CN108414970A - Indoor orientation method - Google Patents
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- CN108414970A CN108414970A CN201810195955.5A CN201810195955A CN108414970A CN 108414970 A CN108414970 A CN 108414970A CN 201810195955 A CN201810195955 A CN 201810195955A CN 108414970 A CN108414970 A CN 108414970A
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Classifications
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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
- G01S5/0278—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 involving statistical or probabilistic considerations
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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
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
Abstract
The invention discloses a kind of indoor orientation method, the method includes：Wi Fi access point received signal strength reference datas are obtained, reference database is built after default calculation process is carried out to it；In point to be determined PiPlace measures the received signal strength from Wi Fi access points, and carries out default calculation process, the distance between received signal strength data and reference data after calculation processing；The corresponding reference point coordinate information of K distance value is chosen according to the sequence of distance value from small to large to be used as with reference to coordinate, is estimated to obtain the location information of the point to be determined according to the reference coordinate.The present invention is unrelated with AP quantity the time required to completing positioning, and is in non-linear relation with reference data quantity, the time required to effectively reducing positioning.Meanwhile the present invention solves the problems, such as that conventional mapping methods need to manually set K values, can be adaptively calculated out suitable K values, therefore effectively increase the positioning accuracy and location efficiency of the indoor positioning technologies based on Wi Fi.
Description
Technical field
The present invention relates to field of locating technology, especially a kind of indoor orientation method.
Background technology
In recent years, with the development of wireless communication technique and the continuous enhancing of mobile terminal device performance, user is to base
It is higher and higher in the demand of location-based service (Location Based Service, LBS).GPS system, Russia including the U.S.
GLONASS systems, China the Big Dipper, Europe Galileo including the global positioning system based on satellite-signal have been able to
Meet requirement of the user to outdoor positioning, and positioning accuracy is also further increasing.But since indoor environment is intricate, and
And satellite-signal cannot penetrate building walls, also lacking at present can widely applied, more mature, the higher interior of precision
Location technology.Therefore, the concern with everybody to indoor positioning technologies, the research of indoor positioning technologies increasingly become current and grind
Study carefully hot spot.
Existing indoor positioning technologies include mainly bluetooth (Bluetooth) technology, infrared ray (Infrared) technology, surpass
Broadband (Ultra Wide Band, UWB) technology, RFID technique, Zig-Bee technologies, ultrasonic technology and Wi-Fi technology etc..
In above-mentioned indoor positioning technologies, equipment volume needed for Bluetooth technology is small, but its stability in complex environment is poor, and bluetooth is believed
Number transmission range is short；Infrared technology needs visual between target to be positioned between detector, this is in complicated indoor environment
In be not achievable；Super-broadband tech needs new addition blind node and power consumption is higher；RFID technique positioning accuracy is high, but it is anti-
Interference performance is poor.Meanwhile in addition to Wi-Fi technology, remaining indoor positioning technologies is in existing public place without more
Perfect suitable infrastructure, and establish these infrastructure and be also required to a large amount of time and economic input.As network is logical
The demand that the development of letter technology and people promote wireless communication speeds has effectively pushed the universal of wireless network, Wi-
Fi access points (Access Point, AP) are also widely deployed, and Wi-Fi signal can almost make in building any position
With.The advantage that this allows for the indoor positioning technologies based on Wi-Fi is more and more significant, becomes a weight in indoor positioning technologies
The research field wanted.
Indoor positioning algorithms based on Wi-Fi are broadly divided into based on received signal strength (Received Signal
Strength, RSS) and based on ranging model two major classes, wherein the location algorithm based on ranging model needs in advance to indoor letter
Road environment is estimated, channel model is established, due to the characteristic that indoor environment is complicated and changeable, the indoor positioning based on ranging model
Method can not be applicable in new environment, and (it is strong to receive signal by Received Signal Strength Indication based on RSSI
Degree instruction) fingerprint indoor positioning algorithms there is advantage outstanding because it adapts to more complex indoor environment.Based on RSSI
Fingerprint indoor positioning algorithms be related to two stages：Positioning stage in off-line training step (generating database) and line.Offline
Stage forms fingerprint letter based on the RSSI of AP around received in reference point locations and position corresponding with RSSI
Breath builds RSSI fingerprint databases using the finger print information of reference point；Positioning stage on line measures what point to be determined received
The fingerprint is compared by the RSSI finger print informations from AP around with each finger print data in fingerprint database, obtains fingerprint
The finger print information to match with measurement RSSI in database, to estimate the current location of point to be determined.
Location algorithm based on fingerprint includes mainly：K nearest neighbor methods (K-Nearest Neighbor, KNN) and weighting K are most
Nearest neighbour method (Weight K-Nearest Neighbor, WKNN).The algorithm is calculated relative to other indoor positionings based on Wi-Fi
Method, the complicated rate of calculating is low, and the speed of service is fast, it is easy to accomplish.But due to universal, the Wi-Fi heat in large-scale place of Wi-Fi technology
Point gradually increases, and reaches hundreds of quantity sometimes, the quantity of location reference point can also increase, therefore fingerprint number and heat
The gradual RSSI fingerprint databases that can cause to construct in off-line phase that increase counted out are more and more huger, KNN and WKNN algorithms
Location efficiency can be greatly affected.Simultaneously as WKNN algorithms positioning stage cannot be adaptive acquisition position in real time
Effective K values of point, need manual setting, can not ensure positioning accuracy.Therefore, being badly in need of one kind can solve in Wi-Fi fingerprint numbers
Positioning time can still be shortened when becoming huge according to library, ensure location efficiency, and adaptive acquisition K values, promote positioning accurate
The solution of degree.
Invention content
In order to solve above-mentioned problems of the prior art, the present invention provides a kind of indoor orientation method.
Indoor orientation method of the present invention includes：
Step S1 obtains Wi-Fi access point received signal strength reference datas, and the Wi-Fi access points are received signal
Intensity reference data carry out default calculation process, and strong based on the data structure Wi-Fi access points reception signal obtained after processing
Spend reference database, wherein the default calculation process is for being converted to Wi-Fi access point received signal strength reference datas
The fixed reference data of length；
Step S2, in point to be determined PiPlace measures the received signal strength from Wi-Fi access points；
Step S3, by point to be determined PiThe Wi-Fi access points received signal strength at place carries out default calculation process, is waited for
Position receiver signal strength data；
Step S4 calculates the received signal strength data to be positioned and joins with the Wi-Fi access points received signal strength
Examine the distance between the reference data in database；
Step S5 chooses the corresponding reference point coordinate information conduct of K distance value according to the sequence of distance value from small to large
Reference coordinate is estimated to obtain the location information of the point to be determined according to the reference coordinate.
Optionally, the step S1 further comprises：
N number of reference point is arranged in step S11, and obtains the location information of N number of reference point, wherein N is positive integer；
Step S12 obtains the Wi-Fi access point received signal strengths received at N number of reference point locations；
The Wi-Fi access points received signal strength data is carried out Hash operation processing, as the Wi- by step S13
Fi access point received signal strength reference datas, structure obtain Wi-Fi access point received signal strength reference databases.
Optionally, the default calculation process is Hash operation processing.
Optionally, the Hash operation processing is MD5 calculation process.
Optionally, the Wi-Fi access points received signal strength data is subjected to Hash operation processing in the step S13
The step of include：
Wi-Fi reference point received signal strength datas are converted into First ray, wherein first sequence by step S131
It is classified as ' 01 ' sequence, i.e., by ' 0 ' and ' 1 ' sequence formed；
Step S132, by 512 complementation of length pair of the obtained First rays of step S131, if complementation result is not equal to 448,
One 1 and n 0 is just filled behind the First ray and obtains the second sequence so that 512 complementation of length pair of the second sequence
As a result it is equal to 448；
Step S133, the second sequence length 64bits sequences that step S132 is generated store, and by this 64bits sequence
Row addition obtains third sequence behind the complementation result that step S132 is generated；
Step S134 initializes four link variables：A, B, C, D, the input as first round operation in step S135；
The third sequence that step S133 is generated is grouped processing, using 4 logical functions to each point by step S135
Group carries out 4 wheel logical function operations, and the output of 4 wheel loop computations of previous grouping is as the corresponding 4 wheel loop computation of next grouping
Input, until obtain the last one 4 wheel loop computation of grouping as a result, as Hash operation result.
Optionally, in the step S4, received signal strength data to be positioned and Wi-Fi access points reception signal are strong
The distance between reference data in degree reference database dist can be calculated using following formula：
Wherein, M indicates the corresponding reference data of each reference point in Wi-Fi access point received signal strength reference databases
Relevant access point sum, RSSImjIt indicates in j-th of reference point RPjWhat place received comes from m-th of Wi-Fi access points APm's
Received signal strength reference data, RSSI 'miIt indicates in i-th of reference point RPiWhat place received comes from m-th of Wi-Fi access point
APmReceived signal strength reference data, u indicate distance classification：As u=1, dist indicates manhatton distance；Work as u=2
When, dist indicates Euclidean distance.
Optionally, in the step S5, it is assumed that K reference coordinate is expressed as (xk,yk), k ∈ [1, K] are then described to be positioned
Estimated coordinates (the x of pointi',yi') can be expressed as：
Optionally, in the step S5, it is assumed that K reference coordinate is expressed as (xk,yk), k ∈ [1, K] are then described to be positioned
Estimated coordinates (the x of pointi',yi') can be expressed as：
Wherein, distkFor the Euclidean distance between k-th of reference point and point to be determined, WkFor weighting coefficient.
Main advantages of the present invention are as follows：The method of the present invention is a kind of Wi-Fi indoor orientation methods based on MD5-KNN,
It, which is efficiently solved, works as fingerprint, i.e., when reference data quantity and hot spot quantity increase, reference data database becomes larger and leads
The problem of location efficiency of cause reduces reduces operation time complexity and reference data Database Reference data bulk size
Relevance, improves location efficiency, at the same can also adaptive defining K value really, effectively improve positioning accuracy.
Description of the drawings
Fig. 1 is the flow chart of indoor orientation method according to an embodiment of the present invention；
Fig. 2 (a) is the position error probability density distribution figure of conventional mapping methods；
Fig. 2 (b) is the position error probability density distribution figure of localization method of the present invention；
Fig. 3 is the position error cumulative distribution function contrast schematic diagram of localization method and conventional mapping methods of the present invention；
Fig. 4 is the operation time complexity of localization method and conventional mapping methods of the present invention with the variation of reference data quantity
Trend comparison diagram；
Fig. 5 is the operation time complexity of localization method and conventional mapping methods of the present invention with the variation tendency pair of AP quantity
Than figure.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
Fig. 1 is the flow chart of indoor orientation method according to an embodiment of the present invention, as shown in Figure 1, in the present invention one
In embodiment, the indoor orientation method includes：
Step S1 obtains Wi-Fi access point received signal strength reference datas, and the Wi-Fi access points are received signal
Intensity reference data carry out default calculation process, and strong based on the data structure Wi-Fi access points reception signal obtained after processing
Spend reference database, wherein the default calculation process is for being converted to Wi-Fi access point received signal strength reference datas
The fixed reference data of length；
Wherein, the Wi-Fi access points received signal strength reference data refers to being received at reference point locations
Wi-Fi access point received signal strength datas, wherein reference point is either one or more, Wi-Fi access points
Can be one or more.
In an embodiment of the present invention, the default calculation process is Hash operation processing, for example MD5 algorithms can be used
(Message-Digest Algorithm 5) is realized, MD5 algorithms have irreversibility so that can not from MD5 sequential values
Backstepping goes out the RSSI information of user, to ensure that the location privacy of user.
In this embodiment, the step S1 further comprises the steps：
N number of reference point is arranged in step S11, and obtains the location information of N number of reference point, wherein N is positive integer；
In the step, when reference point is arranged, reference point can be uniformly arranged in measured zone, it can also be according to actually answering
It needs that reference point is arranged.
Wherein, the location information of the reference point can be indicated by its spatial position coordinate, can also be by other positioning
Location information that method obtains indicates.
Step S12 obtains the Wi-Fi access point received signal strengths received at N number of reference point locations；
The Wi-Fi access points received signal strength data is carried out Hash operation processing, as the Wi- by step S13
Fi access point received signal strength reference datas, structure obtain Wi-Fi access point received signal strength reference databases.
The advantage of MD5 algorithms is that arbitrarily long data can be compressed, and generates the MD5 information of 128bit.It connects down
The step is illustrated by taking MD5 calculation process as an example, in this step, the Wi-Fi access points are received into signal first
Intensity data generates the MD5 information of 128bit, then generates the MD5 sequences of 32 bytes, i.e., after MD5 calculation process, Wi-Fi
Every Wi-Fi access point received signal strength data is converted into 32 bytes in access point received signal strength reference database
MD5 sequences.When realizing, Wi-Fi access point received signal strength datas can be first converted into the sequence of ' 01 ' expression, then led to
It crosses data filling, record message length, be packed into standard magic number, four-wheel loop computation to generate MD5 sequences.
Further, the Wi-Fi access points received signal strength data is carried out at Hash operation in the step S13
The step of reason includes：
Wi-Fi reference point received signal strength datas are converted into First ray, wherein first sequence by step S131
It is classified as ' 01 ' sequence, i.e., by ' 0 ' and ' 1 ' sequence formed；
Step S132, data filling：By the length (unit bit) of the obtained First rays of step S131 to 512 complementations,
If complementation result is not equal to 448, one 1 and n 0 is just filled behind the First ray and obtains the second sequence so that second
The result of 512 complementation of length pair of sequence is equal to 448；
Step S133 records message length：The second sequence length 64bits sequences storage that step S132 is generated, and
By the addition of this 64bits sequence behind the complementation result that step S132 is generated, third sequence is obtained；
Step S134 is packed into standard magic number：Initialize four link variables：A, B, C, D, as the first round in step S135
The input of operation；
In an embodiment of the present invention, A=0x01234567, B=0x89ABCDEF, C=0xFEDCBA98, D=
0x76543210。
The third sequence that step S133 is generated is grouped processing, every group 512, every group 512 is believed by step S135
Breath is divided into 16 32 seat groups, using 4 logical function FF (A, B, C, D, Mj, s, ti), GG (A, B, C, D, Mj, s, ti),
HH (A, B, C, D, Mj, s, ti), II (A, B, C, D, Mj, s, ti) carry out 4 wheel logical function operations to each grouping, often wheel cycle
Final result formed by 4 32, the output of 4 wheel loop computations of previous grouping is as corresponding 4 repeating query of next grouping
The input of ring operation, until obtain the last one 4 wheel loop computation of grouping as a result, as Hash operation result.
Wherein, FF (A, B, C, D, Mj, s, ti) indicates A=B+ ((A+F (B, C, D)+Mj+ti)<<S), GG (A, B, C, D,
Mj, s, ti) indicate A=B+ ((A+G (B, C, D)+Mj+ti)<<S), HH (A, B, C, D, Mj, s, ti) indicate A=B+ ((A+H (B,
C,D)+Mj+ti)<<S), II (A, B, C, D, Mj, s, ti) indicates A=B+ ((A+I (B, C, D)+Mj+ti)<<S), Mj indicates every
J-th of subgroup of a grouping, ti indicate 232* the integer part of abs (sin (i)), i values are 1~64, F (B, C, D)=(B＆C)
| ((~B) ＆D), G (B, C, D)=(B＆D) | (C＆ (~D)), H (B, C, D)=B^C^D, I (B, C, D) and=C^ (B | (~D))<<
Symbolic indication ring shift left, the digit that behalf moves to left.
In an embodiment of the present invention, the Wi-Fi access points received signal strength reference database can be as shown in table 1：
1 received signal strength reference database of table
In table, RPjIndicate that j-th of reference point, j=1 ... N, N indicate the quantity of reference point, (xj,yj) indicate reference point RPj
Position coordinates, APiIndicate that i-th of Wi-Fi access point, i=1 ... M, M indicate the quantity of Wi-Fi access points, RSSIijIt indicates
J-th of reference point RPjWhat place received comes from i-th of Wi-Fi access points APiReceived signal strength reference data, i.e. reference point
RPjReference data information can be expressed as：[(xj,yj), RSSI1j,…,RSSIij,…,RSSIMj].Step S2 is determined undetermined
Site Pi, and obtain point to be determined PiLocation information；
In an embodiment of the present invention, point to be determined PiCoordinate be represented by (xi,yi)。
Step S2, in point to be determined PiPlace measures the received signal strength from Wi-Fi access points；
In an embodiment of the present invention, Wi-Fi number of access point is M, in point to be determined PiWhat place's measurement obtained comes from M
The received signal strength data of a access point is represented by：[RSSI’1i,RSSI’2i,……,RSSI’Mi]。
Step S3, by point to be determined PiThe Wi-Fi access points received signal strength at place carries out default calculation process, is waited for
Position receiver signal strength data；
Wherein, the default calculation process with it is mentioned above for Wi-Fi access point received signal strength reference datas
The default calculation process carried out is identical.
Step S4 calculates the received signal strength data to be positioned and joins with the Wi-Fi access points received signal strength
Examine the distance between the reference data in database；
In an embodiment of the present invention, received signal strength data to be positioned and Wi-Fi access points reception signal are strong
The distance between reference data in degree reference database dist can be calculated using following formula：
Wherein, M indicates the corresponding reference data of each reference point in Wi-Fi access point received signal strength reference databases
Relevant access point sum, u indicate the classification of distance：As u=1, dist indicates manhatton distance；As u=2, dist tables
Show Euclidean distance.
The value of distance dist is smaller, and the position of the position and point to be determined that show the corresponding reference point of corresponding reference data is got over
It is close.
Step S5 chooses the corresponding reference point coordinate information conduct of K distance value according to the sequence of distance value from small to large
Reference coordinate is estimated to obtain the location information of the point to be determined according to the reference coordinate.
Assuming that K reference coordinate is expressed as (xk,yk), k ∈ [1, K], then the estimated coordinates of the point to be determined can indicate
For：
Or：
Wherein, distkFor the Euclidean distance between k-th of reference point and point to be determined；WkFor weighting coefficient.
Position error so between the physical location and estimated location of point to be determined can be expressed as：
Wherein, (xi,yi) indicate point to be determined physical location, (xi',yi') indicate point to be determined estimated location.
In traditional location algorithm based on WI-FI, by distance calculation formula it is found that when the AP numbers in reference database
Amount increases, i.e., when M values increase, calculating the time complexity of distance dist can increase therewith, while when reference database increases,
When i.e. N values increase, obtaining the complexity of K reference coordinate can also increase, to cause location efficiency to decline.Therefore, of the invention
Default calculation process is carried out for the Wi-Fi access points received signal strength at reference data and point to be determined, to pending
Data have carried out simplified conversion, thus greatly reduce computation complexity, save and calculate the time.
The present invention not only can effectively estimate the position of point to be determined, but also can identify and point to be determined phase the most
Close reference point locations, and then K values the most suitable automatically are extrapolated, it is needed in traditional location algorithm manually to solve
The problem of K values are arranged, effectively improves positioning accuracy.
To assess the performance of indoor orientation method proposed by the present invention, selected from a certain floor of a practical building as real
Environment is tested to be tested.The floor area is close to 2000m2, room, cement wall and wooden door between having mostly, floor place
Environment in be equipped with wireless Wi-Fi, without connection.To reduce the unstable influence brought of actual signal, when experiment
Each reference point locations acquire 20 groups of data, and are handled it using mean filter, and actual measurement RSSI assay intervals are 0.8
Second, the Wi-Fi reference databases of construction include 3000 reference datas altogether, and every reference data is altogether comprising from 200 AP points
RSSI information.
Utilize position error probability density function such as Fig. 2 of conventional mapping methods and localization method proposed by the present invention
Shown, wherein Fig. 2 (a) is the position error probability density distribution of conventional mapping methods, and Fig. 2 (b) is localization method of the present invention
Position error probability density distribution：
Figure it is seen that the error distribution of conventional mapping methods more disperses, it is concentrated mainly between 1-8m, and phase
For localization method of the present invention, the error range of localization method of the present invention is further shunk, and positioning accuracy further increases,
It is concentrated mainly between 1-4m.
The position error cumulative distribution function (Cumulative Distribution Function, CDF) of two methods
As shown in figure 3, from figure 3, it can be seen that the positioning accuracy of conventional mapping methods error be 2.5m probability close to 80%, and
The probability of localization method of the present invention is promoted to 90%, and the cumulative distribution function of localization method of the present invention is quickly close to 1,
Show that the locating effect of improved localization method is better than conventional mapping methods.
In addition, for the complexity of each method：
The operation time complexity of conventional mapping methods is expressed from the next：
O(mn)=k1*M*N. (6)
The operation time complexity of localization method of the present invention is expressed from the next：
On=k2*32*N. (7)
In formula, k1, k2The respectively single operation time of two methods, and meet k1＞ k2；N is in reference database
Reference data number；M is the number of AP in every reference data.In localization method of the present invention, due to traditional reference number
Default operation, therefore the operation time complexity of localization method of the present invention have been carried out according to the reference data in database
(Computation of time complexity, CTC) is only influenced by Database Reference number of data, and traditional positioning side
Method is not only influenced by Database Reference number of data, but also AP quantity is influenced in by every reference data.
When one timing of AP quantity, the operation that conventional mapping methods change with localization method of the present invention with reference data quantity
Between complexity it is as shown in Figure 4.Wherein Fig. 4 (a) is the computational complexity comparison diagram that AP quantity is higher than 32 in localization region, wherein scheming
4 (b) is the computational complexity comparison diagram that AP quantity is less than 32 in localization region.
From fig. 4, it can be seen that reference data quantity under the same conditions, when the AP quantity in region be more than 32 when, this
The invention localization method positioning required time is significantly less than the conventional mapping methods required time.And when AP quantity is less than 32
When, for the location efficiency of localization method of the present invention less than conventional mapping methods, this is attributed to the fact that localization method of the present invention joins every
It examines data and has carried out default operation conversion.
During the experiment, the actual location efficiency of two methods is as shown in table 2：
2 location efficiency contrast table of table
As shown in Table 2, when the quantity of reference data expands 6 times, the positioning time of localization method of the present invention increases 2.3
Times, and the positioning time of conventional mapping methods increases nearly 13 times.In megastore or the reference number of other buildings
According in the building process of library, the quantity of reference data can be far more than 3000, and AP quantity also can be far more than 32, therefore the present invention carries
The location efficiency of the localization method gone out has prodigious advantage.
When one timing of reference data quantity in reference database, the operation time complexity of two kinds of algorithms is with AP quantity
Variation is and traditional as shown in figure 5, from fig. 5, it can be seen that the computational complexity due to localization method of the present invention is unrelated with AP quantity
The computational complexity of localization method and AP quantity are in a linear relationship.And in large-scale occasion such as megastore, AP quantity can be far more
In 32, this also indicates that the feasibility and practicability of localization method of the present invention proposed by the present invention.
Compared to traditional indoor orientation method, no matter indoor orientation method proposed by the present invention is in positioning accuracy or fixed
There is larger, apparent improvement in terms of the efficiency of position, there has also been certain raisings for position stability aspect.In large-scale occasion such as quotient
In, since area is big, access is counted out more, and the reference data item number and number of access point of reference database all can gradually increase
More, the requirement to positioning accuracy and location efficiency also increases therewith, can more embody the superiority and availability of the method for the present invention.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect
It describes in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the guarantor of the present invention
Within the scope of shield.
Claims (8)
1. a kind of indoor orientation method, which is characterized in that the method includes：
Step S1 obtains Wi-Fi access point received signal strength reference datas, by the Wi-Fi access points received signal strength
Reference data carries out default calculation process, and based on the data structure Wi-Fi access point received signal strengths ginseng obtained after processing
Examine database, wherein the default calculation process is used to Wi-Fi access point received signal strength reference datas being converted to length
Fixed reference data；
Step S2, in point to be determined PiPlace measures the received signal strength from Wi-Fi access points；
Step S3, by point to be determined PiThe Wi-Fi access points received signal strength at place carries out default calculation process, obtains to be positioned
Received signal strength data；
Step S4 calculates the received signal strength data to be positioned and the Wi-Fi access points received signal strength reference number
According to the distance between the reference data in library；
Step S5 chooses the corresponding reference point coordinate information of K distance value as reference according to the sequence of distance value from small to large
Coordinate is estimated to obtain the location information of the point to be determined according to the reference coordinate.
2. the method as described in claim 1, which is characterized in that the step S1 further comprises：
N number of reference point is arranged in step S11, and obtains the location information of N number of reference point, wherein N is positive integer；
Step S12 obtains the Wi-Fi access point received signal strengths received at N number of reference point locations；
The Wi-Fi access points received signal strength data is carried out Hash operation processing, is connect as the Wi-Fi by step S13
Access point received signal strength reference data, structure obtain Wi-Fi access point received signal strength reference databases.
3. method as claimed in claim 2, which is characterized in that the default calculation process is Hash operation processing.
4. method as claimed in claim 3, which is characterized in that the Hash operation processing is MD5 calculation process.
5. method as claimed in claim 4, which is characterized in that the Wi-Fi access points are received signal in the step S13
Intensity data carry out Hash operation processing the step of include：
Wi-Fi reference point received signal strength datas are converted into First ray by step S131, wherein the First ray is
' 01 ' sequence, i.e., by ' 0 ' and ' 1 ' sequence formed；
Step S132 just exists 512 complementation of length pair of the obtained First rays of step S131 if complementation result is not equal to 448
It is filled behind the First ray one 1 and n 0 and obtains the second sequence so that the result of 512 complementation of length pair of the second sequence
Equal to 448；
Step S133, the second sequence length 64bits sequences that step S132 is generated store, and this 64bits sequence is added
It is added in behind the complementation result that step S132 is generated, obtains third sequence；
Step S134 initializes four link variables：A, B, C, D, the input as first round operation in step S135；
The third sequence that step S133 is generated is grouped processing by step S135, using 4 logical functions to it is each be grouped into
Row 4 takes turns logical function operation, and the output of 4 wheel loop computations of previous grouping is as the defeated of the corresponding 4 wheel loop computation of next grouping
Enter, until obtain the last one 4 wheel loop computation of grouping as a result, as Hash operation result.
6. the method as described in claim 1, which is characterized in that in the step S4, received signal strength data to be positioned with
The distance between reference data in Wi-Fi access points received signal strength reference database dist can using following formula come
It calculates：
Wherein, M indicates that each the corresponding reference data of reference point is related in Wi-Fi access point received signal strength reference databases
Access point sum, RSSImjIt indicates in j-th of reference point RPjWhat place received comes from m-th of Wi-Fi access points APmReception
Signal strength reference data, RSSI 'miIt indicates in i-th of reference point RPiWhat place received comes from m-th of Wi-Fi access points APm
Received signal strength reference data, u indicate distance classification：As u=1, dist indicates manhatton distance；As u=2,
Dist indicates Euclidean distance.
7. the method as described in claim 1, which is characterized in that in the step S5, it is assumed that K reference coordinate is expressed as (xk,
yk), k ∈ [1, K], the then estimated coordinates (x of the point to be determinedi',yi') can be expressed as：
8. the method as described in claim 1, which is characterized in that in the step S5, it is assumed that K reference coordinate is expressed as (xk,
yk), k ∈ [1, K], the then estimated coordinates (x of the point to be determinedi',yi') can be expressed as：
Wherein, distkFor the Euclidean distance between k-th of reference point and point to be determined, WkFor weighting coefficient.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109490914A (en) * | 2018-11-30 | 2019-03-19 | 北京摩拜科技有限公司 | Object positioning method, server and system |
| CN110118954A (en) * | 2019-05-21 | 2019-08-13 | 云盾智能物联有限公司 | A kind of indoor positioning, air navigation aid, device, system |
| CN110231592A (en) * | 2019-04-11 | 2019-09-13 | 深圳市城市交通规划设计研究中心有限公司 | Indoor orientation method, device, computer readable storage medium and terminal device |
| CN110231593A (en) * | 2019-04-11 | 2019-09-13 | 深圳市城市交通规划设计研究中心有限公司 | Indoor orientation method, device, computer readable storage medium and terminal device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103796305A (en) * | 2014-02-11 | 2014-05-14 | 上海交通大学 | Indoor positioning method based on Wi-Fi position fingerprint |
| CN104457758A (en) * | 2014-12-19 | 2015-03-25 | 哈尔滨工业大学 | Video-acquisition-based Visual Map database establishing method and indoor visual positioning method using database |
| CN105530609A (en) * | 2015-12-16 | 2016-04-27 | 上海交通大学 | Indoor positioning method for efficient privacy protection based on Wi-Fi fingerprint |
| WO2017114967A1 (en) * | 2015-12-31 | 2017-07-06 | Robert Bosch Gmbh | Indoor room-localization system and method thereof |
| CN107677989A (en) * | 2017-10-26 | 2018-02-09 | 武汉大学 | A kind of indoor location localization method that RSSI removal noises are carried out based on RSSI maximums |
-
2018
- 2018-03-09 CN CN201810195955.5A patent/CN108414970B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103796305A (en) * | 2014-02-11 | 2014-05-14 | 上海交通大学 | Indoor positioning method based on Wi-Fi position fingerprint |
| CN104457758A (en) * | 2014-12-19 | 2015-03-25 | 哈尔滨工业大学 | Video-acquisition-based Visual Map database establishing method and indoor visual positioning method using database |
| CN105530609A (en) * | 2015-12-16 | 2016-04-27 | 上海交通大学 | Indoor positioning method for efficient privacy protection based on Wi-Fi fingerprint |
| WO2017114967A1 (en) * | 2015-12-31 | 2017-07-06 | Robert Bosch Gmbh | Indoor room-localization system and method thereof |
| CN107677989A (en) * | 2017-10-26 | 2018-02-09 | 武汉大学 | A kind of indoor location localization method that RSSI removal noises are carried out based on RSSI maximums |
Non-Patent Citations (2)
| Title |
|---|
| XINGBIN GE等: "Optimization Wife Indoor Positioning KNN Algorithm Location-based", 《2016 IEEE》 * |
| 钱睿硕: "基于GPU加速的MD5哈希函数加密算法研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109490914A (en) * | 2018-11-30 | 2019-03-19 | 北京摩拜科技有限公司 | Object positioning method, server and system |
| CN109490914B (en) * | 2018-11-30 | 2020-05-29 | 北京摩拜科技有限公司 | Object positioning method, server and system |
| CN110231592A (en) * | 2019-04-11 | 2019-09-13 | 深圳市城市交通规划设计研究中心有限公司 | Indoor orientation method, device, computer readable storage medium and terminal device |
| CN110231593A (en) * | 2019-04-11 | 2019-09-13 | 深圳市城市交通规划设计研究中心有限公司 | Indoor orientation method, device, computer readable storage medium and terminal device |
| CN110118954A (en) * | 2019-05-21 | 2019-08-13 | 云盾智能物联有限公司 | A kind of indoor positioning, air navigation aid, device, system |
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