CN108061878A - Fusion and positioning method, storage device and mobile terminal based on mobile terminal - Google Patents
Fusion and positioning method, storage device and mobile terminal based on mobile terminal Download PDFInfo
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- CN108061878A CN108061878A CN201711353913.1A CN201711353913A CN108061878A CN 108061878 A CN108061878 A CN 108061878A CN 201711353913 A CN201711353913 A CN 201711353913A CN 108061878 A CN108061878 A CN 108061878A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0257—Hybrid positioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The invention discloses a kind of fusion and positioning methods based on mobile terminal, storage device and mobile terminal, it first passes through fusion location algorithm initialization and obtains an initial position, it then will be by merging initial position and turning behavior detection that location algorithm initialization obtains with reference to determining that the initial position positioned is merged in execution, the PDR of the first predetermined step number is performed using definite initial position as starting point, and the last one node of the highest track of PDR posterior probabilities of the multiple first predetermined step numbers will be performed as positioning result, if turning behavior occurs during the PDR of multiple first predetermined step numbers is performed, then PDR is performed by starting point of the position that turning behavior occurs.Multiple positioning modes have been used alternatingly in the present invention, merge multi-source data, improve the accuracy and speed of positioning.
Description
Technical field
The present invention relates to electronic location technical field more particularly to a kind of fusion and positioning method based on mobile terminal, deposit
Storage device and mobile terminal.
Background technology
In recent years, the emergence at full speed of information technology, drives the rapid development of mobile Internet, and then has also affected other
The development of many industries, wherein the most aobvious as the development of the personal mobile intelligent terminal technology and equipment of representative using smart mobile phone
It writes.The popularization of mobile intelligent terminal promotes user further urgent to position demand for services, in pushing position service field and application
While also bring huge challenge.Location technology is basis and core based on location-based service, can realize to people or
The real time location tracking of object and navigation facilitate the trip of people to live.And nowadays, in daily life, people by mobile phone,
The terminals such as tablet computer are carried out location navigation and enjoy the service provided based on position.Such as the preferential shopping activity in push market
Information is searched for neighbouring people's friend-making chat etc., is also had become for an indispensable part.Therefore, location technology, which receives, grinds
Study carefully the attention of personnel.
Using smart mobile phone as platform, positioned using pedestrian's dead reckoning, be limited to mobile phone sensor accuracy itself and
Pedestrian's dead reckoning positioning principle of itself, easily generates accumulated error, in turn results in and positions undesirable situation.And carry out
Wi-Fi is positioned, easily by reflect, multipath effect and equipment otherness are influenced, cause positioning accuracy limited or even can not
Situation about normally positioning.Therefore there are many deficiencies for single mode positioning method.
Therefore, in view of the foregoing drawbacks, the prior art has yet to be improved and developed.
The content of the invention
In view of the deficiencies in the prior art, it is an object of the invention to provide a kind of fusion positioning sides based on mobile terminal
Method, storage device and mobile terminal, it is intended to it is inaccurate or even can not normally position to solve mobile terminal location in the prior art
Problem.
In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:
A kind of fusion and positioning method based on mobile terminal, wherein, including:
Step A, mobile terminal carry out fusion location algorithm initialization, determine what is initialized by merging location algorithm
Start to perform the initial position that fusion positions, mobile terminal detects step in real time, obtains arranging with similarity descending for current step
Multiple candidate reference points of sequence calculate mobile terminal and a plurality of track that the back currently walked obtains are moved to by the first step most
The latter node, distance and course angle with the multiple candidate reference point, and pass through the constraint of fixed step size and course angle, come
It determines to start the initial position for performing fusion positioning;
Step B, will be by merging the initial position for starting to perform fusion positioning and the turning that location algorithm initializes
Behavioral value combines, and determines to perform the initial position of fusion positioning, and the first predetermined step is performed by starting point of definite initial position
Several PDR, and the last one node of the highest track of PDR posterior probabilities of the multiple first predetermined step numbers will be performed as fixed
If position during the PDR of multiple first predetermined step numbers is performed as a result, occur turning behavior, with the position of turning behavior generation
It is set to starting point and performs PDR.
Further, the step A is specifically included:
A1 detects step, and the received signal strength information gathered according to each step by step number detection algorithm, uses base
In the Wi-Fi location fingerprint location algorithms of RSS correlations, a n candidate reference point group with similarity descending sort is obtained
Into sequence Si, fixed step size is set to step_length using the step-size estimation model of fixed step size;
During mobile terminal is moved to the (i-1)-th step by the first step, the institute of acquisition has been calculated by initialization algorithm by A2
The set being made of candidate tracks is denoted as Ti-1If Ti-1In share m track;
A3 calculates Ti-1In every the last one node of track and SiIn the distance between each candidate reference point and course
Angle, then the distance of calculating and course angle are calculated into difference with the course angle of step_length and the i-th step respectively, it obtains based on step
M*n track sets of long otherness and course angle otherness;
A4 is positioned using the last one node of the highest track of probability in m*n track as execution fusion is started
Initial position.
Further, the step A1 is specifically included:
Using step number detection algorithm, step is determined according to the acquisition sensing data of mobile terminal by A11, and according to step
The generation moment finds the Wi-Fi received signal strength information of t seconds before and after the moment in the Wi-Fi data of acquisition, handles shape
Into the online fingerprint fp of the i-th stepi, using fixed step size model, step-length step_length is set, course angle is obtained using fusion
Method, determine the course angle heading of the i-th step of pedestrian;
A12, by the online fingerprint fp of the i-th stepiWith offline fingerprint database comparison match, carry out based on RSS correlations
Wi-Fi location fingerprints position, and obtain the candidate reference point sequence S arranged according to similarity descendingi, SiIn share n candidate reference
Point.
Further, the step A4 is specifically included:
A41, with dkjRepresent Ti-1The distance between j-th reference point in middle the last one node of kth track and the i-th step;
With hkjRepresent Ti-1The vector that j-th of reference point is formed in middle the last one node of kth track and the i-th step and north geographic pole
Angle;North geographic pole vector vnorthAnd Ti-1In middle the last one node of kth track and the i-th step j-th reference point formed to
Measure vnowIt is expressed as:
Vnorth=(0,52.5), vnow=(xij-x(i-1)k,yij-y(i-1)k),
xijAnd yijRefer to the coordinate of j-th of reference point in the i-th step;x(i-1)kWith y (i-1)kRefer to Ti-1Middle kth rail
The coordinate of the last one node of mark;
dkjAnd hkjIt is represented by:
hkj=360-rad2deg (vnorth·vnow/|vnorth|·|vnow|),
Wherein | vnorth| and | vnow| it is vector field homoemorphism;Rad2deg () is that radian is switched to the number of degrees, and scope is -180 degree
To between 180 degree, the number of degrees more than or equal to 0 need to be converted into;
If the i-th step course angle heading and hkjDeviation be hdiff, respectively to hdiffAnd dkjGiven threshold.
A42, to by setting hdiffAnd dkjThreshold value after the probability of every track of trajectory calculation that screens, dkjDistance
Deviation is:
ddiff=| dkj- step-length |,
ddiffAnd hdiffGaussian distributed, ddiffAnd hdiffIt is expressed as:
Wherein σdAnd σhThe respectively standard deviation of range deviation and the deviation of directivity, pdAnd phIt is inclined for range deviation and course angle
The Gaussian Profile probability of difference, with reference to the S positioned by Wi-FiiIn each reference point similarity, similarity is normalized
After operation, the related coefficient p of j-th of reference point Wi-Fi positioning in the i-th step is obtainedkj, pkj、pdAnd ph, Wi-Fi positioning considerations
Track Probability p between the candidate reference point that range deviation and heading angle deviation calculatetotalIt is represented by:
ptotal=ω pkj+(1-ω)pdph, ω is the weight of Wi-Fi similarities, and (1- ω) is range deviation and direction
Weight shared by deviation.
A43, by Probability ptotalThe last one node output of highest track is as positioning result.
Further, the step B is specifically included:
B1, structure landmark information storehouse, by the coordinate record of intersecting point in landmark information storehouse;
When B2, mobile terminal detect the i-th step, judge whether the step occurs turning behavior, if turning behavior occurs, pass through
Wi-Fi positioning results are matched with the landmark locations in landmark information storehouse, are determined landmark locations, and are started with this location determination
Perform the initial position of fusion positioning;It is true to perform fusion location algorithm initialization in step A if turning behavior does not occur
Fixed initial position is the initial position for starting to perform fusion positioning;
B3, using the initial position in step B2 as starting point, carry out N2After step, with N2Positioning result before step is as following
The input of Wi-Fi positioning, Wi-Fi are positioned every N2Step perform, by back track gather in the last one node of certain track and
The distance and N of certain candidate reference point of current step Wi-Fi positioning2*The distance of step_length calculates range deviation, to setting
Distance threshold is adjusted, and with reference to the distance threshold after adjustment and the course angle threshold value set before, carries out track screening, and will
Perform multiple N2The last one node of the highest track of PDR posterior probabilities of step is as positioning result;
B4, walking N2During step, if mobile terminal detects turning behavior, by the step of the turning detected
Subcoordinate matches compared with landmark information storehouse, and using landmark locations as the positioning result currently walked, with the positioning result
As the starting point of PDR, PDR is performed, continues to execute N2Step, if in walking N2Corner behavior is not detected during step, then N2
After step, the Wi-Fi position fixing process in step B3 is performed, and using Wi-Fi positioning results as the starting point of PDR, continues to execute N2Step.
Further, the step B2 performs N2Step B3 is performed after step again.
Further, the N1And N2Respectively 6 and 5.
Further, to d in the step A41kjAnd hdiffGiven threshold is respectively 3 and 40 degree.
The present invention also provides a kind of storage devices, which is characterized in that the storage device stores computer program, described
Computer program can be performed to realize the fusion and positioning method based on mobile terminal as described above.
The present invention also provides, the storage device being connected including processor, with the processor communication, the storage device storage
There is computer program, the computer program is used to implement as described above when being performed by the processor based on mobile terminal
Fusion and positioning method;
The processor is used to call the computer program in the storage device, to perform as described above based on movement
The fusion and positioning method of terminal.
It is described to melt the present invention provides a kind of fusion and positioning method based on mobile terminal, storage device and mobile terminal
Closing localization method includes:Mobile terminal carries out fusion location algorithm initialization, determines to initialize to obtain by merging location algorithm
Start perform the initial position of fusion positioning, mobile terminal detects step in real time, obtain current step with similarity descending
Multiple candidate reference points of sequence calculate mobile terminal and a plurality of track that the back currently walked obtains are moved to by the first step
The last one node, distance and course angle with the multiple candidate reference point, and pass through the constraint of fixed step size and course angle,
To determine to start the initial position for performing fusion positioning;The fusion that starts to perform initialized by merging location algorithm is determined
Initial position and the turning behavior detection of position combine, and determine to perform the initial position of fusion positioning, using definite initial position as
Starting point performs the PDR of the first predetermined step number, and will perform the highest track of PDR posterior probabilities of the multiple first predetermined step numbers most
The latter node is as positioning result, if turning behavior occurs during the PDR of multiple first predetermined step numbers is performed, with
The position that turning behavior occurs performs PDR for starting point.Wi-Fi location fingerprints present invention incorporates PDR, based on RSS correlations
Positioning and terrestrial reference detection improve the precision and robustness of mobile terminal location, and the positioning of WiFi location fingerprints is using based on RSS phases
The localization method of closing property, the device diversity problem that can be positioned to avoid location fingerprint.
Description of the drawings
Attached drawing described herein is used for providing further understanding of the present application, forms the part of the application, this Shen
Schematic description and description please does not form the improper restriction to the application for explaining the application.In the accompanying drawings:
Fig. 1 is the flow chart of the fusion and positioning method preferred embodiment based on mobile terminal of the present invention;
Fig. 2 is the schematic diagram of the i-th step localization region;
Fig. 3 is the schematic diagram of cartographic information.
Fig. 4 is the structure diagram of the mobile terminal preferred embodiment of the present invention.
Specific embodiment
Presently filed embodiment is described in detail below in conjunction with accompanying drawings and embodiments, thereby how the application is applied
Technological means can fully understand and implement according to this to solve technical problem and reach the realization process of technical effect.
It should be noted that the fusion and positioning method of the present invention is applicable not only to interior, outdoor is also applied for, as long as there is shifting
Dynamic terminal is connected to Wi-Fi network, you can uses the fusion and positioning method of the present invention.
Referring to Fig. 1, Fig. 1 is the flow chart of the fusion and positioning method preferred embodiment the present invention is based on mobile terminal, such as
Shown in Fig. 1, a kind of fusion and positioning method based on mobile terminal provided in an embodiment of the present invention comprises the following steps:
Step S100, mobile terminal carry out fusion location algorithm initialization, determine to initialize by merging location algorithm
To start perform the initial position of fusion positioning, mobile terminal detected step, obtains being dropped with similarity for current step in real time
Multiple candidate reference points of sequence sequence calculate mobile terminal and a plurality of track that the back currently walked obtains are moved to by the first step
The last one node, distance and course angle with the multiple candidate reference point, and pass through the pact of fixed step size and course angle
Beam, to determine to start the initial position for performing fusion positioning.
Specifically, the uncertainty due to Wi-Fi signal strength so that the result of Wi-Fi positioning may not be accurate always, and
Merging location algorithm needs an accurate initial position, it is ensured that the precision of positioning, therefore, it is necessary to be initialized to determine out
Begin to perform the initial position for merging location algorithm, and without using initial position of the result of Wi-Fi positioning as algorithm.It is mobile whole
End is moved to a plurality of track that the back that currently walks obtains by the first step, is to have calculated by merging location algorithm initialization to obtain
All candidate tracks obtained if current step is the first step, and are no candidate tracks before the first step, then the first step
Then according to Wi-Fi positioning results, the probability of each position is calculated, is the position location of the first step by the high location determination of probability.
The constraint of fixed step size and course angle all can specifically be set, and be described in detail later.
In further implementation, the step S100 is specifically included:
S110 detects step, and the received signal strength information gathered according to each step by step number detection algorithm, uses
Wi-Fi location fingerprint location algorithms based on RSS correlations obtain a n candidate reference point with similarity descending sort
The sequence S of compositioni, fixed step size is set to step_length using the step-size estimation model of fixed step size;
During mobile terminal is moved to the (i-1)-th step by the first step, acquisition has been calculated by initialization algorithm by S120
The set of all candidate tracks compositions is denoted as Ti-1If Ti-1In share m track;
S130 calculates Ti-1In every the last one node of track and SiIn the distance between each candidate reference point and boat
Difference is calculated with the course angle of step_length and the i-th step respectively to angle, then by the distance of calculating and course angle, is based on
M*n track sets of step-length otherness and course angle otherness;
Specifically, in the step, the calculating of distance and course angle can be used as the existing track of assessment to walk on to by Wi-
The possibility that the current step that Fi positioning obtains is put.
S140, the last one node of the highest track of probability in m*n track is fixed as execution fusion is started
The initial position of position.
In further implementation, the step S110 is specifically included:
Using step number detection algorithm, step is determined according to the acquisition sensing data of mobile terminal by S111, and according to step
The generation moment finds the Wi-Fi received signal strength information of t seconds before and after the moment in the Wi-Fi data of acquisition, handles shape
Into the online fingerprint f of the i-th steppi, using fixed step size model, step-length step_length is set, course angle is obtained using fusion
Method determines the course angle heading of the i-th step of pedestrian;
Specifically, in this step, the space D between experimental situation sampled point is known, and experimental situation sampled point refers to
WiFi location fingerprints sampling position, be exactly when build WiFi location fingerprint maps acquisition fingerprint position, typically according to
Fixed intervals acquisition, D here refers to the distance of two WiFi location fingerprint sampled points.
S112, by the online fingerprint fp of the i-th stepiWith offline fingerprint database comparison match, carry out based on RSS correlations
Wi-Fi location fingerprints positioning, obtain according to similarity descending arrange candidate reference point sequence Si, SiIt is represented by Si=
{(xi1, yi1), (xi2, yi2) ..., (xin, yin)}Si, n is the number of sampled point.
In further implementation, the step S140 is specifically included:
S141, with dkjRepresent Ti-1In middle the last one node of kth track and the i-th step between j-th of reference point away from
From;With hkjRepresent Ti-1The vector and north geographic pole that j-th of reference point is formed in middle the last one node of kth track and the i-th step
Angle;North geographic pole vector vnorthAnd Ti-1J-th of reference point is formed in middle the last one node of kth track and the i-th step
Vector vnowIt is expressed as:
vnorth=(0,52.5),
vnow=(xij-x(i-1)k, yij-y(i-1)k),
xijAnd yijRefer to the coordinate of j-th of reference point in the i-th step;x(i-1)kWith y (i-1)kRefer to Ti-1Middle kth rail
The coordinate of the last one node of mark;
Pass through formula vnorthAnd vnowIt can draw, dkjAnd hkjIt can be obtained by the following formula:
hkj=360-rand2deg (vnorth·vnow/|Vnorth|·|vnow|),
Wherein | vnorth| and | vnow| it is vector field homoemorphism;Rad2deg () is that radian is switched to the number of degrees, and scope is -180 degree
To between 180 degree, the number of degrees more than or equal to 0 need to be converted into;
If the i-th step course angle heading and hkjDeviation be hdiff, respectively to hdiffAnd dkjGiven threshold;
Specifically, in this step, the i-th step course angle heading and h need to be calculatedkjDeviation be hdiff, and corresponding conversion is extremely
0 to being compared in the scope of 180 degree, respectively to hdiffAnd dkjGiven threshold represents Ti-1The last one knot of middle kth track
The heading angle deviation of j-th reference point and distance need to be in threshold ranges o'clock into the i-th step, which can just be considered, otherwise
Be considered as can not possibly existing track, and by its Probability ptotal0 is set to, schematic diagram such as Fig. 2 in above-mentioned calculating process, can encounter
Ti-1J-th of reference point is the situation with position in middle the last one node of kth track and the i-th step, the two formed zero to
Amount, direction can not determine, however, two continuous steps are located in simultaneously in same reference point, be allowed, because pedestrian
Step-length is less than the spacing of sampled point, and therefore, it is necessary to give the heading angle deviation h of such casediffCertain angle value is assigned, is included
Within limit of consideration.According to actual experiment, the deviation in the case of this is set to 10 degree, while sets dkj< 3 and hdiff< 40, dkj's
Unit is m (rice).
By above-mentioned to dkjAnd hdiffGiven threshold is screened, and meets the reference point of above-mentioned condition, also needs further to count
Calculate the Probability p of Qi Dui trackstotal, to weigh its possibility, according to step S111 above, set using fixed step size model
Step-length step_length has been put, so:
S142, to by setting hdiffAnd dkjThreshold value after the probability of every track of trajectory calculation that screens, dkjDistance
Deviation is:
ddifr=| dkj- stgp-length |,
Assuming that ddiffAnd hdiffGaussian distributed, therefore obtain following equation:
Wherein σdAnd σhThe respectively standard deviation of range deviation and the deviation of directivity, pdAnd phIt is inclined for range deviation and course angle
The Gaussian Profile probability of difference, on the basis of gaussian probability is obtained, with reference to the S positioned by Wi-FiiIn each reference point phase
Like degree, after operation is normalized to similarity, the related coefficient p of j-th of reference point Wi-Fi positioning in the i-th step is obtainedkj、
pkj、pdAnd ph, Wi-Fi positioning considers the track probability between the candidate reference point that range deviation and heading angle deviation calculate
ptotalIt is represented by:
ptotal=ω pkj+(1-ω)pdph, ptotalConsider what range deviation and the deviation of directivity calculated for Wi-Fi positioning
Track probability between candidate reference point, ω are the weight of Wi-Fi similarities, and (1- ω) is shared by range deviation and the deviation of directivity
Weight;According to actual experiment, ω is set to 0.7.
S143, by Probability ptotalThe last one node output of highest track is as positioning result.
Specifically, in step S143, to the m*n track foundation p obtained in step S130totalDescending sort is pressed
The track that probability sorts from high to low, and form track set Ti.According to the implementation procedure of initialization algorithm, the value of m is ni -1, and so on, completing the positioning of the i-th step needs to perform niSecondary computing, correspondence obtain niCandidate tracks, but wherein exist big
The track for being 0 through range deviation and heading angle deviation constraint posterior probability of amount, therefore, after the positions calculations of each step are completed,
Calculation amount in the positions calculations for next step, is reduced in the highest track of N probability before need to only retaining.N is basis herein
What the experiment of early period determined, rule of thumb, N can be set to 4.
In addition, in above process, because it is contemplated that continuous several steps may be located in the situation of same position, to same position
The deviation of directivity between putting imparts initial value so that the track Probability p of same position formation is likely to occur in follow-up calculatingdAlways compared with
Greatly.Again because range deviation is 0, the gaussian probability p of range deviationhAlso larger, Wi-Fi is positioned due to having done normalization operation,
Similarity value is relatively small, so in this case, just with (1- ω) pdphProbability based on, cause to navigate to same position always
It puts, for this problem that algorithm initialization occurs, with reference to sampled point spacing and step sizes, can set when same knot in track
Point accumulation is continuously more than or equal to(it is the meaning to round up to the calculated value in bracket in this formula
Think, for example, [1.1]=2) it is secondary when, be considered as impossible track, ptotalIt is set to 0.
During performing the initialization algorithm proposed, it is defeated that the highest track of probability is all corresponded to the last one node by each step
Go out as positioning result, positioned by continuous several steps, may be such that position error continuously decreases convergence, and by the highest track of probability
In the last one node as start perform fusion positioning initial position.
The execution that starts initialized by merging location algorithm is merged the initial position of positioning with turning by step S200
Curved behavioral value combines, and determines to perform the initial position of fusion positioning, and it is predetermined to perform first using definite initial position as starting point
The PDR of step number, and will perform the last one node of the highest track of PDR posterior probabilities of the multiple first predetermined step numbers as
Positioning result if turning behavior occurs during the PDR of multiple first predetermined step numbers is performed, is occurred with turning behavior
Position performs PDR for starting point.
Specifically, on the basis of the above-mentioned fusion location algorithm initialization operation to proposition, PDR is merged and has been determined
Position, however there are accumulated errors by PDR, it is therefore desirable to it is corrected, it will be from WiFi positioning, cartographic information, terrestrial reference detection etc.
PDR algorithms are merged, its positioning result are corrected, it is ensured that positioning accuracy.
In further implementation, the step S200 is specifically included:
S210, structure landmark information storehouse, by the coordinate record of intersecting point in landmark information storehouse;
Specifically, in this step, it is terrestrial reference to pay the utmost attention to using turning behavior, and other terrestrial reference behaviors can equally pass through biography
The analyses such as sensor data obtain, by the coordinate record of turning point in landmark information storehouse, in case being used during detection turning.
When S220, mobile terminal detect the i-th step, judge whether the step occurs turning behavior, if turning behavior occurs, lead to
It crosses Wi-Fi positioning results to be matched with the landmark locations in landmark information storehouse, determines landmark locations, and opened with this location determination
Begin to perform the initial position that fusion positions;If turning behavior does not occur, to perform fusion location algorithm initialization in step A
Definite initial position is the initial position for starting to perform fusion positioning;
Specifically, in above-mentioned steps, using smart mobile phone, sensing data and Wi-Fi data are obtained, are detected using step number
Method carry out step detection, after step is detected, be set to the i-th step, meanwhile, by Wi-Fi data according to step occur the moment into
Row data are distributed, and form the online fingerprint of the i-th step, using comer detection methods, according to the variation of course angle, judge whether to occur to turn
Curved behavior when turning, is matched, definitely by Wi-Fi positioning results with the landmark locations in landmark information storehouse
Cursor position, and execution is started with this location determination and merges the initial position positioned.
If turning behavior does not occur for the i-th step, using initialization algorithm, obtaining for fusion location algorithm initial position is carried out
It takes, while user is positioned using the position of the last one node in the highest track of probability, which usually holds N1Step
After can obtain initial position, in N1In step, if detecting that turning behavior occurs for certain step, preferentially turned with detecting
Initial position of the terrestrial reference of behavior as blending algorithm stops performing initialization algorithm.N1It is drawn by a large amount of actual experiments, it can
It is arranged to 6.
S230, using the initial position in step S220 as starting point, carry out N2After step, with N2Positioning result before step, which is used as, to be connect
The input of the Wi-Fi that gets off positioning, Wi-Fi are positioned every N2Step performs, the last one knot of certain track during back track is gathered
The distance and N of point and certain candidate reference point of current step Wi-Fi positioning2*The distance of step_length calculates range deviation, pair sets
Fixed distance threshold is adjusted, and with reference to the distance threshold after adjustment and the course angle threshold value set before, carries out track screening,
And multiple N will be performed2The last one node of the highest track of PDR posterior probabilities of step is as positioning result;
Specifically, after above-mentioned steps S220 gets initial position and records, start to perform fusion location algorithm, it is first
First with the starting point, step number testing result, fusion course angle and step-length carry out PDR (pedestrian's dead reckoning), often carry out N2After step,
With N2The input that positioning result before step is positioned as following Wi-Fi.
It is positioned using the Wi-Fi for considering range deviation, heading angle deviation, and therefrom chooses ptotalHighest
Track in the last one node position as positioning result, Wi-Fi is positioned every N2Step performs, and therefore, calculates distance partially
When poor, the last one node of certain track and certain candidate reference point of current step Wi-Fi positioning during need to back track be gathered
Distance and N2The distance of step_length calculates range deviation, meanwhile, it is accordingly adjusted for the distance threshold needs of setting
Whole, by experiment, distance threshold is set to N2Step_length+2, heading angle deviation and threshold value combine the two without adjustment
Track screening is carried out, for being located in the track of same position situation twice in succession, by its Probability ptotal0 is set to, is rejected.
N2It is drawn by a large amount of actual experiments, may be configured as 5.
S240, walking N2During step, if mobile terminal detects turning behavior, by the turning detected
Step coordinate matches compared with landmark information storehouse, and using landmark locations as the positioning result currently walked, with the positioning knot
Starting point of the fruit as PDR performs PDR, continues to execute N2Step, if in walking N2Corner behavior is not detected during step,
Then N2After step, the Wi-Fi position fixing process in step S230 is performed, and using Wi-Fi positioning results as the starting point of PDR, continues to execute N2
Step, and so on.
S250, in above-mentioned steps S220, S230, S240, the result positioned every time also needs to combining cartographic information, so-called
Cartographic information refers to the constraint Grid square more intensive compared with fingerprint sampled point, as shown in Figure 3.
In conclusion by above-mentioned steps, by algorithm initialization, fusion positioning initial position is obtained to starting to perform fusion
Location algorithm in algorithm, has been used alternatingly multiple positioning modes, has merged multi-source data, realize the quick positioning to user.
The present invention can also carry out adaptive step study:In location algorithm implementation procedure set forth above, the step of pedestrian
Length is not that in pedestrian walks position fixing process, can be detected and turned by comer detection methods using fixed step-length always
The position of behavior when continuously across two corners, can obtain the distance between angular position, while be detected by step number, can obtain
Step number of the pedestrian between distance is obtained, when having multigroup distance and step number, you can the coefficient in cadence step-length model is extrapolated, so as to
The step-length of pedestrian is estimated, and so on, realize adaptive pedestrian step-length.
The present invention also provides a kind of storage device, the storage device stores computer program, the computer program
It can be performed to realize the fusion and positioning method based on mobile terminal as described above.
The present invention also provides a kind of mobile terminal, Fig. 4 is the structure diagram of the mobile terminal preferred embodiment of the present invention, such as
Shown in Fig. 4, mobile terminal includes processor 100, the storage device 200 with the processor 100 communication connection, the storage dress
It puts 200 and stores computer program, the computer program is used to implement when being performed by the processor to be based on as described above
The fusion and positioning method of mobile terminal;
The processor 100 is used to call the computer program in the storage device 200, to perform base as described above
In the fusion and positioning method of mobile terminal.
It should be noted that the present invention has simply merged pedestrian's dead reckoning, the Wi-Fi positions based on RSS correlations at present
Fingerprint location, cartographic information and several data of terrestrial reference detection are put, used sensor is also not limited to mention in the present invention
Sensor, with the increase of smart mobile phone built-in sensors, other sensors can be used to realize Activity recognition and opposite
The reckoning of movement locus.
In conclusion the invention discloses a kind of fusion and positioning method based on mobile terminal, storage device and movement eventually
End, the fusion and positioning method include:Mobile terminal carries out fusion location algorithm initialization, determines at the beginning of by merging location algorithm
What beginningization obtained, which start, performs the initial position of fusion positioning, and mobile terminal detects step in real time, obtain current step with phase
Like degree descending sort multiple candidate reference points, calculate mobile terminal be moved to by the first step back currently walked obtain it is more
The last one node of track, distance and course angle with the multiple candidate reference point, and pass through fixed step size and course
The constraint at angle, to determine to start the initial position for performing fusion positioning;The beginning that will be initialized by merging location algorithm
The initial position and turning behavior detection for performing fusion positioning combine, and determine to perform the initial position of fusion positioning, with what is determined
Initial position performs the PDR of the first predetermined step number for starting point, and will perform the PDR posterior probabilities of the multiple first predetermined step numbers most
The last one node of high track is as positioning result, if occurring during the PDR of multiple first predetermined step numbers is performed
Turning behavior then performs PDR by starting point of the position that turning behavior occurs.Present invention incorporates PDR, based on RSS correlations
The positioning of Wi-Fi location fingerprints, cartographic information and terrestrial reference detection, improve the precision and robustness of mobile terminal location, WiFi
Fingerprint location is put using the localization method based on RSS correlations, the device diversity problem that can be positioned to avoid location fingerprint.
It should be appreciated that the application of the present invention is not limited to the above, it for those of ordinary skills, can
To be improved or converted according to the above description, all these modifications and variations should all belong to the guarantor of appended claims of the present invention
Protect scope.
Claims (10)
1. a kind of fusion and positioning method based on mobile terminal, which is characterized in that including:
Step A, mobile terminal carry out fusion location algorithm initialization, determine the beginning initialized by merging location algorithm
Perform the initial position of fusion positioning, mobile terminal detects step in real time, obtain current step with similarity descending sort
Multiple candidate reference points, calculating mobile terminal are moved to last for a plurality of track that the back currently walked obtains by the first step
A node, distance and course angle with the multiple candidate reference point, and pass through the constraint of fixed step size and course angle, to determine
Start to perform the initial position that fusion positions;
Step B, the initial position and turning behavior that start to perform fusion positioning that will be initialized by merging location algorithm
Detection combines, and determines to perform the initial position of fusion positioning, the first predetermined step number is performed by starting point of definite initial position
PDR, and the last one node that will perform the highest track of PDR posterior probabilities of the multiple first predetermined step numbers is tied as positioning
Fruit, if turning behavior occurs during the PDR of multiple first predetermined step numbers is performed, using the position that turning behavior occurs as
Starting point performs PDR.
2. the fusion and positioning method according to claim 1 based on mobile terminal, which is characterized in that the step A is specific
Including:
A1, by step number detection algorithm detect step, and according to each step gather received signal strength information, using based on
The Wi-Fi location fingerprint location algorithms of RSS correlations are obtained one and are formed with n candidate reference point of similarity descending sort
Sequence Si, fixed step size is set to step_length using the step-size estimation model of fixed step size;
During mobile terminal is moved to the (i-1)-th step by the first step, all times of acquisition have been calculated by initialization algorithm by A2
The set that track forms is selected to be denoted as Ti-1If Ti-1In share m track;
A3 calculates Ti-1In every the last one node of track and SiIn the distance between each candidate reference point and course angle, then
The distance of calculating and course angle are calculated into difference with the course angle of step_length and the i-th step respectively, obtained based on step-length difference
M*n track sets of property and course angle otherness;
A4 merges the first of positioning using the last one node of the highest track of probability in m*n track as execution is started
Beginning position.
3. the fusion and positioning method according to claim 2 based on mobile terminal, which is characterized in that the step A1 is specific
Including:
A11 using step number detection algorithm, determines step according to the acquisition sensing data of mobile terminal, and is occurred according to step
At the moment, the Wi-Fi received signal strength information of t seconds before and after the moment is found in the Wi-Fi data of acquisition, processing forms i-th
The online fingerprint fp of stepi, using fixed step size model, step-length step_length is set, the side of course angle is obtained using fusion
Method determines the course angle heading of the i-th step of pedestrian;
A12, by the online fingerprint fp of the i-th stepiWith offline fingerprint database comparison match, the Wi-Fi based on RSS correlations is carried out
Location fingerprint positions, and obtains the candidate reference point sequence S arranged according to similarity descendingi, SiIn share n candidate reference point.
4. the fusion and positioning method according to claim 3 based on mobile terminal, which is characterized in that the step A4 is specific
Including:
A41, with dkjRepresent Ti-1The distance between j-th reference point in middle the last one node of kth track and the i-th step;With hkj
Represent Ti-1The angle of vector and north geographic pole that j-th of reference point is formed in middle the last one node of kth track and the i-th step;
North geographic pole vector vnorthAnd Ti-1The vector v that j-th of reference point is formed in middle the last one node of kth track and the i-th stepnow
It is expressed as:
vnorth=(0,52.5),
xijAnd yijRefer to the coordinate of j-th of reference point in the i-th step;WithRefer to Ti-1Middle kth track is last
The coordinate of one node;
dkjAnd hkjIt is represented by:
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hkj=360-rad2deg (vnorth·vnow/|vnorth|·|vnow|),
Wherein | vnorth| and | vnow| it is vector field homoemorphism;Rad2degO is that radian is switched to the number of degrees, and scope is -180 degree to 180 degree
Between, the number of degrees more than or equal to 0 need to be converted into;
If the i-th step course angle heading and hkjDeviation be hdiff, respectively to hdiffAnd dkjGiven threshold;
A42, to by setting hdiffAnd dkjThreshold value after the probability of every track of trajectory calculation that screens, dkjRange deviation
For:
ddiff=| dkj- step_length |,
ddiffAnd hdiffGaussian distributed, ddiffAnd hdiffIt is expressed as:
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Wherein σdAnd σhThe respectively standard deviation of range deviation and the deviation of directivity, pdAnd phFor range deviation and the height of heading angle deviation
This distribution probability, with reference to the S positioned by Wi-FiiIn each reference point similarity, similarity is normalized operation
Afterwards, the related coefficient p of j-th of reference point Wi-Fi positioning in the i-th step is obtainedkj, pkj、pdAnd ph, Wi-Fi positioning consider away from
Track Probability p between the candidate reference point calculated from deviation and heading angle deviationtotalIt is represented by:
ptotal=ω pkj+(1-ω)pdph, ω is the weight of Wi-Fi similarities, and (1- ω) is range deviation and the deviation of directivity
Shared weight;
A43, by Probability ptotalThe last one node output of highest track is as positioning result.
5. the fusion and positioning method according to claim 4 based on mobile terminal, which is characterized in that the step B is specific
Including:
B1, structure landmark information storehouse, by the coordinate record of intersecting point in landmark information storehouse;
When B2, mobile terminal detect the i-th step, judge whether the step occurs turning behavior, if turning behavior occurs, pass through Wi-
Fi positioning results are matched with the landmark locations in landmark information storehouse, are determined landmark locations, and are started to hold with this location determination
The initial position of row fusion positioning;If turning behavior does not occur, determined with performing fusion location algorithm initialization in step A
Initial position be start perform fusion positioning initial position;
B3, using the initial position in step B2 as starting point, carry out N2After step, with N2Positioning result before step is as following Wi-Fi
The input of positioning, Wi-Fi are positioned every N2Step performs, the last one node of certain track and current step during back track is gathered
The distance and N of certain candidate reference point of Wi-Fi positioning2* the distance of step_length calculates range deviation, to the distance of setting
Threshold value is adjusted, and with reference to the distance threshold after adjustment and the course angle threshold value set before, is carried out track screening, and will be performed
Multiple N2The last one node of the highest track of PDR posterior probabilities of step is as positioning result;
B4, walking N2During step, if mobile terminal detects turning behavior, the step of the turning detected is sat
Mark matching with landmark information storehouse compared with, and using landmark locations as the positioning result currently walked, using the positioning result as
The starting point of PDR performs PDR, continues to execute N2Step, if in walking N2Corner behavior is not detected during step, then N2Step
Afterwards, the Wi-Fi position fixing process in step B3 is performed, and using Wi-Fi positioning results as the starting point of PDR, continues to execute N2Step.
6. the fusion and positioning method according to claim 5 based on mobile terminal, which is characterized in that the step B2 is performed
N2Step B3 is performed after step again.
7. the fusion and positioning method according to claim 6 based on mobile terminal, which is characterized in that the N1And N2Respectively
For 6 and 5.
8. the fusion and positioning method according to claim 4 based on mobile terminal, which is characterized in that in the step A41
To dkjAnd hdiffGiven threshold is respectively 3 and 40.
9. a kind of storage device, which is characterized in that the storage device stores computer program, and the computer program can
It is performed to realize such as fusion and positioning method of claim 1 to 8 any one of them based on mobile terminal.
10. a kind of mobile terminal, which is characterized in that including:Processor, the storage device being connected with the processor communication, institute
Stating storing device for storing has computer program, and the computer program is used to implement claim 1 when being performed by the processor
To fusion and positioning method of 8 any one of them based on mobile terminal;
The processor is used to call the computer program in the storage device, is required with perform claim described in 1 to 8 any one
The fusion and positioning method based on mobile terminal.
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