CN104618863A - Regional positioning system and method - Google Patents
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Abstract
The invention provides a regional positioning system, which comprises a server, a wireless signal transmitting device and a communication device. The wireless signal transmitting device defines the positioning range of the system in a specific form. When the target object with the communication device enters the positioning range, the communication device captures the intensity of the wireless signal from the wireless signal transmitting device, and the server analyzes the correlation between the target object and the positioning range according to the intensity of the captured wireless signal, so as to generate a positioning result. The technology focuses on the estimation and calculation of the divided region, and gives the system the regional positioning capability by adding map information and adopting the region average algorithm and/or the grade distribution algorithm.
Description
Technical field
The present invention mainly provides a kind of regional navigation system, particularly about a kind of navigation system containing area map information.
Background technology
In recent years, location technology generalizes in various entity apparatus and the equipment with Internet communication capacity gradually, such as computer, vehicle-carried and portable electronic devices etc.Carry universalness by wisdom mobile phone, people easily and exactly can understand self geographical position, also can therefore ability and know other services that periphery provides, as neighbouring dining room, sight spot and Information etc.The interior space is as the same, and such as, space in some building is very broad and complicated (comprising shopping mall market, hospital or government organs etc.), easily makes to get lost into interior personnel.Say from management layer, the personal management in this large-scale interior space and tracking be very inconvenience also.In order in response to these demands, the development of indoor positioning technologies also becomes a popular subject under discussion.
General indoor locating system can adopt radio frequency system to be used as solution, and the kind of this radio frequency system can comprise Wi-Fi, bluetooth and/or radio frequency identification (RFID).Compared with the environment that outdoor positioning is more spacious, the interference of the more necessary consideration barrier of indoor positioning, this is because the distribution density of indoor barrier is more intensive.For example, in the shopping plaza being full of the crowd or hospital, the error that wireless signal may cause signal to transmit because of the directivity of human body hinders.The hospital that such as partition architecture is more again, the wall of indoor compartment easily causes the reflection of wireless signal and causes somewhere reception bad.
Summary of the invention
Main purpose of the present invention is to provide a kind of navigation system that can solve indoor positioning.For achieving the above object, the invention provides a kind of regional navigation system, its framework has a plurality of wireless access point, one or more communication device and one or more server.These plural wireless access points are mainly to provide wireless signal covering scope and the orientation range defining native system with this.The object that described communication device will be located for native system, is responsible for receiving the wireless signal in orientation range, and responds the location information corresponding to wireless signal to server.The location information that server mainly arranges to utilize communication device to respond is to estimate region or the position of communication device.
Described server mainly performs following action: a virtual map relevant with a mapping intelligence (such as indoor coordinate diagram) is divided into nonoverlapping plurality of blocks, each block comprises one or more reference point, and each reference point corresponds to the one group wireless signal intensity (be considered as the position feature of this reference point) relevant with this reference point locations; According to the intensity of wireless signal relevant with described communication device and the intensity of each group wireless signal relevant with each reference point, determine the intensity distance of the wireless signal that described communication device is relevant with each reference point; According in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, determine the similarity of this block; And determine that described communication device is positioned at the probability of this block according to the similarity of these plurality of blocks.
Accompanying drawing explanation
Fig. 1 is the regional navigation system schematic diagram of one embodiment of the invention.
Fig. 2 illustrates a plane domain, and the setting position of its display wireless access point and object receive the schematic diagram of signal.
Fig. 3 A is the off-line phase running schematic diagram of the regional navigation system of the present invention.
Fig. 3 B is the line step operation schematic diagram of the regional navigation system of the present invention.
Fig. 4 is that the regional navigation system of the present invention is in the workflow diagram of off-line phase.
Fig. 5 is the block set by Fig. 2 region and reference point.
The zone leveling algorithm steps of Fig. 6 performed by the regional navigation system of the present invention.
Fig. 7 is the schematic diagram of illustration one orientation range and object.
The grade partition algorithm steps of Fig. 8 performed by the regional navigation system of the present invention.
Symbol description:
10 servers
12 wireless signal emitters (AP)
14 communication devices
20 wireless signal emitters (AP)
22 objects
A, B, C, D compartment
30 device ends (off-line phase)
32 server-sides (off-line phase)
34 device ends (line stage)
36 server-sides (line stage)
40 to 48 steps
51 blocks
52 reference points (RP)
60 to 68 steps
7 orientation ranges
A, b, c, d block
A1 to d4 reference point (RP)
80 to 84 steps
Embodiment
Describe cooperation diagram in detail illustrative embodiments below.But these embodiments can be contained in different forms, and should not be interpreted as limiting the present invention.Thering is provided of these embodiments makes exposure of the present invention clear and definite and abundant, and the people knowing this technology can understand content of the present invention via those embodiments.
In whole part specification and claim, term have within a context suggested or hint, exceed its meaning clearly stated.Similarly, term " in one embodiment ", for time herein, might not refer to identical specific embodiment, and term " in another embodiment " is for time herein, also not necessarily refers to different specific embodiments.For example, original idea wishes that the target advocated can comprise the combination of illustrative embodiment on the whole or in part.
Generally speaking, can making for understanding term from the context at least partly.For example, used in this article similarly be " and ", "or" or " and/or " etc. term can comprise various meaning, it is determined according to using the context of this kind of term at least partly.Generally speaking, such as, if use "or" to associate a list, A, B or C, then refer to it is as inclusive meaning A, B and C herein, and specificity meaning A, B or C.In addition, term " one or more " is at least part of in this article has any feature of singulative, structure or characteristic based on context in order to describe, or the combination of the feature of plural form, structure or characteristic.Similarly, such as the term such as " ", " being somebody's turn to do " or " described " is also based on context be understood to pass on singulative usage or pass on plural form usage at least partly.In addition, term " based on " be interpreted as not necessarily to pass on one group of special factor, but other factors that may not be described explanation can be there are, it is based on context determined at least partly.
In the following embodiment of the present invention, calculation is performed by one or more server, described server has the ability of network communication, especially have and through the ability of base station and communication device communication and the ability of locating and calculating can be performed, and comprise at least one storage device (as memory body) store algorithm and one or more processor perform as described in algorithm.Server is the information returned according to one or more base station of providing services on the Internet, and calculates the position of the communication device corresponding to base station.In other embodiments of the present invention, described calculation also can performed by the communication device of tool computing capability itself, and this communication device itself has with the ability of one or more server communication and comprises one or more processor and carrys out execution algorithm.Described communication device can be Wearable communication device, such as, have wisdom mobile phone, the smart watch of ability to communicate, or the electronic type fetters that specifically monitored object is dressed.
Consult shown in Fig. 1, be an embodiment of the regional navigation system of the present invention, described system, with performing a regional localization method, obtains a positioning result by this.This system comprises one or more server 10, one or more wireless signal emitter 12 and one or more communication device 14.Described server 10 is provided with one or more processor, a storage device, a conversion module and an estimation module.Described server 10 has the ability (such as through network connectivity) of data transmission, and the ability that server 10 itself has execution computing given by processor.Above-mentioned module mainly performs specific algorithm respectively according to a metrology data.And the foundation of metrology data and the algorithm performed by each module will describe in detail in subsequent paragraph.
Described storage device is arranged in server 10, with store server 10 collected (or collection) data (as aforementioned metrology data) and by server 10 the data storage set up, for processor access.But this storage device also can be arranged at outside server 10, as high in the clouds hard disc, access for server.Described module of changing arranges with the data received by server 10 or data transaction or converges whole into a profile, performs positions calculations for estimation module according to this profile.Described estimation module mainly utilizes provincial characteristics contained in this profile to calculate the probability that object appears at certain region.
Described wireless signal emitter 12 arranges to provide a wireless signal covering scope.The kind of wireless signal can comprise Wi-Fi, bluetooth and/or other forms, is preferably Wi-Fi.The intensity of wireless signal is relevant with signal propagation distance and terrain obstruction.Consult shown in Fig. 2, a two dimensional surface region illustrated in the embodiment of the present invention, it comprises a plurality of compartment, as illustrated A to F.In this region, scattering device has four wireless signal emitters 20 (wireless access point), and it is distinctly positioned in compartment A, B, E and F.For this two dimensional surface region, the setting position of wireless signal emitter 20 and magnitude setting not as in figure limit, it can adjust according to actual geographic environment.If such as the area of single compartment is enough large, then can consider to set up plural wireless signal emitter 20.Must guarantee, any one position in this region must at least contain by the wireless signal of a wireless signal emitter 20, be all the state having reception for including any position of orientation range in Yi Jigai district.In other embodiments of the invention, according to the difference of mapping intelligence, such as hospital or office, and 2 dimensional region or three-dimensionally to consider, the configuration of wireless signal emitter 20 need correspondingly adjust, and the magnitude setting of such as wireless signal emitter 20 can be greater than or less than four.It should be noted that the mapping intelligence illustrated in Fig. 2 is place in a sealing chamber; So, the mapping intelligence that the regional navigation system of the present invention and method adopt is not limited to this type of, also can comprise the place of semi open model, the combination of the such as interior space and balcony or periphery garden.Described wireless signal emitter 20 has the ability with communication device 14 line, but in other embodiments of the invention, described wireless signal emitter 20 also can with server 10 and communication device 14 line (not shown).
Described communication device 14 has the ability with server 10 communication, and has the ability receiving wireless signal, and such as mobile phone, computer, portable apparatus and/or Wearable device etc., be preferably Wearable device.The setting of described communication device 14 is relevant with the position for localizing objects thing (as shown in Figure 2 22).Such as, described communication device 14 can be a kind of electronic fetter with ability to communicate, and it can depend on it convict, as native system want the object of locating and monitoring.Described communication device 14 has intensity (the Received Signal Strength of the wireless signal that detecting receives, hereinafter referred to as RSS) ability, such as can represent by dB, and the wireless signal emitter 12 corresponding to this RSS can be distinguished, such as with Fig. 2, communication device 14 periodically can capture RSS, and it comprises RSS
a, RSS
b, RSS
eand RSS
f.The computing that the RSS information performance objective thing that namely server 10 is collected according to communication device 14 is located.In other embodiments of the present invention, work performed by the alternative aforementioned server 10 of some communication device 14 (such as wisdom mobile phone), namely meaning can pass through and is configured with processor, storage device, conversion module and estimates that the communication device 14 of module is to perform algorithm of the present invention.
Be different from the position that traditional indoor positioning can only estimate object, navigation system of the present invention is then adopt a kind of concept of Region dividing to take the location of object.Through the metric data associated by Region dividing, just calculate the probability in a certain region, object place through a zone leveling algorithm and first-class grating division calculation method.
Consult shown in Fig. 3 A and Fig. 3 B, navigation system of the present invention can be divided into two stage operation, is namely divided into off-line phase (offline phase) and line stage (online phase).
As Fig. 3 A, described off-line phase, be to set up a profile storehouse relevant to mapping intelligence, the wireless signal that meaning i.e. this stage mainly arranges (two dimensional surface region, three dimensions) in mapping intelligence relevant range is therewith contained, and record the RSS data of each ad-hoc location in this region, as the feature of each ad-hoc location.As Fig. 3 B, namely the described line stage enters the state of total system practical operation, and its instant data returned at profile and the object of the construction of off-line phase institute according to system obtains the positioning result of object via described algorithm.Below will be described with Fig. 3 A and Fig. 3 B other flow charts of arranging in pairs or groups.
At the framework shown in Fig. 3 A, device end 30 and server-side 32 can be divided into.Described device end 30 is a device, and it has the ability of identification RSS and the ability with server-side 32 communication, such as communication device.In another embodiment of the invention, device end 30 can be plural devices, and such as can be can the measuring equipment of identification RSS and the input unit etc. with server-side 32 communication.Server-side 32 itself can have data and converge whole ability, the data to arrange received from device end 30 is become well-regulated data bank and stores.About the detailed step building data bank, will illustrate in subsequent paragraph.
Consult shown in Fig. 4, for native system is at the operating procedure flow chart of off-line phase.First, the scope (step 40) for location is determined according to a mapping intelligence.If Fig. 2 is the interior space including the plurality of compartments such as A, B, C, D, E and F.Certainly, described mapping intelligence also can be the region of semi open model, or the indoor/external space of solid.With the orientation range associated by mapping intelligence can virtual after be stored in the storage device of server 10, participate in the computing of subsequent step.
Then, the position (step 42) of the wireless signal emitter 12 being associated with described orientation range is defined.Again consult Fig. 2, in the off-line phase of native system, according to shape and the position of one or more wireless signal emitter 12 of barrier (such as wall) determining positions that comprises of orientation range, guarantee suitable wireless signal transmission and covering scope.In further embodiments, the position of wireless signal emitter 12 not necessarily will be arranged at within orientation range.Each wireless signal emitter 12 of the embodiment of the present invention can be considered the wireless access point (Wireless AccessPoint, hereinafter referred to as AP) in this region.Once in the position determining each AP in present stage, also remain unchanged after entering the line stage.
Consult shown in Fig. 5, show the region identical with Fig. 2.System of the present invention determines a plurality of location block 51 (step 44) according to described orientation range.This means, orientation range is divided into plurality of blocks 51.If orientation range is region, be then divided into a plurality of plane block.If orientation range is solid space, be then divided into a plurality of three-dimensional block (not shown).The size of these plural number location blocks 51 is equal, and can be adjacent or non-conterminous between these location blocks 51, but not overlapping.In further embodiments, the block 51 divided not necessarily needs identical size.It should be noted that the consistency of these location block 51 sizes, and between these blocks 51, adjacent degree can determine the accuracy of final positioning result.
Further, determine one or more reference point 52 (ReferencePoint, hereinafter referred to as RP) according to determined block 51, described RP 52 is for being arranged at the virtual location (step 46) of each block 51.And the arrangement mode of described RP 52 can be determined by the size of block 51, embodiment as shown in Figure 5, each block 51 is provided with the RP 52 that two take advantage of two, and arranges in equidistant mode between 2.Each RP 52 should comprise and the orientation information associated by it further, such as east, south, west, north.This is that the orientation residing for object is relevant with the result of location due in actual location operation.
Therefore, for the ease of follow-up explanation, each RP 52 may be defined as described below,
Wherein k represents a kth block 51, n
krepresent n-th in a kth block 51
kindividual RP 52, o represents the orientation (east, south, west, north) of this PR.Position according to these plural RP 52 obtains the RSS information (step 48) about these plural AP.Specifically, measure the RSS relevant with these plural AP in the position of each RP 52, suppose that its RSS sequence definition of RSS measuring h time from m platform AP is
Then will
average RSS Definition of Vector be,
Wherein
for
receive the average RSS of m platform AP.
Then by above-mentioned
the MAC address (MAC address) of corresponding coordinate (namely the position of described mapping intelligence, block, AP, block and RP can by XY coordinate definition), each AP and
etc. information, with in the storage device of the form of data bank stored in described server, in order to as the feature about positioning action.If mapping intelligence is solid space, then can be other three-dimensional coordinates to define each position.After having built of data bank, the off-line phase of native system can be terminated, and the company's present stage entering native system carries out the location of object.The present invention is by illustration one zone leveling algorithm (AreaAverage) and first-class level partition algorithm (Level Assigning), what both taked is a kind of estimation of area concept, belong to a kind of region algorithm for estimating, it is the positioning result being associated with described object based on aforementioned built data bank.
Zone leveling algorithm
Again consult the framework shown in Fig. 3 B, device end 34 and server-side 36 can be divided into.The portable apparatus of described device end 34 entrained by localizing objects thing (as wisdom mobile phone) or Wearable device (as wisdom wrist-watch), it mainly has the ability with aforementioned set AP and server communication.Device end 34 periodically can transmit the information relevant with object position to server-side 36.Connect present stage at this, server-side 36 according to the information received from device end 34 (with object position about) be associated with a positioning result via performing the region predictive algorithm that server-side 36 itself configures.Server-side 32 herein can be identical person with the server-side 32 described in Fig. 3 A, also can be different person, but can jointly access the data in storage device, as can to off-line phase the data bank that builds access.Server-side 34 carries out analyzing according to received information (namely receiving the information relevant with object position from device end 34) and estimates that algorithm is associated with positioning result via region.About the detailed step building data bank, will illustrate in subsequent paragraph.In other embodiments of the present invention, described region algorithm also performed by other devices outside server-side, or can be performed by multiple device segmentation.
Consult shown in Fig. 6, this algorithm can performed by server-side.First, server-side is according to the data bank that built and define and reference point from the data that device end receives
relevant RSS distance (step 60).Specifically, receive the one group of RSS being associated with these plural AP device end 34 meeting periodicity (such as every 5 seconds once) and be sent to server-side 36.This group RSS making device end 34 receive at time point t (corresponding to a coordinate position) is,
Wherein,
for device receives the RSS of m platform AP at moment t.Then, will
with data bank
compare, to define object and reference point
relevant RSS distance, such as, can be Ou Ji Reed distance (Euclidean Distance),
Therefore
numerical value depend on
with q
tsimilarity, the degree that namely object (device end) and reference point are close.In other words,
number less, represent object and likely appear at corresponding reference point
near.D is made to be all
set, namely
specifically, above-mentioned computing is the mode utilizing RSS distance, is presented by object in the relevance between the position and all reference points of this time point t.
Described region algorithm, is mainly to utilize T before in each block (the block A to F as Fig. 2)
rthe RSS distance that name is minimum
mean value go to calculate the similarity degree in each region and object position in the probability of this block, finally find out estimation region and coordinate.For specifically presenting this algorithm, cooperation Fig. 7 is described by the step of the following stated.
Perform step 62, for T front in region each in orientation range
rthe minimum RSS distance of name gets its mean value.For example, Fig. 7 illustrates an orientation range 7, it is divided into region a, b, c and d of the quartering, and each region is provided with four reference points, and wherein a1 to a4, b1 to b4, c1 to c4 and d1 to d4 are respectively a RP, the 2nd RP, the 3rd RP and the 4th RP in each region.When object 71 be positioned at as illustrated in the drawing position time, according to step 60, the relevance between this object 71 and each RP can by RSS distance
determine.The numerical value of described RSS distance can be determined by the position relevance between this object 71 and RP and orientation.As table one illustrate each reference point of this object 71 corresponding block a the RSS distance that calculates, and according to the result of RSS distance size rank.
Table one, RSS distance rank corresponding relation between object and region a reference point.
Make T
requal 3, namely get the front three of RSS distance minimum value, and get its mean value
with table one, relevant to block a
by that analogy, sequentially calculate relevant to block b, c and d
it should be noted that T
rnumerical value should be less than the quantity of RP in each block (with Fig. 7, T
rcan be 3,2 or 1).
Enter step 64, make D
afor all blocks
set, with the example of Fig. 7, then the set of the result of calculation of block a to d.Therefore, D
ain minimum
value, it reflects that corresponding block is the block that object most possibly occurs.Then, the similarity of a block depends on this block
be worth immediate front T
adifference between the block of name.Specifically, suppose what block a to d calculated
value as shown in Table 2, this for try to achieve the block of similarity be bring with
numerical ranks is (T
a+ 1) high block subtracts each other.Such as, T is being made
abe under the condition of 3, the similarity of block a, block b and block c then calculates, as shown in following table three according to this rule.
The average RSS distance that each region that table two, illustration are associated with this object calculates.
| Block | a | b | c |
| Similarity | 50-20＝30 | 50-30＝20 | 50-40＝10 |
The similarity (degree that object may occur) of table three, each block.
It should be noted that T
anumerical value should be less than the quantity of block, and table three does not show block d, be due to its calculate after similarity be zero.
Enter step 66, determine object position probability within a block according to described similarity.Specifically, the probability that this object comes across a block equaled the similarity of this block except former T
aname similarity sum.Such as, with table three, at T
aunder the condition remained unchanged, the probability of each block can this rule calculate, and its probit value is as shown in following table four.
The probability (object is positioned at the probability of each block) of table four, each block.
Then, according to a threshold value ρ
aAselect a probability set.Such as, select probability be greater than and/or equal ρ
aAblock sets, and these break through threshold value ρ
aAblock sets can be regarded as a positioning result.This positioning result can present via any display unit with this server-side line, and the mode presented can be the form of block to probability numerical value presents, or presents in the mode of virtual map block.Such as, with table four, ρ
aAcan be 30%, then object positioning result drops on block a and block b.It can thus be appreciated that the number of positioning result can be relevant with the setting of threshold value.
Above-mentioned positioning result shows in zonal mode to point out the position of object in plane domain; Certain above-mentioned steps also can be used for the object location in solid space.In other words, for the location of solid space, data bank build and in computing must adopt three-dimensional coordinate system to define mapping intelligence, AP position and RP position etc.This field has knows that the knowledgeable should be able to understand that above-mentioned algorithm can change its mode of operation in response to other coordinate systems usually, thus related content no longer this repeats.
In order to estimate object location point residing within a block further, zone leveling algorithm provided by the present invention can comprise the step that object coordinate is estimated further.The result that this coordinate is estimated is relevant with the positioning result of aforementioned algorithm, and its detail specifications is as follows.
Continuity step 68, wherein according to described threshold value ρ
aAselected block sets, T before finding out in these blocks
plittle RSS distance, wherein T
pfor being used for the RP quantity that estimated coordinates considers, such as, can be T
p=3, and the RSS distance defined in RSS distance herein and step 60
identical, and each
value is associated with again a RP.In other words, the coordinate of object is estimated first surely to determine the RP more close with this object position.Certainly, in other enforcements of this case, the degree of closeness of object and each RP also can adopt other modes to define.Next, utilize according to T
pone or more RP determined decides the estimated coordinates of this object.For example, the estimated coordinates of this object can be three and (supposes T
p=3) average with this object immediate RP coordinate.So, give this system can estimate in positioning result further object may near or position coordinate position.
Grade partition method
Consult shown in Fig. 8, this algorithm can performed by the server-side 36 of Fig. 3 B.First, server-side 36 carrys out objective definition thing RSS distance (step 80) relevant with described RP according to the data bank built and from the data that device end 34 receives, and namely defines as abovementioned steps 60
therefore its detailed content no longer this repeats.Following steps are supposed to explain with the example of Fig. 7 equally.
According to RSS distance definition one distribution of grades that front L name is minimum, described distribution of grades is made up of a plurality of grade, and wherein each grade is associated with a rating fraction (step 82).Specifically, the little value of L before getting in the set of the RSS distance acquired by step 80.As following table five, for getting the minimum RSS distance of top ten list (L=10), namely meaning finds out ten RP be close most with current goal object location, and according to its RSS distance size rank.Then, be partitioned into a plurality of interval between minimum RSS distance (a4-1,18.1) in RSS distance rank and the numerical value of maximum RSS distance (c2-1,25.6), namely each interval is defined as a grade.
| Rank | Reference point RP (according to orientation) | RSS distance | Rating fraction |
| 1 | a4-1 | 18.1 | 10 |
| 2 | a2-1 | 18.3 | 10 |
| 3 | b3-1 | 19.2 | 9 |
| 4 | a4-0 | 19.5 | 9 |
| 5 | b1-2 | 20 | 8 |
| 6 | a2-2 | 22.1 | 5 |
| 7 | b1-3 | 22.6 | 5 |
| 8 | c2-0 | 23.5 | 3 |
| 9 | d1-0 | 24.8 | 2 |
| 10 | c2-1 | 25.6 | 1 |
The rating fraction (L=10) of RSS distance corresponding in determined distribution of grades that table five, front L name are minimum.
For example, ten interval deciles can be partitioned between 18.1 and 25.6, namely each is divided into 0.75=(25.6-18.1)/10, then the first interval is 18.1 to 18.85, second interval is 18.5 to 19.6,3rd interval is 19.6 to 20.35,4th interval is 20.35 to 21.1,5th interval is 21.1 to 21.85,6th interval is 21.85 to 22.6, is 22.6 to 23.35 between SECTOR-SEVEN, is 23.35 to 24.1 between Section Eight, 9th interval is the 24.1 to 24.85, ten interval is 24.85 to 25.6.These complex interval are considered as different brackets, each grade gives a rating fraction, such as 18.1 to 18.85 give rating fraction for very, 18.85 to 19.6 to give rating fraction be nine, can give the rating fraction of these grades one to ten by that analogy, mark is higher, and to represent the correlation degree of described RP and this object position higher.Therefore, as shown in Table 5, the interval (grade) of each RP wherein corresponding to its RSS distance values can be associated with a rating fraction.
In above-described embodiment, interval dividing number determined by L.But dividing number interval in other embodiments also can be greater than or less than L, and the parsing degree of this visual object thing and RP relevance decides.
After defining the rating fraction of each rank RP, the rating fraction according to these blocks corresponding to rank RP and rank RP calculates the probability (step 84) that this object is positioned at described block.Specifically, the block of determined rating fraction according to RP place is done to add up as s
k(s
k, k is a kth block), be considered as the similarity of this block and this object.With table five for example, the rating fraction of reference point a4-1, a2-1, a4-0 and a2-2 adds up the similarity for block a, and the rating fraction of reference point b3-1, b1-2 and b1-3 adds up the similarity for block b, by that analogy.Therefore, the similarity that can obtain block a according to the rating fraction of table five is 34 points, block b is 22 points, block c is four points, block d is two points.Then object is positioned at the probability of a kth block and is
If with table five, the probability result of calculation of each block is as shown in following table six.
The probability (object is positioned at the probability of each block) of table six, each block.
Then, according to a threshold value ρ
lAselect a probability set.Such as, select probability be greater than and/or equal ρ
lAblock sets, and these break through threshold value ρ
lAblock sets can be regarded as a positioning result.This positioning result can present via any display unit with this server-side line, and the mode presented can be the form of block to probability numerical value presents, or presents in the mode of virtual map block.Such as, ρ
lAcan be 30%, then drop on block a and block b with the object positioning result of table six.
Above-mentioned positioning result shows in zonal mode to point out the position of object in plane domain; Certain above-mentioned steps also can be used for the object location in solid space.In other words, for the location of solid space, data bank build and in computing must adopt three-dimensional coordinate system to define mapping intelligence, AP position and RP position etc.This field has knows that the knowledgeable should be able to understand that above-mentioned algorithm can change its mode of operation in response to other coordinate systems usually, thus related content no longer this repeats.
In addition, identical with region algorithm, the coordinate estimation that step 84 carries out object can be continued in grade partition algorithm.According to described threshold value ρ
lAselected block sets, T before finding out in these blocks
plittle RSS distance, and the coordinate corresponding to it is in addition average, obtain the estimated coordinates of this object.So, give this system can estimate in positioning result further object may near or position coordinate position.
Demonstrated by above embodiments of the invention, regional navigation system provided by the present invention, mainly set up (comprising mapping intelligence, the setting of AP, RP and relative RSS feature), reference point RP and the technical characterstic such as the similarity analysis of object and the conversion of rank, similarity and probability via data bank, the position of object and plane/area of space are produced association, and then produce the positioning result of this object, and the average concept of similarity can be utilized again further to estimate the coordinate of this object.
Claims (28)
1. a regional navigation system, comprises:
One communication device, receive multiple wireless signals that a plurality of wireless access point sends, and judge the intensity of these wireless signals, these plural wireless signals determine the orientation range of this system; And
One server, with described communication device line, to receive the intensity of these wireless signals that described communication device transmits, and performs:
This orientation range is divided into nonoverlapping plurality of blocks, and each block comprises one or more reference point, and each reference point corresponds to the intensity of the one group wireless signal relevant with this reference point locations;
According to the intensity of wireless signal relevant with described communication device and the intensity of each group wireless signal relevant with each reference point, determine the intensity distance of the wireless signal that described communication device is relevant with each reference point;
According in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, determine the similarity of this block; And
Similarity according to these plurality of blocks determines that described communication device is positioned at the probability of this block.
2. regional navigation system according to claim 1, is characterized in that, these plurality of blocks be divided measure-alike.
3. regional navigation system according to claim 1, is characterized in that, these plural reference points are defined in each block in mode equidistant each other.
4. regional navigation system according to claim 1, is characterized in that, the intensity that the execution of described server still comprises intensity average out to one wireless signal of this group wireless signal by being associated with each reference point is average, and it is relevant with each reference point.
5. regional navigation system according to claim 4, it is characterized in that, the intensity distance of the wireless signal that described communication device is relevant with each reference point on average determined by the intensity of the intensity of the wireless signal relevant with described communication device and the wireless signal relevant with each reference point.
6. the regional navigation system according to any one in claim 1 to 5, it is characterized in that, described foundation in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, the intensity distance of these wherein relevant with these part reference points wireless signals sorts by one of numerical values recited and determines, the total amount of described sequence is less than the quantity of reference point in this block.
7. regional navigation system according to claim 6, it is characterized in that, the intensity distance of wireless signal relevant with these part reference points in described server each block average, to determine the intensity distance of the average wireless signal relevant with each block.
8. regional navigation system according to claim 7, is characterized in that, the difference between the intensity distance of the average wireless signals of these plural numbers that described server foundation is relevant with these plurality of blocks, determines the similarity of each block.
9. regional navigation system according to claim 8, is characterized in that, described server, according to the proportionate relationship of the relevant similarity of these plurality of blocks, determines that described communication device is positioned at the probability of each block.
10. the regional navigation system according to any one in claim 1 to 5, it is characterized in that, described server according in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, the intensity of these wherein relevant with these part reference points wireless signals sorts by one of numerical values recited and determines, the total amount of described sequence is less than the reference point quantity in these plurality of blocks.
11. regional navigation systems according to claim 10, it is characterized in that, each reference point one rating fraction in these part reference points specified respectively by described server according to a distribution of grades, this distribution of grades defined by a maximum relevant with these part reference points and a minimum value.
12. regional navigation systems according to claim 11, it is characterized in that, the rating fraction relevant with these part reference points adds up by each block by described server, and the rating fraction that the rating fraction added up according to each block and these Partial Block entirety add up, determine that described communication device is positioned at the probability of each block.
13. regional navigation systems according to claim 1, it is characterized in that, described server determines the block the most close with described communication device according to a threshold value, and the reference point in the block utilizing this threshold value to determine produces an estimated position of closing and being connected in described communication device.
14. regional navigation systems according to claim 1, is characterized in that, these plural wireless access points described, according to a mapping intelligence scattering device.
15. 1 kinds of regional localization methods, the covering scope of a plurality of wireless signals that its orientation range is sent by a plurality of wireless signal access point determined, comprises:
Via a server, this orientation range is divided into nonoverlapping plurality of blocks, each block comprises one or more reference point, and each reference point corresponds to the intensity of the one group wireless signal relevant with this reference point locations;
Via a server, according to the intensity of wireless signal relevant with described communication device and the intensity of each group wireless signal relevant with each reference point, determine the intensity distance of the wireless signal that described communication device is relevant with each reference point;
Via a server, according to the intensity of wireless signal relevant with described communication device and the intensity of each group wireless signal relevant with each reference point, determine the intensity distance of the wireless signal that described communication device is relevant with each reference point;
Via a server, according in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, determine the similarity of this block; And
Via a server, the similarity according to these plurality of blocks determines that described communication device is positioned at the probability of this block.
16. regional localization methods according to claim 15, is characterized in that, these plurality of blocks be divided measure-alike.
17. regional localization methods according to claim 15, is characterized in that, these plural reference points are defined in each block in mode equidistant each other.
18. regional localization methods according to claim 15, is characterized in that, comprise via a server, and by average for the intensity being associated with intensity average out to one wireless signal of this group wireless signal of each reference point, it is relevant with each reference point.
19. regional localization methods according to claim 15, it is characterized in that, the intensity distance of the wireless signal that described communication device is relevant with each reference point on average determined by the intensity of the intensity of the wireless signal relevant with described communication device and the wireless signal relevant with each reference point.
20. according to claim 15 to the regional localization method described in any one in 19, it is characterized in that, described foundation in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, the intensity distance of these wherein relevant with these part reference points wireless signals sorts by one of numerical values recited and determines, the total amount of described sequence is less than the quantity of reference point in this block.
21. regional localization methods according to claim 20, it is characterized in that, comprise the intensity distance carrying out wireless signal relevant with these part reference points in each block average via a server, to determine the intensity distance of the average wireless signal relevant with each block.
22. regional localization methods according to claim 21, is characterized in that, comprise via a server according to the average wireless signals of these plural numbers relevant with these plurality of blocks intensity distance between difference, determine the similarity of each block.
23. regional localization methods according to claim 22, is characterized in that, comprise via the proportionate relationship of a server according to the relevant similarity of these plurality of blocks, determine that described communication device is positioned at the probability of each block.
24. according to claim 15 to the regional localization method described in any one in 19, it is characterized in that, comprise via one server according in these plurality of blocks with the intensity distance of the related wireless signal of part reference point, the intensity distance of these wherein relevant with these part reference points wireless signals sorts by one of numerical values recited and determines, the total amount of described sequence is less than the reference point quantity in these plurality of blocks.
25. regional localization methods according to claim 24, it is characterized in that, comprise and specify each reference point one rating fraction in these part reference points via a server respectively according to a distribution of grades, this distribution of grades defined by a maximum relevant with these part reference points and a minimum value.
26. regional localization methods according to claim 25, it is characterized in that, comprise and via a server, the rating fraction relevant with these part reference points is added up by each block, and the rating fraction that the rating fraction added up according to each block and these Partial Block entirety add up, determine that described communication device is positioned at the probability of each block.
27. regional localization methods according to claim 26, it is characterized in that, comprise and determine the block the most close with described communication device via a server according to a threshold value, and the reference point in the block utilizing this threshold value to determine produces an estimated position of closing and being connected in described communication device.
28. regional localization methods according to claim 27, is characterized in that, these plural wireless access points, according to a mapping intelligence scattering device.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW103146028A TWI583984B (en) | 2014-12-29 | 2014-12-29 | System and method for regional positioning |
| TW103146028 | 2014-12-29 |
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| CN104618863A true CN104618863A (en) | 2015-05-13 |
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| CN201510038270.6A Withdrawn CN104618863A (en) | 2014-12-29 | 2015-01-26 | Regional positioning system and method |
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| TW (1) | TWI583984B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI637189B (en) * | 2016-10-27 | 2018-10-01 | 臺灣高等法院檢察署 | Indoor area positioning system and method thereof |
| CN112017259A (en) * | 2020-08-27 | 2020-12-01 | 河北工业大学 | Indoor positioning and image building method based on depth camera and thermal imager |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI650973B (en) * | 2017-03-30 | 2019-02-11 | 財團法人電信技術中心 | Wireless communication based method for collecting data |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7711375B2 (en) * | 2002-08-06 | 2010-05-04 | Hang Liu | Method and system for determining a location of a wireless transmitting device and guiding the search for the same |
| US7151446B2 (en) * | 2003-08-01 | 2006-12-19 | Spectrum Tracking Systems, Inc. | System for tracking and locating an object using a cellular network |
| TWI392890B (en) * | 2008-05-09 | 2013-04-11 | Sheng Feng Huang | A local positioning information system implemented with gps information, local positioning space coordinate system and short-distance positioning signal sender/receiver |
| CN101592722B (en) * | 2008-05-28 | 2013-08-28 | 无锡奥盛信息科技有限公司 | Area positioning system and method thereof |
| CN103874016B (en) * | 2012-12-18 | 2017-10-20 | 中兴通讯股份有限公司 | Area positioning system and method |
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2014
- 2014-12-29 TW TW103146028A patent/TWI583984B/en active
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2015
- 2015-01-26 CN CN201510038270.6A patent/CN104618863A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI637189B (en) * | 2016-10-27 | 2018-10-01 | 臺灣高等法院檢察署 | Indoor area positioning system and method thereof |
| CN112017259A (en) * | 2020-08-27 | 2020-12-01 | 河北工业大学 | Indoor positioning and image building method based on depth camera and thermal imager |
| CN112017259B (en) * | 2020-08-27 | 2023-08-01 | 河北工业大学 | Indoor positioning and image building method based on depth camera and thermal imager |
Also Published As
| Publication number | Publication date |
|---|---|
| TWI583984B (en) | 2017-05-21 |
| TW201624001A (en) | 2016-07-01 |
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