CN106982414A

CN106982414A - A kind of positioned update method, device and mobile terminal

Info

Publication number: CN106982414A
Application number: CN201610029328.5A
Authority: CN
Inventors: 沈慧; 吴剑; 姚云蛟
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2016-01-15
Filing date: 2016-01-15
Publication date: 2017-07-25
Anticipated expiration: 2036-01-15
Also published as: CN106982414B

Abstract

The embodiment of the present application provides a kind of positioned update method, device and mobile terminal, ensures the precision of Wifi positioning to be updated to Wifi fingerprints.Described method includes：Screened according to earth magnetism positioning result point alternative to Wifi, determine that Wifi screens point；Wifi raster datas are determined according to the Wifi the first Wifi data for screening point；According to the walking collection information of mobile terminal, the 2nd Wifi data of tracing point are determined；By the matching of the 2nd Wifi data and Wifi raster datas, Wifi finger print datas are updated.Ensure the ageing of Wifi fingerprints, improve the precision of Wifi positioning.

Description

Positioning updating method and device and mobile terminal

Technical Field

The present application relates to the field of positioning technologies, and in particular, to a positioning updating method, a positioning updating apparatus, and a mobile terminal.

Background

Wifi (WIreless-Fidelity) positioning is an indoor positioning method which is relatively easy to implement at present. Because general market all covers Wifi, consequently need not additionally to lay equipment, just can accomplish indoor location function.

However, Wifi positioning requires fingerprint collection, which consumes a lot of human resources, and Wifi fingerprints have timeliness, which is about 6 months. Therefore, as the business changes and the Wifi AP (Wireless Access Point) changes, the Wifi fingerprint will slowly lose its effectiveness, resulting in the reduction of the positioning accuracy.

Therefore, one technical problem that needs to be urgently solved by those skilled in the art is: a positioning updating method, a positioning updating device and a mobile terminal are provided to update Wifi fingerprints to ensure the accuracy of Wifi positioning.

Disclosure of Invention

The technical problem to be solved by the embodiment of the application is to provide a positioning updating method to update a Wifi fingerprint to ensure the accuracy of Wifi positioning.

Correspondingly, the embodiment of the application also provides a positioning updating device and a mobile terminal, which are used for ensuring the realization and the application of the method.

In order to solve the above problem, an embodiment of the present application discloses a positioning update method, including: screening Wifi alternative points according to the geomagnetic positioning result, and determining Wifi screening points; determining Wifi raster data according to the first Wifi data of the Wifi screening point; determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal; and updating the Wifi fingerprint data through matching the second Wifi data with the Wifi raster data.

The embodiment of the present application further discloses a positioning update device, including: the geomagnetic screening module is used for screening the Wifi alternative points according to the geomagnetic positioning result and determining Wifi screening points; the grid determining module is used for determining Wifi grid data according to the first Wifi data of the Wifi screening point; the track Wifi determining module is used for determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal; and the matching updating module is used for updating the Wifi fingerprint data through matching of the second Wifi data and the Wifi raster data.

The embodiment of the application also discloses a mobile terminal, which comprises: memory, display, processor and input unit, the processor is used for carrying out the method of any one of the embodiments of this application.

Compared with the prior art, the embodiment of the application has the following advantages:

in this application embodiment, the data of earth magnetic signal is relatively more stable, consequently adopts the earth magnetic positioning result to filter Wifi alternate site, confirms Wifi screening site, then the foundation Wifi grid data is confirmed to Wifi screening site's first Wifi data, according to mobile terminal's walking information gathering, confirms the second Wifi data of track point, the rethread Wifi data and Wifi grid data's matching are updated Wifi fingerprint data to guarantee the timeliness of Wifi fingerprint, improve the precision of Wifi location.

Drawings

FIG. 1 is a flow chart of the steps of an embodiment of a location update method of the present application;

fig. 2 is a schematic diagram of a positioning update method according to an embodiment of the present application;

FIG. 3 is a flow chart of steps in another embodiment of a location update method of the present application;

fig. 4 is a flowchart of a screening step of Wifi alternative points in another embodiment of the location updating method of the present application;

fig. 5 is a schematic diagram of Wifi alternate point clustering in an embodiment of the present application;

FIG. 6 is a flow chart of a grid map determination step in another embodiment of the location update method of the present application;

FIG. 7 is a flowchart illustrating a step of filtering Wifi update points in another embodiment of the location update method of the present application;

fig. 8 is a flowchart illustrating a geomagnetic positioning result method according to an embodiment of the present application;

fig. 9 is a flowchart illustrating a step of determining a geomagnetic grid in a geomagnetic positioning result method according to an embodiment of the present application;

fig. 10 is a flowchart illustrating a step of matching and determining a positioning result in a geomagnetic positioning result method according to an embodiment of the present application;

FIG. 11 is a block diagram of an embodiment of a positioning update apparatus according to the present application;

FIG. 12 is a block diagram of another embodiment of a location update apparatus of the present application;

FIG. 13 is a block diagram of a raster data determination submodule in an alternative embodiment of the location update apparatus of the present application;

fig. 14 is a block diagram of an update point filter sub-module in another embodiment of the positioning update apparatus of the present application;

FIG. 15 is a block diagram of an update submodule in another embodiment of a location update apparatus of the present application;

fig. 16 is a block diagram of an embodiment of an intelligent terminal according to the present application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.

wifi fingerprint: positioning is achieved by measuring the signal strength (RSSI) of various locations in the room. The wifi fingerprint is formed by mainly measuring the surrounding wifi signal strength (RSSI) through each indoor position point needing to be positioned<ID₁:RSSI₁,ID₂:RSSI₂···ID_n:RSSI_n,Poisition>(ii) a And finally, N wifi fingerprints are generated in the whole area to form a wifi fingerprint map.

However, with the change of the merchant, the wifi AP may move, replace, disappear, and also move a hotspot, etc.; these variations can cause wifi fingerprints to be different from real fingerprints; the longer the time lapse, the larger the difference; the larger the difference, the worse the positioning accuracy using the fingerprint method. Called wifi fingerprint failure.

In order to solve the problem that Wifi fingerprints lose efficacy along with time, each embodiment of the application updates the Wifi fingerprints based on geomagnetism and PDR tracks, and based on the long-term stable and unchangeable characteristic of geomagnetic signals, the data returned by the user in positioning is utilized, and after the selection is performed, so that Wifi self-updating is performed, the precision is high, and the implementability is good.

One of the core concepts of the embodiments of the present application is to provide a positioning updating method, an apparatus and a mobile terminal, so as to update Wifi fingerprints to ensure Wifi positioning accuracy. The data of the geomagnetic signals are relatively stable, therefore, a geomagnetic positioning result is adopted to screen a Wifi candidate point, the Wifi screening point is determined, then Wifi raster data is determined according to first Wifi data of the Wifi screening point, Wifi fingerprint data is updated according to walking acquisition information of the mobile terminal, and therefore timeliness of Wifi fingerprints is guaranteed, and accuracy of Wifi positioning is improved.

The geomagnetic positioning is performed according to a soft magnetic field formed by a steel bar structure in a building, and according to the direction specificity and the magnetic field specificity of a magnetic field vector. Although geomagnetic data is easily interfered by other electromagnetic data such as mobile phones and computers, the interference strength and the distance form a geometric multiple relationship, and the geomagnetic data can be basically ignored after being separated by dozens of centimeters. And for the data of the geomagnetic signal, a stable result is obtained for a relatively long time. The direction and strength differences of the indoor geomagnetic field strength can be used to accomplish indoor positioning. The geomagnetic positioning can be used for measuring geomagnetic fingerprints, wherein the geomagnetic fingerprints are magnetic fingerprints corresponding to wifi fingerprints; each data point of the magnetic fingerprint is a magnetic vector, and the collection of the magnetic fingerprint is usually completed by using a mobile phone in the form of lines or points with special collection software.

PDR (Pedestrian Dead Reckoning). The PDR uses the acceleration, the gyroscope and the magnetic sensor in the mobile phone sensor to comprehensively calculate the track of the walking of the pedestrian, and the result of the PDR is a series of relative tracks of the walking.

In this embodiment, the mobile terminal refers to a mobile terminal device with a multimedia function, and these devices support audio, video, data and other functions. This mobile terminal includes intelligent mobile terminal, panel computer, intelligent wearing equipment etc. in this embodiment.

Example one

Referring to fig. 1, a flowchart illustrating steps of an embodiment of a location update method according to the present application is shown, which may specifically include the following steps:

and step 102, screening the Wifi alternative points according to the geomagnetic positioning result, and determining Wifi screening points.

According to the soft magnetic field formed by the steel bar structure in the building, the orientation, namely the geomagnetic orientation, can be carried out according to the direction specificity and the magnetic field specificity of the magnetic field vector of the soft magnetic field. The data of the geomagnetic signals are stable results within a relatively long time, so that updating of Wifi positioning assisted by geomagnetic positioning can be adopted, and timeliness of Wifi fingerprints is guaranteed. Therefore, the geomagnetic positioning result can be determined firstly, and then the geomagnetic positioning result screens the Wifi alternate points, namely the Wifi alternate points with higher geomagnetic positioning scores are screened out and serve as Wifi screening points.

And step 104, determining Wifi raster data according to the first Wifi data of the Wifi screening point.

First Wifi data of the screened Wifi screening points can then be determined, the first Wifi data including first coordinate data of the Wifi screening points and first scanning data, the scanning data including Wifi signal intensity determined through scanning, Wifi raster data being determined through the first Wifi data. The grid structure is a spatial data structure, the grid structure is a data organization which represents the distribution of spatial ground features or phenomena in a regular array, and each data in the organization represents the non-geometric attribute characteristics of the ground features or phenomena. A designated area (e.g., map, earth's surface) may be divided into an array of uniformly sized closely adjacent grids, each defined by rows and columns as a pixel or pixel, and containing a code indicating the type or magnitude of the attribute of the pixel, or including a pointer to its record of the attribute, etc.

And step 106, determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal.

In this embodiment, a Pedestrian Dead Reckoning (PDR) track is fused with Wifi to perform Wifi positioning observation. Therefore, the PDR track of the user, namely walking acquisition information, can be acquired through a sensor in the mobile terminal, each track point of the walking track of the user is determined according to the walking acquisition information, and second Wifi data of the track point is calculated.

And step 108, updating the Wifi fingerprint data through matching of the second Wifi data and the Wifi raster data.

Executing Wifi fine grading to update Wifi fingerprint data, namely matching the Wifi data with Wifi raster data, namely traversing second Wifi data of each track point in a walking track for a given target acquisition point Pm, matching the second Wifi data with the Wifi raster data, determining matching scores of the track points, determining that the Wifi fingerprint points need to be updated according to the matching scores, and updating the Wifi fingerprint data.

In conclusion, data of the geomagnetic signals are relatively stable, therefore, a geomagnetic positioning result is adopted to screen the Wifi alternate points, the Wifi alternate points are determined, Wifi grid data are determined according to first Wifi data of the Wifi alternate points, second Wifi data of track points are determined according to walking acquisition information of the mobile terminal, and then the Wifi fingerprint data are updated through matching of the second Wifi data and the Wifi grid data, so that timeliness of Wifi fingerprints are guaranteed, and Wifi positioning accuracy is improved.

Example two

Each embodiment of this application updates the Wifi fingerprint based on earth magnetism and PDR orbit, based on the unchangeable characteristic of earth magnetism signal's long-term stability, utilizes the data of user's location passback, swipes the back to carry out Wifi and update certainly.

Referring to fig. 2, a schematic diagram of a positioning update method according to an embodiment of the present application is shown.

Wifi fingerprints are updated based on geomagnetism and PDR tracks, and the input of the Wifi fingerprints is composed of three parts:

1) trajectory data

Wherein, the track data is composed of n sections of tracks; a trace datum is a sensor datum for a user walking with a mobile phone in a continuous time, including: wifi data, geomagnetic data, and the like.

2) Magnetic fingerprint

The magnetic fingerprint can adopt the magnetic fingerprint data collected by a special data collecting tool, and the magnetic fingerprint data cannot be changed for a long time after the collection is finished. Of course, the magnetic field can be measured and determined by a mobile terminal having a magnetic sensor, such as a mobile phone.

3) Wifi fingerprint

The Wifi fingerprint can also adopt a special data acquisition tool or Wifi fingerprint data acquired by a mobile terminal, the acquisition method is the same as the magnetic fingerprint acquisition method, but the Wifi fingerprint is easy to change along with the change of time.

And the input track data is applied to the wifi fingerprint after a series of operation steps, so that the wifi self-updating process is completed. The method comprises the steps of firstly acquiring PDR track data, Wifi fingerprints and a geomagnetic positioning result, then screening the PDR tracks, screening the Wifi fingerprints to determine Wifi candidate points, then screening the Wifi candidate points by adopting the geomagnetic positioning result, determining the Wifi candidate points, carrying out comprehensive comparison matching by adopting the PDR tracks and the Wifi candidate points, and updating the Wifi fingerprints.

Referring to fig. 3, a flowchart illustrating steps of another embodiment of the location updating method of the present application is shown, which may specifically include the following steps:

and step 302, screening the track points according to the walking acquisition information of the mobile terminal, and determining the track points which accord with a second rule.

In this embodiment, walking acquisition information of the PDR track (i.e., walking track) is acquired by sensors such as an acceleration, a gyroscope, and a magnetic sensor in the mobile terminal. The track data can be by "T1, T2.. Tn" a track point is constituteed, and a section track comprises n track point data promptly, and the track point is continuous track point, configures into a track point with every step of PDR track. Therefore, the walking acquisition information in the walking period can be acquired, and the walking acquisition information comprises the following steps: the attitude angle of the mobile terminal, the magnetic vector Mg, the second Scan information Scan2, and the attitude change rate of the mobile terminal.

Wherein, the attitude angle includes: course angle, roll angle, pitch angle, etc.; and the magnetic vector Mc obtained by the original measurement is in a mobile terminal coordinate system, and can be rotated to a geodetic coordinate system by using the attitude angle of the mobile terminal to obtain a magnetic vector Mg. The attitude change rate is used for describing indexes of three-axis shaking degree of the mobile terminal, and in addition, second scanning information Scan2 is not arranged on each track point in the track.

And then, screening the track points according to the walking acquisition information of the mobile terminal, and determining the track points which accord with a second rule. Wherein the second rule comprises at least one of: number rule, rate of change rule and angle rule:

1) the quantity rule can be configured to that the number of the acquired track points reaches a quantity threshold value, so that if the number of the track points is too small, namely the number of the track points does not reach the quantity threshold value, the quantity is small, the track point does not have referential property, and the track section can be deleted.

2) The change rate rule can be configured to be that the average attitude change rate of the acquired track points is smaller than a change rate threshold, if the average mobile phone change rate of the track points in the track is larger, if the average attitude change rate is larger than the change rate threshold, the mobile terminal shakes more severely, the relative error ratio is larger, and the track can be deleted.

3) An angle rule comprising: a first rule and a second rule; the first rule may be configured that, if the absolute value of the roll angle is not greater than the roll angle threshold, the segment of track is deleted if the absolute value of the roll angle is greater than the roll angle threshold; the second rule may be configured such that if the absolute value of the pitch angle is not greater than the pitch angle threshold, then the segment of track is deleted if the absolute value of the pitch angle is greater than the pitch angle threshold.

Therefore, the tracks are screened through the number of track points, the attitude transformation rate, the roll angles and multiple dimensions of the roll angles, the accuracy of track data is improved, and an accurate data base is provided for subsequent positioning and updating.

And step 304, screening Wifi alternate points from the Wifi fingerprint points.

One of the purposes of Wifi screening is to use Wifi scan data and Wifi fingerprint maps to carry out primary screening for the first time, eliminate obviously impossible positions and narrow the range of subsequent searching.

Namely determining the Wifi matching number of Wifi fingerprint points; and screening the Wifi fingerprint points with the Wifi matching number exceeding a second threshold value as Wifi alternate points. And determining the candidate central point by adopting a Wifi candidate point, and taking the Wifi fingerprint point within the preset range of the candidate central point as the Wifi candidate point.

The trace point that has Wifi scan data in the last frame in n trace points can be extracted out, then adopt this trace point as Wifi fingerprint point, with all the Wifi fingerprint map of fingerprint point on carry out the matching, confirm the number on the Wifi matches, the number of matching with the Wifi of every trace point is ranked. And then comparing the Wifi matching number with a second threshold value, determining Wifi fingerprint points of which the Wifi matching number exceeds the second threshold value, and taking the fingerprint points as Wifi alternate points. In this embodiment, the maximum matching number is configured, the second threshold may be equal to the maximum matching number, or configured as s% of the maximum matching number, for example, the maximum matching number whose number reaches 80%.

The candidate center points can also be determined by adopting Wifi candidate point, namely, the horizontal and vertical coordinates of the corresponding coordinate data of all the Wifi candidate points are weighted (authority matching number) to be averaged, namely, weighted averaging is performed based on the authority matching number, one candidate center point (aver _ x, aver _ y) is determined, the Wifi fingerprint point in the preset range R of the candidate center point (aver _ x, aver _ y) is used as the Wifi candidate point, and the Wifi candidate point is the result of Wifi rough screening.

Step 306, determining a geomagnetic positioning result.

For geomagnetic positioning, geomagnetic information, that is, first magnetic information, may be collected first, and then, a magnetic map is rasterized according to the first magnetic information to obtain geomagnetic raster data. And determining second magnetic information of the track points according to the walking acquisition information of the mobile terminal, wherein the track points comprise the corresponding track points in the walking track of the walking acquisition information.

And then, performing geomagnetic observation to determine a geomagnetic positioning result, namely matching the second magnetic information with the geomagnetic grid data, namely traversing the second magnetic information of each track point in the walking track for a given target acquisition point Pm, matching the second magnetic information with the geomagnetic grid data, and determining a matching score of the track point to determine the geomagnetic positioning result of the target acquisition point Pm.

And 308, screening the Wifi alternate points according to the geomagnetic positioning result, and determining Wifi screening points.

In this embodiment, the screening of the Wifi candidate point according to the geomagnetic positioning result, as shown in fig. 4, includes the following sub-steps:

and a substep 402 of obtaining geomagnetic positioning results corresponding to the Wifi alternative points.

And a substep 404 of determining whether the geomagnetic positioning result is greater than the Wifi alternative point of the first threshold.

If yes, namely the geomagnetic positioning result is greater than the Wifi alternate point of the first threshold value, executing a substep 406; if not, the geomagnetic positioning result is not greater than the Wifi alternative point with the first threshold, and the step returns to the substep 404 to continue the judgment.

And a substep 406 of selecting Wifi candidate points for screening.

And a substep 408 of clustering the filtered Wifi candidate points according to the distance to determine each cluster set.

And a substep 410 of screening the Wifi alternative point with the maximum observation score in the geomagnetic positioning result as a Wifi screening point for each cluster set.

Can obtain the earth magnetic localization result of each collection point through earth magnetic localization to each Wifi is equipped with the earth magnetic localization result that all corresponds of selection point, and magnetism score that earth magnetism and PDR are synthesized promptly observes the score promptly, then judges the Wifi of earth magnetic localization result whether is greater than first threshold and prepares with the selection point. In this embodiment, the maximum matching score is configured, the first threshold may be configured to be equal to the maximum matching score, or may be configured to be a maximum score of a certain proportion, such as the maximum matching score × q% (e.g., q is 80).

Therefore, Wifi alternate points with the geomagnetic positioning result larger than the first threshold value are screened out, namely the screened Wifi alternate points are determined, then the Wifi screening points are determined by hierarchical clustering of the screened Wifi alternate points, namely the screened Wifi alternate points are hierarchically clustered according to the actual physical distance by using a hierarchical clustering method. The filtered Wifi candidate points can be clustered according to the distance to determine each clustering set, as shown in fig. 5, the black points in the graph are the filtered Wifi candidate points, and the oval boxes represent clustering results, that is, each oval box represents one clustering set. And aiming at each cluster set, selecting a Wifi alternative point with the highest geomagnetic score, namely the observation score, from each cluster set as a final selection point of the cluster set, namely a Wifi screening point. Therefore, if the clustering result is m types, m Wifi screening points can be screened out, wherein m is a positive integer larger than 1.

Therefore, the Wifi candidate points are screened through the geomagnetic positioning result, the Wifi screening points are determined, and secondary screening of Wifi fingerprint points is carried out.

Step 310, map data is divided, and a plurality of grids are determined on the map data.

And step 312, traversing each Wifi screening point, determining Wifi raster data of each grid according to the first Wifi data, and generating rasterized map data by using the grids and the Wifi raster data.

The method can be used for rasterizing the Wifi map, namely dividing map data according to a certain proportion and distance, and determining a plurality of grids on the map data. Then traversing each Wifi screening point, and determining Wifi raster data of each grid by adopting first Wifi data of the Wifi screening points, wherein the first Wifi data comprises: coordinate data and first scan information.

In an alternative embodiment of the present application, as shown in fig. 6, determining the grid map includes the following sub-steps:

and a substep 602, matching the source grids of each Wifi screening point respectively according to the coordinate data, and determining the corresponding first scanning information as Wifi data of each source grid.

Traversing each Wifi screening point, and determining first Wifi data W1(Scan1, Px, Py) of the Wifi screening point, wherein the first Wifi data W1 includes: latitude and longitude coordinate data (Px, Py) and first Scan information Scan 1. From (Px, Py), a corresponding grid identifier (Gx, Gy) can be calculated, which is used to identify a grid, and the grid corresponding to the grid identifier is used as the source grid.

Substep 604, finding the target grid within the preset distance range with each source grid as the center, respectively.

Sub-step 606, determining the distance of the target grid to the source grid.

For a source grid (Gx, Gy), taking (Gx, Gy) as a center, searching grids within a preset distance range, that is, m × m range, configuring indexes of W1 for the grids, that is, configuring Wifi grid data, calculating the distance from the grid to the source grid (Gx, Gy), configuring dist attributes as distances, and further taking first scanning information Scan1 corresponding to the source grid as Wifi data of the grid, the Wifi grid data includes: wifi data Scan1 and distance dist.

And a substep 608 of detecting whether Wifi raster data is recorded in the target mesh.

When the target mesh of one source mesh is determined, the target mesh may already be the target mesh of other source meshes and recorded with Wifi raster data, so that it is also determined whether the target mesh records Wifi raster data.

If yes, namely the target grid records Wifi raster data, executing substep 612; if not, that is, the target mesh does not record Wifi raster data, go to substep 610.

And a substep 610 of recording the distance and the Wifi data of the corresponding source mesh as Wifi raster data of the target mesh.

If the target grid does not record the Wifi raster data, recording the distance and the Wifi data corresponding to the source grid into the Wifi raster data of the target grid.

Sub-step 612, determining a current distance of the target grid from a current source grid and a previous distance of the target grid from a previous source grid.

And if the target grid records Wifi raster data, determining the current distance between the target grid and the current source grid and the previous distance between the target grid and the previous source grid.

And a substep 614 of comparing the current distance with the previous distance.

When the distances between the target grid and different source grids are different, the corresponding Wifi data are also different, so that the current distance and the previous distance can be compared.

When the current distance is greater than the previous distance, the recorded Wifi raster data is retained, i.e., return to sub-step 604 to continue matching the target mesh of the source mesh.

When the current distance is less than the previous distance, performing substep 616; when the current distance is equal to the previous distance, sub-step 618 is performed.

And a substep 616 of updating the recorded Wifi raster data with the current distance and the first scanning information of the current source mesh.

And when the current distance is smaller than the previous distance, replacing the original record with the current distance and the first scanning information of the current source grid, and updating the recorded Wifi raster data.

And a substep 618 of calculating an average value of the first scanning information of the current source grid and the first scanning information of the previous source grid, and updating the recorded Wifi grid data by using the current distance and the average value.

And when the current distance is the same as the previous distance, calculating the average value of the first scanning information of the current source grid and the first scanning information of the previous source grid, and updating the recorded Wifi raster data by adopting the current distance and the average value.

That is, if the mesh to be filled is already filled with the Wifi raster data value, comparing which is smaller between the dist to be filled (current distance) and the dist to be filled (previous distance), selecting the Wifi data Scan1 of smaller dist, that is, if the previous distance is small, the original record is kept, if the current distance is small, the record is updated, and if the distance is the same, the two first scanning information Scan1 are added and averaged.

The Wifi raster data of each mesh includes distance information and Wifi data, so that rasterized map data is generated using the meshes and the Wifi raster data. In the embodiment, GMAP is used for representing the whole rasterized map data; MData represents rasterized map data, that is, Wifi raster data of a mesh, where each MData has Scan1 and dist data inside, and MData _ x _ y is GMAP (x, y) representing rasterized map data at a position x, y.

And step 314, determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal.

Through the screening of above-mentioned step to the track point, can confirm the track point that accords with the second rule, the walking acquisition information of two meters track points includes: an attitude angle of the mobile terminal, a magnetic vector Mg, second scan information, and an attitude change rate of the mobile terminal.

Then, acquiring walking acquisition information of each track point, and determining second Wifi data of the track points, wherein one PDR track consists of step _ num, step _ angle and Scan 2.

Wherein, the track angle step _ angle can be the angle of the track point of the PDR; the step number identifier step _ num can be the step number of the track point of the PDR, such as a first step, a second step and the like; STEP can represent the data of a PDR track point; accordingly, STEP1, STEP2, … …, STEPn are PDR trace data of n trace points.

Because each track point does not have the second scanning information Scan2, the walking track data is determined according to the walking acquisition information of the mobile terminal, the track point with the second scanning information Scan2 is obtained from the walking track data, and the second Wifi data of the track point is obtained.

Step 316, determine the target acquisition point.

After the second Wifi data corresponding to the Wifi raster data and the PDR track are obtained, the Wifi raster data and the PDR track can be matched, the higher the matching degree of the Wifi raster data and the PDR track is, the more possible the Wifi raster data and the PDR track are in the position, namely, the observation score is determined through matching, namely, each Wifi screening point is given a score, the probability of the current position in the position is evaluated, and therefore Wifi positioning is achieved.

The grid map GMAP is determined, each element of the GMAP is Wifi grid data MData, and the content in each MData is data of Scan1 and dist. The PDR trajectory data may be second Wifi data of trajectory points composed of n STEPs, the second Wifi data of each trajectory point containing Scan2, STEP _ num, STEP _ angle, and the like.

In this embodiment, first, a target collection point is determined, Wifi screening points in each search range can be traversed, each Wifi screening point is used as a target collection point, then, according to matching of the second Wifi data and the Wifi raster data, the target collection point is located, and Wifi update points are screened from the target collection points. The acquisition lines of the Wifi screening points can be segmented according to a certain distance, the middle point of each segment after segmentation is used as a target acquisition point, and the corresponding information of the target acquisition point comprises Wifi data such as position and Scan.

And traversing second Wifi data of each track point in the walking track aiming at each target acquisition point, and then matching the second Wifi data with the Wifi raster data to obtain a corresponding matched score so as to screen Wifi update points. The method comprises the following specific steps:

and 318, determining the matching range of the walking track according to the target acquisition point.

And 320, respectively matching the second Wifi data of each track point in the matching range by adopting the Wifi raster data, and screening Wifi updating points from target collection points.

For a selected Wifi screening point, namely a target acquisition point Pm, let ZERO _ ANGLE be the angular range of the track search, STEP _ SIZE _ MIN be the minimum STEP search range, and STEP _ SCAL _ MAX be the maximum STEP search range. Then the STEP distance range between-ZERO _ ANGLE range and STEP _ SIZE _ MIN-STEP _ SCAL _ MAX, i.e. the matching range of the walking trajectory determined by the target acquisition point, corresponds to. Wherein, ZERO _ ANGLE, STEP _ SIZE _ MIN and STEP _ SCAL _ MAX can be set according to actual requirements, such as empirical values.

And traversing each track point in the matching range to match the second Wifi data with the Wifi raster data, and performing a plurality of times of dispersion, namely performing dispersion search on a track error model, so that the highest score of the search in a dispersion space is used as the observation score of the target acquisition point Pm to screen Wifi update points from the target acquisition points.

In an optional embodiment of the present application, as shown in fig. 7, screening Wifi update points by matching specifically includes the following sub-steps:

and a substep 702, determining a corresponding matching range of the walking track by taking the target acquisition point as a terminal point.

And a substep 704 of performing discretization according to the end point, the step search range and the track zero position angle, and traversing the track point from the end point to the front in the matching range.

And a substep 706, determining Wifi raster data corresponding to the track points for each track point in the matching range.

And a substep 708 of calculating a Wifi matching difference and a distance matching difference according to the second Wifi data and the Wifi raster data of the trace point.

And a substep 710, determining the matching score of each track point in the matching range according to the Wifi matching difference and the distance matching difference.

And a substep 712, using the maximum matching score in the matching range as the observed score of the target collection point.

And a substep 714, determining a total score by using the observation score of the target acquisition point and the corresponding geomagnetic positioning result.

And a substep 716 of determining the target collection points meeting the first rule as Wifi update points by comparing the total score of each target collection point with the positioning scoring result.

In a specific example, for a given target acquisition point Pm, a given track zero angle, a given step search range step size, a final match score F score may be calculated from a segment of matching PDR track data.

Taking the target acquisition point as an end point, determining a starting point corresponding to the walking track according to the matching range so as to determine the matching range, and traversing each PDR track data from the end point to the starting point, namely from back to front, so as to execute discrete search of a track error model, wherein the specific process is as follows:

and determining the coordinate range of the target acquisition point Pm, namely enabling Cx to be Pm (x), namely the abscissa of the Pm point, and enabling Cy to be Pm (y), namely the ordinate of the Pm point. And then carrying out dispersion according to the end point, the step size search range step _ size and the track zero angle zero _ angle, and traversing track points from the end point to the front in the matching range, namely:

Cx＝Cx-STEP(step_num)*step_size*cos(STEP(step_angle)+zero_angle)

Cy＝Cy-STEP(step_num)*step_size*sin(STEP(step_angle)+zero_angle)

and then determining Wifi raster data corresponding to the track points aiming at each track point in the matching range, wherein second scanning data in second Wifi data of the matched track points is STEP (Scan2), corresponding positions Cx in correspondingly matched grid maps are WMAP (Cx, Cy). And then calculating Wifi matching difference and distance matching difference according to the second Wifi data and the Wifi raster data of the track points, namely:

the difference Dscan (WMap (cx, cy) -STEP (Scan2)) of each trace point is obtained by subtracting the second Scan information from the first Scan information of the Wifi raster data, wherein the difference of the Scan information is the sum of the squares of the signal intensity differences of each matched trace point in Scan1 and Scan 2.

The distance matching difference Ddist of each track point is WMap (cx, cy).

And calculating the mean value of the Wifi matching of each track point, and taking the mean value as the Wifi matching difference between the PDR track and the Wifi grid map, namely:

then, calculating the mean value of the distance matching differences of the track points, and taking the mean value as the distance matching difference between the PDR track and the Wifi grid map, namely:

wherein n is the number of PDR track points.

And then determining the matching score of the target acquisition point according to the Wifi matching difference and the distance matching difference. Namely, the matching range is discretized according to the Wifi matching difference and the distance matching difference to obtain the corresponding matching score, for example, the matching score is discretized through a gaussian function, namely:

the PDR track and the Wifi matching score of the Wifi grid map are as follows:

S_AllScan＝Guass(D_AllScan,P1)；

distance matching scores of the PDR trajectory and the Wifi grid map:

S_AllDist＝Guass(D_AllDist,P2)；

wherein, S _ AllScan range 0-1, S _ AllDist range 0-1, Guass is Gaussian function, P1, P2 are parameters of Gaussian function respectively.

And then calculating a matching score according to the magnetic matching score and the distance matching score, namely:

F_score＝S_AllDist*S_AllScan

wherein, F _ score is the matching score of the final trajectory and the Wifi grid map.

For a given target acquisition point Pm, all step size, zero angle calculated maximum F score calculated for the traversal is selected as the final observed score for the target acquisition point Pm.

The target collection point is the Wifi screening point, so that the geomagnetic positioning result of the target collection point can be determined, and the total score is determined by adopting the observation score of the target collection point and the corresponding geomagnetic positioning result:

all _ score is the geomagnetic score, and All _ score is the total score.

And obtaining the maximum median score of all the total scores as S, and comparing the total scores of all the target acquisition points with the positioning scoring result to determine whether the first rule is met.

And if All _ score < S × t% can be configured to meet the first rule, the target acquisition point meeting the first rule is used as a Wifi updating point, and t can be configured according to actual requirements.

And step 322, updating the Wifi fingerprint data of the Wifi updating point.

After determining the Wifi update point, the Wifi fingerprint data may be updated, as shown in fig. 8, which specifically includes the following sub-steps:

and a substep 802 of acquiring coordinate data, observation scores, geomagnetic scores in geomagnetic positioning results and walking track data of each Wifi update point aiming at each Wifi update point.

And a substep 804 of determining track points with second Wifi data from the walking track data as target track points.

And a substep 806 of determining the track coordinate data of the target locus point and Wifi data of a grid corresponding to the track coordinate data.

And a substep 808 of determining weighting information according to the observation score and the geomagnetic score.

And a substep 810 of determining Wifi fingerprint data of the Wifi update point according to the weight data, the Wifi data and the second scanning data of the target track point.

Based on the foregoing STEPs, an observation Score F _ Score, a geomagnetic Score M _ Score, and corresponding walking trajectory data STEP1, STEP2 … STEPn of the Wifi update point (Px, Py) can be determined.

Then, a target track point can be screened from the walking track data, Wifi data of the target track point is determined, in the STEPs 1 to STEPn, a track point with second Wifi data is searched to serve as the target track point and is recorded as STEP _ Wifi, then the position of the STEP _ Wifi, namely, track coordinate data, and the Wifi data, namely, first scanning information Scan1 of grids corresponding to the track coordinate data are determined.

Then, determining weight information according to the observation score and the geomagnetic score:

weight information w ═ F _ score ═ M _ score ═ k

Determining Wifi fingerprint data of a Wifi updating point according to the weight data, the Wifi data and the second scanning information of the target track point

Scan_new＝(Scan 1*1+w*STEP_WIFI(wifi))/(1+w)

If one Wifi update point has two or even a plurality of Wifi signals, its corresponding Scan1 may be determined as the average of the Scan information of each Wifi signal, for example, the first Scan information of the two Wifi signals is Scan1_ a and Scan1_ b, respectively, for any mac address in Scan1_ a (corresponding to intensity d1), if Scan1_ b also exists, the signal intensity of the mac address in the last Scan1 is averaged after adding, and if Scan1_ b does not exist, d1 is taken as the signal intensity of the mac address. The above operation is repeated again traversing each mac address in Scan1_ b.

And k is an updating weight proportion coefficient, and the larger k is, the larger the fingerprint updating influence degree is.

And repeating the operation for each STEP _ WIFI to complete the data updating, and circularly and continuously repeating the whole process to complete the Wifi self-updating process.

The determination of the geomagnetic positioning result can be implemented by the following steps:

referring to fig. 8, a flowchart illustrating steps of a geomagnetic positioning result method according to an embodiment of the present application may specifically include the following steps:

and step 802, acquiring first magnetic information corresponding to each acquisition line through the mobile terminal.

In this embodiment, a start point and an end point of line collection are specified in advance, where a collection line may be an indoor passable road, collection may be started by clicking on a mobile terminal, the start end is level with the mobile terminal and moves at a constant speed, and collection may be stopped by clicking when the end point is reached. Recording all the magnetic data Mc1, the first time t1, the first attitude angle Q1, and the start point and the end point in the moving process as the geomagnetic fingerprint information of one acquisition line, that is, recording the first magnetic information corresponding to each acquisition line, where the first magnetic information includes the geomagnetic fingerprint information. The acquisition of the entire map is made up of several line acquisitions.

In this embodiment, in order to ensure the safety of the magnetic data, the magnetic data may be calibrated by using a calibration method, where the magnetic data may include first magnetic information, second magnetic information, a geomagnetic positioning result, wireless positioning data, indoor positioning data, and the like, in an example, a magnetic field calibration of 8 parameters may be performed on the magnetic sensor by using a method of eight-character calibration, that is, a series of trained magnetic data is input, then 8 parameters CP8 of the magnetic calibration are calculated, then the magnetic data Mo is calibrated by using the calculated magnetic parameters, and Mc that is, the calibrated magnetic data may be obtained. Wherein Mo may include magnetic sensor vector data of the mobile terminal in original, and x, y, z, Mc in three dimensions may include magnetic sensor vector data of the mobile terminal after calibration, x, y, z in three dimensions.

Step 804, dividing the map data, and determining a plurality of grids on the map data.

Step 806, determining geomagnetic grid data of each grid according to the first magnetic information of each acquisition line, and generating rasterized map data by using the grids and the geomagnetic grid data.

The magnetic map may be rasterized, that is, map data may be divided according to a certain proportion and distance, and a plurality of meshes may be determined on the map data. And then matching the grids by adopting the first magnetic information of each acquisition line, determining geomagnetic grid data of each grid, and generating rasterized map data by adopting the grids and the geomagnetic grid data.

In an alternative embodiment of the present application, the determining geomagnetic grid data for each grid according to the first magnetic information of each acquisition line, as shown in fig. 9, includes the following sub-steps:

and a substep 902 of traversing each acquisition line and determining magnetic coordinate data of each acquisition point according to the first magnetic information of each acquisition line.

Substep 904 determining first geomagnetic data for each source grid from the magnetic coordinate data.

Traversing each acquisition line, and calculating magnetic coordinate data of each acquisition point according to the starting point and the end point of the acquisition line, the time of the magnetic data and the linear difference, wherein the geomagnetic coordinate data comprises: the longitude and latitude coordinates, the first magnetic data and the first attitude angle. Such as magnetic coordinate data (Px, Py, Mc1, Q1), where Px, Py are latitude and longitude coordinates, Mc1 is the first magnetic data, and Q1 is the first attitude angle. Wherein,

in an optional embodiment of the present application, the determining the first geomagnetic data for each source grid according to the magnetic coordinate data includes: determining grid identification according to the longitude and latitude coordinates, and taking a grid corresponding to the grid identification as a source grid; and rotating the first magnetic data according to the first attitude angle, and determining first geomagnetic data corresponding to the source grid in a geodetic coordinate system.

From (Px, Py), a corresponding grid identifier (Gx, Gy) can be calculated, which is used to identify a grid, and the grid corresponding to the grid identifier is used as the source grid. Then, the Mc1 is rotated by using Q1 according to the first attitude angle Q1 of the mobile terminal and the first magnetic data Mc1, and the first geomagnetic data Mg1, which is the magnetic data vector of the rotated geodetic coordinate system, can be calculated.

Substep 906, finding the target grid within the preset distance range with each source grid as the center, respectively.

Sub-step 908, determining the distance of the target grid to the source grid.

For a source mesh (Gx, Gy), the mesh within a preset distance range, namely m × m range, is searched by taking (Gx, Gy) as the center, then, geomagnetic grid data is configured for the mesh, the distance from the mesh to the source mesh (Gx, Gy) is calculated, dist attributes are configured as distances, first geomagnetic data Mg of magnetic coordinate data corresponding to the source mesh can also be used as the magnetic data of the mesh, and then, the geomagnetic grid data comprises the first geomagnetic data Mg and the distances dist.

Sub-step 910, detecting whether the target mesh records geomagnetic grid data.

When the target mesh of one source mesh is determined, the target mesh may already be recorded with the geomagnetic grid data as the target mesh of the other source mesh, and therefore, it is also determined whether the target mesh is recorded with the geomagnetic grid data.

If yes, namely the target grid records geomagnetic grid data, executing substep 914; if not, that is, the geomagnetic grid data is not recorded in the target grid, go to step 912.

Sub-step 912, recording the distance and the first geomagnetic data corresponding to the source mesh as geomagnetic grid data of the target mesh.

And if the geomagnetic grid data is not recorded in the target grid, recording the distance and the first geomagnetic data corresponding to the source grid into the geomagnetic grid data of the target grid.

Sub-step 914, determining a current distance of the target mesh from a current source mesh and a previous distance of the target mesh from a previous source mesh.

And if the target mesh records geomagnetic grid data, determining the current distance between the target mesh and the current source mesh and the previous distance between the target mesh and the previous source mesh.

Sub-step 916, comparing the current distance with the previous distance.

When the target grid is at different distances from different source grids, the corresponding magnetic data are also different, so that the current distance and the previous distance can be compared.

When the current distance is greater than the previous distance, the recorded geomagnetic grid data is retained, i.e., return to sub-step 906 to continue matching the target grid of the source grid.

Performing substep 918 when the current distance is less than the previous distance; when the current distance is equal to the previous distance, substep 920 is performed.

Sub-step 918, updating the recorded geomagnetic grid data by using the current distance and the first geomagnetic data of the current source grid.

And when the current distance is smaller than the previous distance, replacing the original record with the current distance and the first geomagnetic data of the current source grid, and updating the recorded geomagnetic grid data.

And a substep 920, calculating an average value of the first geomagnetic data of the current source grid and the first geomagnetic data of the previous source grid, and updating the recorded geomagnetic grid data by using the current distance and the average value.

And when the current distance is the same as the previous distance, calculating the mean value of the first geomagnetic data of the current source grid and the first geomagnetic data of the previous source grid, and updating the recorded geomagnetic grid data by adopting the current distance and the mean value.

That is, if the mesh to be filled has already been filled with the geomagnetic lattice data value, which is smaller, is compared with the dist to be filled (current distance) and the dist to be filled (previous distance), the magnetic data value of the smaller dist is selected, that is, the previous distance is smaller, the original recording is kept, the recording is updated if the current distance is smaller, and if the distance is the same, the two pieces of first geomagnetic data Mg1 are added and averaged.

The geomagnetic grid data of each mesh includes distance information and first magnetic data, so that rasterized map data is generated using the meshes and the geomagnetic grid data. In the embodiment, GMAP is used for representing the whole rasterized map data; MData represents a rasterized map data, that is, a mesh of geomagnetic raster data, where each MData has data of Mg1 and dist inside, and MData _ x _ y ═ GMAP (x, y) represents the rasterized map data at the position x, y.

And 808, acquiring information according to the walking of the mobile terminal.

Step 810, rotating the second magnetic data by adopting the second attitude angle, and determining second geomagnetic data corresponding to the track point in a geodetic coordinate system; and acquiring the track angle, the step number identification and the second geomagnetic data of each track point to generate second geomagnetic information.

In this embodiment, the walking acquisition information is acquired based on the PDR technique to determine the second geomagnetic information. That is, walking collection information of PDR track (i.e. walking track) is collected by sensors such as acceleration, gyroscope and magnetic sensor in the mobile terminal, wherein the walking collection information includes: second magnetic data, a second attitude angle.

In this embodiment, each step of the PDR trajectory is configured to be one trajectory point, and then the PDR trajectory is composed of a plurality of trajectory points, so that the attitude angle (Q) of the mobile terminal during the period of walking and the three-axis vector (Mc) of the magnetic sensor can be obtained, that is, on each trajectory point of the PDR, the walking acquisition information corresponding to each step is obtained, including the second magnetic data Mc2, the second attitude angle Q2, the angle of the trajectory point, and the like.

And then determining second geomagnetic information according to the walking acquisition information, rotating the second magnetic data Mc2 by using the second attitude angle Q2, and determining second geomagnetic data corresponding to the track point in a geodetic coordinate system. In the present embodiment, when the function R is a function that rotates Mc into Mg using Q, Mg 2 ═ R (Q2, Mc 2). Then the second magnetic data of a PDR trace point in the geodetic coordinate system may be:

where Mg _ step designates the second magnetic data of a step, and n is the number of groups of Q2 and Mc2 in the step.

And then acquiring the track angle, the STEP number identification and the second geomagnetic data of each track point to generate second geomagnetic information, wherein one PDR track consists of STEP _ num, STEP _ angle, Mg _ STEP and STEP.

Wherein, the track angle step _ angle can be the angle of the track point of the PDR; the step number identifier step _ num can be the step number of the track point of the PDR, such as a first step, a second step and the like; the second geomagnetic data Mg _ step PDR track point is magnetic data of a geodetic coordinate system; STEP can represent the data of a PDR track point; accordingly, STEP1, STEP2, … …, STEPn are PDR trace data of n trace points.

Step 812, determine target acquisition points.

After acquiring the second magnetic information corresponding to the geomagnetic grid data and the PDR track, the geomagnetic grid data and the PDR track may be matched, and the higher the matching degree of the two is, the more likely the geomagnetic observation score is to be determined at the position, that is, a score value is given to each geomagnetic fingerprint point, and the probability that the current position is at the position is evaluated, so as to realize geomagnetic positioning.

The grid map GMAP is determined, each element of the GMAP is geomagnetic grid data MData, and the content in each MData is data of Mg1 and dist. The PDR track data may include second geomagnetic information of track points formed by n STEPs, where the second geomagnetic information of each track point includes Mg _ STEP, STEP _ num, STEP _ angle, and the like.

In this embodiment, first, a target acquisition point is determined, magnetic fingerprint points in each search range may be traversed, each magnetic fingerprint point is used as a target acquisition point, and then, according to matching between the second magnetic information and the geomagnetic grid data, the target acquisition point is located, and a geomagnetic location result of the target acquisition point is determined. The acquisition lines of the magnetic fingerprints can be segmented according to a certain distance, the midpoint of each segmented line segment is used as a target acquisition point (namely a magnetic acquisition point), and the corresponding information of the target acquisition point comprises position, Mg and other magnetic data.

And traversing second magnetic information of each track point in the walking track aiming at each target acquisition point, and then matching the second magnetic information with the geomagnetic grid data to obtain a corresponding matched score so as to determine a geomagnetic positioning result of the target acquisition point. The method comprises the following specific steps:

and 814, determining the matching range of the walking track according to the target acquisition point.

And 816, matching the second magnetic information of each track point in the matching range by adopting the geomagnetic grid data respectively, and determining a geomagnetic positioning result of the target acquisition point.

For a selected magnetic acquisition point, namely the target acquisition point Pm, let ZERO _ ANGLE be the angular range of the track search, STEP _ SIZE _ MIN be the minimum STEP search range, and STEP _ SCAL _ MAX be the maximum STEP search range. Then the STEP distance range between-ZERO _ ANGLE range and STEP _ SIZE _ MIN-STEP _ SCAL _ MAX, i.e. the matching range of the walking trajectory determined by the target acquisition point, corresponds to. Wherein, ZERO _ ANGLE, STEP _ SIZE _ MIN and STEP _ SCAL _ MAX can be set according to actual requirements, such as empirical values.

And traversing each track point in the matching range to match the second magnetic information with the geomagnetic grid data, and performing a plurality of times of dispersion, namely performing dispersion search on a track error model, so that the highest score of the search in a dispersion space is used as an observation score of the target acquisition point Pm, namely a geomagnetic positioning result.

In an optional embodiment of the present application, as shown in fig. 10, the determining, by matching, a geomagnetic positioning result of the target acquisition point specifically includes the following sub-steps:

and a substep 1002, determining a matching range corresponding to the walking track by taking the target acquisition point as a terminal point.

And a substep 1004 of performing discretization according to the end point, the step search range and the track zero-bit angle, and traversing the track points from the end point to the front in the matching range.

And a substep 1006, determining geomagnetic grid data corresponding to the track points for each track point in the matching range.

And a substep 1008 of calculating a magnetic matching difference and a distance matching difference according to the second magnetic information of the track points and the geomagnetic grid data.

And a substep 1010 of determining a geomagnetic positioning result of the target acquisition point according to the magnetic matching difference and the distance matching difference.

Cx＝Cx-STEP(step_num)*step_size*cos(STEP(step_angle)+zero_angle)

Cy＝Cy-STEP(step_num)*step_size*sin(STEP(step_angle)+zero_angle)

and then, for each track point in the matching range, determining magnetic grid data corresponding to the track point, wherein the second magnetic information of the matched track point is STEP (Mg _ STEP), the corresponding position Cx in the correspondingly matched grid map is obtained, and the geomagnetic grid data on the Cy is GMAP (Cx, Cy). Then, calculating magnetic matching difference and distance matching difference according to the second magnetic information of the track points and the geomagnetic grid data, namely:

the magnetic matching difference Dmg for each track point is (GMap (cx, cy) -STEP (Mg _ STEP)), that is, the difference is calculated by subtracting the magnetic vectors of the second magnetic information and the geomagnetic grid data, that is, the difference is calculated by subtracting the first magnetic data Mg1 and the second magnetic data Mg _ STEP.

Distance matching difference Ddist of each track point is GMap (cx, cy).

Then, calculating the average value of the magnetic matching difference of each track point, and taking the average value as the magnetic matching difference of the PDR track and the grid map, namely:

then, calculating the mean value of the distance matching differences of each track point, and taking the mean value as the distance matching difference between the PDR track and the grid map, namely:

wherein n is the number of PDR track points

And then determining a geomagnetic positioning result of the target acquisition point according to the magnetic matching difference and the distance matching difference. In another optional embodiment of the present application, determining a geomagnetic positioning result of the target acquisition point according to the magnetic matching difference and the distance matching difference includes: determining the matching score of each track point in the matching range according to the magnetic matching difference and the distance matching difference; and taking the maximum matching score in the matching range as an observation score of the target acquisition point, and taking the observation score as a geomagnetic positioning result of the target acquisition point. That is, the matching range is discretized according to the magnetic matching difference and the distance matching difference to obtain the corresponding matching score, for example, the matching score is discretized through a gaussian function, that is:

a magnetic matching score S _ AllMg ═ guaass (D _ AllMg, P1) for the PDR trajectory and the grid map;

a distance matching score S _ AllDist ═ guaass (D _ AllDist, P2) of the PDR trajectory and the grid map;

wherein, S _ AllMg range 0-1, S _ AllDist range 0-1, Guass is Gaussian function, P1, P2 are parameters of Gaussian function respectively.

F_score＝S_AllDist*S_AllMg

where F score is the matching score of the final trajectory and the grid map.

Correspondingly, for a given target acquisition point Pm, selecting a matching range formed by all traversed step _ size and zero _ angle, determining the matching score of the track point, then comparing the matching scores, and determining the maximum matching score in the matching range, wherein the maximum matching score F _ score _ max is the final score of the target acquisition point Pm, namely the observed score of the target acquisition point.

If the geomagnetic positioning is only performed, F _ score _ max of all the target acquisition points Pm is calculated according to the above steps to be used as a geomagnetic positioning result, and then the geomagnetic positioning can be completed.

It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.

EXAMPLE III

Referring to fig. 11, a block diagram of a positioning update apparatus according to an embodiment of the present application is shown, which may specifically include the following modules:

and the geomagnetic screening module 1102 is used for screening the Wifi candidate points according to the geomagnetic positioning result to determine Wifi screening points.

And the grid determining module 1104 is configured to determine Wifi grid data according to the first Wifi data of the Wifi screening point.

And a track Wifi determining module 1106, configured to determine second Wifi data of the track point according to the walking acquisition information of the mobile terminal.

And a matching updating module 1108, configured to update Wifi fingerprint data through matching of the second Wifi data and Wifi raster data.

In conclusion, the data of the geomagnetic signals are relatively stable, therefore, a geomagnetic positioning result is adopted to screen Wifi alternate points, the Wifi alternate points are determined, Wifi grid data are determined according to first Wifi data of the Wifi alternate points, second Wifi data of track points are determined according to walking acquisition information of the mobile terminal, and then the Wifi fingerprint data are updated through matching of the second Wifi data and the Wifi grid data, so that timeliness of Wifi fingerprints is guaranteed, and Wifi positioning accuracy is improved.

Referring to fig. 12, a block diagram of another embodiment of the positioning update apparatus of the present application is shown, which may specifically include the following modules:

the track point screening module 1110 is configured to screen track points according to the walking acquisition information of the mobile terminal, and determine track points that meet a second rule, where the second rule includes at least one of the following: number rules, rate of change rules, and angle rules.

An alternative point determining module 1112, configured to determine a Wifi matching number of Wifi fingerprint points; and screening the Wifi fingerprint points with the Wifi matching number exceeding a second threshold value as Wifi alternate points.

The candidate point determining module 1112 is further configured to determine a candidate central point by using a Wifi candidate point, and use a Wifi fingerprint point within a preset range of the candidate central point as the Wifi candidate point.

Wherein, the geomagnetic screening module 1102 includes:

and the geomagnetic determination sub-module 11022 is configured to obtain a geomagnetic positioning result corresponding to each Wifi alternative point.

And the alternative point screening submodule 11024 is configured to screen Wifi alternative points of which the geomagnetic positioning results are greater than a first threshold.

And the clustering submodule 11026 is used for determining the Wifi screening points by carrying out hierarchical clustering on the screened Wifi alternative points.

The clustering submodule 11026 is configured to cluster the filtered Wifi candidate points according to the distance, and determine each clustering set; and screening the Wifi alternate point with the maximum observation score in the geomagnetic positioning result as a Wifi screening point aiming at each clustering set.

A grid determination module 1104, comprising:

a mesh division sub-module 11042 for dividing the map data on which a plurality of meshes are determined.

The grid data determining submodule 11044 is configured to traverse each Wifi filtering point, determine Wifi grid data of each grid according to first Wifi data, and generate rasterized map data by using the grids and the Wifi grid data, where the first Wifi data includes: coordinate data and first scan information.

Referring to fig. 13, a block diagram of a grid data determination submodule in another embodiment of the present application is shown.

The raster data determination sub-module 11044 includes:

and a Wifi data determining unit 110442, configured to match the source grids of each Wifi screening point respectively according to the coordinate data, and determine the corresponding first scanning information as Wifi data of each source grid.

And a searching unit 110444, configured to search the target grids within the preset distance range respectively with each source grid as a center.

And the grid data recording unit 110446 is configured to determine a distance between the target grid and the source grid, and record the distance and Wifi data corresponding to the source grid as Wifi grid data of the target grid.

The grid data recording unit 110446 is further configured to determine, if the target mesh has recorded Wifi data, a current distance between the target mesh and a current source mesh and a previous distance between the target mesh and a previous source mesh; when the current distance is greater than the previous distance, reserving recorded Wifi raster data; when the current distance is smaller than the previous distance, updating the recorded Wifi raster data by adopting the current distance and the first scanning information of the current source grid; and when the current distance is the same as the previous distance, calculating the average value of the first scanning information of the current source grid and the first scanning information of the previous source grid, and updating the recorded Wifi raster data by adopting the current distance and the average value.

A match update module 1108 comprising:

an acquisition point determination sub-module 11082 for determining a target acquisition point.

And the update point screening submodule 11084 is configured to screen Wifi update points from target collection points according to matching between the second Wifi data and the Wifi raster data.

And the updating submodule 11086 is used for updating the Wifi fingerprint data of the Wifi updating point.

Referring to fig. 14, a block diagram of an update point filter submodule in another embodiment of the present application is shown.

Update point filter submodule 11084 includes:

and the range determining unit 110842 is configured to determine a matching range of the walking trajectory according to the target acquisition point.

And the screening unit 110844 is configured to match the second Wifi data of each trace point within the matching range with the Wifi raster data, and screen Wifi update points from the target collection points.

The range determining unit 110842 is configured to determine a matching range corresponding to the walking track with the target collection point as a terminal point; and carrying out dispersion according to the end point, the step length search range and the track zero position angle, and traversing the track point from the end point to the front in the matching range.

The screening unit 110844 is configured to determine Wifi raster data corresponding to each trace point in the matching range; calculating a Wifi matching difference and a distance matching difference according to the second Wifi data and the Wifi raster data of the track points; and screening Wifi updating points from the target acquisition points according to the Wifi matching difference and the distance matching difference.

The screening unit 110844 is configured to determine a matching score of each trace point within the matching range according to the Wifi matching difference and the distance matching difference; taking the maximum matching score in the matching range as the observation score of the target acquisition point; determining a total score by adopting the observation score of the target acquisition point and the corresponding geomagnetic positioning result; and comparing the total score of each target acquisition point with the positioning grading result, and determining the target acquisition points meeting the first rule as Wifi update points.

Referring to fig. 15, a block diagram of an update submodule in another embodiment of the positioning update apparatus of the present application is shown.

The update sub-module 11086 includes:

the data acquisition unit 110862 is configured to acquire, for each Wifi update point, coordinate data, an observation score, and geomagnetic scores and walking trajectory data in geomagnetic positioning results of the Wifi update point;

the screening and determining unit 110864 is configured to screen a target track point from the walking track data, and determine Wifi data corresponding to the target track point;

a weight determination unit 110866 configured to determine weight information according to the observation score and the geomagnetic score;

and the fingerprint updating unit 110868 is configured to determine Wifi fingerprint data of the Wifi updating point according to the weight data, the Wifi data, and the second scanning information of the target trace point.

The screening determining unit 110864 is configured to determine, from the walking trajectory data, a trajectory point having second Wifi data as a target trajectory point; and determining the track coordinate data of the target track point and Wifi data of grids corresponding to the track coordinate data.

And a track Wifi determining module 1106, configured to determine walking track data according to the walking acquisition information of the mobile terminal, and obtain second Wifi data of each track point from the walking track data.

Example four

On the basis of the above embodiment, the embodiment also discloses an intelligent terminal.

Referring to fig. 16, a block diagram of an embodiment of an intelligent terminal according to the present application is shown, which may specifically include the following modules:

this intelligent terminal 1600 includes: memory 1610, display 1620, processor 1630, and input unit 1640.

The input unit 1640 may be used for receiving numeric or character information input by a user, and control signals, among others. Specifically, in the embodiment of the present invention, the input unit 1640 may include a touch screen 1641, which may collect touch operations of a user on or near the touch screen 1641 (for example, operations of the user on the touch screen 1641 by using any suitable object or accessory such as a finger or a stylus pen), and drive the corresponding connection device according to a preset program. Of course, the input unit 1640 may include other input devices such as a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a mouse, etc., in addition to the touch screen 1641.

The display 1620 includes a display panel, and the display panel may be configured in the form of a Liquid Crystal Display (LCD) or an Organic Light-Emitting Diode (OLED). The touch screen may cover the display panel to form a touch display screen, and when the touch display screen detects a touch operation on or near the touch display screen, the touch display screen transmits the touch operation to the processor 630 to perform corresponding processing.

In the embodiment of the present invention, the processor 1630 is configured to filter Wifi candidate points according to the geomagnetic positioning result by calling a software program and/or a module and/or data stored in the memory 1610, so as to determine Wifi filter points; determining Wifi raster data according to the first Wifi data of the Wifi screening point; determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal; and updating the Wifi fingerprint data through matching the second Wifi data with the Wifi raster data.

Optionally, the step of screening the Wifi alternate points according to the geomagnetic positioning result to determine the Wifi screening points includes: acquiring a geomagnetic positioning result corresponding to each Wifi alternative point; screening Wifi alternative points with the geomagnetic positioning result larger than a first threshold; and determining the Wifi screening points by performing hierarchical clustering on the screened Wifi alternative points.

Optionally, the determining the Wifi screening point by performing hierarchical clustering on the filtered Wifi candidate point includes: clustering the screened Wifi alternative points according to the distance, and determining each clustering set; and screening the Wifi alternate point with the maximum observation score in the geomagnetic positioning result as a Wifi screening point aiming at each clustering set.

Optionally, determining Wifi raster data according to the first Wifi data of the Wifi screening point includes: dividing map data, and determining a plurality of grids on the map data; traversing each Wifi screening point, determining Wifi raster data of each grid according to first Wifi data, and generating rasterized map data by adopting the grids and the Wifi raster data, wherein the first Wifi data comprises: coordinate data and first scan information.

Optionally, the determining Wifi raster data of each mesh according to the first Wifi data, and generating rasterized map data by using the meshes and the Wifi raster data includes: respectively matching the source grids of each Wifi screening point according to the coordinate data, and determining corresponding first scanning information as Wifi data of each source grid; respectively taking each source grid as a center, and searching a target grid within a preset distance range; and determining the distance from the target grid to the source grid, and recording the distance and the Wifi data corresponding to the source grid as Wifi raster data of the target grid.

Optionally, after searching for a target grid within a preset distance range with the current source grid as a center, the method further includes: if the target grid records Wifi data, determining the current distance between the target grid and the current source grid and the previous distance between the target grid and the previous source grid; when the current distance is greater than the previous distance, reserving recorded Wifi raster data; when the current distance is smaller than the previous distance, updating the recorded Wifi raster data by adopting the current distance and the first scanning information of the current source grid; and when the current distance is the same as the previous distance, calculating the average value of the first scanning information of the current source grid and the first scanning information of the previous source grid, and updating the recorded Wifi raster data by adopting the current distance and the average value.

Optionally, the updating of the Wifi fingerprint data through the matching of the second Wifi data and the Wifi raster data includes: determining a target acquisition point; screening Wifi updating points from target collecting points according to matching of the second Wifi data and the Wifi raster data; and updating the Wifi fingerprint data of the Wifi updating point.

Optionally, screening Wifi update points from target collection points according to matching between the second Wifi data and the Wifi raster data, including: determining the matching range of the walking track according to the target acquisition point; and respectively matching the second Wifi data of each track point in the matching range by adopting the Wifi raster data, and screening Wifi updating points from target acquisition points.

Optionally, determining a matching range of the walking trajectory according to the target acquisition point includes: determining a corresponding matching range of the walking track by taking the target acquisition point as a terminal point; and carrying out dispersion according to the end point, the step length search range and the track zero position angle, and traversing the track point from the end point to the front in the matching range.

Optionally, the second Wifi data of each trace point in the matching range is adopted, the Wifi raster data is respectively matched, Wifi update points are screened from target collection points, and the method includes: for each track point in the matching range, determining Wifi raster data corresponding to the track point; calculating a Wifi matching difference and a distance matching difference according to the second Wifi data and the Wifi raster data of the track points; and screening Wifi updating points from the target acquisition points according to the Wifi matching difference and the distance matching difference.

Optionally, screening Wifi update points from target collection points according to the Wifi matching difference and the distance matching difference, including: determining the matching score of each track point in the matching range according to the Wifi matching difference and the distance matching difference; taking the maximum matching score in the matching range as the observation score of the target acquisition point; determining a total score by adopting the observation score of the target acquisition point and the corresponding geomagnetic positioning result; and comparing the total score of each target acquisition point with the positioning grading result, and determining the target acquisition points meeting the first rule as Wifi update points.

Optionally, the updating the Wifi fingerprint data of the Wifi update point includes: acquiring coordinate data, observation scores and geomagnetic scores and walking track data in geomagnetic positioning results of each Wifi updating point; screening target track points from the walking track data, and determining Wifi data corresponding to the target track points; determining weight information according to the observation score and the geomagnetic score; and determining the Wifi fingerprint data of the Wifi updating point according to the weight data, the Wifi data and the second scanning information of the target track point.

Optionally, screening target track points from the walking track data, and determining Wifi data of the target track points, including: determining track points with second Wifi data from the walking track data to serve as target track points; and determining the track coordinate data of the target track point and Wifi data of grids corresponding to the track coordinate data.

Optionally, according to the walking collection information of the mobile terminal, determining second Wifi data of the track point, including: and determining walking track data according to the walking acquisition information of the mobile terminal, and acquiring second Wifi data of each track point from the walking track data.

Optionally, the method further includes: and (3) screening the track points: screening the track points according to the walking acquisition information of the mobile terminal, and determining the track points which accord with a second rule, wherein the second rule comprises at least one of the following items: number rules, rate of change rules, and angle rules.

Optionally, the method further comprises the step of screening Wifi alternate points: determining the Wifi matching number of Wifi fingerprint points; and screening the Wifi fingerprint points with the Wifi matching number exceeding a second threshold value as Wifi alternate points.

Optionally, the method further includes: and determining the candidate central point by adopting a Wifi candidate point, and taking the Wifi fingerprint point within the preset range of the candidate central point as the Wifi candidate point.

For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

In a typical configuration, the computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (fransitory media), such as modulated data signals and carrier waves.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.

Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.

The positioning updating method, the positioning updating device and the mobile terminal provided by the application are introduced in detail, and a specific example is applied in the text to explain the principle and the implementation of the application, and the description of the above embodiment is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A method of location updating, comprising:

screening Wifi alternative points according to the geomagnetic positioning result, and determining Wifi screening points;

determining Wifi raster data according to the first Wifi data of the Wifi screening point;

determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal;

and updating the Wifi fingerprint data through matching the second Wifi data with the Wifi raster data.

2. The method as claimed in claim 1, wherein the step of screening the Wifi alternative points according to the geomagnetic positioning result to determine Wifi screening points comprises:

acquiring a geomagnetic positioning result corresponding to each Wifi alternative point;

screening Wifi alternative points with the geomagnetic positioning result larger than a first threshold;

and determining the Wifi screening points by performing hierarchical clustering on the screened Wifi alternative points.

3. The method as claimed in claim 2, wherein determining Wifi candidate points by hierarchical clustering of the filtered Wifi candidate points comprises:

clustering the screened Wifi alternative points according to the distance, and determining each clustering set;

and screening the Wifi alternate point with the maximum observation score in the geomagnetic positioning result as a Wifi screening point aiming at each clustering set.

4. The method of claim 1, wherein determining Wifi raster data from the first Wifi data of the Wifi screening point comprises:

dividing map data, and determining a plurality of grids on the map data;

traversing each Wifi screening point, determining Wifi raster data of each grid according to first Wifi data, and generating rasterized map data by adopting the grids and the Wifi raster data, wherein the first Wifi data comprises: coordinate data and first scan information.

5. The method as claimed in claim 4, wherein the determining Wifi raster data of each mesh according to the first Wifi data, and generating rasterized map data using the meshes and the Wifi raster data comprises:

respectively matching the source grids of each Wifi screening point according to the coordinate data, and determining corresponding first scanning information as Wifi data of each source grid;

respectively taking each source grid as a center, and searching a target grid within a preset distance range;

and determining the distance from the target grid to the source grid, and recording the distance and the Wifi data corresponding to the source grid as Wifi raster data of the target grid.

6. The method of claim 5, wherein after finding the target grid within the preset distance range centered on the current source grid, further comprising:

if the target grid records Wifi data, determining the current distance between the target grid and the current source grid and the previous distance between the target grid and the previous source grid;

when the current distance is greater than the previous distance, reserving recorded Wifi raster data;

when the current distance is smaller than the previous distance, updating the recorded Wifi raster data by adopting the current distance and the first scanning information of the current source grid;

7. The method of claim 1, wherein updating the Wifi fingerprint data by matching the second Wifi data with Wifi raster data comprises:

determining a target acquisition point;

screening Wifi updating points from target collecting points according to matching of the second Wifi data and the Wifi raster data;

and updating the Wifi fingerprint data of the Wifi updating point.

8. The method as claimed in claim 7, wherein screening Wifi update points from target collection points according to matching of the second Wifi data and the Wifi raster data comprises:

determining the matching range of the walking track according to the target acquisition point;

and respectively matching the second Wifi data of each track point in the matching range by adopting the Wifi raster data, and screening Wifi updating points from target acquisition points.

9. The method of claim 8, wherein determining a matching range of a walking trajectory from the target acquisition points comprises:

determining a corresponding matching range of the walking track by taking the target acquisition point as a terminal point;

and carrying out dispersion according to the end point, the step length search range and the track zero position angle, and traversing the track point from the end point to the front in the matching range.

10. The method as claimed in claim 8, wherein the step of respectively matching the second Wifi data of each trace point in the matching range by using the Wifi raster data and screening Wifi update points from target collection points comprises:

for each track point in the matching range, determining Wifi raster data corresponding to the track point;

calculating a Wifi matching difference and a distance matching difference according to the second Wifi data and the Wifi raster data of the track points;

and screening Wifi updating points from the target acquisition points according to the Wifi matching difference and the distance matching difference.

11. The method as claimed in claim 10, wherein screening Wifi update points from target collection points according to the Wifi matching difference and the distance matching difference comprises:

determining the matching score of each track point in the matching range according to the Wifi matching difference and the distance matching difference;

taking the maximum matching score in the matching range as the observation score of the target acquisition point;

determining a total score by adopting the observation score of the target acquisition point and the corresponding geomagnetic positioning result;

and comparing the total score of each target acquisition point with the positioning grading result, and determining the target acquisition points meeting the first rule as Wifi update points.

12. The method as claimed in claim 11, wherein the updating the Wifi fingerprint data of the Wifi update point comprises:

acquiring coordinate data, observation scores and geomagnetic scores and walking track data in geomagnetic positioning results of each Wifi updating point;

screening target track points from the walking track data, and determining Wifi data corresponding to the target track points;

determining weight information according to the observation score and the geomagnetic score;

and determining the Wifi fingerprint data of the Wifi updating point according to the weight data, the Wifi data and the second scanning information of the target track point.

13. The method of claim 12, wherein the step of screening target track points from the walking track data and determining Wifi data of the target track points comprises:

determining track points with second Wifi data from the walking track data to serve as target track points;

and determining the track coordinate data of the target track point and Wifi data of grids corresponding to the track coordinate data.

14. The method of claim 12, wherein determining the second Wifi data of the trace point according to the walking collection information of the mobile terminal comprises:

and determining walking track data according to the walking acquisition information of the mobile terminal, and acquiring second Wifi data of each track point from the walking track data.

15. The method of claim 1, further comprising: and (3) screening the track points:

screening the track points according to the walking acquisition information of the mobile terminal, and determining the track points which accord with a second rule, wherein the second rule comprises at least one of the following items: number rules, rate of change rules, and angle rules.

16. The method of claim 1, further comprising the step of screening Wifi alternate points:

determining the Wifi matching number of Wifi fingerprint points;

and screening the Wifi fingerprint points with the Wifi matching number exceeding a second threshold value as Wifi alternate points.

17. The method of claim 1, further comprising:

and determining the candidate central point by adopting a Wifi candidate point, and taking the Wifi fingerprint point within the preset range of the candidate central point as the Wifi candidate point.

18. A positioning update apparatus, comprising:

the geomagnetic screening module is used for screening the Wifi alternative points according to the geomagnetic positioning result and determining Wifi screening points;

the grid determining module is used for determining Wifi grid data according to the first Wifi data of the Wifi screening point;

the track Wifi determining module is used for determining second Wifi data of the track points according to the walking acquisition information of the mobile terminal;

and the matching updating module is used for updating the Wifi fingerprint data through matching of the second Wifi data and the Wifi raster data.

19. The apparatus of claim 18, wherein the geomagnetic screening module comprises:

the geomagnetic determination submodule is used for acquiring geomagnetic positioning results corresponding to the Wifi alternative points;

the alternate point screening submodule is used for screening Wifi alternate points of which the geomagnetic positioning results are larger than a first threshold value;

and the clustering submodule is used for determining the Wifi screening points by carrying out hierarchical clustering on the screened Wifi alternative points.

20. The apparatus of claim 19,

the clustering submodule is used for clustering the screened Wifi alternative points according to the distance and determining each clustering set; and screening the Wifi alternate point with the maximum observation score in the geomagnetic positioning result as a Wifi screening point aiming at each clustering set.

21. The apparatus of claim 18, wherein the grid determination module comprises:

the grid division submodule is used for dividing map data and determining a plurality of grids on the map data;

the grid data determining submodule is used for traversing each Wifi screening point, determining Wifi grid data of each grid according to first Wifi data, and generating rasterized map data by adopting the grids and the Wifi grid data, wherein the first Wifi data comprises: coordinate data and first scan information.

22. The apparatus of claim 21, wherein the raster data determination sub-module comprises:

the Wifi data determining unit is used for respectively matching the source grids of each Wifi screening point according to the coordinate data and determining the corresponding first scanning information as Wifi data of each source grid;

the searching unit is used for respectively taking each source grid as a center and searching a target grid within a preset distance range;

and the raster data recording unit is used for determining the distance from the target grid to the source grid and recording the distance and the Wifi data corresponding to the source grid as the Wifi raster data of the target grid.

23. The apparatus of claim 21,

the grid data recording unit is further configured to determine a current distance between the target grid and a current source grid and a previous distance between the target grid and a previous source grid if the target grid records Wifi data; when the current distance is greater than the previous distance, reserving recorded Wifi raster data; when the current distance is smaller than the previous distance, updating the recorded Wifi raster data by adopting the current distance and the first scanning information of the current source grid; and when the current distance is the same as the previous distance, calculating the average value of the first scanning information of the current source grid and the first scanning information of the previous source grid, and updating the recorded Wifi raster data by adopting the current distance and the average value.

24. The apparatus of claim 18, wherein the match update module comprises:

the acquisition point determining submodule is used for determining a target acquisition point;

the updating point screening submodule is used for screening the Wifi updating points from the target collecting points according to the matching of the second Wifi data and the Wifi raster data;

and the updating submodule is used for updating the Wifi fingerprint data of the Wifi updating point.

25. The apparatus of claim 24, wherein the update point filter submodule comprises:

the range determining unit is used for determining the matching range of the walking track according to the target acquisition point;

and the screening unit is used for respectively matching the second Wifi data of each track point in the matching range by adopting the Wifi raster data and screening Wifi updating points from the target acquisition points.

26. The apparatus of claim 25,

the range determining unit is used for determining a corresponding matching range of the walking track by taking the target acquisition point as a terminal point; and carrying out dispersion according to the end point, the step length search range and the track zero position angle, and traversing the track point from the end point to the front in the matching range.

27. The method of claim 25,

the screening unit is used for determining Wifi raster data corresponding to the track points aiming at each track point in the matching range; calculating a Wifi matching difference and a distance matching difference according to the second Wifi data and the Wifi raster data of the track points; and screening Wifi updating points from the target acquisition points according to the Wifi matching difference and the distance matching difference.

28. The apparatus of claim 27,

the screening unit is used for determining the matching score of each track point in the matching range according to the Wifi matching difference and the distance matching difference; taking the maximum matching score in the matching range as the observation score of the target acquisition point; determining a total score by adopting the observation score of the target acquisition point and the corresponding geomagnetic positioning result; and comparing the total score of each target acquisition point with the positioning grading result, and determining the target acquisition points meeting the first rule as Wifi update points.

29. The apparatus of claim 28, wherein the update submodule comprises:

the data acquisition unit is used for acquiring coordinate data, observation scores and geomagnetic scores and walking track data in geomagnetic positioning results of the Wifi update points aiming at each Wifi update point;

the screening and determining unit is used for screening target track points from the walking track data and determining Wifi data corresponding to the target track points;

the weight determining unit is used for determining weight information according to the observation score and the geomagnetic score;

and the fingerprint updating unit is used for determining the Wifi fingerprint data of the Wifi updating point according to the weight data, the Wifi data and the second scanning information of the target track point.

30. The apparatus of claim 29,

the screening and determining unit is used for determining track points with second Wifi data from the walking track data as target track points; and determining the track coordinate data of the target track point and Wifi data of grids corresponding to the track coordinate data.

31. The apparatus of claim 29,

and the track Wifi determining module is used for determining walking track data according to the walking acquisition information of the mobile terminal and acquiring second Wifi data of each track point from the walking track data.

32. The apparatus of claim 18, further comprising:

and the track point screening module is used for screening the track points according to the walking acquisition information of the mobile terminal and determining the track points which accord with a second rule, wherein the second rule comprises at least one of the following items: number rules, rate of change rules, and angle rules.

33. The apparatus of claim 18, further comprising:

the alternate point determining module is used for determining the Wifi matching number of the Wifi fingerprint points; and screening the Wifi fingerprint points with the Wifi matching number exceeding a second threshold value as Wifi alternate points.

34. The apparatus of claim 18,

and the candidate point determining module is also used for determining a candidate central point by adopting a Wifi candidate point, and taking a Wifi fingerprint point in a preset range of the candidate central point as the Wifi candidate point.

35. A mobile terminal, characterized in that the mobile terminal comprises: memory, a display, a processor and an input unit, the processor being adapted to perform the method of any of the preceding claims 1-17.