CN117295158B - WiFi positioning method, device, equipment and medium based on fingerprint matching - Google Patents
WiFi positioning method, device, equipment and medium based on fingerprint matching Download PDFInfo
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Abstract
The invention provides a WiFi positioning method, a device, equipment and a medium based on fingerprint matching, wherein the method comprises the following steps: acquiring reference signal intensities of m wireless access points, and constructing a sub-fingerprint library according to the m reference signal intensities to obtainA sub-fingerprint library; acquiring the received signal strengths of m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location; according toSub fingerprint libraryObtaining sub-fingerprints of each positionSubspaces and respectively atDetermining K adjacent reference point coordinates in the subspace according to the corresponding Euclidean distance of the signal intensity; according to respectivelyWeighting calculation is carried out on K adjacent reference point coordinates corresponding to the subspace to obtainCoarse positioning of position coordinates and according toThe coarse positioning position coordinates obtain target positioning position coordinates so as to effectively reduce the shielding of objects in the environment on the wireless access pointThe influence of signal interference caused by signals effectively improves the precision and the robustness of the WiFi positioning technology.
Description
Technical Field
The invention relates to the technical field of object positioning, in particular to a WiFi positioning method, device, equipment and medium based on fingerprint matching.
Background
In recent years, with the continuous development of wireless communication technology and internet, outdoor positioning technology is mature, but in indoor environment, under the influence of factors such as shielding of buildings and signal interference, outdoor positioning technology cannot be effectively applied in indoor environment, so the current demand for indoor positioning technology with high precision and high reliability is also rising.
Currently, among many positioning technologies in the indoor positioning field, as the wireless fidelity (wireless fidelity, wiFi) indoor technology can effectively utilize a widely distributed WiFi network, and provides conditions of low cost and convenient implementation, fingerprint matching positioning technology based on WiFi received signal strength indication (received signal strength indicator, RSSI) becomes a hotspot for researching indoor positioning in recent years, however, in a complex indoor environment, the situation that signals of a WiFi wireless Access Point (AP) fluctuate due to object shielding is unavoidable, so that positioning accuracy of the WiFi positioning technology can be affected.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the invention provides a WiFi positioning method, electronic equipment and medium based on fingerprint matching, which aim to solve the technical problem that the positioning accuracy of a WiFi positioning technology is affected by fluctuation of signals of a wireless access point in the prior art and can improve the accuracy and robustness of the WiFi positioning technology.
To achieve the above objective, a first aspect of an embodiment of the present invention provides a WiFi positioning method based on fingerprint matching, including:
acquiring reference signal intensities of m wireless access points, and constructing a sub-fingerprint library according to the m reference signal intensities to obtainA sub-fingerprint library;
acquiring the received signal strengths of m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location;
according toThe sub fingerprint library and +.>The sub-fingerprints of the positions are +.>Subspaces and respectively atDetermining K adjacent reference point coordinates in each subspace according to the corresponding Euclidean distance of the signal intensity;
according to respectivelyWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain Coarse positioning position coordinates and according to +.>And obtaining the target positioning position coordinates by the coarse positioning position coordinates.
In some embodiments, the said respectivelyDetermining K adjacent reference point coordinates in each subspace according to the corresponding signal intensity euclidean distance, including:
respectively atThe following steps are carried out in each subspace:
calculating Euclidean distances between a plurality of reference signal intensities corresponding to the subspace and a plurality of received signal intensities;
determining a minimum Euclidean distance from a plurality of Euclidean distances;
calculating distance differences between a plurality of the Euclidean distances and the minimum Euclidean distance;
and determining K adjacent reference point coordinates corresponding to the subspace according to the distance differences.
In some embodiments, the determining K adjacent reference point coordinates corresponding to the subspace according to the plurality of distance differences includes:
obtaining a target limit value;
performing data screening processing on a plurality of distance differences according to the target limit value to obtain K target distance differences smaller than or equal to the target limit value from the plurality of distance differences;
and determining the position coordinates of the reference points corresponding to the K target distance differences as adjacent reference point coordinates.
In some embodiments, the reference signal strengths of the m wireless access points are obtained, and the sub-fingerprint library construction process is performed according to the m reference signal strengths to obtainA sub-fingerprint library comprising:
acquiring fingerprint database data, wherein the fingerprint database data comprises position coordinates of a plurality of reference points and reference fingerprint information, and the reference fingerprint information comprises reference signal intensities of m wireless access points;
traversing m reference signal intensities, and constructing a sub-fingerprint library according to (m-1) reference signal intensities except the current traversed object in the traversing process to obtainAnd each sub fingerprint library.
In some embodiments, the receiving signal intensities of the m wireless access points are obtained, and the location sub-fingerprint construction process is performed according to the m receiving signal intensities to obtainA sub-fingerprint of a location, comprising:
acquiring position fingerprint information received by a current position, wherein the position fingerprint information comprises the received signal strengths of m wireless access points;
traversing m of said junctionsThe intensity of the received signal and constructing a position sub-fingerprint according to (m-1) the intensity of the received signal except the current traversing object in the traversing process to obtain And each of the location sub-fingerprints.
In some embodiments, the said respectively according toWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain +.>A coarse positioning location coordinate comprising:
respectively atThe following steps are carried out in each subspace:
and carrying out weighted calculation on the K adjacent reference point coordinates corresponding to the subspace based on a preset coordinate estimation expression and the Euclidean distance to obtain a coarse positioning position coordinate corresponding to the subspace, wherein the coordinate estimation expression is as follows:
，
wherein,for the coarse positioning position coordinates, +.>For the adjacent reference point coordinates +.>And the Euclidean distance corresponding to the adjacent reference point coordinate is obtained.
In some embodiments, the said methodObtaining the target positioning position coordinates by the coarse positioning position coordinates comprises the following steps:
based on a preset average filtering expression, forThe coarse positioning position coordinates are averaged,
and obtaining the target positioning position coordinates, wherein the average filtering expression is as follows:
，
wherein,locating position coordinates for the object, +.>For the coarse positioning position coordinates, +.>And the number of the coarse positioning position coordinates is the number.
To achieve the above object, a second aspect of the embodiments of the present invention provides a WiFi positioning device based on fingerprint matching, including:
The sub fingerprint library construction module is used for acquiring the reference signal intensities of m wireless access points and carrying out sub fingerprint library construction processing according to the m reference signal intensities so as to obtainA sub-fingerprint library;
the position sub-fingerprint determining module is used for acquiring the received signal strengths of the m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location;
a proximity coordinate determination module for determining a proximity coordinate based onThe sub fingerprint library and +.>The sub-fingerprints of the positions are obtainedSubspace and are respectively +.>Determining K adjacent reference point coordinates in each subspace according to the corresponding Euclidean distance of the signal intensity;
target position determining modules for respectively according toWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain +.>Coarse positioning position coordinates and according to +.>And obtaining the target positioning position coordinates by the coarse positioning position coordinates.
To achieve the above object, a third aspect of the embodiments of the present invention provides an electronic device, which includes a memory, a processor, where the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.
To achieve the above object, a fourth aspect of the embodiments of the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of the first aspect.
The invention provides a WiFi positioning method, a device, equipment and a medium based on fingerprint matching, which are used for acquiring the reference signal strength of each wireless access point in the whole target area in an off-line database building stage to constructEstablishing a sub-fingerprint library, combining position sub-fingerprints obtained according to the received signal strength in an online positioning stage to form a plurality of subspaces, performing coarse positioning in the subspaces according to Euclidean distances between the reference signal strength and the received signal strength, and finally integrating coarse positioning position coordinates obtained in each subspace to estimate target positioning position coordinates, wherein the target positioning position coordinates are estimated due to the fact thatThe subspaces are formed by arranging and combining m wireless access points, each wireless access point has a unique MAC address, and certain constraint is provided for different positions, namely, the constraint of a plurality of wireless access points is stronger than that of a single wireless access point, so when signals of a certain wireless access point are shielded by an object to generate signal fluctuation, the subspaces with different wireless access point combinations can be used for positioning, and the positioning results of the subspaces are fused, so that the signal distribution of the wireless access points in a positioning environment is fully considered, the influence of the object in the environment on signal interference caused by shielding of the wireless access points is effectively reduced, the constraint of a WiFi positioning technology on the positioning position is further enhanced, and the precision and the robustness of the WiFi positioning technology are effectively improved.
Drawings
Fig. 1 is a flow chart of a WiFi positioning method based on fingerprint matching according to an embodiment of the present invention;
fig. 2 is a flowchart of a WiFi positioning method based on fingerprint matching according to another embodiment of the present application;
fig. 3 is a flowchart of a WiFi positioning method based on fingerprint matching according to another embodiment of the present application;
fig. 4 is a flowchart of a WiFi positioning method based on fingerprint matching according to another embodiment of the present application;
fig. 5 is a flowchart of a WiFi positioning method based on fingerprint matching according to another embodiment of the present application;
fig. 6 is a flowchart of a WiFi positioning method based on fingerprint matching according to another embodiment of the present application;
FIG. 7 is a schematic diagram of an adaptive fingerprint matching process provided in another embodiment of the present application;
FIG. 8 is a schematic diagram of an adaptive fingerprint subspace matching positioning procedure provided in another embodiment of the present application;
fig. 9 is a schematic structural diagram of a WiFi positioning device based on fingerprint matching according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It should be noted that although functional block division is performed in a device diagram and a logic sequence is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.
In recent years, with the continuous progress of technology, indoor positioning requirements are more and more remarkable, especially in the situation that indoor activities account for 80%. Traditional outdoor satellite navigation systems, such as Beidou and global navigation satellite systems, cannot meet the demands in the indoor space due to the problems of building shielding, signal interference and the like. Indoor positioning technologies are numerous, including RFID, bluetooth, ultrasound, ultra wideband, inertial navigation, and WLAN, which achieve high positioning accuracy in specific environments, but there are also respective limitations, such as: RFID positioning is limited by power and is only suitable for use in close range positioning; the bluetooth positioning requires higher early-stage work and equipment cost; the ultrasonic positioning is greatly influenced by the environment, and the cost is high; the equipment required by ultra-wideband positioning is expensive, and the requirements of consumer level cannot be met; the inertial navigation positioning has accumulated drift errors in positioning, and the errors are larger and larger as time advances; WLAN positioning is susceptible to environmental interference and requires considerable preparation in the early stages.
Among many positioning technologies in the indoor positioning field, the WiFi positioning technology is paid attention to, although it has drawbacks such as signal fluctuation and environmental interference, but a widely distributed WiFi network provides low cost and convenient implementation conditions for the WiFi positioning technology, and in order to improve the positioning accuracy of the WiFi fingerprint matching, a plurality of innovative algorithms are provided by the skilled person, including optimizing K value, dynamic sub-area limitation, kalman filtering, and multi-technology fusion, etc., however, in the application process of the WiFi positioning technology, the situation that the signal of the WiFi wireless Access Point (AP) fluctuates due to the object shielding is unavoidable, so that the positioning accuracy of the WiFi positioning technology can be affected.
Based on the above, the embodiment of the invention provides a WiFi positioning method, electronic equipment and medium based on fingerprint matching, which aim to solve the technical problem that the signal of a wireless access point fluctuates to influence the positioning precision of the WiFi positioning technology in the prior art, and can improve the precision and the robustness of the WiFi positioning technology.
Referring to fig. 1, fig. 1 shows a flowchart of a WiFi positioning method based on fingerprint matching according to an embodiment of the present application, and as shown in fig. 1, an image card number identification method includes, but is not limited to, steps S110 to S140:
Step S110, obtaining the reference signal intensities of m wireless access points, and constructing a sub-fingerprint library according to the m reference signal intensities to obtainA sub-fingerprint library;
step S120, obtaining the received signal strength of m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location;
step S130, according toSub fingerprint library and->The sub-fingerprint of the individual location is +.>Subspaces and respectively atDetermining K adjacent reference point coordinates in the subspace according to the corresponding Euclidean distance of the signal intensity;
step S140, according toWeighting calculation is carried out on K adjacent reference point coordinates corresponding to the subspace to obtainCoarse positioning position coordinates and according to +.>And obtaining the target positioning position coordinates by the rough positioning position coordinates.
In some embodiments, step S110 corresponds to an off-line database creation stage, and steps S120 to S140 correspond to an on-line positioning stage, in the off-line database creation stage, reference signal intensities of each wireless access point in the whole target area are obtained to construct a sub-fingerprint database, and position sub-fingerprints obtained according to the received signal intensities in the on-line positioning stage are combined to form a plurality of subspaces, and then the subspaces are combined according to the reference signal intensities and the reference signal intensities in the plurality of subspaces Coarse positioning is carried out on Euclidean distance between received signal intensities, and finally coarse positioning position coordinates obtained from each subspace are integrated, so that target positioning position coordinates are estimated, wherein the coarse positioning position coordinates are obtained due to the fact thatThe subspaces are formed by arranging and combining m wireless access points, each wireless access point has a unique MAC address, and certain constraint is provided for different positions, namely, the constraint of a plurality of wireless access points is stronger than that of a single wireless access point, so when signals of a certain wireless access point are shielded by an object to generate signal fluctuation, the subspaces with different wireless access point combinations can be used for positioning, and the positioning results of the subspaces are fused, so that the signal distribution of the wireless access points in a positioning environment is fully considered, the influence of the object in the environment on signal interference caused by shielding of the wireless access points is effectively reduced, the constraint of a WiFi positioning technology on the positioning position is further enhanced, and the precision and the robustness of the WiFi positioning technology are effectively improved.
In some embodiments, steps S110 to S140 correspond to the fingerprint subspace matching positioning procedure of the present application, and it is conceivable that the subspaces in the present application refer to a plurality of different wireless Access Point (AP) combinations, which do not limit specific reference points or test points, i.e. if the reference signal strength and the received signal strength of the reference points or test points meet the AP combinations of any subspace, the corresponding reference signal strength and the received signal strength can be substituted into the subspaces to perform euclidean distance calculation, so as to determine K adjacent reference point coordinates from the reference point coordinates, specifically, in the spatial positioning, assuming that there are m APs in total, selecting (m-1) APs as 1 subset (subspace), so that by permutation and combination, we can obtain Subspaces, in each of which K adjacent reference points can be determined by Euclidean distance according to corresponding signal strengthAnd (3) carrying out position estimation by a coordinate method, namely respectively solving Euclidean distances between a sub-fingerprint library corresponding to the AP combination of the subspace and the sub-fingerprint at the corresponding position of the plurality of reference point coordinates, determining the Euclidean distances between the sub-fingerprint library and the sub-fingerprint at the position by the corresponding plurality of reference signal intensities and the received signal intensities, and finally integrating the positions of all the subspaces to obtain the final positioning position.
In some embodiments, please refer to fig. 2, fig. 2 shows a flow chart of an image card number recognition method according to an embodiment of the present application, as shown in fig. 2, respectivelyK adjacent reference point coordinates are determined in the subspace according to the corresponding Euclidean distance of the signal intensity, including but not limited to the steps S210 to S240:
respectively atThe following steps are performed in the subspace:
step S210, calculating Euclidean distances between a plurality of reference signal intensities corresponding to the subspace and a plurality of received signal intensities;
step S220, determining the minimum Euclidean distance from a plurality of Euclidean distances;
step S230, calculating distance differences between a plurality of Euclidean distances and the minimum Euclidean distance;
In step S240, K adjacent reference point coordinates corresponding to the subspace are determined according to the plurality of distance differences.
In some embodiments, step S210 to step S240 correspond to the present application, and the adaptive fingerprint matching process is performed by an adaptive weighted K-nearest neighbor scheme, where, according to characteristics of a WiFi fingerprint matching algorithm, a generally adopted K-nearest neighbor method and a K value in a weighted K-nearest neighbor algorithm are fixed, adaptability is weak, K reference points nearest to each other when positioning are performed at different positions, there is a larger probability that there is a reference point far away from each other, which may cause serious influence on a positioning result, so that the adaptive K value introduced in the present application may effectively attenuate such influence.
In some embodiments, since steps S210 to S240 are performed in each subspace, in the divided subspaces, the steps may be performed in each subspace to perform coarse positioning, and the position sub-fingerprints are constructed by using the RSSI received at different test points, wherein the following logic is used to perform euclidean distance determination: in each subspace of different AP combinations, a sub-fingerprint library corresponding to a plurality of reference points under the subspace AP combination and a position sub-fingerprint corresponding to the current test point position under the subspace AP combination are provided, wherein the sub-fingerprint library comprises (m-1) reference signal intensities corresponding to the subspace AP combination, the position sub-fingerprint comprises (m-1) received signal intensities corresponding to the subspace AP combination, on the basis, the Euclidean distance between the sub-fingerprint library of each reference point and the position sub-fingerprint of the current test point position can be calculated by sheathing the Euclidean distance formula between the plurality of reference signal intensities in the sub-fingerprint library and the plurality of received signal intensities in the position sub-fingerprint, and then after the Euclidean distance corresponding to each reference point is determined, all the Euclidean distances can be ordered, and the minimum Euclidean distance is selected according to the order from small to large lSpecifically, the euclidean distance formula may be as follows:
（1）；
wherein,the Euclidean distance between the sub-fingerprint of the position of the ith test point and the sub-fingerprint library; />The signal intensity received for the ith test point is the sub-fingerprint of the corresponding position; />For the RSSI of each reference point in the ith sub-fingerprint library, namely the corresponding sub-fingerprint library, the Euclidean distance between a plurality of reference signal intensities and a plurality of received signal intensities between the sub-fingerprint and the sub-fingerprint library can be solved through the formula, and finally the Euclidean distance between the sub-fingerprint library of the reference point and the sub-fingerprint of the position can be obtained.
Specifically, the formula of the difference between the euclidean distance of each reference point and the minimum euclidean distance is expressed as follows:
（2）；
wherein,Dthe difference between the minimum Euclidean distance and the Euclidean distance of each reference point;Lis composed ofA Euclidean distance matrix is formed;Eis in combination withLThe same row and column number of the same row matrix, wherein the elements are all formed bylComposition is prepared.
In some embodiments, please refer to fig. 3, fig. 3 shows a flowchart of an image card number identification method provided in the embodiments of the present application, as shown in fig. 3, determining K adjacent reference point coordinates corresponding to a subspace according to a plurality of distance difference values, including but not limited to steps S310 to S330:
Step S310, obtaining a target limit value;
step S320, performing data screening processing on the plurality of distance differences according to the target limit value to obtain K target distance differences smaller than or equal to the target limit value from the plurality of distance differences;
in step S330, the position coordinates of the reference points corresponding to the K target distance differences are determined as the coordinates of the neighboring reference points.
In some embodiments, steps S310-S330 are performed by comparing with a target threshold μSelecting the nearest K adjacent points as adjacent reference points of the self-adaptive fingerprint matching algorithm, wherein the target limit value is the limit value corresponding to the optimal performance, and setting the target limit value according to the requirement of a specific application scene on positioning precision by solving the difference value between the minimum Euclidean distance and the Euclidean distance of each reference pointdSetting a target limit value mu, judging through a discriminant to select K reference points with difference values smaller than the target limit value as adjacent points, and determining the position coordinates of the K reference points as adjacent reference point coordinates, wherein the value of K is not fixed, and the K values in different subspaces can be different; and finally, integrating the positioning coordinates of each subspace, estimating the final positioning coordinates, and effectively reducing signal interference caused by shielding of objects in the environment on AP signals.
In some embodiments, please refer to fig. 4, fig. 4 shows a flowchart of an image card number identification method provided in an embodiment of the present application, as shown in fig. 4, reference signal intensities of m wireless access points are obtained, and sub-fingerprint library construction processing is performed according to the m reference signal intensities to obtainA sub fingerprint library including, but not limited to, steps S410 to S420:
step S410, fingerprint database data is acquired, wherein the fingerprint database data comprises position coordinates of a plurality of reference points and reference fingerprint information, and the reference fingerprint information comprises reference signal intensities of m wireless access points;
step S420, traversing m reference signal intensities, and constructing a sub-fingerprint library according to (m-1) reference signal intensities except the current traversed object during the traversal process to obtainA sub-fingerprint library.
In some embodiments, the fingerprint database data is obtained corresponding to an offline database building stage of the application, the fingerprint database data may include position coordinates of a plurality of reference points and reference fingerprint information, the reference fingerprint information includes reference signal strengths of m wireless access points, and specifically, the data in the fingerprint database may be expressed as
In the off-line database establishment stage, the data in the fingerprint database can be expressed as
（3）；
（4）；
（5）；
Wherein,as for the spatial position coordinates of the ith reference point, it is conceivable that the positioning technique aimed at in the present application is aimed at positioning on a two-dimensional plane only, so that only the X-axis and the Y-axis are involved, and the Z-cycle is not highly nerve-related; />Signal strength RSSI at the i-th reference point; />To receive the RSSI of the mth AP.
According to the above formulas (3) to (5), a fingerprint library composed of m APs can be constructed by permutation and combinationThe individual is->Sub-fingerprint library composed of AP, sub-fingerprint library can be expressed as
（6）；
Wherein,for the ith sub-fingerprint library, there is +.>A sub-fingerprint library.
It is conceivable that the fingerprint database data includes spatial position coordinates of a plurality of reference points, and includes a plurality of sets of reference signal intensities at m wireless access points corresponding to the plurality of reference points, so that in a subsequent step, euclidean distances between a plurality of reference point sub-fingerprint databases and position sub-fingerprints in a plurality of subspaces can be determined according to the data, and K adjacent reference point coordinates corresponding to the subspaces can be determined.
In some embodiments, please refer to fig. 5, fig. 5 shows a flowchart of an image card number identification method provided in an embodiment of the present application, and as shown in fig. 5, the received signal strengths of m wireless access points are obtained, and location sub-fingerprint construction processing is performed according to the m received signal strengths to obtain The location sub-fingerprints include, but are not limited to, steps S510 through S520:
step S510, obtaining position fingerprint information received by the current position, wherein the position fingerprint information comprises the received signal strengths of m wireless access points;
step S520, traversing mReceived signal strength, and constructing position sub-fingerprints according to (m-1) received signal strengths except the current traversing object in the traversing process to obtainAnd (3) sub-fingerprints of the positions.
In some embodiments, steps S510 to S520 correspond to an online positioning stage, where the location sub-fingerprint is a location fingerprint formed by first constructing the RSSI signal strength of each AP received by the t location, where the t location is the current location of the current test point, and specifically, it is assumed that the current location fingerprint may be expressed as:
（7）；
wherein,a location fingerprint received for a t location; />Is the received RSSI of the mth AP.
Constructing the current position fingerprint by permutation and combination corresponding to the sub fingerprint librarySub-fingerprints of locations, expressed as
（8）；
Wherein,for the ith position sub-fingerprint, there is a common +.>And (3) sub-fingerprints of the positions.
It is contemplated that the present application masks the AP signal for no objects in the environment, thereby causing the AP signal to wave The situation of the positioning result is affected by the motion, and m APs are arranged and combined to obtainSub fingerprint library (++>，/>，…，/>Wherein subscript c corresponds to +.>) And->Personal location sub-fingerprint (+)>，/>，…，) Further according to->Sub fingerprint library and->The sub-fingerprint of the individual location is +.>The individual is->The subspaces formed by the APs, because each subspace does not contain the signal intensity data of a specific AP, the influence of the specific AP can be eliminated when each subspace performs position estimation, and finally the subspaces are integrated at the estimated positions to obtain the final positioning seatAfter the positioning method is adopted, the signal interference of the shielding object to part of the AP can be effectively reduced, the constraint on the position is enhanced, and the positioning accuracy and the positioning robustness are improved.
In some embodiments, please refer to fig. 6, fig. 6 shows a flowchart of an image card number recognition method according to an embodiment of the present application, as shown in fig. 6, according toWeighting calculation is carried out on K adjacent reference point coordinates corresponding to the subspace to obtain +.>The coarse positioning location coordinates include, but are not limited to, step S610:
respectively atThe following steps are performed in the subspace:
step S610, carrying out weighted calculation on K adjacent reference point coordinates corresponding to subspaces based on a preset coordinate estimation expression and Euclidean distance to obtain coarse positioning position coordinates corresponding to the subspaces;
Wherein, when K reference points with difference smaller than the threshold value are selected as K neighboring points to be used as neighboring reference points of the adaptive fingerprint matching scheme, the K neighboring points generated in an adaptive manner are used for euclidean distance reciprocal weighting to calculate the estimated coordinates of the test point, wherein the coordinate estimation expression of the euclidean distance reciprocal weighting is as follows:
（9）；
wherein,for coarse positioning position coordinates +.>To select K adjacent reference point coordinates +.>Is the euclidean distance corresponding to the coordinates of the adjacent reference points.
In some embodiments, according toObtaining the target positioning position coordinates from the coarse positioning position coordinates, including:
based on a preset average filtering expression, forAnd carrying out average calculation on the coarse positioning position coordinates to obtain target positioning position coordinates, wherein an average filtering expression is as follows:
（10）；
wherein, through the subspaces divided before, the self-adaptive fingerprint matching scheme is used for positioning in each subspace, the coarse positioning positions are calculated, the coarse positioning positions of the subspaces are integrated, the average filtering is adopted for accurate positioning,locating position coordinates for the object, +.>For coarse positioning position coordinates +.>For the number of coarse positioning position coordinates, there is a common +. >And integrating the positioned coarse positions of each subspace in an average filtering mode, so that the influence of overlarge or overlarge coarse positions in the subspace is reduced.
Referring to fig. 7, fig. 7 is a schematic diagram illustrating an adaptive fingerprint matching process according to another embodiment of the present application; corresponding to the processes from step S210 to step S240 in the present application, in FIG. 7LBetween the test point and the reference point in the fingerprint databaseIs a euclidean distance set;lis thatLThe minimum euclidean distance in (a);Da difference set for the minimum euclidean distance and each distance in the euclidean distance set; e is the same row matrix as the row number of L, wherein elements are all formed bylComposition;dis an element in D;μis a threshold value.
It can be seen from FIG. 7 that the Euclidean distance between the test point and each reference point is obtained by using the nearest neighbor methodLAnd find the minimum Euclidean distance among the Euclidean distanceslThen, the difference between the minimum Euclidean distance and the Euclidean distance of each reference point is obtaineddSetting a threshold value of optimal performanceμAnd judging by a discriminant. If so, screening the reference point as a neighboring point; if the difference value between all the reference points is not satisfied, the reference points are eliminated, the most suitable K adjacent points are found by judging the difference value between all the reference points, and finally, the estimated coordinates of the test points are obtained by utilizing the inverse Euclidean distance weighting mode.
Referring to fig. 8, fig. 8 is a schematic diagram illustrating an adaptive fingerprint subspace matching positioning procedure according to another embodiment of the present application; the adaptive fingerprint subspace matching positioning process provided by the application is shown in fig. 8, and the positioning process is mainly divided into: in the off-line database establishment stage, the RSSIs of all the APs received in the whole target area are collected and processed, stored in a total fingerprint database, and constructed into a sub fingerprint database, namely a subspace; coarse positioning is respectively carried out in each subspace by using an adaptive fingerprint matching algorithm, and an adaptive method is adopted in the positioning process, so that the interference of remote adjacent points on positioning is reduced; and finally, integrating the positioning coordinates of each subspace, and estimating the final positioning coordinates. The subspace is composed of a plurality of APs, and is usedThe subspace is used for positioning, even if the signal of a certain AP is shielded by an object to generate signal fluctuation, the fusion of the subspace can reduce signal interference caused by the shielding of the object to the AP signal in the environment, and has better enhancement effect on the constraint of the position, and the acquired fingerprints are conceivable to be constructed into a total fingerprint library in the off-line stage, and the sub fingerprint libraries are constructed by combining different APs, such as ，/>，…，/>Etc.; in the on-line positioning stage, the fingerprints acquired from the current position are constructed into sub-fingerprints according to the same combination, such as +.>，/>，…，/>And the same AP combined fingerprint library and sub-fingerprints form a subspace; through introducing subspaces, during each 1 positioning, the signal distribution of a plurality of APs in a positioning environment is fully considered, the signal interference from a shielding object is reduced, then the coarse positioning is carried out in each subspace by using an adaptive fingerprint matching algorithm based on a threshold value, and finally the coarse position of each subspace is processed by adopting average filtering, so that the accurate positioning is carried out.
In a second aspect, referring to fig. 9, an embodiment of the present invention further provides a WiFi positioning device based on fingerprint matching, including: the sub fingerprint library construction module 901 is configured to obtain reference signal intensities of m wireless access points, and perform sub fingerprint library construction processing according to the m reference signal intensities to obtainSub-fingerA grain library; a location sub-fingerprint determining module 902, configured to obtain received signal strengths of m wireless access points, and perform location sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location; a proximity coordinate determination module 903 for determining the proximity coordinate according to +.>Sub fingerprint library and->The sub-fingerprint of the individual location is +. >Subspace and are respectively +.>Determining K adjacent reference point coordinates in the subspace according to the corresponding Euclidean distance of the signal intensity; target position determining module 904 for determining the target position according to +.>Weighting calculation is carried out on K adjacent reference point coordinates corresponding to the subspace to obtain +.>Coarse positioning position coordinates and according to +.>And obtaining the target positioning position coordinates by the rough positioning position coordinates.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: the WiFi positioning method based on fingerprint matching comprises a memory, a processor, a program stored in the memory and capable of running on the processor and a data bus for realizing connection communication between the processor and the memory, wherein the program is executed by the processor to realize the WiFi positioning method based on fingerprint matching. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.
Referring to fig. 10, fig. 10 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:
the processor 1001 may be implemented by using a general-purpose CPU (central processing unit), a microprocessor, an application-specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. to execute related programs to implement the technical solution provided by the embodiments of the present invention;
The memory 1002 may be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage, dynamic storage, or random access memory (RandomAccessMemory, RAM). The memory 1002 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 1002, and the processor 1001 invokes a WiFi positioning method based on fingerprint matching to perform the embodiments of the present disclosure;
an input/output interface 1003 for implementing information input and output;
the communication interface 1004 is configured to implement communication interaction between the present device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);
a bus 1005 for transferring information between the various components of the device (e.g., the processor 1001, memory 1002, input/output interface 1003, and communication interface 1004);
wherein the processor 1001, the memory 1002, the input/output interface 1003, and the communication interface 1004 realize communication connection between each other inside the device through the bus 1005.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where one or more programs are stored, where the one or more programs may be executed by one or more processors to implement the foregoing WiFi positioning method based on fingerprint matching.
The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiments described in the embodiments of the present invention are for more clearly describing the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.
It will be appreciated by those skilled in the art that the solutions shown in fig. 1 to 8 do not constitute a limitation of the embodiments of the present invention, and may include more or fewer steps than shown, or may combine certain steps, or different steps.
The terms "first," "second," "third," "fourth," and the like in the description of the invention and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods disclosed above, corresponding systems, may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer readable storage media (or non-transitory media) and communication media (or transitory media). The term computer-readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, and are not thereby limiting the scope of the claims of the embodiments of the present invention. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present invention shall fall within the scope of the claims of the embodiments of the present invention.
Claims (8)
1. A WiFi positioning method based on fingerprint matching, the method comprising:
acquiring reference signal intensities of m wireless access points, and constructing a sub-fingerprint library according to the m reference signal intensitiesAnd then is managed to obtainA sub-fingerprint library;
acquiring the received signal strengths of m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location;
according toThe sub fingerprint library and +.>The sub-fingerprints of the positions are +.>Subspace and are respectively +.>Determining K adjacent reference point coordinates in each subspace according to the corresponding Euclidean distance of the signal intensity;
according to respectivelyWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain +.>Coarse positioning position coordinates and according to +.>Obtaining target positioning position coordinates by the coarse positioning position coordinates;
Wherein the said parts are respectively atPersonal stationDetermining K adjacent reference point coordinates in the subspace according to the corresponding Euclidean distance of the signal intensity, wherein the method comprises the following steps:
respectively atThe following steps are carried out in each subspace:
calculating Euclidean distances between a plurality of reference signal intensities corresponding to the subspace and a plurality of received signal intensities;
determining a minimum Euclidean distance from a plurality of Euclidean distances;
calculating distance differences between a plurality of the Euclidean distances and the minimum Euclidean distance;
determining K adjacent reference point coordinates corresponding to the subspace according to the distance differences;
the determining, according to the distance differences, K adjacent reference point coordinates corresponding to the subspace includes:
obtaining a target limit value;
performing data screening processing on a plurality of distance differences according to the target limit value to obtain K target distance differences smaller than or equal to the target limit value from the plurality of distance differences;
determining the position coordinates of the reference points corresponding to the K target distance differences as adjacent reference point coordinates;
wherein the magnitude of K characterizes the number of reference points for which the corresponding distance difference is smaller than the target limit value.
2. The WiFi positioning method based on fingerprint matching according to claim 1, wherein the reference signal strengths of m wireless access points are obtained, and sub fingerprint library construction processing is performed according to the m reference signal strengths, so as to obtainA sub-fingerprint library comprising:
acquiring fingerprint database data, wherein the fingerprint database data comprises position coordinates of a plurality of reference points and reference fingerprint information, and the reference fingerprint information comprises reference signal intensities of m wireless access points;
traversing m reference signal intensities, and constructing a sub-fingerprint library according to (m-1) reference signal intensities except the current traversed object in the traversing process to obtainAnd each sub fingerprint library.
3. The WiFi positioning method according to claim 1, wherein the acquiring the received signal strengths of the m wireless access points performs a location sub-fingerprint construction process according to the m received signal strengths to obtainA sub-fingerprint of a location, comprising:
acquiring position fingerprint information received by a current position, wherein the position fingerprint information comprises the received signal strengths of m wireless access points;
traversing m received signal intensities, and constructing a position sub-fingerprint according to (m-1) received signal intensities except the current traversed object in the traversing process to obtain And each of the location sub-fingerprints.
4. The fingerprint matching based WiFi positioning method according to claim 1, wherein the steps are respectively according toWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain +.>A coarse positioning location coordinate comprising:
respectively atThe following steps are carried out in each subspace:
and carrying out weighted calculation on the K adjacent reference point coordinates corresponding to the subspace based on a preset coordinate estimation expression and the Euclidean distance to obtain a coarse positioning position coordinate corresponding to the subspace, wherein the coordinate estimation expression is as follows:
；
wherein,for the coarse positioning position coordinates, +.>For the adjacent reference point coordinates +.>And the Euclidean distance corresponding to the adjacent reference point coordinate is obtained.
5. The fingerprint matching based WiFi positioning method according to claim 1, wherein the data is based onObtaining the target positioning position coordinates by the coarse positioning position coordinates comprises the following steps:
based on a preset average filtering expression, forThe coarse positioning position coordinates are averaged,
and obtaining the target positioning position coordinates, wherein the average filtering expression is as follows:
；
wherein, Locating position coordinates for the object, +.>For the coarse positioning position coordinates, +.>And the number of the coarse positioning position coordinates is the number.
6. WiFi positioner based on fingerprint matches, characterized by includes:
the sub fingerprint library construction module is used for acquiring the reference signal intensities of m wireless access points and carrying out sub fingerprint library construction processing according to the m reference signal intensities so as to obtainA sub-fingerprint library;
the position sub-fingerprint determining module is used for acquiring the received signal strengths of the m wireless access points, and performing position sub-fingerprint construction processing according to the m received signal strengths to obtainA sub-fingerprint of each location;
a proximity coordinate determination module for determining a proximity coordinate based onThe sub fingerprint library and +.>The sub-fingerprints of the positions are +.>Subspace and are respectively +.>Determining K adjacent reference point coordinates in each subspace according to the corresponding Euclidean distance of the signal intensity;
target position determining modules for respectively according toWeighting calculation is carried out on the coordinates of the K adjacent reference points corresponding to the subspaces to obtain +.>Coarse positioning position coordinates and according to +.>Obtaining target positioning position coordinates by the coarse positioning position coordinates;
wherein the said parts are respectively at Determining K adjacent reference point coordinates in each subspace according to the corresponding signal intensity euclidean distance, including:
respectively atThe following steps are carried out in each subspace:
calculating Euclidean distances between a plurality of reference signal intensities corresponding to the subspace and a plurality of received signal intensities;
determining a minimum Euclidean distance from a plurality of Euclidean distances;
calculating distance differences between a plurality of the Euclidean distances and the minimum Euclidean distance;
determining K adjacent reference point coordinates corresponding to the subspace according to the distance differences;
the determining, according to the distance differences, K adjacent reference point coordinates corresponding to the subspace includes:
obtaining a target limit value;
performing data screening processing on a plurality of distance differences according to the target limit value to obtain K target distance differences smaller than or equal to the target limit value from the plurality of distance differences;
determining the position coordinates of the reference points corresponding to the K target distance differences as adjacent reference point coordinates;
wherein the magnitude of K characterizes the number of reference points for which the corresponding distance difference is smaller than the target limit value.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a fingerprint matching based WiFi positioning method according to any of claims 1 to 5 when the computer program is executed by the processor.
8. A computer readable storage medium, characterized in that a computer program is stored, which, when being executed by a processor, implements a fingerprint matching based WiFi positioning method according to any of claims 1 to 5.
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