CN105043380A - Indoor navigation method based on a micro electro mechanical system, WiFi (Wireless Fidelity) positioning and magnetic field matching - Google Patents

Indoor navigation method based on a micro electro mechanical system, WiFi (Wireless Fidelity) positioning and magnetic field matching Download PDF

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CN105043380A
CN105043380A CN201510369139.8A CN201510369139A CN105043380A CN 105043380 A CN105043380 A CN 105043380A CN 201510369139 A CN201510369139 A CN 201510369139A CN 105043380 A CN105043380 A CN 105043380A
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magnetic field
wifi
positioning result
fingerprint
data
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牛小骥
李由
张鹏
庄园
程政
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Wuhan University WHU
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Wuhan University WHU
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
    • G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Automation & Control Theory (AREA)
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  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Environmental & Geological Engineering (AREA)
  • General Life Sciences & Earth Sciences (AREA)
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Abstract

The invention discloses an indoor navigation method based on a micro electro mechanical system, WiFi (Wireless Fidelity) positioning and magnetic field matching, a navigation result which is more reliable and stable than the navigation result of a traditional indoor navigation method can be obtained by aiming at an indoor navigation method of the consuming electronic products, by fully utilizing a built-in MEMS (Micro-electromechanical Systems) sensor in the consuming electronic products and a WiFi (Wireless Fidelity) signal in public places, and an additional labor field workload is not needed. The indoor navigation method provided by the invention can effectively reduce the positioning error matching rate through the interaction of the MEMS sensor and the WiFi signal under the hostile navigation condition (such as the WiFi signal is weak, the distribution of hot spots is poor and an indoor magnetic field gradient is not obvious ).

Description

Based on the indoor navigation method of micro-electro-mechanical sensors, WiFi location, magnetic field coupling
Technical field
The present invention relates to indoor positioning, wireless telecommunications and micro-electromechanical system field, particularly relate to a kind of indoor navigation method based on micro-electro-mechanical sensors, WiFi location, magnetic field coupling.
Background technology
Day by day universal along with in the face of mobile terminals such as the arriving in location-based service (LBS) epoch of the public and smart mobile phones, the demand obtaining individual position and ambient services information whenever and wherever possible increases day by day.As the Main Means obtaining spatial positional information, navigator fix is a core technology of LBS.Especially people on average have the time of more than 70% in indoor, and therefore, indoor positioning technologies is most important in real time, accurately.
The difficult point of indoor positioning is the sensor performance difference etc. that cannot receive in indoor in worldwide navigation positioning system (GNSS) signal, indoor navigation circumstance complication and consumer electronics product.Although based on the location technology of radiofrequency signal, as WiFi, bluetooth, RFID, UWB, ZigBee etc., can position, these technology need special implantation of device and maintenance usually, and need special signal receiver.A special case is WiFi location technology, because public arena has had Wi-Fi hotspot (router) to lay mostly, and existing WiFi receiving chip in current consumer products.Therefore, WiFi location gets the attention.The difficult point of WiFi location is: 1) as a kind of absolute fix technology, and the performance of WiFi location depends on the laying of Wi-Fi hotspot.Do not having focus or the bad place of hotspot's distribution, WiFi precision is difficult to be guaranteed; 2) WiFi signal intensity is unstable, is easily interfered, decays and the impact of multipath effect in indoor; 3) difference of WiFi receiving chip performance in distinct device, also will cause positioning error.These factors will cause the instability of WiFi result, easily occur " error hiding " or " by mistake location ", cause the positioning error of huge (may reach tens of rice).
The MEMS sensor (as gyro, accelerometer, magnetometer) produced along with the development of micro-electromechanical system (MEMS) (Micro-ElectroMechanicalSystems) technology in recent years has that cost low (time in enormous quantities), size are little, lightweight, low in energy consumption, high reliability, makes it be widely used in consumer electronics product.Pedestrian's reckoning (PDR) technology can utilize the information of gyro and accelerometer constantly can calculate the position of user.The sharpest edges of PDR technology are its independence, namely do not rely on the laying of any external unit, are therefore also not easy to be subject to environmental interference.But the shortcoming of PDR technology is its high precision that can only provide short-term, and long-term navigation accuracy is because the existence of sensor error and the integral algorithm in calculating that navigates, and reduces rapidly.Although use accelerometer can computing equipment horizontal attitude angle (i.e. the angle of pitch, roll angle) and compensated, course attitude angle can increase sharply when not having other information constrained and cause site error.Although, use magnetometer to pass through inductively magnetic field, determine the course of equipment.But under indoor environment, environmental magnetic field is subject to the interference of Artificial facilities and is no longer terrestrial magnetic field.Therefore, magnetometer is difficult in indoor provide reliable course.Indoor magnetic field is the large problem using magnetic strength measurement course and pedestrian navigation to face extremely.
On the other hand, it is abnormal that researchers also make use of indoor magnetic field, and it can be used as a kind of fingerprint to come for location.The precondition of coupling location, magnetic field is that indoor magnetic field is stablized in time, and the spatially property of there are differences.The thought of magnetic field coupling and WiFi fingerprint recognition is similar, but there are two advantages: 1) magnetic field is ubiquitous, without any need for transmitter.2) consumer electronics produce in the sampling rate high (usually above 10Hz) of magnetometer.The difficult point of magnetic field coupling is that magnetic field fingerprint only has three dimensions.And because in navigation procedure, course information is inaccurate, causes using accelerometer to distinguish two magnetic field dimensions, i.e. horizontal magnetic field and vertical magnetic field (or total magnetic field and magnetic dip).In order to improve the dimension of magnetic field fingerprint when additionally not increasing sensor, researchers have proposed the method for coupling continuously.The method of continuous coupling the continuous navigation information (namely measuring track) of a period of time is all left, and then compares with a series of continuous known point (i.e. candidate tracks) in database, find the highest point of matching degree.The method of batch coupling for the navigation of the high-precision gravity of outdoor, earth magnetism and terrain match, and has the location algorithm of relative maturity, as TERCOM, ICCP etc.In order to ensure the accurately fixed of coupling, need to guarantee to measure track identical with the length of candidate tracks.So, be equipped with a high-grade inertial navigation system (INS) in high-precision independent navigational system, and use constraint condition (as nonholonomic restriction (NHC), zero-velocity curve (ZUPT) etc.) to provide high-precision unique measurement.But the inertial sensor errors in consumption electronic product is large, cannot provide accurate displacement measurement; And pedestrian's DYNAMIC COMPLEX, be difficult to excavate effective constraint information (unless fixed by equipment, as being arranged on pin or on waist).Therefore, there is certain error hiding rate in the magnetic field matching technique that current indoor magnetic field matching technique or inertia are assisted.Once error hiding, it is even more that navigation error may reach tens of rice, greatly affects Consumer's Experience.
In sum, all there is certain limitation in WiFi, PDR and magnetic field matching technique: WiFi signal intensity easily fluctuates, the impact of counting out and distributing and precision is heated; PDR can provide short-term navigation result, but long-term accuracy reduces rapidly; Magnetic field matching technique precision is high but easily occur error hiding.Above technology or its existing combination, as the combination of the combination of PDR technology and WiFi location technology, PDR technology and magnetic field matching technique, all there is the limitation of use scenes, still can not whenever meet consumer product, demand that in real time location accurately and reliably all can be carried out in any place.
Summary of the invention
For the limitation of prior art, the present invention proposes a kind of indoor navigation method based on micro-electro-mechanical sensors, WiFi location, magnetic field coupling, the method can utilize the WiFi signal in MEMS sensor (comprising gyro, accelerometer and magnetometer) built-in in consumer electronics product and public arena, completes indoor positioning accurately and reliably.
For solving the problems of the technologies described above, the present invention adopts following technical scheme:
One, the magnetic field matching locating method that WiFi fingerprint recognition is auxiliary, comprises step:
S1 is along the mapping track image data of planning, the database of WiFi fingerprint and magnetic field fingerprint is built in conjunction with position when data and data acquisition, described data comprise WiFi data and magnetic field data, WiFi data comprise WiFi signal intensity and mac address, and magnetic field data comprises the data of gyro, accelerometer and magnetometer;
S2 adopts WiFi fingerprint recognition method to treat anchor point and positions, and obtains the WiFi positioning result in site undetermined;
S3 determines match search region, magnetic field based on WiFi positioning result, treats anchor point and carry out magnetic field coupling in match search region, magnetic field, obtains the magnetic field coupling positioning result in site undetermined; Match search region, magnetic field is that radius of circle or rotational symmetry polygonal side length are empirical value with WiFi positioning result be the center of circle or center circle or rotational symmetry polygon.
S1 comprises further:
1.1 according to target area map planning mapping track, and obtain mapping track key node position, described key node comprises starting point, terminal, intersection node and the node that turns round;
1.2 gather WiFi data and magnetic field data along mapping track;
The WiFi data of 1.3WiFi reference point and position form WiFi fingerprint, the magnetic field data of magnetic field reference point and formation magnetic field, position fingerprint; The step point in WiFi reference point and WiFi Data Update moment, by the interpolated point preset interpolation distance interpolation and obtain between magnetic field reference point and step point and adjacent step point;
The database of 1.4 structure WiFi fingerprints and magnetic field fingerprint.
Above-mentioned step point position is adopted and is obtained with the following method:
According to adjacent two key node positions and this adjacent crucial two internodal step numbers on mapping track, obtain each step point position on mapping track through interpolation.
Above-mentioned magnetic field fingerprint comprises the magnetic field vector m obtained according to magnetic field data k=[BB db h], wherein, B=|B| is total magnetic intensity, and B is three axle output vectors of magnetometer; B dand B hbe respectively vertical component and the horizontal component of magnetic field intensity.
WiFi fingerprint recognition method described in S2 is the WiFi fingerprint recognition method based on k neighbor point, is specially:
The WiFi signal intensity at WiFi reference point place each in the WiFi signal intensity of site undetermined and database is compared, find k the WiFi reference point nearest with the signal intensity in site undetermined, using the weighted mean value of this k WiFi reference point locations as site location undetermined, weights are the signal intensity distance of site undetermined and each WiFi reference point.
In S3, described radius of a circle or the polygonal length of side of rotational symmetry are set to ε σ wifi, ε is the natural number artificially set according to actual conditions, σ wififor WiFi positioning precision;
Described WiFi positioning precision obtains according to WiFi positioning result statistics, is specially:
Series of points is chosen in indoor, the WiFi positioning result of each point and the WiFi positioning error of coordinate true value and each point, the standard deviation of the WiFi positioning error of this series of points and WiFi positioning precision.
Treating anchor point carry out magnetic field coupling in match search region, magnetic field described in S3, comprises further:
3.1 magnetic field datas walking magnetic field reference point locations in step and correspondence according to the nearest N1 in site undetermined form the magnetic field fingerprint in site undetermined, and N1 rule of thumb and requirements set;
Magnetic field, site undetermined fingerprint mates with the database magnetic field fingerprint in match search region, magnetic field by 3.2, finds the k minimum with magnetic field, site undetermined fingerprint difference according to magnetic field, storehouse fingerprint;
3.3 with the magnetic field fingerprint difference of site undetermined magnetic field fingerprint and database magnetic field fingerprint for weights, k is asked weighted mean value according to magnetic field reference point locations in the fingerprint of magnetic field, storehouse, namely obtains the Magnetic oriented result in site undetermined.
Two, based on an indoor navigation method for micro-electro-mechanical sensors, WiFi location, magnetic field coupling, step is comprised:
S1 is along the mapping track image data of planning, the database of WiFi fingerprint and magnetic field fingerprint is built in conjunction with position when data and data acquisition, described data comprise WiFi data and magnetic field data, WiFi data comprise WiFi signal intensity and mac address, and magnetic field data comprises the data of gyro, accelerometer and magnetometer;
S2 adopts WiFi fingerprint recognition method to treat anchor point and positions, and obtains the WiFi positioning result in site undetermined;
S3 determines match search region, magnetic field based on WiFi positioning result, treats anchor point and carry out magnetic field coupling in match search region, magnetic field, obtains the magnetic field coupling positioning result in site undetermined; Wherein, match search region, magnetic field is that radius of circle or rotational symmetry polygonal side length are empirical value with WiFi positioning result be the center of circle or center circle or rotational symmetry polygon;
S4, with PDR error equation structure Kalman filtering state equation, with WiFi positioning result and magnetic field coupling positioning result structure measurement equation, adopts Kalman filtering method to carry out integrated navigation.
S4 comprises further:
4.1 utilize PDR positioning result to detect the error hiding of WiFi positioning result and magnetic field coupling positioning result, if WiFi positioning result and magnetic field coupling positioning result are error hiding, with PDR positioning result for integrated navigation result; Otherwise, perform step 4.2;
4.2 with PDR error equation structure Kalman filtering state equation, with WiFi positioning result and magnetic field coupling positioning result structure measurement equation, adopts Kalman filtering method to merge WiFi positioning result, magnetic field coupling positioning result and PDR positioning result.
In sub-step 4.1, if the distance of WiFi positioning result and PDR positioning result is less than threshold value Th d_PDR, then this WiFi positioning result is error hiding; If the distance of magnetic field coupling positioning result and PDR positioning result is less than threshold value Th d_PDR, then coupling positioning result in this magnetic field is error hiding; Th d_PDRwith radius or the length of side in match search region, magnetic field.
The present invention be directed to the indoor orientation method of consumption electronic product, take full advantage of the WiFi signal in MEMS sensor built-in in consumer electronics product and public arena, do not need artificial field process amount especially, the navigation results more reliable and stable than traditional indoor navigation method can be obtained.When navigational environment severe (as weak in WiFi signal, poor, the indoor magnetic field gradient of Wi-Fi hotspot distribution is not obvious), the present invention is cooperatively interacted by MEMS sensor and WiFi signal, effectively can reduce and locate error hiding rate.
Compared to the prior art, tool of the present invention has the following advantages and beneficial effect:
1, the Database of WiFi and magnetic field coupling can be completed simultaneously, do not need extra artificial field operation cost.
2, the complementarity making full use of multiple technologies strengthens the reliability of integrated navigation: utilize WiFi positioning result to determine magnetic field match search scope, thus effectively reduces error hiding rate and the calculated amount of magnetic field coupling; Result carries out Detection of Gross Errors to the positioning result based on WiFi and magnetic field coupling to utilize PDR to calculate.
3, the step number utilizing inertial sensor to detect carrys out rough calculation course length to be matched.Meanwhile, for the coarse problem of matching track length computation in pedestrian navigation, DTW algorithm is used to improve the precision of magnetic field coupling.
4, utilize the pitch attitude angle calculated by accelerometer information and roll attitude angle, excavate the vertical of magnetic field and horizontal component, thus form three-dimensional magnetic field vector, thus increase magnetic field fingerprint dimension, improve magnetic field matching precision.
Accompanying drawing explanation
Fig. 1 is pedestrian navigation positioning system structure schematic diagram of the present invention;
Fig. 2 is the database product process figure of WiFi fingerprint and magnetic field fingerprint;
Fig. 3 is the mapping track schematic diagram planned in embodiment;
Fig. 4 is step detection exemplary plot in embodiment;
Fig. 5 is the schematic diagram that in the present invention, WiFi positioning result determines magnetic field match search scope;
Fig. 6 is assignment test trajectory diagram in embodiment;
Fig. 7 is WiFi positioning result in embodiment;
Fig. 8 is coupling positioning result in magnetic field in embodiment;
Fig. 9 is the positioning result based on WiFi positioning result auxiliary magnetic field coupling in embodiment;
Figure 10 is PDR and WiFi integrated positioning result in embodiment;
Figure 11 is the magnetic field coupling positioning result that in embodiment, PDR and WiFi is auxiliary;
Figure 12 is PDR, WiFi in embodiment, magnetic field coupling integrated positioning result.
Embodiment
Below in conjunction with specific embodiment, the present invention is described in detail.Following examples will contribute to those skilled in the art and understand the present invention further, but not limit the present invention in any form.It should be pointed out that for those of ordinary skills, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.
The present invention comprises off-line mapping and two stages of tuning on-line, and the object in off-line mapping stage is the database generating WiFi fingerprint and magnetic field fingerprint, uses for the tuning on-line stage.
Concrete steps of the present invention are as follows:
Step 1, builds the database of WiFi fingerprint and magnetic field fingerprint.
The present invention disposablely can complete the Database of WiFi fingerprint and magnetic field fingerprint, compares simple WiFi fingerprint database or the foundation of magnetic field fingerprint database, and the present invention does not need extra artificial field operation cost.
The process flow diagram that database generates is shown in Fig. 2, and concrete steps are as follows:
Step 1.1: according to target area map, planning mapping track.
Because the object setting up the database of WiFi fingerprint and magnetic field fingerprint is for indoor positioning, so mapping track need cover pedestrian's scope of activities possible in target area as far as possible.Meanwhile, survey and draw track and should avoid repetition, to reduce mapping operations amount as far as possible.The present embodiment has planned 4 mapping tracks, and every bar mapping track data acquisition time is 5-10 minute.Fig. 3 is 4 mapping tracks of the present embodiment target area map and design, sees figure (a) ~ (b) respectively.
Obtain the coordinate of key node on mapping track, coordinate system can adopt earth coordinates or plane right-angle coordinate, selects earth coordinates in the present embodiment.Earth coordinates are using latitude, longitude and elevation as X, Y, Z axis, and plane right-angle coordinate is using north orientation, east orientation, vertical as X, Y, Z axis direction.Described key node comprises starting point, terminal, intersection node and the node that turns round.
Step 1.2: gather WiFi data and magnetic field data.
Mapping worker handheld test equipment covers 4 mapping tracks respectively, gathers WiFi data and magnetic field datas simultaneously, gather WiFi data and comprise WiFi signal intensity and mac address, magnetic field data comprises the data of gyro, accelerometer and magnetometer.Described testing apparatus can be installed the consumer electronics product of data acquisition software.
Step 1.3: generate WiFi fingerprint and magnetic field fingerprint.
(1) generation of WiFi fingerprint.
Because testing apparatus WiFi Data Update frequency (as 0.3Hz) is low, therefore in mapping worker walking process when detecting WiFi Data Update, WiFi data and updated time mapping worker step point (i.e. WiFi reference point) position are combined, forms WiFi fingerprint FW i, see formula (1).
FW i = { pos i , σ p o s i , ( mac i , 1 , RSS i , 1 ) , ( mac i , 2 , RSS i , 2 ) , ... , ( mac i , m i , RSS i , m i ) } - - - ( 1 )
In formula (1):
I represents that WiFi reference point is numbered, and j represents that Wi-Fi hotspot is numbered;
FW ibe the WiFi fingerprint of i-th WiFi reference point, i-th WiFi reference point is expressed as RP ipoint;
Pos iand σ posirepresent RP respectively ithe position of point and positional precision;
Mac i,jand RSS i,jrepresent RP respectively ithe MAC Address of the jth Wi-Fi hotspot that point receives and signal intensity;
M irepresent RP ithe Wi-Fi hotspot quantity that point can receive.
RP ipoint positional precision σ posidefining method as follows:
Assuming that adjacent key node A and B spacing are L on mapping track aB, and total N between key node A and B aBindividual step point, then this N aBthe positional precision of individual step point α is scale-up factor.
The defining method of scale-up factor α is as follows:
First, mapping course length L is calculated.Then, mapping worker handheld test equipment repeatedly covers this mapping track, often covers and once surveys and draws track i.e. one group of experiment, obtains the step number often organizing experiment and the displacement calculated through PDR.Assuming that the step number of b group experiment is N b, the displacement calculated through PDR is P b, then the scale-up factor of b group experiment according to the ratio system α that each group is tested bobtain n is experimental group number.
The step point position of mapping worker is adopted and is obtained with the following method: according to adjacent two key node positions and this adjacent crucial two internodal step numbers on mapping track, obtains often walking corresponding position, i.e. step point position along in mapping track walking process through interpolation.Adjacent two internodal step numbers can be detected by inertial sensor and obtain.
(2) generation of magnetic field fingerprint.
Because magnetometer sampling rate is high, therefore, each step point position and corresponding magnetic field vector are combined, namely forms magnetic field fingerprint.In addition, supposing at the uniform velocity to move between adjacent step point, carrying out interpolation by presetting interpolation distance (as 0.1m), using each interpolated point position and corresponding magnetic field vector as magnetic field fingerprint, magnetic field reference point comprises step point and interpolated point here.
The magnetic field vector that interpolated point is corresponding is obtained by interpolation, namely according to step point place magnetic field vector, generates a series of magnetic field vector, preset interpolation distance here and preset interpolation distance with in the last period in adjacent step point by default interpolation distance interpolation.Spacing rule of thumb and requirements set, suitably increases spacing and can improve magnetic field vector dimension, but will increase calculated amount.In the present embodiment, spacing is preset as 0.1 meter.
Magnetic field fingerprint FM psee formula (2):
FM p＝{pos p,σ posp,m p}(2)
In formula (2):
FM pbe the magnetic field fingerprint of p magnetic field reference point, p magnetic field reference point is expressed as RP ppoint;
Pos pand σ posprepresent RP respectively pthe position of point and positional precision;
M prepresent RP pthe magnetic field vector of point.
Interpolated point positional precision σ between adjacent step point pospthe i.e. mean value of this adjacent step point positional precision, the defining method of step point positional precision is with RP in WiFi fingerprint ithe defining method of some positional precision.
Utilize the pitch attitude angle and roll attitude angle that are calculated by accelerometer data in the present embodiment, excavate the vertical of magnetic field intensity and horizontal component, form three-dimensional magnetic field vector, thus increase magnetic field fingerprint dimension, improve magnetic field matching precision.
Pitch attitude angle φ and roll attitude angle θ is calculated as follows:
φ = a tan 2 ( - f y , - f z ) θ = a tan 2 ( f x , f y 2 + f z 2 ) - - - ( 3 )
In formula (3): f i(i=x, y, z) represents that the i axle of accelerometer exports.
The vertical component B of magnetic field intensity dfor:
B D＝-sinθ·B x+sinφcosθ·B y+cosφcosθ·B z(4)
In formula (4): [B xb yb z] represent that three axles of magnetometer export.
Therefore, magnetic field vector m in the present invention k=[BB db h], B=|B| is total magnetic intensity, and B is three axle output vectors of magnetometer; for the horizontal component of magnetic field intensity.
In concrete enforcement, the specific force mould acquisition of signal user step after moving window smoothing processing can be utilized, be specially: to the ratio force vector of accelerometer measures carry out asking mould: represent the ratio force vector that accelerometer exports in t.Then, to specific force mould signal a tsmoothing process, obtains signal smoothing window length is (2L+1), and L is mapping course length.Finally, the specific force mould signal is smoothly found out trough, if trough value is less than given threshold value Th step, then this trough corresponding moment is detected as step, sees Fig. 4.
Step 1.4: WiFi fingerprint and magnetic field fingerprint write into Databasce are stored.
Step 2, WiFi locates.
The present embodiment adopts the WiFi fingerprint identification technology based on k neighbor point to carry out WiFi location.Compared by the WiFi signal intensity at each WiFi reference point place in WiFi signal intensity that site undetermined is received and database, find k the WiFi reference point nearest with the signal intensity in site undetermined, using the weighted mean value of this k WiFi reference point locations as site location undetermined, weights are the signal intensity distance of site undetermined and each WiFi reference point.The value of k is calculated by the WiFi data statistics gathered in region to be measured tries to achieve: in region to be measured, gather a large amount of WiFi data (dynamic or static), then set respectively k=1,2,3 ... 10, fingerprint recognition location is carried out to each group of WiFi data.Finally count the root mean square of WiFi positioning error corresponding to different k values, and the k value selecting corresponding standard deviation minimum.
Signal intensity distance d ibe calculated as follows:
d i = | SS r e c , l u j - SS D B , i j | , RP i ∈ I R P - - - ( 5 )
In formula (5):
D ifor signal intensity distance, i.e. site undetermined and WiFi reference point RP iwiFi signal strength difference;
represent the WiFi signal intensity that lu place, site undetermined receives;
represent WiFi reference point RP in database iwiFi signal intensity;
I rPfor the set of WiFi reference point in database.
Being calculated as follows of site location undetermined:
r ^ = Σ i = 1 k ( c i C r i ) - - - ( 6 )
In formula (6):
represent the site location undetermined calculating and obtain;
R irepresent and i-th WiFi reference point locations in k the WiFi reference point that the signal intensity in site undetermined is nearest;
C i=1/d i, d irepresent the signal intensity distance of site undetermined and i-th WiFi reference point, i-th WiFi reference point here refers to i-th WiFi reference point in k the WiFi reference point nearest with the signal intensity in site undetermined.
Step 3, based on WiFi positioning result auxiliary magnetic field coupling location.
This step is specific as follows:
Step 3.1: determine match search region, magnetic field based on WiFi positioning result.
The WiFi positioning result that the present invention proposes to obtain based on step 2 reduces match search region, magnetic field, thus can reduce magnetic field coupling error hiding rate and calculated amount.See Fig. 5, in the present embodiment magnetic field match search region be with WiFi positioning result be the center of circle, 3 σ wififor the border circular areas of radius, σ wififor WiFi positioning precision.
Certainly, match search region, magnetic field is not limited to shown in Fig. 5, match search region, magnetic field can be that search radius or the region of search length of side are the empirical value artificially set according to actual conditions with WiFi positioning result be the center of circle or center circle or rotational symmetry polygon.Such as, search radius or the region of search length of side can be set to ε σ wifi, ε is the natural number artificially set according to actual conditions, generally gets 1 ~ 5.
WiFi positioning precision obtains according to WiFi positioning result statistics, is specially:
Series of points is evenly chosen in indoor, obtains the coordinate true value of this series of points from the electronic chart of these indoor, and coordinate true value can be absolute coordinates or relative coordinate.Then, the static WiFi data gathered in Preset Time (as 2 minutes) in this series of points, use WiFi location algorithm to process the static WiFi data of each point respectively respectively, realize the WiFi location of each point.Finally, the WiFi positioning result of each point is deducted corresponding coordinate true value, obtains the WiFi positioning error of each point, the standard deviation of WiFi positioning error a little and WiFi positioning precision σ wifi.
Step 3.2: the magnetic field fingerprint gathering site undetermined.
Detect step and record, magnetometer of simultaneously holding the record exports.When step number reaches step threshold value N1, often detect user and walked a step, the magnetic field vector of the magnetic field reference point locations in N1 step nearest for current step point and correspondence is formed the magnetic field fingerprint in current step point (i.e. site undetermined).Current step point is made to be n 0, its nearest N1 step is pressed and is followed successively by n from the near to the remote 1, n 2... n n1, then magnetic field reference point comprises step point n 0, step point n n1and step point n 0and n n1interior all step points and interpolated point, interpolation distance is with the default interpolation distance of interpolation magnetic field reference point in the fingerprint generation step of sub-step 1.3 magnetic field.Rule of thumb and requirements set, N1 crosses young pathbreaker and is difficult to embody changes of magnetic field step threshold value N1, thus error hiding rate is increased; N1 increases can improve matching precision, but can increase calculated amount simultaneously.N1 is set greater than 5 by suggestion, and in the present embodiment, N1 is set to 10, and namely detecting user carries out first time magnetic field coupling after having walked 10 steps; User often makes a move afterwards, and the magnetic field fingerprint of 10 steps all adopting current step nearest carries out magnetic field coupling.
Step 3.3: magnetic field is mated.
The present invention proposes k neighbor point magnetic field matching method, magnetic field, the site undetermined fingerprint and the database magnetic field fingerprint in the match search region, magnetic field limited in step 3.1 that obtain by step 3.2 abbreviation of magnetic field fingerprint (namely in database) mate, be used for the database magnetic field fingerprint length of carrying out mating should with magnetic field, site undetermined fingerprint similar length.During coupling, find k minimum with magnetic field, site undetermined fingerprint difference in match search region, magnetic field according to magnetic field, storehouse fingerprint, magnetic field fingerprint difference MAD adopts formula (7) to calculate.
M A D = 1 N | S - M | - - - ( 7 )
In formula (7): S represents magnetic field, site undetermined fingerprint; M represents database magnetic field fingerprint in match search region, magnetic field, and N represents course length.
For improving magnetic field matching precision when measuring course length out of true, dynamic time warping (DTW) algorithm is used for mating based on the magnetic field of step by this step.DTW algorithm is former in automatic speech recognition field, and the present embodiment is introduced into magnetic field coupling during out of true step-length.DTW algorithm, by compress or two seasonal effect in time series time shafts of the coupling that stretches improve matching precision, and uses regular path distance to weigh the similarity between two time serieses.Suppose that two time serieses to be matched are S={s 1, s 2..., s aand M={m 1, m 2..., m b, then the form in regular path is w=w (1), w (2) ..., w (n), wherein, w (i)=[i (n), j (n)], i and j represents the time shaft of S and M respectively.Next, the object of DTW makes cost function minimum, wherein, finally obtain regular path γ (i, j)=δ (w (n))+min [γ (i-1, j), γ (i-1, j-1), γ (i, j-1)] that distance is the shortest.When calculating mapping course length, also need to use user's step-length, step-length can according to model s k=Af k+ B obtains, wherein, and s krepresent step-length; f k=1/ (t k-t k-1) be walk frequency, t k-1, t krepresent the time that adjacent bipod beans-and bullets shooter is corresponding, A and B is constant coefficient, tries to achieve according to high number of row personal data statistics.
Step 3.4: Magnetic oriented.
K is asked weighted mean according to position in the fingerprint of magnetic field, storehouse, namely obtains the Magnetic oriented result in site undetermined
r ^ M = Σ i = 1 k m i M r M , i - - - ( 8 )
In formula (8):
for magnetic field coupling positioning result, the site location undetermined namely calculated;
R m,irepresent the magnetic field reference point locations of k according to i-th database magnetic field fingerprint in the fingerprint of magnetic field, storehouse;
M i=1/ ρ i, ρ irepresent the magnetic field fingerprint difference of site undetermined magnetic field fingerprint and i-th database magnetic field fingerprint, i-th database magnetic field fingerprint refers to that k is according in the fingerprint of magnetic field, storehouse i-th here.
K value in the coupling of magnetic field is obtained by the magnetic field data statistical computation gathered in region to be measured: in region to be measured, gather magnetic field data (comprising dynamically or static state), then set respectively k=1,2,3 ... 10, coupling location, magnetic field is carried out to each group of magnetic field data.Finally count the root mean square of magnetic field coupling positioning error corresponding to different k values, and the k value selecting corresponding standard deviation minimum.Magnetic field coupling positioning error is the difference of magnetic field coupling positioning result and coordinate true value.
Step 4: based on the integrated navigation of PDR, WiFi location, magnetic field coupling.
Traditional PDR/WiFi/ magnetic field coupling integrated navigation technology uses PDR to carry out position prediction, uses WiFi location and magnetic field coupling to carry out location updating, use certain method of estimation (as Kalman filtering or particle filter) to carry out data fusion.The present invention then gives full play to PDR, WiFi location and respective advantage is mated in magnetic field, avoids respective inferior position, thus improves positioning system reliability.The present invention uses WiFi locator data auxiliary magnetic field to mate, and significantly to reduce the error hiding rate of magnetic field coupling, ensures the reliability of magnetic field matching result.In addition, the present invention uses the error hiding in the further detecting and elimination WiFi location of PDR reckoning result and magnetic field matching result.In the present embodiment, integrated navigation uses Kalman filtering to complete, and wherein, uses PDR error equation to construct Kalman filtering state equation, the magnetic field coupling positioning result structure measurement equation using WiFi positioning result and WiFi positioning result to assist.
Step 4.1: utilize PDR positioning result to detect the error hiding of WiFi positioning result and magnetic field coupling positioning result.
PDR algorithm is a kind of relative positioning mode, and by a upper step point position, the course that combined sensor is measured or calculated and step information, calculate next step point position.The present embodiment PDR used error equation is as follows:
In formula (9):
λ, ψ, s represent latitude, longitude, course and step-length respectively;
R mand R nrepresent radius of curvature of meridian and radius of curvature in prime vertical respectively;
H is elevation;
Subscript k and k+1 represents that adjacent step point is numbered.
If WiFi positioning result or the distance between magnetic field coupling positioning result and PDR positioning result are less than threshold value Th d_PDR, then step 4.2 is entered; Otherwise, WiFi positioning result and magnetic field matching result are all labeled as rough error.Threshold value Th d_PDRbe set with multiple method, the present embodiment use Th d_PDR=3 σ wifi, σ wififor WiFi positioning precision.Threshold value Th d_PDRwith search radius or the region of search length of side in match search region, magnetic field, artificially can set according to actual conditions, also can be set to ε σ according to WiFi positioning precision wifi, ε is the natural number artificially set according to actual conditions.
Step 4.2: by WiFi positioning result and magnetic field coupling positioning result and PDR positioning result combine, carry out location estimation.
The present embodiment adopt Kalman filtering method, its state equation and measurement equation as follows:
δx k+1＝Φ k+1,kδx k+Γ kw k
(10)
z k+1＝H k+1δx k+1+v k+1
In formula (10), each matrix and vectorial being expressed as follows:
Γ k = 0 0 0 1 0 0 0 Δ t 0 1 T , w k＝[w sw b] T.
δ λ, δ ψ, δ s, b are followed successively by latitude error, longitude error, course error, step error and vertical gyro zero error partially; w sand w bbe respectively step-length and vertical gyro zero white noise partially.When WiFi positioning result can be used and not be error hiding through detection, corresponding observation vector and observing matrix are respectively h wiFi, k+1=[I 2 × 30 2 × 2]; When magnetic field matching result can be used and not be error hiding, corresponding observation vector and observing matrix are respectively h mM, k+1=[I 2 × 30 2 × 2], v k+1for corresponding measurement noise vector is mated in WiFi or magnetic field. with be respectively latitude and the longitude of PDR prediction, be respectively latitude, the longitude of the latitude of WiFi positioning result, longitude and magnetic field matching result.I 2 × 2with 0 2 × 3representation unit matrix and null matrix respectively, subscript represents its dimension.
Kalman prediction process equation is as follows:
δx k + 1 - = Φ k + 1 , k δx k P k + 1 - = Φ k + 1 , k P k Φ k + 1 , k T + Γ k Q k Γ k T - - - ( 11 )
Measurement equation is as follows:
K k + 1 = P k + 1 - H k + 1 T [ H k + 1 P k + 1 - H k + 1 T + R k + 1 ] - 1 δx k + 1 = δx k + 1 - + K k + 1 [ z k + 1 - H k + 1 δx k + 1 - ] P k + 1 = [ I - K k + 1 H k + 1 ] P k + 1 - - - - ( 12 )
In formula (10) ~ (11), P is the covariance matrix of state vector δ x to be estimated, and K is Kalman filtering gain matrix, Q and R represents state-noise battle array and measurement noise battle array respectively.Subscript k and k+1 represents moment t kand t k+1, subscript "-" represents that corresponding entry is predicted value.
For effect of the present invention is described, below rating test of the present invention and result will be provided
Test device therefor is Samsung GalaxyS3 and S4 mobile phone, and wherein S3 mobile phone is used for database mapping, and S4 is used for positioning experiment.Experimental Area area is 140m × 60m, and its map and database mapping track are shown in Fig. 3.Assignment test track is shown in Fig. 6.The superiority of single indoor positioning technologies and combination thereof is compared for embodying navigator fix performance of the present invention, magnetic field coupling integrated positioning (scheme 5) that the present embodiment tests WiFi location (scheme 1) respectively, location (scheme 2) is mated in magnetic field, WiFi positioning result is auxiliary coupling location, magnetic field (scheme 3), PDR/WiFi integrated positioning (scheme 4), PDR/WiFi are assisted, and the integrated positioning (scheme 6) of PDR/WiFi/ magnetic field of the present invention coupling.In addition, in order to improve the cogency of test, the present embodiment test four kinds of typical mobile phones dynamically under indoor positioning performance.These four kinds are dynamically respectively: hand-heldly to hold level with both hands, make a phone call, hand heldly to swing conveniently, be placed on trouser pocket.Fig. 7-12 illustrates hand-held positioning result of holding level with both hands representatively.Wherein every width figure comprises three subgraphs, and left side subgraph is positioning track, and middle subgraph is positioning error figure, and right side subgraph is the Cumulative Distribution Function of positioning error.
For convenience of contrast, the statistical value (the error burst value at maximal value Max, root mean square RMS and 80% error place) of each scheme positioning error is listed in table 1.
Table 1. each scheme positioning error statistical value (unit: rice)
Visible, the inventive method four kinds survey pedestrian dynamically in the RMS value of positioning error be all less than 3.5m, be better than scheme 1 ~ 5.Its main cause is the complementarity utilizing each location technology, detects and eliminates most error hiding.The present invention only relies on built-in sensors and existing WiFi in consumer electronics product, and makes full use of environmental magnetic field information, can provide continuously indoor positioning result reliably, the development that can effectively promote indoor location to serve.

Claims (10)

  1. The magnetic field matching locating method that 1.WiFi fingerprint recognition is auxiliary, is characterized in that, comprise step:
    S1 is along the mapping track image data of planning, the database of WiFi fingerprint and magnetic field fingerprint is built in conjunction with position when data and data acquisition, described data comprise WiFi data and magnetic field data, WiFi data comprise WiFi signal intensity and mac address, and magnetic field data comprises the data of gyro, accelerometer and magnetometer;
    S2 adopts WiFi fingerprint recognition method to treat anchor point and positions, and obtains the WiFi positioning result in site undetermined;
    S3 determines match search region, magnetic field based on WiFi positioning result, treats anchor point and carry out magnetic field coupling in match search region, magnetic field, obtains the magnetic field coupling positioning result in site undetermined; Match search region, magnetic field is that radius of circle or rotational symmetry polygonal side length are empirical value with WiFi positioning result be the center of circle or center circle or rotational symmetry polygon.
  2. 2. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 1 is auxiliary, is characterized in that:
    S1 comprises further:
    1.1 according to target area map planning mapping track, and obtain mapping track key node position, described key node comprises starting point, terminal, intersection node and the node that turns round;
    1.2 gather WiFi data and magnetic field data along mapping track;
    The WiFi data of 1.3WiFi reference point and position form WiFi fingerprint, the magnetic field data of magnetic field reference point and formation magnetic field, position fingerprint; The step point in WiFi reference point and WiFi Data Update moment, by the interpolated point preset interpolation distance interpolation and obtain between magnetic field reference point and step point and adjacent step point;
    The database of 1.4 structure WiFi fingerprints and magnetic field fingerprint.
  3. 3. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 2 is auxiliary, is characterized in that:
    Step point position is adopted and is obtained with the following method:
    According to adjacent two key node positions and this adjacent crucial two internodal step numbers on mapping track, obtain each step point position on mapping track through interpolation.
  4. 4. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 1 is auxiliary, is characterized in that:
    Described magnetic field fingerprint comprises the magnetic field vector m obtained according to magnetic field data k=[BB db h], wherein, B=|B| is total magnetic intensity, and B is three axle output vectors of magnetometer; B dand B hbe respectively vertical component and the horizontal component of magnetic field intensity.
  5. 5. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 1 is auxiliary, is characterized in that:
    WiFi fingerprint recognition method described in S2 is the WiFi fingerprint recognition method based on k neighbor point, is specially:
    The WiFi signal intensity at WiFi reference point place each in the WiFi signal intensity of site undetermined and database is compared, find k the WiFi reference point nearest with the signal intensity in site undetermined, using the weighted mean value of this k WiFi reference point locations as site location undetermined, weights are the signal intensity distance of site undetermined and each WiFi reference point.
  6. 6. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 1 is auxiliary, is characterized in that:
    In S3, described radius of a circle or the polygonal length of side of rotational symmetry are set to ε σ wifi, ε is the natural number artificially set according to actual conditions, σ wififor WiFi positioning precision;
    Described WiFi positioning precision obtains according to WiFi positioning result statistics, is specially:
    Series of points is chosen in indoor, the WiFi positioning result of each point and the WiFi positioning error of coordinate true value and each point, the standard deviation of the WiFi positioning error of this series of points and WiFi positioning precision.
  7. 7. the magnetic field matching locating method that WiFi fingerprint recognition as claimed in claim 1 is auxiliary, is characterized in that:
    Treating anchor point carry out magnetic field coupling in match search region, magnetic field described in S3, comprises further:
    3.1 magnetic field datas walking magnetic field reference point locations in step and correspondence according to the nearest N1 in site undetermined form the magnetic field fingerprint in site undetermined, and N1 rule of thumb and requirements set;
    Magnetic field, site undetermined fingerprint mates with the database magnetic field fingerprint in match search region, magnetic field by 3.2, finds the k minimum with magnetic field, site undetermined fingerprint difference according to magnetic field, storehouse fingerprint;
    3.3 with the magnetic field fingerprint difference of site undetermined magnetic field fingerprint and database magnetic field fingerprint for weights, k is asked weighted mean value according to magnetic field reference point locations in the fingerprint of magnetic field, storehouse, namely obtains the Magnetic oriented result in site undetermined.
  8. 8., based on an indoor navigation method for micro-electro-mechanical sensors, WiFi location, magnetic field coupling, it is characterized in that, comprise step:
    S1 is along the mapping track image data of planning, the database of WiFi fingerprint and magnetic field fingerprint is built in conjunction with position when data and data acquisition, described data comprise WiFi data and magnetic field data, WiFi data comprise WiFi signal intensity and mac address, and magnetic field data comprises the data of gyro, accelerometer and magnetometer;
    S2 adopts WiFi fingerprint recognition method to treat anchor point and positions, and obtains the WiFi positioning result in site undetermined;
    S3 determines match search region, magnetic field based on WiFi positioning result, treats anchor point and carry out magnetic field coupling in match search region, magnetic field, obtains the magnetic field coupling positioning result in site undetermined; Wherein, match search region, magnetic field is that radius of circle or rotational symmetry polygonal side length are empirical value with WiFi positioning result be the center of circle or center circle or rotational symmetry polygon;
    S4, with PDR error equation structure Kalman filtering state equation, with WiFi positioning result and magnetic field coupling positioning result structure measurement equation, adopts Kalman filtering method to carry out integrated navigation.
  9. 9., as claimed in claim 1 based on the indoor navigation method of micro-electro-mechanical sensors, WiFi location, magnetic field coupling, it is characterized in that:
    S4 comprises further:
    4.1 utilize PDR positioning result to detect the error hiding of WiFi positioning result and magnetic field coupling positioning result, if WiFi positioning result and magnetic field coupling positioning result are error hiding, with PDR positioning result for integrated navigation result; Otherwise, perform step 4.2;
    4.2 with PDR error equation structure Kalman filtering state equation, with WiFi positioning result and magnetic field coupling positioning result structure measurement equation, adopts Kalman filtering method to merge WiFi positioning result, magnetic field coupling positioning result and PDR positioning result.
  10. 10., as claimed in claim 1 based on the indoor navigation method of micro-electro-mechanical sensors, WiFi location, magnetic field coupling, it is characterized in that:
    In sub-step 4.1, if the distance of WiFi positioning result and PDR positioning result is less than threshold value Th d_PDR, then this WiFi positioning result is error hiding; If the distance of magnetic field coupling positioning result and PDR positioning result is less than threshold value Th d_PDR, then coupling positioning result in this magnetic field is error hiding; Th d_PDRwith radius or the length of side in match search region, magnetic field.
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