample point data comprises: area, line name, sample point number, sample point longitude and latitude, line direction, network signal fingerprint feature list. According to the longitude and latitude and the line direction of the position fingerprint sample points, the position fingerprint sample points are inserted into corresponding positions of a equidirectional line position fingerprint sample point library according to the line sequence, and a line position fingerprint sample library with consistent line direction, continuous positions and uniform intervals is constructed, and is a sample library with traffic line characteristics, which is different from a fingerprint library used in the prior art.
The line position fingerprint library module comprises a fingerprint data updating unit, the fingerprint data updating unit receives a line basic information sampling point sequence, the line position fingerprint library comprises a plurality of line position fingerprint sample points m, basic information sampling points, the positions of which are within a wireless signal fingerprint distance range DFPRINT, of the line position fingerprint sample points m are searched in the line basic information sampling point sequence, a network signal fingerprint feature list is obtained according to the mobile network signal list data processing of the basic information sampling points, and the network signal feature list of the line position fingerprint sample points m is updated according to the obtained network signal fingerprint feature list. The fingerprint data updating unit processes the line basic information sampling point sequence, finds out matched line basic information sampling point data according to the longitude and latitude positions of the position fingerprint sample points, and automatically updates the sample point signal fingerprint characteristics of the line position fingerprint sample library by using the fingerprint characteristic data generated by the matched basic information sampling points, so that the real-time performance and the accuracy of the fingerprint position sample library are realized.
The network data analysis adaptive module collects and analyzes third-party network data, provides a network data adaptive analysis processing method according to different network data types, generates a sampling point sequence to be positioned containing mobile network signals, preferably automatically analyzes the network data according to the recording time of the network data to generate the sampling point data sequence to be positioned, and the preferred field of the sampling point data to be positioned contains: terminal identification, sampling time and a mobile network positioning signal list. And the network data analysis and adaptation module sends the data sequence with the positioning sampling points to the terminal positioning processing module.
And the terminal positioning processing module performs classified identification on the data of the sampling point to be positioned and sampling point line position fingerprint positioning by using the data of the line position fingerprint sample library.
Specifically, a line position fingerprint sample library is used for carrying out position fingerprint positioning processing on the sequence data of the sampling point to be positioned, and the positioning processing process of the sampling point to be positioned is divided into two links: and (4) classifying and identifying sampling points, and positioning sampling point line position fingerprints. In the sampling point classification and identification link, the base station identifier is used as the characteristic data of classification and identification, the base station identifier in the mobile network positioning signal list of the sampling point to be positioned and the base station identifier in the line position fingerprint sample base are used for performing classification processing on the sampling point to be positioned, and the sampling point to be positioned after processing can be divided into: the classification processing method is realized by adopting the prior art. And in the sampling point line position fingerprint positioning link, processing the data of the sampling points to be positioned by adopting a position fingerprint positioning method according to the fingerprint characteristic data of the line position fingerprint sample library, matching proper position fingerprint sample points for the sampling points to be positioned, and marking corresponding position labels: the method comprises the steps of line name, line point number, line point direction and line point longitude and latitude, so that accurate positioning of line scene network data is achieved.
The above embodiments are described in detail below using light rails as examples:
(1) the method comprises the steps that a line basic data acquisition module is installed on a light rail carriage to automatically acquire data, the sampling type of the acquisition module is set to be a light rail, the light rail is sent from a starting point A and driven to a terminal point B, a line basic information sampling point sequence is acquired and generated by the line basic data acquisition module in the driving process, and the line basic information sampling point sequence is provided for a line signal fingerprint library module through a real-time acquisition interface.
(2) The line position fingerprint library module receives a line basic information sampling point sequence, and searches and associates the names of the upper light rail lines in the subway map according to the sampling types and the longitude and latitude of the line basic information sampling points: the method comprises the steps that M lines are obtained, line sampling point sections from a starting point A to an end point B are obtained according to the sequence of line basic information sampling point sequences and the line direction of movement of sampling points, interval distances MDIS are preset, a line track reference point is generated at each interval of the line sampling point sections according to a position interpolation algorithm, finally, a line track reference point sequence S formed by a series of track reference points at intervals of the MDIS from A to B along a track line is obtained, and a network signal fingerprint feature list of each line track reference point is generated according to a mobile network reference signal list of the line track reference points. And searching line position fingerprint sample points of the light rail M number line in a line position fingerprint sample library, wherein no M number line position fingerprint sample points exist in the sample library, the line position fingerprint sample point similarity comparison results are not similar, generating line position fingerprint sample point data according to line track reference point data, and sequentially inserting the sample point data into the line position fingerprint sample library to obtain a complete position fingerprint sample point sequence of the light rail M number line from A to B.
(3) Similarly, when the light rail runs from B to A, the line position fingerprint library module obtains line sampling point paragraphs from B to A according to the sequence of the line basic information sampling point sequences and the line direction of the movement of the sampling points, processes and obtains a line track reference point sequence Q formed by a series of trace reference points which are spaced from the MDIS along the track line from B to A according to the preset spacing distance MDIS, generates a network signal fingerprint feature list of each line track reference point in the sequence Q, and also searches line position fingerprint sample points of the light rail M number line in the line position fingerprint sample library, because the line direction of the M number line position fingerprint sample points in the sample library is from A to B, the results of the similarity comparison of the line track reference points in the line track reference point sequence Q are dissimilar, the line track reference points in the sequence Q generate position fingerprint sample points, and inserting the position fingerprint sample points into a fingerprint library according to the line sequence to generate a position fingerprint sample point sequence of the M lines from the B direction to the A direction.
(4) The network data analysis and adaptation module acquires LTE network MR data, automatically analyzes the MR data to generate a data sequence of sampling points to be positioned, generates data of the sampling points to be positioned according to fields of ue, time, ci, ltescrrp, ltenbPci, ltencrp and the like in the MR data, and transmits the data sequence of the sampling points to be positioned to the terminal positioning processing module.
(5) The terminal positioning processing module classifies and identifies the data of the sampling points to be positioned by using the base station identifier of the M-number line sample point data in the line position fingerprint sample library, and divides the sampling points after classification into: and for the data of the sampling points to be positioned, which are classified and identified as light rails, processing the data of the sampling points to be positioned by adopting a position fingerprint positioning method according to the fingerprint sample library data of the line with the number M, and matching the sampling points to be positioned with the position fingerprint tags: the method comprises the steps of obtaining the positioning position of a sampling point to be positioned on the M number light rail line by the aid of line names, line point numbers, line point directions and line point longitudes and latitudes.
According to the mobile network data positioning system based on the traffic route position fingerprint database, the basic data of a vehicle in the advancing process is automatically acquired, the route position fingerprint sample database is automatically generated, the positioning processing is realized, the whole process is automatically processed, manual participation is not needed, the position fingerprint database construction efficiency is improved, the test data is used for automatically updating the fingerprint data, the real-time performance and the effectiveness of the fingerprint data are good, the position correlation and the directionality exist among the fingerprint positions, and the accuracy and the effectiveness of terminal positioning by using the mobile network signal data in a traffic route scene are enhanced.
In the first embodiment, a mobile network data positioning system based on a traffic route location fingerprint library is provided, and correspondingly, the application also provides a mobile network data positioning method based on a traffic route location fingerprint library. Please refer to fig. 2, which is a flowchart illustrating a mobile network data positioning method based on a traffic route location fingerprint database according to a second embodiment of the present invention. Since the method embodiment is basically similar to the device embodiment, the description is simple, and the relevant points can be referred to the partial description of the device embodiment. The method embodiments described below are merely illustrative.
As shown in fig. 2, it is a flowchart illustrating a mobile network data positioning method based on a traffic route location fingerprint database according to a second embodiment of the present invention, and the method includes the following steps:
and S1, receiving and acquiring the basic data of the line of the vehicle in the traveling process, and generating a basic information sampling point sequence according to the sampling time sequence.
The basic information sampling point sequence comprises: the method comprises the following steps of sampling type, sampling time, longitude and latitude and a mobile network signal list, wherein the line track reference point sequence comprises the following steps: area, line name, reference point number, line direction, reference point longitude and latitude and mobile network reference signal list.
And S2, generating line track reference point sequence data with the same line direction and uniform position intervals of lines according to the acquired basic information sampling point sequence correlation sampling point route names and the preset distance intervals of adjacent line points, generating signal fingerprint characteristics of track reference points from the line track reference point sequence data, receiving and storing the line track reference point sequence data, generating a line position fingerprint sample base according to the line track reference point sequence data, finding out the basic information sampling point data of matched lines according to the longitude and latitude positions of the position fingerprint sample points, and automatically updating the sample point signal fingerprint characteristics of the position fingerprint sample base by using the fingerprint characteristic data generated by the matched basic information sample points.
Specifically, the area information and the route name of the basic information sampling point are acquired from the map data, for example: road name, subway line name, high-speed rail line name, light rail line name. Due to the continuity and the directionality of the traffic route track, the continuous route basic information sampling points with the same route name and the same movement direction in the route basic information sampling point sequence can be divided into the same route sampling point paragraph based on the route name, the longitude and the latitude and the movement route direction of the sampling points, and the sampling points in the route sampling point paragraph have the same route name and the same route direction and are arranged according to the route sequence. Calculating the cumulative distance from each sampling point to the first sampling point and the total length of the line sampling point section according to the sequence of the sampling points in the line sampling point section, wherein the cumulative distance DIS [ i ], DIS [ i ] ═ DIS [ i-1] + d (i, i-1), wherein d (i, i-1) is the linear distance between two points between the adjacent sampling points i and i-1, the accumulated distance DIS [ n ] from the last sampling point n to the first sampling point is also the total length of the line sampling point segment, the distance interval parameter MDIS between the adjacent line points is preset, generating a line track reference point sequence according to a preset adjacent line point distance interval MDIS and a line sampling point paragraph, wherein the line track reference point sequence is formed by a series of line track reference points which are in position connection and are uniformly spaced according to a line sequence, and the line track reference point data comprises: the method comprises the following steps of taking a first sampling point of a path sampling point paragraph as a point in a path reference point sequence, generating a path track reference point j at intervals of MDIS from the first sampling point, and mapping and interpolating the path reference point j to a straight line segment between two adjacent path sampling points k and k +1 according to a position interpolation algorithm by using the longitude and latitude of the path sampling point paragraph according to a position interpolation algorithm, wherein the longitude and latitude coordinates of the path track reference point j are calculated, and the distance relationship between the path track reference point j and the path sampling points k and k +1 needs to be satisfied: DIS [ k ] < ═ Ref [ j ] < ═ DIS [ k +1], according to the preset wireless signal fingerprint distance parameter DFPRINT, searching the basic information sampling point in the distance range DFPRINT with the longitude and latitude position of the line track reference point j in the line base information sampling point sequence, adding the mobile network signal list data of the basic information sampling point meeting the condition to the mobile network reference signal list of the line track reference point j, and adding the line track reference point j to the line track reference point sequence in sequence, and transmitting the generated line track reference point sequence data to the line position fingerprint sample library module to generate the line position fingerprint sample library.
Receiving a line basic information sampling point sequence, wherein the line position fingerprint library comprises a plurality of line position fingerprint sample points m, searching the basic information sampling points which are positioned in the distance range DFPRINT of the wireless signal fingerprint with the line position fingerprint sample points m in the line position basic information sampling point sequence, processing the basic information sampling points according to the mobile network signal list data of the basic information sampling points to obtain a network signal fingerprint feature list, and updating the network signal feature list of the line position fingerprint sample points m by the obtained network signal fingerprint feature list. The fingerprint data updating unit processes the line basic information sampling point sequence, finds out matched line basic information sampling point data according to the longitude and latitude positions of the position fingerprint sample points, and automatically updates the sample point signal fingerprint characteristics of the line position fingerprint sample library by using the fingerprint characteristic data generated by the matched basic information sampling points, so that the real-time performance and the accuracy of the fingerprint position sample library are realized.
And S3, collecting and analyzing third-party network data, providing network data self-adaptive analysis processing according to different network data types, and generating a sampling point sequence to be positioned containing mobile network signals.
Specifically, the method for carrying out self-adaptive analysis and adaptation on the acquired different types of network data, providing correct data analysis and processing according to the analyzed data types, preferably automatically analyzing the network data according to the recording time of the network data to generate a data sequence of sampling points to be positioned, wherein the data sequence of the sampling points to be positioned contains the following optimized fields: terminal identification, sampling time and a mobile network positioning signal list.
And S4, using the line position fingerprint sample library data to perform classified identification on the sampling point data to be positioned and positioning the sampling point line position fingerprint.
Specifically, a line position fingerprint sample library is used for carrying out position fingerprint positioning processing on the sequence data of the sampling point to be positioned, and the positioning processing process of the sampling point to be positioned is divided into two links: and (4) classifying and identifying sampling points, and positioning sampling point line position fingerprints. In the sampling point classification and identification link, the base station identifier is used as the characteristic data of classification and identification, the base station identifier in the mobile network positioning signal list of the sampling point to be positioned and the base station identifier in the line position fingerprint sample base are used for performing classification processing on the sampling point to be positioned, and the sampling point to be positioned after processing can be divided into: the classification processing method is realized by adopting the prior art. And in the sampling point line position fingerprint positioning link, processing the data of the sampling points to be positioned by adopting a position fingerprint positioning method according to the fingerprint characteristic data of the line position fingerprint sample library, matching proper position fingerprint sample points for the sampling points to be positioned, and marking corresponding position labels: the method comprises the steps of line name, line point number, line point direction and line point longitude and latitude, so that accurate positioning of line scene network data is achieved.
The mobile network data positioning method based on the traffic route position fingerprint library and the mobile network data positioning system based on the traffic route position fingerprint library have the same inventive concept and the same beneficial effects, and are not repeated herein.
As shown in fig. 3, a block diagram of an intelligent terminal according to a third embodiment of the present invention is shown, where the terminal includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, the memory is used for storing a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the second embodiment.
It should be understood that in the embodiments of the present invention, the Processor may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of the fingerprint), a microphone, etc., and the output device may include a display (LCD, etc.), a speaker, etc.
The memory may include both read-only memory and random access memory, and provides instructions and data to the processor. The portion of memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In a specific implementation, the processor, the input device, and the output device described in the embodiments of the present invention may execute the implementation described in the method embodiments provided in the embodiments of the present invention, and may also execute the implementation described in the system embodiments in the embodiments of the present invention, which is not described herein again.
The invention also provides an embodiment of a computer-readable storage medium, in which a computer program is stored, which computer program comprises program instructions that, when executed by a processor, cause the processor to carry out the method described in the above embodiment.
The computer readable storage medium may be an internal storage unit of the terminal described in the foregoing embodiment, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the terminal and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal and method can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. A mobile network data location system based on a traffic route location fingerprint database, comprising: a circuit basic data acquisition module, a circuit position fingerprint library module, a network data analysis and adaptation module and a terminal positioning processing module, wherein,
the line basic data acquisition module is used for automatically acquiring line basic data of a vehicle in the advancing process and generating a basic information sampling point sequence according to the sampling time sequence;
the circuit position fingerprint library module is used for generating a circuit track reference point sequence with the same circuit direction and uniform position intervals of circuits according to the association of the acquired basic information sampling point sequence with the sampling point route names and the preset distance intervals of adjacent circuit points, generating signal fingerprint characteristics of track reference points from the circuit track reference point data, receiving and storing the circuit track reference point sequence data, generating a circuit position fingerprint sample library according to the circuit track reference point sequence data, finding out the matched circuit basic information sampling point data according to the longitude and latitude positions of the position fingerprint sample points, and automatically updating the sample point signal fingerprint characteristics of the position fingerprint sample library by using the fingerprint characteristic data generated by the matched basic information sample points;
the network data analysis adaptive module acquires and analyzes third-party network data, provides a network data adaptive analysis processing method according to different network data types, and generates a to-be-positioned sampling point sequence containing mobile network signals;
the terminal positioning processing module uses the data of the line position fingerprint sample library, marks type labels on the sampling points to be positioned by adopting a classification method taking the base station as a special type, processes the data of the sampling points to be positioned by using a position fingerprint positioning method, and marks matched position fingerprint labels on the sampling points to be positioned.
2. The system of claim 1, wherein the sequence of base information samples comprises: the method comprises the following steps of sampling type, sampling time, longitude and latitude and a mobile network signal list, wherein the line track reference point sequence comprises the following steps: area, line name, reference point number, line direction, reference point longitude and latitude and mobile network reference signal list.
3. The system of claim 2, wherein the line location fingerprint library module includes a location fingerprint generating unit, the location fingerprint generating unit uses a sampling type and longitude and latitude of the line basic information sampling points, acquires area information and a line name of the basic information sampling points according to map data, divides the continuous line basic information sampling points having the same line name and movement direction in the line basic information sampling point sequence into a same line sampling point segment, calculates an accumulated distance from each sampling point to a first sampling point and a total length of the line sampling point segment according to a sampling point sequence in the line sampling point segment, generates a line trajectory reference point sequence according to a preset adjacent line point distance interval and the line sampling point segment, takes the first sampling point of the line sampling point segment as a point in the line reference sequence, and generating a line track reference point at intervals of a distance from a first sampling point, calculating longitude and latitude coordinates of the line track reference point according to a position interpolation algorithm, searching basic information sampling points which are within a preset wireless signal fingerprint distance range from the longitude and latitude positions of the line track reference point in a line basic information sampling point sequence, adding mobile network signal list data of the sampling points meeting the basic information of conditions to a mobile network reference signal list of the line track reference point, adding the line track reference points to line track reference point sequence data in sequence, and generating the signal fingerprint characteristics of the track reference point from the line track reference point sequence data.
4. The system of claim 3, wherein the line location fingerprint library module includes a line location fingerprint sample library unit, the line location fingerprint sample library unit receives and stores line trajectory reference point sequence data, and generates a line location fingerprint sample library based on the line trajectory reference point sequence data, including: generating a reference point network signal fingerprint feature list according to mobile network reference signal list data of a line track reference point, presetting position similar distance parameters, according to the sequence of the reference points in the sequence, the line track reference points and the position fingerprint sample points in the same line direction in the line position fingerprint sample library are compared in position similarity, whether the distance interval is within the set similar distance range or not is judged, if yes, marking the line track reference points as similar positions, if not, marking the line track reference points as dissimilar positions, generating line position fingerprint sample point data by the line track reference points marked as dissimilar positions, according to the longitude and latitude and the line direction of the position fingerprint sample points, the position fingerprint sample points are inserted into the corresponding positions of the equidirectional line position fingerprint sample point library according to the line sequence, and constructing a line position fingerprint sample library with consistent line direction, continuous positions and uniform intervals.
5. The system of claim 3, wherein the circuit position fingerprint library module comprises a fingerprint data updating unit, the fingerprint data updating unit receives a circuit basic information sampling point sequence, the circuit position fingerprint library comprises a plurality of circuit position fingerprint sample points, basic information sampling points which are within a distance range of a wireless signal fingerprint from the circuit position fingerprint sample points are searched in the circuit basic information sampling point sequence, a network signal fingerprint feature list is obtained through processing according to mobile network signal list data of the basic information sampling points, and the network signal fingerprint feature list of the circuit position fingerprint sample points is updated through the obtained network signal fingerprint feature list.
6. A mobile network data positioning method based on a traffic route position fingerprint database is characterized by comprising the following steps:
receiving and acquiring line basic data of a vehicle in the advancing process, and generating a basic information sampling point sequence according to the sampling time sequence;
generating line track reference point sequence data with the same line direction and uniform position intervals of lines according to the acquired basic information sampling point sequence association sampling point route names and the preset distance intervals of adjacent line points, generating signal fingerprint characteristics of track reference points from the line track reference point sequence data, receiving and storing the line track reference point sequence data, generating a line position fingerprint sample base according to the line track reference point sequence data, finding out the basic information sampling point data of a matched line according to the longitude and latitude positions of the position fingerprint sample points, and automatically updating the sample point signal fingerprint characteristics of the position fingerprint sample base by using the fingerprint characteristic data generated by the matched basic information sample points;
acquiring and analyzing third-party network data, providing network data self-adaptive analysis processing according to different network data types, and generating a to-be-positioned sampling point sequence containing a mobile network signal;
and marking the sampling points to be positioned with type labels by using the data of the line position fingerprint sample library and adopting a classification method taking the base station as a special type, processing the data of the sampling points to be positioned by using a position fingerprint positioning method, and marking matched position fingerprint labels on the sampling points to be positioned.
7. The method of claim 6, wherein the sequence of base information samples comprises: the method comprises the following steps of sampling type, sampling time, longitude and latitude and a mobile network signal list, wherein the line track reference point sequence comprises the following steps: area, line name, reference point number, line direction, reference point longitude and latitude and mobile network reference signal list.
8. The method as claimed in claim 7, wherein the generating of the line track reference point sequence data with the same line direction and uniform position intervals of the lines according to the preset distance intervals between adjacent line points by associating the sampling point route names with the collected basic information sampling point sequence comprises:
using the sampling type and longitude and latitude of the line basic information sampling points, acquiring the area information and line name of the basic information sampling points according to map data, dividing the continuous line basic information sampling points with the same line name and motion direction in the line basic information sampling point sequence into the same line sampling point paragraph, calculating the accumulated distance from each sampling point to the first sampling point and the total length of the line sampling point paragraph according to the sequence of the sampling points in the line sampling point paragraph, generating a line track reference point sequence according to the preset distance interval of adjacent line points and the line sampling point paragraph, taking the first sampling point of the line sampling point paragraph as one point in the line reference sequence, generating a line track reference point at intervals from the first sampling point, calculating the longitude and latitude coordinates of the line track reference point according to a position interpolation algorithm, searching basic information sampling points with longitude and latitude positions of a line track reference point within a preset wireless signal fingerprint distance range from the line base information sampling point sequence, adding mobile network signal list data of the sampling points meeting the condition basic information into a mobile network reference signal list of the line track reference point, sequentially adding the line track reference points into line track reference point sequence data, and generating signal fingerprint characteristics of a track reference point from the line track reference point sequence data;
the generating of the line location fingerprint sample database according to the line trajectory reference point sequence data specifically includes:
generating a reference point network signal fingerprint feature list according to mobile network reference signal list data of a line track reference point, presetting position similar distance parameters, according to the sequence of the reference points in the sequence, the line track reference points and the position fingerprint sample points in the same line direction in the line position fingerprint sample library are compared in position similarity, whether the distance interval is within the set similar distance range or not is judged, if yes, marking the line track reference points as similar positions, if not, marking the line track reference points as dissimilar positions, generating line position fingerprint sample point data by the line track reference points marked as dissimilar positions, according to the longitude and latitude and the line direction of the position fingerprint sample points, the position fingerprint sample points are inserted into the corresponding positions of the equidirectional line position fingerprint sample point library according to the line sequence, and constructing a line position fingerprint sample library with consistent line direction, continuous positions and uniform intervals.
9. An intelligent terminal comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, the memory being adapted to store a computer program, the computer program comprising program instructions, characterized in that the processor is configured to invoke the program instructions to perform the method according to any of claims 6-8.
10. A computer-readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method according to any of claims 6-8.
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