CN103200676A - Method and device for building fingerprint database - Google Patents
Method and device for building fingerprint database Download PDFInfo
- Publication number
- CN103200676A CN103200676A CN2013101083331A CN201310108333A CN103200676A CN 103200676 A CN103200676 A CN 103200676A CN 2013101083331 A CN2013101083331 A CN 2013101083331A CN 201310108333 A CN201310108333 A CN 201310108333A CN 103200676 A CN103200676 A CN 103200676A
- Authority
- CN
- China
- Prior art keywords
- collection point
- signal strength
- signal intensity
- strength signal
- described target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Abstract
The invention discloses a method and device for building a fingerprint database. The method and device for building the fingerprint database can decrease the number of noise points in the fingerprint database. The method comprises the steps of confirming whether a target acquisition point is a noise point according to the signal strength of the target acquisition point and the signal strength of at least one acquisition point; conforming the signal strength of the target acquisition point according to the signal strength of at least one acquisition point if the target acquisition point is the noise point; correspondingly memorizing the signal strength of the target acquisition point and position information of a pre-memorized target acquisition point and building the fingerprint database. Therefore, the acquisition point is selected according to the signal strength so as to filter the noise point, and accordingly the number of the noise points in the fingerprint database can be decreased. The method and device for building the fingerprint database is mainly applied to fingerprint database building, and the number of the noise points in the fingerprint database can be decreased.
Description
Technical field
The present invention relates to field of locating technology, particularly a kind of method for building up of fingerprint base and device.
Background technology
The location technology of fingerprint matching is a kind of technology that realizes indoor positioning.The location technology of fingerprint matching can be divided into two stages, i.e. off-line phase (Offline stage) and online stage (Online stage).After off-line phase referred to choose fingerprint point (fingerprint point also can be called fingerprint collecting point or reference point), AP(access point around each fingerprint point, English full name was Access Point) signal strength signal intensity set up fingerprint base.After the online stage refers to set up fingerprint base, the signal strength signal intensity of AP around portable terminal receives, signal strength signal intensity and database that portable terminal is received carry out matching operation, determine the position at portable terminal place.
Because the signal of different AP and the phase mutual interference between other signal, a certain fingerprint point may differ greatly with the signal strength signal intensity of the same AP that fingerprint point around it is gathered, and such fingerprint point is called noise spot.The signal strength signal intensity that noise spot is gathered is bigger with the signal intensity difference of fingerprint point collection on every side, the signal intensity profile of fingerprint base that causes introducing noise spot is irregular, application exists the fingerprint base of noise spot to carry out the matching operation in online stage, influences the accuracy of positioning result.
Therefore, how reducing the quantity of the noise spot in the fingerprint base to improve setting accuracy, is the current problem that needs solution.
Summary of the invention
The embodiment of the invention provides a kind of method for building up and device of fingerprint base, can reduce the quantity of the noise spot in the fingerprint base.
The embodiment of the invention adopts following technical scheme:
First aspect provides a kind of method for building up of fingerprint base, comprising:
According to the signal strength signal intensity of at least one contiguous collection point of the signal strength signal intensity of target collection point and described target collection point, determine whether described target collection point is noise spot; If described target collection point is noise spot, then according to the signal strength signal intensity of described at least one collection point, determine the signal strength signal intensity of described target collection point; With the signal strength signal intensity of described target collection point, with the positional information corresponding stored of the described target collection point that prestores, set up fingerprint base.
Alternatively, the signal strength signal intensity of described contiguous at least one collection point of signal strength signal intensity and described target collection point according to the target collection point, determine that whether described target collection point is before the noise spot, also comprises:
Gather neighborhood of a point by pre-conditioned definite described target, described neighborhood is made up of described target collection point and described at least one collection point.
Alternatively, the signal strength signal intensity of the described contiguous collection point of signal strength signal intensity and described target collection point according to the target collection point, determine whether described target collection point is that noise spot comprises:
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the first similarity average of described target collection point; According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the second similarity average of described at least one collection point; The described first similarity average and the second similarity average are compared, if the described first similarity average greater than the described second similarity average, then described target collection point is noise spot.
Alternatively, described signal strength signal intensity according to described at least one collection point, determine that the signal strength signal intensity of described target collection point comprises:
With the signal strength signal intensity average of described at least one collection point, as the signal strength signal intensity of described target collection point; Perhaps, filtering noise point from described at least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of described target collection point.
Alternatively, described according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine that the first similarity average of described target collection point comprises:
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the similarity of described target collection point and described at least one collection point, with the mean value of the similarity of described target collection point and described at least one collection point, as the first similarity average of described target collection point; Described according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, the second similarity average of determining described at least one collection point comprises: according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine in described at least one collection point each collection point and the similarity of adjacent collection point separately, according to described each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of described at least one collection point.
Second aspect provides a kind of apparatus for establishing of fingerprint base, comprising:
First determining unit is used for the signal strength signal intensity according at least one contiguous collection point of the signal strength signal intensity of target collection point and described target collection point, determines whether described target collection point is noise spot; Second determining unit is noise spot if be used for described target collection point, then according to the signal strength signal intensity of described at least one collection point, determines the signal strength signal intensity of described target collection point; Memory cell, be used for the signal strength signal intensity of described target collection point, with the positional information corresponding stored of the described target collection point that prestores, set up fingerprint base.
Alternatively, also comprise:
The 3rd determining unit is used for gathering neighborhood of a point by pre-conditioned definite described target, and described neighborhood is made up of described target collection point and described at least one collection point.
Alternatively, described first determining unit comprises:
First determines subelement, is used for according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determines the first similarity average of described target collection point; Second determines subelement, is used for according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determines the second similarity average of described at least one collection point; The 3rd determines subelement, be used for the described first similarity average and the second similarity average are compared, if the described first similarity average greater than the described second similarity average, then described target collection point is noise spot.
Alternatively, described second determining unit specifically is used for, with the signal strength signal intensity average of described at least one collection point, as the signal strength signal intensity of described target collection point; Perhaps, described second determining unit specifically is used for, and filtering noise point from described at least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of described target collection point.
Alternatively, described first determines that subelement specifically is used for, according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the similarity of described target collection point and described at least one collection point, with the mean value of the similarity of described target collection point and described at least one collection point, as the first similarity average of described target collection point; Described second determines that subelement specifically is used for, according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine in described at least one collection point each collection point and the similarity of adjacent collection point separately, according to described each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of described at least one collection point.
Based on technique scheme, the method for building up of the fingerprint base that the embodiment of the invention provides and device, signal strength signal intensity according to the contiguous collection point in the signal strength signal intensity of target collection point and target collection point, determine that the target collection point is for behind the noise spot, signal strength signal intensity according to contiguous collection point, target collection point, determine the signal strength signal intensity of target collection point, with the signal strength signal intensity of target collection point, with the positional information corresponding stored of the target collection point that prestores, set up fingerprint base.Like this, by according to signal strength signal intensity the filtering noise point being selected in the collection point, thereby can reduce the quantity of noise spot in the fingerprint base.
Description of drawings
In order to be illustrated more clearly in the technical scheme in the embodiment of the invention, the accompanying drawing of required use is done to introduce simply in will describing embodiment below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
The flow chart of the method for building up of a kind of fingerprint base that Fig. 1 provides for the embodiment of the invention;
The flow chart of the method for building up of the another kind of fingerprint base that Fig. 2 provides for the embodiment of the invention;
A kind of neighborhood schematic diagram that Fig. 3 a provides for the embodiment of the invention;
The another kind of neighborhood schematic diagram that Fig. 3 b provides for the embodiment of the invention;
Another neighborhood schematic diagram that Fig. 3 c provides for the embodiment of the invention;
A kind of signal intensity profile schematic diagram that Fig. 4 a provides for the embodiment of the invention;
Fig. 4 b divides schematic diagram for a kind of neighborhood that the embodiment of the invention provides;
The flow chart of the method for building up of another fingerprint base that Fig. 5 provides for the embodiment of the invention;
The structural representation of the apparatus for establishing of a kind of fingerprint base that Fig. 6 provides for the embodiment of the invention;
The structural representation of the apparatus for establishing of the another kind of fingerprint base that Fig. 7 provides for the embodiment of the invention;
The structural representation of the apparatus for establishing of another fingerprint base that Fig. 8 provides for the embodiment of the invention.
Embodiment
For the purpose, technical scheme and the advantage that make the embodiment of the invention clearer, below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.
The embodiment of the invention can be applied to various communication systems, WCDMA(Wideband Code Division Multiple Access for example, Wideband Code Division Multiple Access (WCDMA)) system, LTE(Long Term Evolution, Long Term Evolution) system etc.Signal strength signal intensity in the embodiment of the invention can be indicated for the signal strength signal intensity that RSSI(receives, and English full name is Received Signal Strength Indication).
See also Fig. 1, the method for building up of a kind of fingerprint base that the embodiment of the invention provides, this method can comprise:
101, according to the signal strength signal intensity of at least one contiguous collection point of the signal strength signal intensity of target collection point and this target collection point, determine whether this target collection point is noise spot.
Wherein, at least one contiguous collection point of this target collection point is the collection point that is positioned at same neighborhood with this target collection point, and definite method of neighborhood sees also further part.
If 102 these target collection points are noise spot, then according to the signal strength signal intensity of this at least one collection point, determine the signal strength signal intensity of this target collection point.
103, with the signal strength signal intensity of this target collection point, with the positional information corresponding stored of this target collection point that prestores, set up fingerprint base.
The method for building up of embodiment of the invention fingerprint base can realize that the apparatus for establishing of this fingerprint base can be computer system or other equipment by the apparatus for establishing of fingerprint base, and the embodiment of the invention does not limit this.
The method for building up of the fingerprint base of the embodiment of the invention, signal strength signal intensity according to the contiguous collection point in the signal strength signal intensity of target collection point and target collection point, determine that the target collection point is for behind the noise spot, signal strength signal intensity according to contiguous collection point, target collection point, determine the signal strength signal intensity of target collection point, with the signal strength signal intensity of target collection point, with the positional information corresponding stored of the target collection point that prestores, set up fingerprint base.Like this, by according to signal strength signal intensity the filtering noise point being selected in the collection point, thereby can reduce the quantity of noise spot in the fingerprint base.
As shown in Figure 2, in the embodiment of the invention, alternatively, before above-mentioned 101, also comprise:
100, gather neighborhood of a point by pre-conditioned definite this target, this neighborhood is made up of this target collection point and this at least one collection point.
The embodiment of the invention can be determined this target collection neighborhood of a point by default rule (as shape).For example,
Target collection point p (i
1, j
1) determine a collection point set U, p (i according to a certain rule or shape f
1, j
1) with U in a certain collection point q (i
2, j
2) relevant.P (i then
1, j
1) neighborhood
Be defined as follows:
From (1-1) p (i as can be known
1, j
1) neighborhood
Do not comprise p (i
1, j
1), can be called hollow neighborhood; If p (i
1, j
1) neighborhood
Comprise p (i
1, j
1), can be expressed as N
pOr N.Choosing p (i
1, j
1) neighborhood
In the collection point time, can choose by being shaped as square, rectangle or criss-cross rule.Common neighborhood has the 4-territory, the 8-territory, and the 12-territory, centered by the solid dot shown in Fig. 3 a, 3b, 3c, the neighborhood that the dashed rectangle of point comprises is respectively 4-territory, 8-territory, l2-territory.
The embodiment of the invention based on fingerprint matching algorithm when setting up fingerprint base, after the signal strength signal intensity that obtains the target collection point (as the RSS signal vector), the positional information of record object collection point (as the coordinate of target collection point), with the positional information of collection point with the signal strength signal intensity (as the RSS signal vector) of collection point as a fingerprint typing fingerprint base, the collection point in the fingerprint base exists certain spatial relationship.
In the embodiment of the invention, alternatively, in above-mentioned 101 according to the signal strength signal intensity of the contiguous collection point in the signal strength signal intensity of target collection point and this target collection point, when determining whether this target collection point is noise spot, can determine the first similarity average of this target collection point according to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point; According to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point, determine the second similarity average of this at least one collection point; This first similarity average and the second similarity average are compared, if this first similarity average greater than this second similarity average, then this target collection point is noise spot.
Wherein, above-mentioned according to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point, when determining the first similarity average of this target collection point, can be according to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point, determine the similarity of this target collection point and this at least one collection point, with the mean value of the similarity of this target collection point and this at least one collection point, as the first similarity average of this target collection point; Above-mentioned according to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point, when determining the second similarity average of this at least one collection point, can be according to the signal strength signal intensity of this target collection point and the signal strength signal intensity of this at least one collection point, determine in this at least one collection point each collection point and the similarity of adjacent collection point separately, according to this each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of this at least one collection point.
In the embodiment of the invention, according to the noise spot in the distribution difference fingerprint base of AP signal strength signal intensity.The distribution map of AP signal strength signal intensity in free space that Fig. 4 a provides for the embodiment of the invention, as shown in Figure 4, the signal of AP has covered regional collection point, because different with the distance of AP, the signal strength signal intensity that different AP receive may be different.The scope of different label area sub-signal intensity levels among Fig. 4 a.
C(target collection point, collection point in judging Fig. 4 b) when whether being noise spot, the 8-neighborhood of collection point C can be set up, whether noise spot of collection point C can be judged according to the signal strength signal intensity of other collection points of 8-neighborhood of collection point C among the signal strength signal intensity of collection point C and the 4b.The signal strength signal intensity of adjacent two collection points has certain similitude, determines the similarity value of adjacent two collection points in the embodiment of the invention, when similarity value during less than pre-set threshold value, comprises noise spot in adjacent two collection points.
The embodiment of the invention can be determined the similarity of adjacent two collection points with (1-2), (1-2) middle L (a, the b) similarity of adjacent two the collection point a of expression and b, R
aAP is at the RSSI of collection point a value, R in expression
bAP is in the RSSI of collection point b value in expression.
L(a,b)=-(R
a-R
b)
2 (1-2)
Describe in detail below and judge that whether the target collection point is the method for noise spot, if do not comprise the 8-neighborhood of collection point C is not
The 8-neighborhood that comprises collection point C is N
c, then:
N
c={P
1,P
2,...,P
8,C} (1-3)
If comprise in the 8-neighborhood of collection point C collection point P
i(P
i≠ similarity the summation that C) is adjacent the collection point is
Then:
Wherein,
In the 8-neighborhood that comprises collection point C, with collection point P
iThe set of adjacent collection point is collection point P2, collection point P4 and collection point C as the collection point adjacent with collection point P1.The collection point adjacent with collection point P4 is collection point P1, collection point P2, collection point P6, collection point 7, and collection point C.
Collection point P
i(P
i≠ C) with the similarity average of consecutive points
For:
Wherein
Be P
i(P
iThe number of collection point in ≠ C) the neighborhood, as
N
CIn except the C of collection point the average similarity of all collection point points
For:
The similarity summation of collection point C and adjacent collection point
For:
The similarity average of collection point C and adjacent collection point
For:
When
The time, collection point C is noise spot, on the contrary collection point C is non-noise spot.
In the embodiment of the invention, alternatively, in above-mentioned 102 according to the signal strength signal intensity of this at least one collection point, when determining the signal strength signal intensity of this target collection point, can be with the signal strength signal intensity average of this at least one collection point, as the signal strength signal intensity of this target collection point; Perhaps, filtering noise point from this at least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of this target collection point.
For example, when collection point C was noise spot among Fig. 4 b, the average of the signal strength signal intensity of the collection point in the neighborhood with collection point C, beyond the C of collection point was as the signal strength signal intensity of collection point C.
Perhaps, in the neighborhood with collection point C, in the collection point beyond the C of collection point, the average of the signal strength signal intensity of the collection point of non-noise spot is as the signal strength signal intensity of collection point C.For example, can determine the signal strength signal intensity of collection point C with (1-9).
Wherein, R
NBe the signal strength signal intensity of the noise spot after upgrading, R
iBe the signal strength signal intensity of non-noise spot in the neighborhood, n is the collection point number of non-noise spot in the neighborhood.
Need to prove, be that example describes with single AP only in the embodiment of the invention, when the signal that the collection point receives a plurality of AP simultaneously in the practice is set up fingerprint base, repeat the method that above-mentioned single AP judges noise spot and replaces the signal strength signal intensity of noise spot, travel through each AP, the method of setting up fingerprint base gets final product, and does not give unnecessary details.When using a plurality of AP and setting up fingerprint base, because the signal cover of AP is limited, when the collection point does not receive the collection point of certain AP signal, this AP signal strength signal intensity be set to not influence calculating value (as-100dBm) and add fingerprint base to, behind all AP of traversal, each collection point of whole fingerprint base all comprises all AP signal strength signal intensities like this.
The number of steps of the embodiment of the invention only for distinguishing different steps, does not constitute the restriction to the embodiment of the invention.
The method for building up of the fingerprint base of the embodiment of the invention, signal strength signal intensity according to the contiguous collection point in the signal strength signal intensity of target collection point and target collection point, determine that the target collection point is for behind the noise spot, signal strength signal intensity according to contiguous collection point, target collection point, determine the signal strength signal intensity of target collection point, with the signal strength signal intensity of target collection point, with the positional information corresponding stored of the target collection point that prestores, set up fingerprint base.Like this, by according to signal strength signal intensity the filtering noise point being selected in the collection point, thereby can reduce the quantity of noise spot in the fingerprint base.
Describe the specific implementation process of method for building up of the fingerprint base of the embodiment of the invention below in detail.
See also Fig. 5, the method for building up of the another kind of fingerprint base that the embodiment of the invention provides, this method can comprise:
301, travel through the fingerprint base that prestores, find the set Q of all AP in the fingerprint base that prestores.
For example, Q={AP
1, AP
2..., AP
n.
302, the signal strength signal intensity of each collection point in the fingerprint base that prestores is filled with the form of set Q.
Namely, when the signal strength signal intensity (as the RSS signal vector) of collection point does not comprise the signal strength signal intensity of certain AP among the set Q, the signal strength signal intensity of this AP that in the signal strength signal intensity of collection point, add to receive, if do not receive this AP signal strength signal intensity of signal of this AP be set to not influence calculating value (as-100dBm).
303, in Q, choose each AP as signal source, travel through the noise spot that each AP is determined in all collection points, and redefine the signal strength signal intensity of the noise spot of each AP.
304, upgrade the signal strength signal intensity of each collection point in the fingerprint base that prestores, with positional information (as the coordinate) corresponding stored of each collection point, set up new fingerprint base.
Wherein, the positional information of each collection point can be stored in the above-mentioned fingerprint base that prestores.
Above-mentioned 301-304 only is brief description, and implementation procedure sees also the method for building up of the fingerprint base of other embodiment of the present invention in detail.
The method for building up of the fingerprint base of the embodiment of the invention by according to signal strength signal intensity the filtering noise point being selected in the collection point, thereby can reduce the quantity of noise spot in the fingerprint base.
See also Fig. 6, the embodiment of the invention provides a kind of apparatus for establishing of fingerprint base, comprising: first determining unit 41, second determining unit 42, memory cell 43, wherein:
First determining unit 41 is used for the signal strength signal intensity according at least one contiguous collection point of the signal strength signal intensity of target collection point and described target collection point, determines whether the target collection point is noise spot;
Second determining unit 42 is noise spot if be used for the target collection point, then according to the signal strength signal intensity of at least one collection point, determines the signal strength signal intensity of target collection point;
As shown in Figure 7, in the embodiment of the invention, alternatively, said apparatus can also be drawn together by bag:
The 3rd determining unit 40 is used for gathering neighborhood of a point by pre-conditioned definite target, and neighborhood is made up of target collection point and at least one collection point.
As shown in Figure 8, in the embodiment of the invention, alternatively, first determining unit 41 can comprise:
First determines subelement 411, is used for according to the signal strength signal intensity of target collection point and the signal strength signal intensity of at least one collection point, determines the first similarity average of target collection point;
Second determines subelement 412, is used for according to the signal strength signal intensity of target collection point and the signal strength signal intensity of at least one collection point, determines the second similarity average of at least one collection point;
The 3rd determines subelement 413, be used for the first similarity average and the second similarity average are compared, if the first similarity average greater than the second similarity average, then the target collection point is noise spot.
In the embodiment of the invention, alternatively, second determining unit 42 can specifically be used for, with the signal strength signal intensity average of at least one collection point, as the signal strength signal intensity of target collection point;
Perhaps, second determining unit 42 can specifically be used for, and filtering noise point from least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of target collection point.
As shown in Figure 8, in the embodiment of the invention, alternatively, first determines that subelement 411 can specifically be used for, according to the signal strength signal intensity of target collection point and the signal strength signal intensity of at least one collection point, determine the similarity of target collection point and at least one collection point, with the mean value of the similarity of target collection point and at least one collection point, as the first similarity average of target collection point;
Second determines that subelement 412 can specifically be used for, according to the signal strength signal intensity of target collection point and the signal strength signal intensity of at least one collection point, determine at least one collection point each collection point and the similarity of adjacent collection point separately, according to each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of at least one collection point.
The apparatus for establishing of the fingerprint base of the embodiment of the invention can be computer system or other equipment, and the embodiment of the invention does not limit this.The apparatus for establishing of the fingerprint base of the embodiment of the invention can be realized said method embodiment, and the concrete function of a unit only is concise and to the point the description in the apparatus for establishing of fingerprint base, and implementation procedure sees also the corresponding steps of said method embodiment in detail.
Each element number only for distinguishing different unit, does not constitute the restriction to the embodiment of the invention in the embodiment of the invention.
The apparatus for establishing of the fingerprint base of the embodiment of the invention, signal strength signal intensity according to the contiguous collection point in the signal strength signal intensity of target collection point and target collection point, determine that the target collection point is for behind the noise spot, signal strength signal intensity according to contiguous collection point, target collection point, determine the signal strength signal intensity of target collection point, with the signal strength signal intensity of target collection point, with the positional information corresponding stored of the target collection point that prestores, set up fingerprint base.Like this, by according to signal strength signal intensity the filtering noise point being selected in the collection point, thereby can reduce the quantity of noise spot in the fingerprint base.
The embodiment of the invention is mainly used in sets up fingerprint base, can reduce the quantity of noise spot in the fingerprint base.
Need to prove: the device that above-described embodiment provides, only the division with above-mentioned each functional unit is illustrated, in the practical application, can as required the above-mentioned functions distribution be finished by different functional units or module, the internal structure that is about to device is divided into different functional units or module, to finish all or part of function described above.In addition, the apparatus and method method embodiment that above-described embodiment provides belongs to same design, and its specific implementation process sees method embodiment for details, repeats no more here.
The invention described above embodiment sequence number does not represent the quality of embodiment just to description.
The all or part of step that one of ordinary skill in the art will appreciate that realization above-described embodiment can be finished by hardware, also can instruct relevant hardware to finish by program, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium of mentioning can be read-only memory, disk or CD etc.
The above only is preferred embodiment of the present invention, and is in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of doing, is equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. the method for building up of a fingerprint base is characterized in that, comprising:
According to the signal strength signal intensity of at least one contiguous collection point of the signal strength signal intensity of target collection point and described target collection point, determine whether described target collection point is noise spot;
If described target collection point is noise spot, then according to the signal strength signal intensity of described at least one collection point, determine the signal strength signal intensity of described target collection point;
With the signal strength signal intensity of described target collection point, with the positional information corresponding stored of the described target collection point that prestores, set up fingerprint base.
2. method according to claim 1 is characterized in that, the signal strength signal intensity of described contiguous at least one collection point of signal strength signal intensity and described target collection point according to the target collection point determines that whether described target collection point is before the noise spot, also comprises:
Gather neighborhood of a point by pre-conditioned definite described target, described neighborhood is made up of described target collection point and described at least one collection point.
3. method according to claim 1 and 2 is characterized in that, the signal strength signal intensity of the described contiguous collection point of signal strength signal intensity and described target collection point according to the target collection point determines whether described target collection point is that noise spot comprises:
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the first similarity average of described target collection point;
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the second similarity average of described at least one collection point;
The described first similarity average and the second similarity average are compared, if the described first similarity average greater than the described second similarity average, then described target collection point is noise spot.
4. according to claim 1 or 2 or 3 described methods, it is characterized in that described signal strength signal intensity according to described at least one collection point determines that the signal strength signal intensity of described target collection point comprises:
With the signal strength signal intensity average of described at least one collection point, as the signal strength signal intensity of described target collection point;
Perhaps, filtering noise point from described at least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of described target collection point.
5. method according to claim 3 is characterized in that, and is described according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determines that the first similarity average of described target collection point comprises:
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the similarity of described target collection point and described at least one collection point, with the mean value of the similarity of described target collection point and described at least one collection point, as the first similarity average of described target collection point;
Described according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine that the second similarity average of described at least one collection point comprises:
According to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine in described at least one collection point each collection point and the similarity of adjacent collection point separately, according to described each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of described at least one collection point.
6. the apparatus for establishing of a fingerprint base is characterized in that, comprising:
First determining unit is used for the signal strength signal intensity according at least one contiguous collection point of the signal strength signal intensity of target collection point and described target collection point, determines whether described target collection point is noise spot;
Second determining unit is noise spot if be used for described target collection point, then according to the signal strength signal intensity of described at least one collection point, determines the signal strength signal intensity of described target collection point;
Memory cell, be used for the signal strength signal intensity of described target collection point, with the positional information corresponding stored of the described target collection point that prestores, set up fingerprint base.
7. device according to claim 6 is characterized in that, also comprises:
The 3rd determining unit is used for gathering neighborhood of a point by pre-conditioned definite described target, and described neighborhood is made up of described target collection point and described at least one collection point.
8. according to claim 6 or 7 described devices, it is characterized in that described first determining unit comprises:
First determines subelement, is used for according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determines the first similarity average of described target collection point;
Second determines subelement, is used for according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determines the second similarity average of described at least one collection point;
The 3rd determines subelement, be used for the described first similarity average and the second similarity average are compared, if the described first similarity average greater than the described second similarity average, then described target collection point is noise spot.
9. according to claim 6 or 7 or 8 described devices, it is characterized in that described second determining unit specifically is used for, with the signal strength signal intensity average of described at least one collection point, as the signal strength signal intensity of described target collection point;
Perhaps, described second determining unit specifically is used for, and filtering noise point from described at least one collection point is with the signal strength signal intensity average of residue collection point, as the signal strength signal intensity of described target collection point.
10. device according to claim 8, it is characterized in that, described first determines that subelement specifically is used for, according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine the similarity of described target collection point and described at least one collection point, with the mean value of the similarity of described target collection point and described at least one collection point, as the first similarity average of described target collection point;
Described second determines that subelement specifically is used for, according to the signal strength signal intensity of described target collection point and the signal strength signal intensity of described at least one collection point, determine in described at least one collection point each collection point and the similarity of adjacent collection point separately, according to described each collection point and the mean value of the similarity of adjacent collection point separately, determine the second similarity average of described at least one collection point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310108333.1A CN103200676B (en) | 2013-03-29 | 2013-03-29 | The method for building up of fingerprint base and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310108333.1A CN103200676B (en) | 2013-03-29 | 2013-03-29 | The method for building up of fingerprint base and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103200676A true CN103200676A (en) | 2013-07-10 |
| CN103200676B CN103200676B (en) | 2016-06-15 |
Family
ID=48722992
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310108333.1A Active CN103200676B (en) | 2013-03-29 | 2013-03-29 | The method for building up of fingerprint base and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103200676B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105491590A (en) * | 2014-09-15 | 2016-04-13 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| WO2018112825A1 (en) * | 2016-12-22 | 2018-06-28 | 华为技术有限公司 | Positioning method based on wi-fi access point, and device |
| CN109598723A (en) * | 2018-12-11 | 2019-04-09 | 讯飞智元信息科技有限公司 | A kind of picture noise detection method and device |
| CN110008671A (en) * | 2017-12-28 | 2019-07-12 | 腾讯科技（深圳）有限公司 | Data verification method and device |
| CN110099442A (en) * | 2019-05-05 | 2019-08-06 | 北京三快在线科技有限公司 | The change in location of the network equipment determines method, apparatus, computer equipment and medium |
| CN111837459A (en) * | 2018-03-06 | 2020-10-27 | 昕诺飞控股有限公司 | System and method for initializing lighting nodes using wireless signal characteristics for automatic re-network entry |
| CN113543307A (en) * | 2021-06-01 | 2021-10-22 | 北京邮电大学 | Visual information feature fingerprint database construction method, positioning method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090319448A1 (en) * | 2007-12-31 | 2009-12-24 | Industrial Technology Research Institute | Method and system for positioning |
| CN102111872A (en) * | 2009-12-23 | 2011-06-29 | 中国移动通信集团公司 | Location method and device based on fingerprint location technology |
| CN102186239A (en) * | 2011-04-13 | 2011-09-14 | 福建星网锐捷网络有限公司 | Radio frequency (RF) fingerprint positing method, device and network equipment |
| CN102695272A (en) * | 2012-05-25 | 2012-09-26 | 北京邮电大学 | Matching location method and mobile terminal |
-
2013
- 2013-03-29 CN CN201310108333.1A patent/CN103200676B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090319448A1 (en) * | 2007-12-31 | 2009-12-24 | Industrial Technology Research Institute | Method and system for positioning |
| CN102111872A (en) * | 2009-12-23 | 2011-06-29 | 中国移动通信集团公司 | Location method and device based on fingerprint location technology |
| CN102186239A (en) * | 2011-04-13 | 2011-09-14 | 福建星网锐捷网络有限公司 | Radio frequency (RF) fingerprint positing method, device and network equipment |
| CN102695272A (en) * | 2012-05-25 | 2012-09-26 | 北京邮电大学 | Matching location method and mobile terminal |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105491590A (en) * | 2014-09-15 | 2016-04-13 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| WO2018112825A1 (en) * | 2016-12-22 | 2018-06-28 | 华为技术有限公司 | Positioning method based on wi-fi access point, and device |
| US10925029B2 (en) | 2016-12-22 | 2021-02-16 | Huawei Technologies Co., Ltd. | Wi-Fi access point-based positioning method and device |
| CN110008671A (en) * | 2017-12-28 | 2019-07-12 | 腾讯科技（深圳）有限公司 | Data verification method and device |
| CN110008671B (en) * | 2017-12-28 | 2022-04-05 | 腾讯科技（深圳）有限公司 | Data verification method and device |
| CN111837459A (en) * | 2018-03-06 | 2020-10-27 | 昕诺飞控股有限公司 | System and method for initializing lighting nodes using wireless signal characteristics for automatic re-network entry |
| CN111837459B (en) * | 2018-03-06 | 2023-06-16 | 昕诺飞控股有限公司 | System, method and computer readable medium for initializing lighting nodes using wireless signal characteristics for automatic re-networking |
| CN109598723A (en) * | 2018-12-11 | 2019-04-09 | 讯飞智元信息科技有限公司 | A kind of picture noise detection method and device |
| CN110099442A (en) * | 2019-05-05 | 2019-08-06 | 北京三快在线科技有限公司 | The change in location of the network equipment determines method, apparatus, computer equipment and medium |
| CN110099442B (en) * | 2019-05-05 | 2020-10-23 | 北京三快在线科技有限公司 | Method and device for determining position change of network equipment, computer equipment and medium |
| CN113543307A (en) * | 2021-06-01 | 2021-10-22 | 北京邮电大学 | Visual information feature fingerprint database construction method, positioning method and device |
| CN113543307B (en) * | 2021-06-01 | 2022-06-03 | 北京邮电大学 | Visual information feature fingerprint database construction method, positioning method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103200676B (en) | 2016-06-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103200676A (en) | Method and device for building fingerprint database | |
| CN105933294B (en) | Network user's localization method, device and terminal | |
| CN105338498A (en) | Construction method for fingerprint database in WiFi indoor positioning system | |
| CN105282758A (en) | Self-adaptive dynamic construction method of WIFI indoor positioning system fingerprint database | |
| CN104837142A (en) | Calibration method of positioning reference point in wireless positioning system, and wireless positioning system | |
| CN103220780A (en) | Indoor positioning method, device and system | |
| CN113252053B (en) | High-precision map generation method and device and electronic equipment | |
| CN109982361A (en) | Signal interference analysis method, device, equipment and medium | |
| CN104463141A (en) | Fingerprint template input method and device based on intelligent card | |
| CN104936140A (en) | Positioning method, positioning device, fingerprint data obtaining method and fingerprint data obtaining device | |
| CN110798804A (en) | Indoor positioning method and device | |
| CN104715127A (en) | Identification method and system for complaint hot spot region | |
| CN104778238A (en) | Video saliency analysis method and video saliency analysis device | |
| CN108600945A (en) | Identify method, apparatus, equipment and the storage medium of double-terminal smart card | |
| CN105005024A (en) | Compression sensing and positioning method | |
| CN103781087A (en) | Information processing method and mobile terminal | |
| CN104457733A (en) | Indoor electronic device positioning system and method | |
| CN109558518A (en) | The method, apparatus and storage medium of community discovery in a kind of determining social networks | |
| CN110621025B (en) | Equipment model selection method and device | |
| CN106413084B (en) | A kind of equipment localization method and device | |
| CN102026144A (en) | Roaming performance test method, equipment and system thereof | |
| CN108419245A (en) | Sub-network division method and apparatus | |
| CN109766398B (en) | Method and device for dividing raster subareas based on GIS data | |
| CN103916873A (en) | Adjacent region configuring method and device for present network compensation station | |
| CN102968926A (en) | Symbol configuration system of zonal statistical map and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |