CN109951798A - Merge the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth - Google Patents
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Abstract
The invention discloses a kind of enhancing location fingerprint indoor orientation methods for merging Wi-Fi and bluetooth, the present invention incorporates Wi-Fi and bluetooth both of which and carries out indoor positioning using signal strength instruction RSSI location fingerprint, the mapping relations of received signal strength and space physics position are only needed to position, it can be effectively reduced positioning system cost, and the robustness of multipath effect under complex environment greatly improved；The RSSI vector value for receiving respectively corresponding test position to several access points AP node apparatus preset from environment to be measured corrects RSSI dynamic state of parameters, nearest neighbour method is weighted using k, the result that location fingerprint method can be made to obtain is farthest close to physical location, to improve positioning accuracy.The present invention has given full play to the advantage of bimodulus positioning using the decision level fusion of Wi-Fi and bluetooth, and can effectively promote indoor position accuracy in the case where adaptive most of complex.
Description
Technical field
The present invention relates to a kind of enhancing location fingerprint indoor orientation methods for merging Wi-Fi and bluetooth, belong to wireless location
Technical field.
Background technique
Positioning under indoor environment is always the field that many problems are not solved.Due to signal deep fades and
Multipath effect, general outdoor positioning facility (such as GPS) can not effectively work in building, meanwhile, accurate positioning
Property is also a problem.The infrastructure that we can build complete set indoors is used to position, but needs so very big
Cost, the frequency spectrum resource occupied including positioning signal, insertion in a mobile device additional hard for perceptual positioning signal
Part, the anchor node for being used to send positioning signal for being mounted on fixed position.In this case, present Wi-Fi and bluetooth be all
It is popularized on a large scale, all there is Wi-Fi and bluetooth under most of indoor environment, therefore positioned using Wi-Fi and bluetooth
It is the method for saving very much cost without additionally disposing hardware device.However Wi-Fi and bluetooth are not exclusively for positioning
And design, traditional localization method based on time and angle is not particularly suited for them, and position precision is also not high enough.It is based on
The positioning of RSSI is the localization method studied and be most widely used at present, and location base is according to mobile terminal wireless signal
Monitor the RSSI information with scanning for beacon base station.Such as in wlan network, mobile terminal Wi-Fi module by active scan or
The signal from each AP in the user terminal range of receiving is passively listened, AP is identified according to MAC Address and SSID, and collect note
Record its received signal strength indication.These data combination Given informations are handled by analysis to estimate the position of mobile terminal.And
Field of locating technology, improving indoor position accuracy based on a variety of location technologies fusion position fingerprint algorithm is reasonable.
If a mobile device can receive the signal from multiple emission sources, or fixed multiple base stations can perceive it is same
A mobile device, then we, which can also use, forms a RSSI from the RSSI of multiple emission sources or multiple receivers
Vector, as the fingerprint being associated with position.It (may be successively to survey that most of network interface cards, which can measure the RSSI from a variety of AP,
Amount).Now in most of indoor scenes, mobile device usually can detecte a variety of AP, therefore using from a variety of AP's
RSSI is meaningful as location fingerprint, has such as merged the bimodulus fusion positioning of bluetooth sensing network and Wi-Fi sensing network
Algorithm.
In current multimodality fusion location technology, Gonz á lez J et al. is fixed by GPS and two kinds of UWB using Bayesian inference
Position technology, which is merged and is applied on data level, is continuously tracked positioning, allows users to carry out with outdoor indoors flat
Sliding cutting changes, i.e. outdoor application GPS is positioned, indoor then positioned using UWB, while in order to improve precision, also using
Particle filter carries out likelihood solution.But the above method has a defect: bandwidth shared by UWB is very big, is unfavorable for for indoor positioning
Otherwise any wide-area deployment AP is easy to interfere other indoor wireless devices, therefore orientation range has comparable limitation；
Xu Congfu et al. is proposed is merged the positioning result of multiple sensors using D-S evidence theory in decision level, but and
Bayes method equally has independence assumption, is not easy to meet in practical applications, while computation complexity is too high, with number
According to the increase of amount, computation complexity can exponentially increase, and there is no too solid theoretical basis for D-S composite formula；King
Farsighted et al. proposition is merged the positioning result of bluetooth and Wi-Fi using fingerprint algorithm in decision level, and carries out grid conjunction
And but its when using Euclidean distance as similarity, used the special circumstances of k nearest neighbour method, i.e. k=1, positioning result exists
Certain particularity, application scenarios are more concerned with real-time, and effect is general in terms of positioning accuracy.
Summary of the invention
Goal of the invention: in order to overcome the deficiencies in the prior art, the present invention provides a kind of fusion Wi-Fi and bluetooth
Enhance location fingerprint indoor orientation method, the present invention is incorporated Wi-Fi and bluetooth both of which and indicated using signal strength
(Received Signal Strength Indicator, RSSI) location fingerprint carries out indoor positioning, it is only necessary to receive signal
The mapping relations of intensity and space physics position position, and without additionally increasing special hardware, can be effectively reduced positioning system
System cost, and the robustness of multipath effect under complex environment is greatly improved；In view of identical propagation distance and identical hair
It penetrates under signal strength, the received signal strength that may be measured has larger difference, or even several times of difference, therefore to pre- from environment to be measured
If several AP node apparatus receive the RSSI vector value of respectively corresponding test position and carry out the amendment of RSSI dynamic state of parameters, one
Determine to eliminate influence of the environmental factor for positioning accuracy in degree；The tested point position observed in view of different access points
There are different errors, under normal circumstances, the closer position with the physical location of access point, to the contribution journey of positioning accuracy
Degree is bigger, and weight factor is also bigger, therefore k is used to weight nearest neighbour method, and the result that location fingerprint method can be made to obtain is maximum
Degree close to physical location, to improve positioning accuracy.This method is given full play to using the decision level fusion of Wi-Fi and bluetooth
The advantage of bimodulus positioning, and indoor position accuracy can be effectively promoted in the case where adaptive most of complex.
Technical solution: to achieve the above object, the technical solution adopted by the present invention are as follows: a kind of fusion Wi-Fi and bluetooth
Enhance location fingerprint indoor orientation method, specifically includes the following steps:
Step 1): when carrying out indoor objects positioning using fingerprint identification method, need to dispose the fixed Wi-Fi in a small amount of position
With Bluetooth AP node apparatus, receiving node receives RSSI vector using the multiple AP signal strengths building received.But due to existing
It has all been deployed with corresponding AP node in the widely available of Wi-Fi and bluetooth, many places buildings, therefore has not been needed dedicated
Hardware module.
Step 2): acquisition and processing of the single mode location fingerprint method based on signal characteristic, be divided into the off-line data collecting stage and
The online position estimation stage.Due in the present invention, using the acquisition of the data of Wi-Fi sensing network and bluetooth sensing network and
Position estimation process is consistent.
For convenience of description, the RSSI vector that receiving node observes is expressed asWherein, t=
1,2, t=1, indicate Wi-Fi network, t=2 indicates blueteeth network,It is i-thtBeaconing nodes transmitting, receiving node receive
RSSI value, PtFor beaconing nodes sum in network t, the fingerprint base that training obtains is expressed asWherein 1
≤jt≤Rt, RtIt is total for fingerprint base vector in network t, it is each in fingerprint baseCorresponding position is all known.
Step 3): in view of under identical propagation distance and identical transmitting signal strength, the reception signal that may be measured is strong
Degree has larger difference, or even several times of difference, and the RSSI vector that exclusive use receiving node receives in practice may be by environment
Influence reduces precision, therefore is modified using RSSI dynamic corrections parameter Estimation mode to RSSI vector, to improve positioning
Precision.
Sensing network (Wi-Fi sensing network and bluetooth sensing network) is set in this scene PtA AP node, is expressed asWherein Pt≥3；Equipped with mtA reference point,
Wherein mt≥1；There is ntThe set of a APWherein 3≤nt≤Pt, AKt∈At；This nt
A AP forms a network area Ot, find a reference point RPt0, this reference point to this ntThe distance and H of a nodetIt is most short,
Specific method for solving is as follows:
If RPt0It receives this momentSignal strength indication be To RPt0Distance beAt this time altogether
There is ntIt is rightCombination, the formula for calculating signal strength distance loss are as follows:
Wherein, in ntIt is rightIn combination, b is takentGroup is as (the d in formula (2)t0, RSSIt0), dt0For ginseng
Examine distance；RSSIt0Be distance be dt0When the signal strength that receives；dtIt is true measurement distance；RSSItBe distance be dtWhen connect
The signal strength received；It is environmental factor, ηtIt is path loss index；It is the constant between 2.0~3.3, and is built
The property for building object is related:
Remaining nt- 1 group is used as (dt, RSSIt) be brought into (2) formula, obtain equation:
This ntA environmental factorReflect network area OtAmbient conditions, network is obtained using average weighted mode
Region OtEnvironmental factor this moment
Step 4): in a certain position received signal intensity s in spacetWith the position l where ittThere are certain mapping passes
System, the mapping relations indicate as follows:
lt=f (st) (8)
Wherein, ltFor 2D coordinate (xt, yt)。
Use above-mentioned steps 3 in the off-line data collecting stage based on the mapping relations) method, each seat in space
Punctuate acquires multiple AP signal data, the environmental factor that will be acquired every timeWith path loss index ηt, reference distance dt0, practical
Distance dt, reference signal value RSSIt0, real signal value RSSItSubstitution formula (2) obtains multiple RSSI vectors, is expressed asIt averages respectively to each component of all RSSI vectors of each coordinate points, it is obtained flat
Equal RSSI vector value can be as the characteristic value of the pointThat is:
Wherein,ForKthtA component,ForKthtA component and 1≤k of satisfactiont≤Pt, ntFor the coordinate
The RSSI vector sum of point acquisition；Each coordinate obtains such feature vector in this way in scene, and all coordinates
Feature vector just constitutes fingerprint baseTo establish the mapping relations in formula (8).
Step 5): it will be received in the online position estimation stage when some position that receiving node is positioned in the space
From PtThe signal of a AP, signal strength equally use above-mentioned steps 3) method handled, constitute RSSI vectorRSSI fingerprint as real-time measurement；It goes to measure with Euclidean distance algorithm at this timeWithInBetween similarity, target position is estimated with this；Euclidean distance formula is as follows:
Wherein,For the RSSI fingerprint of real-time measurement,It is the RSSI fingerprint in fingerprint base, it willWithSubstitute into above formula
(10), the position at this time can be obtainedWithEuclidean distance Lt, asWithSimilarity.
Step 6): in view of different AP nodes is observed obtaining tested point position, there are different errors, under normal circumstances,
The closer position with the physical location of access point, bigger to the percentage contribution of positioning accuracy, weight factor is also bigger.
Therefore k weighting nearest neighbour method, in all similarity positions that step 5) obtains, k before choosing is used in the present inventiontA similarity is most
High position, by this preceding ktThe corresponding reference fingerprint in a positionSubstitute into the position location that WKNN formula can be estimatedThat is:
In formula, ε is that prevent divisor be zero, d to the normal number of very littlegReal time fingerprint and reference fingerprint when for mobile target it
Between distance,For the preceding k of estimationtA position location.
Step 7): the positioning result (x obtained according to step 6)t, yt), then the fusion of decision level is carried out according to the following formula:
Wherein, t1=2；whIt is the weight of h class network AP and meets ∑ wh=1, the last fused positioning result of bimodulus
For L=(X, Y).Due to having only used the AP node of two kinds of sensing networks of Wi-Fi and bluetooth in this method, therefore take n=2；Experiment
It has been shown that, when the weight of bluetooth is slightly above the weight of Wi-Fi, position error is weighed compared to Wi-Fi weight and bluetooth weight etc.
Situation is smaller, therefore in the present invention, the weight of Wi-Fi takes w1=0.4, the weight of bluetooth takes w2=0.6, finally obtain its positioning
As a result L (X, Y).
The present invention compared with prior art, has the advantages that
First, the present invention connects AP node apparatus on the basis of existing single mode indoor positioning and multimode indoor positioning
The RSSI vector value for receiving respectively corresponding test position carries out the amendment of RSSI dynamic state of parameters, makes environmental factor to the shadow of positioning accuracy
Sound substantially reduces, and weights nearest neighbour method using k in the comparison of the similarity of location fingerprint, and location fingerprint method can be made to obtain
As a result farthest close to physical location, to improve positioning accuracy.
Second, since the present invention is based on the methods of Wi-Fi and the fusion of bluetooth sensing network bimodulus, solve single mode positioning
Limitation, and relative to the indifference fusion carried out on data level, the fusion of decision level can give full play to bimodulus positioning
Advantage.
Third benefits from widely available, this hair of Wi-Fi and bluetooth since the present invention is based on Indoor Position Techniques Based on Location Fingerprint
It is bright not need dedicated hardware module, existing facility can be made full use of, have no need to change the hardware of mobile device, system without
Few extras are needed or only increase, upgrading and maintenance are smaller to customer impact.
Specific embodiment
Combined with specific embodiments below, the present invention is furture elucidated, it should be understood that these examples be merely to illustrate the present invention and
It is not used in and limits the scope of the invention, after the present invention has been read, those skilled in the art are to various shapes of equal value of the invention
The modification of formula falls within the application range as defined in the appended claims.
A kind of enhancing location fingerprint indoor orientation method merging Wi-Fi and bluetooth, specifically includes the following steps:
Step 1): when carrying out indoor objects positioning using fingerprint identification method, need to dispose the fixed Wi-Fi in a small amount of position
With Bluetooth AP node apparatus, receiving node receives RSSI vector using the multiple AP signal strengths building received.But due to existing
It has all been deployed with corresponding AP node in the widely available of Wi-Fi and bluetooth, many places buildings, therefore has not been needed dedicated
Hardware module.
Step 2): acquisition and processing of the single mode location fingerprint method based on signal characteristic, be divided into the off-line data collecting stage and
The online position estimation stage.Due in the present invention, using the acquisition of the data of Wi-Fi sensing network and bluetooth sensing network and
Position estimation process is consistent.
For convenience of description, the RSSI vector that receiving node observes is expressed asWherein, t=
1,2, t=1, indicate Wi-Fi network, t=2 indicates blueteeth network,It is i-thtBeaconing nodes transmitting, receiving node receive
RSSI value, PtFor beaconing nodes sum in network t, the fingerprint base that training obtains is expressed asWherein 1
≤jt≤Rt, RtIt is total for fingerprint base vector in network t, it is each in fingerprint baseCorresponding position is all known.
Step 3): in view of under identical propagation distance and identical transmitting signal strength, the reception signal that may be measured is strong
Degree has larger difference, or even several times of difference, and the RSSI vector that exclusive use receiving node receives in practice may be by environment
Influence reduces precision, therefore is modified using RSSI dynamic corrections parameter Estimation mode to RSSI vector, to improve positioning
Precision.
Sensing network (Wi-Fi sensing network and bluetooth sensing network) is set in this scene PtA AP node, is expressed asWherein Pt≥3；Equipped with mtA reference point,
Wherein mt≥1；There is ntThe set of a APWherein 3≤nt≤Pt, AKt∈At；This nt
A AP forms a network area Ot, find a reference point RPt0, this reference point to this ntThe distance and H of a nodetIt is most short,
Specific method for solving is as follows:
If RPt0It receives this momentSignal strength indication be To RPt0Distance beAt this time altogether
There is ntIt is rightCombination, the formula for calculating signal strength distance loss are as follows:
Wherein, in ntIt is rightIn combination, b is takentGroup is as (the d in formula (2)t0, RSSIt0), dt0For ginseng
Examine distance；RSSIt0Be distance be dt0When the signal strength that receives；dtIt is true measurement distance；RSSItBe distance be dtWhen connect
The signal strength received；It is environmental factor, ηtIt is path loss index；It is the constant between 2.0~3.3, with building
The property of object is related:
Remaining nt- 1 group is used as (dt, RSSIt) be brought into (2) formula, obtain equation:
This ntA environmental factorReflect network area OtAmbient conditions, network is obtained using average weighted mode
Region OtEnvironmental factor this moment
Step 4): in a certain position received signal intensity s in spacetWith the position l where ittThere are certain mapping passes
System, the mapping relations indicate as follows:
lt=f (st) (8)
Wherein, ltFor 2D coordinate (xt, yt)。
Use above-mentioned steps 3 in the off-line data collecting stage based on the mapping relations) method, each seat in space
Punctuate acquires multiple AP signal data, the environmental factor that will be acquired every timeWith path loss index ηt, reference distance dt0, practical
Distance dt, reference signal value RSSIt0, real signal value RSSItSubstitution formula (2) obtains multiple RSSI vectors, is expressed asIt averages respectively to each component of all RSSI vectors of each coordinate points, it is obtained flat
Equal RSSI vector value can be as the characteristic value of the pointThat is:
Wherein,ForKthtA component,ForKthtA component and 1≤k of satisfactiont≤Pt, ntFor the coordinate
The RSSI vector sum of point acquisition；Each coordinate obtains such feature vector in this way in scene, and all coordinates
Feature vector just constitutes fingerprint baseTo establish the mapping relations in formula (8).
Step 5): it will be received in the online position estimation stage when some position that receiving node is positioned in the space
From PtThe signal of a AP, signal strength equally use above-mentioned steps 3) method handled, constitute RSSI vectorRSSI fingerprint as real-time measurement；It goes to measure with Euclidean distance algorithm at this timeWithInBetween similarity, target position is estimated with this；Euclidean distance formula is as follows:
Wherein,For the RSSI fingerprint of real-time measurement,It is the RSSI fingerprint in fingerprint base, it willWithSubstitute into above formula
(10), the position at this time can be obtainedWithEuclidean distance Lt, asWithSimilarity.
Step 6): in view of different AP nodes is observed obtaining tested point position, there are different errors, under normal circumstances,
The closer position with the physical location of access point, bigger to the percentage contribution of positioning accuracy, weight factor is also bigger.
Therefore k weighting nearest neighbour method, in all similarity positions that step 5) obtains, k before choosing is used in the present inventiontA similarity is most
High position, by this preceding ktThe corresponding reference fingerprint in a positionSubstitute into the position location that WKNN formula can be estimatedThat is:
In formula, ε is that prevent divisor be zero, d to the normal number of very littlegReal time fingerprint and reference fingerprint when for mobile target it
Between distance,For the preceding k of estimationtA position location.
Step 7): the positioning result (x obtained according to step 6)t, yt), then the fusion of decision level is carried out according to the following formula:
Wherein, t1=2；whIt is the weight of h class network AP and meets ∑ wh=1, the last fused positioning result of bimodulus
For L=(X, Y).Due to having only used the AP node of two kinds of sensing networks of Wi-Fi and bluetooth in this method, therefore take n=2；Experiment
It has been shown that, when the weight of bluetooth is slightly above the weight of Wi-Fi, position error is weighed compared to Wi-Fi weight and bluetooth weight etc.
Situation is smaller, therefore in the present invention, the weight of Wi-Fi takes w1=0.4, the weight of bluetooth takes w2=0.6, finally obtain its positioning
As a result L (X, Y).
The off-line data collecting stage, each coordinate points acquired the signal of multiple AP in space in step 4) of the present invention
Data (RSSI vector value) are obtained by RSSI dynamic state of parameters correcting mode.
Physical location fingerprint and the highest preceding k position of reference position fingerprint similarity are made in step 7) of the present invention
Nearest neighbour method is weighted with k, obtains the positioning result of such AP.
It is indoor fixed using signal strength instruction RSSI location fingerprint progress that the present invention incorporates Wi-Fi and bluetooth both of which
Position, it is only necessary to the mapping relations of received signal strength and space physics position position, and can be effectively reduced positioning system cost,
And the robustness of multipath effect under complex environment is greatly improved；To several access points preset from environment to be measured
The RSSI vector value that AP node apparatus receives respectively corresponding test position corrects RSSI dynamic state of parameters, weights neighbour using k
Method, the result that location fingerprint method can be made to obtain is farthest close to physical location, to improve positioning accuracy.The present invention
The advantage of bimodulus positioning is given full play to using the decision level fusion of Wi-Fi and bluetooth, and can be in adaptive most of complexity
Indoor position accuracy is effectively promoted in the case where environment.
The above is only a preferred embodiment of the present invention, it should be pointed out that: for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (6)
1. a kind of enhancing location fingerprint indoor orientation method for merging Wi-Fi and bluetooth, which comprises the following steps:
Step 1): deployment Wi-Fi and Bluetooth AP node, receiving node are received using the multiple AP signal strengths building received
RSSI vector；
Step 2): the RSSI vector that receiving node observes is expressed asWherein, t=1,2, t=
1, indicate Wi-Fi network, t=2 indicates blueteeth network,It is i-thtThe RSSI that beaconing nodes transmitting, receiving node receive
Value, PtFor beaconing nodes sum in network t, the fingerprint base that training obtains is expressed asWherein 1≤jt≤
Rt, RtIt is total for fingerprint base vector in network t, it is each in fingerprint baseCorresponding position is all known；
Step 3): being modified RSSI vector using RSSI dynamic corrections parameter Estimation mode, to improve the precision of positioning；
There is P in sensing networktA AP node, is expressed asWherein Pt≥3；There is mtA ginseng
Examination point,Wherein mt≥1；There is ntThe set of a APWherein 3≤nt≤Pt, AKt∈At；This ntA AP forms a network area Ot,
Find a reference point RPt0, this reference point to this ntThe distance and H of a nodetMost short, specific method for solving is as follows:
If RPt0It receives this momentSignal strength indication beTo RPt0Distance beN is shared at this timetIt is rightCombination, the formula for calculating signal strength distance loss are as follows:
Wherein, in ntIt is rightIn combination, b is takentGroup is as (the d in formula (2)t0,RSSIt0), dt0For with reference to away from
From；RSSIt0Be distance be dt0When the signal strength that receives；dtIt is true measurement distance；RSSItBe distance be dtWhen receive
Signal strength；ζtIt is environmental factor, ηtIt is path loss index；
Remaining ηt- 1 group is used as (dt,RSSIt) be brought into (2) formula, obtain equation:
This ntA environmental factorReflect network area OtAmbient conditions, network area is obtained using average weighted mode
OtEnvironmental factor this moment
Step 4): in a certain position received signal intensity s in spacetWith the position l where ittThere are certain mapping relations, should
Mapping relations indicate as follows:
lt=f (st) (8)
Wherein, ltFor 2D coordinate (xt,yt)；
Use above-mentioned steps 3 in the off-line data collecting stage based on the mapping relations) method, each coordinate points in space
Acquire multiple AP signal data, the environmental factor that will be acquired every timeWith path loss index ηt, reference distance dt0, actual range
dt, reference signal value RSSIt0, real signal value RSSItSubstitution formula (2) obtains multiple RSSI vectors, is expressed asIt averages respectively to each component of all RSSI vectors of each coordinate points, it is obtained flat
Equal RSSI vector value can be as the characteristic value of the pointThat is:
Wherein,ForKthtA component,ForKthtA component and 1≤k of satisfactiont≤Pt, ntIt is adopted for the coordinate points
The RSSI vector sum of collection；Each coordinate obtains such feature vector in this way in scene, and the feature of all coordinates
Vector just constitutes fingerprint baseTo establish the mapping relations in formula (8)；
Step 5): the online position estimation stage will receive when some position that receiving node is positioned in the space from Pt
The signal of a AP, signal strength equally use above-mentioned steps 3) method handled, constitute RSSI vectorRSSI fingerprint as real-time measurement；It goes to measure with Euclidean distance algorithm at this timeWithInBetween similarity, target position is estimated with this；Euclidean distance formula is as follows:
Wherein,For the RSSI fingerprint of real-time measurement,It is the RSSI fingerprint in fingerprint base, it willWithIt substitutes into above formula (10),
The position at this time can be obtainedWithEuclidean distance Lt, asWithSimilarity；
Step 6): in view of different AP nodes observes obtaining tested point position, there are different errors, and k is used to weight neighbour
Method, in all similarity positions that step 5) obtains, k before choosingtA highest position of similarity, by this preceding ktA position pair
The reference fingerprint answeredSubstitute into the position location that WKNN formula can be estimatedThat is:
In formula, ε is that prevent divisor be zero, d to the normal number of very littlegTo move real time fingerprint when target and between reference fingerprint
Distance,For the preceding k of estimationtA position location；
Step 7): the positioning result (x obtained according to step 6)t,yt), then the fusion of decision level is carried out according to the following formula:
Wherein, t1=2；whIt is the weight of h class network AP and meets ∑ wh=1, the last fused positioning result of bimodulus is L
=(X, Y).
2. merging the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth according to claim 1, it is characterised in that:
Path loss index ηtIt is the constant between 2.0~3.3.
3. merging the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth according to claim 2, it is characterised in that:
Path loss index ηt:
4. merging the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth according to claim 3, it is characterised in that:
When the weight of bluetooth is slightly above the weight of Wi-Fi, position error weighs situation more compared to Wi-Fi weight and bluetooth weight
It is small.
5. merging the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth according to claim 4, it is characterised in that:
The weight w of Wi-Fi1=0.4.
6. merging the enhancing location fingerprint indoor orientation method of Wi-Fi and bluetooth according to claim 5, it is characterised in that:
The weight w of bluetooth2=0.6.
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| CN110320495A (en) * | 2019-08-01 | 2019-10-11 | 桂林电子科技大学 | A kind of indoor orientation method based on Wi-Fi, bluetooth and PDR fusion positioning |
| CN110536235A (en) * | 2019-08-30 | 2019-12-03 | 哈尔滨工程大学 | A kind of indoor orientation method based on location fingerprint screening |
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| CN111079787A (en) * | 2019-11-15 | 2020-04-28 | 上海航天控制技术研究所 | Position fingerprint identification method |
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| CN113259883A (en) * | 2021-05-18 | 2021-08-13 | 南京邮电大学 | Multi-source information fusion indoor positioning method for mobile phone user |
| CN113271542A (en) * | 2021-04-08 | 2021-08-17 | 复旦大学 | Indoor mobile terminal positioning method based on Bluetooth and visible light |
| CN114466453A (en) * | 2022-04-08 | 2022-05-10 | 浙江口碑网络技术有限公司 | Positioning method, device, terminal and server |
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| CN113271542A (en) * | 2021-04-08 | 2021-08-17 | 复旦大学 | Indoor mobile terminal positioning method based on Bluetooth and visible light |
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