CN1602020A - Indoor precision positioner and positioning algorithm of radio local network - Google Patents
Indoor precision positioner and positioning algorithm of radio local network Download PDFInfo
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- CN1602020A CN1602020A CN 200410067530 CN200410067530A CN1602020A CN 1602020 A CN1602020 A CN 1602020A CN 200410067530 CN200410067530 CN 200410067530 CN 200410067530 A CN200410067530 A CN 200410067530A CN 1602020 A CN1602020 A CN 1602020A
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Abstract
The invention is particularly applicable to locating in doors local area and vertical space range. The system is composed of locating environment, locating induction points, and locating devices including location inductor, location retuning back system and design for location inductors. Locating algorithm includes: basic locating algorithm based on probability distribution, median filtering algorithm, four direction filtering algorithm and weight algorithm of locating induction points etc. Based on wireless local area network, the method possesses features of steady technique, high precision, and locating capability to 3-5 meters.
Description
Technical field
The present invention relates to the accurate positioning device and the location algorithm in a kind of radio signal propagation field, refer to a kind of WLAN (wireless local area network) indoor accurate position device and location algorithm of positioning in indoor local scope and spatial vertical scope of being used for especially.
Background technology
Location technology one is to being made earnest efforts one of technology of studying, the technology that is used for location-based service has at present developed several generations, maximum is the GPS system that is called as GPS (Global PositionSystem), the gps satellite of 24 roamings aloft of this dependence is given the system of global user-provided location service, provide crucial information to the people who needs the position location in a large number, solved that open-air position is determined and problem such as track following.And in the last few years, wide area cellular network location technology based on RF has had significant progress, it utilizes broad covered area in the city, accept the high characteristics of precision, adopted the measuring-signal decay, measure the angle of arrival (AOA), the method of step-out time analysis (TDOA), progressively improved positioning accuracy, incity, city position application has been pushed to practicability, particularly the universalness of its terminal equipment-mobile phone and to the requirement of terminal equipment not as the so high characteristic of GPS, make domestic consumer under the situation that low cost is pointed out, can enjoy positioning service, promote rapidly and become possibility, the technology that adopts Gao Tong company to be developed in the KDDI of Japan company for example, the technology of 100 different position-based services was provided already, and the head of a family can utilize mobile phone to follow the trail of the position of its child in the park, and the cellphone subscriber can find the commodity of Tokyo Ginza cents-off promotion etc.In Korea S, also have about 2,000,000 citizen utilize the wireless location service of cellular network seek near friend or easily coffee shop get together.
Though location technology has obtained significant progress, on market, obtained success, obtained income, but the precision that present location technology can reach also is not very high, no matter be the location technology that GPS also is based on the 2.5G mobile communication technology, can only about 50 meters scopes, position substantially, so use occasion is confined to outdoor and part is indoor, technical limitation has limited application and development, can't implement on the indoor basis that is applied in these technology of carrying out information and positional information interaction.
Summary of the invention
In order to overcome above-mentioned weak point, main purpose of the present invention aims to provide a kind of new, an effective Algorithm Analysis method of cover and theory, can carry out accurate localization device and location algorithm in indoor local scope and spatial vertical scope, this method is based on employed location algorithm in the terminal positioning technology on the WLAN (wireless local area network) Wireless Local Area Network, by this algorithmic technique, can on the WLAN (wireless local area network) stationkeeping ability, obtain the WLAN (wireless local area network) indoor accurate position device and the location algorithm of considerable raising.
The technical problem to be solved in the present invention is: solve the relevant software and hardware problem in wireless local area network technology and the signal communications, solve in the WLAN (wireless local area network) location, the input parameter of signal is not abundant, it is simple that the matching way of signal also seems, but but not situation so in actual conditions, under actual conditions, exist following situation:
1, signal has certain human factor and causes signal drift in test and in actual location;
2, environment is very important to the influence of signal, comprises the density of surrounding population, the variation of temperature humidity;
3, different points may have very similarly signal numerical value;
The existence of these problems makes that the effect of location algorithm is very obvious, and this patent will solve technical problems such as an effective Algorithm Analysis method of cover and theory.
The technical solution adopted for the present invention to solve the technical problems is: this system is made up of systems such as localizing environment, location induction point and positioning equipments, comprise: positioning inductor, location return system, positioning inductor are arranged, signal passback wireless local area network (WLAN) system is arranged and location induction point design, wherein:
Positioning inductor arranges that module, signal passback wireless local area network (WLAN) system layout are connected with Design Orientation environment arrangement module respectively with location induction point design module, and Design Orientation environment arrangement module is gathered acquisition module, location algorithm design module and terminal positioning module with positional parameter successively and is connected.
The terminal positioning of described WLAN (wireless local area network) indoor accurate position device comprises: regularly obtains the current location information module, provides positional information module, position mobile module and obtain reposition associated multimedia information module to centrally-located server sending module, server Algorithm Analysis, wherein:
Regularly obtaining the current location information module is connected with providing positional information module, position mobile module to centrally-located server sending module, server Algorithm Analysis and obtain reposition associated multimedia information module successively.
The basic principle of WLAN (wireless local area network) location algorithm is: the semaphore that WLAN (wireless local area network) is interior is at the regional level gathered, form one and be called the set of empirical value data of database, in this data acquisition system, each signaling point that need locate all has one group of data, is respectively the signal numerical value of ambient signals inductor difference projection on this four direction.In actual location, current demand signal numerical value that user terminal is sent and the numerical value in the empirical value database mate, obtain then may the probability maximum anchor point return to the user.
A kind of WLAN (wireless local area network) indoor accurate position algorithm, this WLAN (wireless local area network) location algorithm comprises: based on the basic fixed position algorithm of probability distribution, median filtering algorithm, four-way filtering algorithm and anchor point induction Weight algorithm etc., this algorithm semaphore that WLAN (wireless local area network) is interior is at the regional level gathered, form an empirical value data of database set, in this data acquisition system, each signaling point that need locate all has one group of data, be respectively the signal numerical value of ambient signals inductor difference projection on this four direction, and the current demand signal numerical value that user terminal is sent and the numerical value in the empirical value database mates, obtain then may the probability maximum anchor point return to the user; Its concrete job step mainly is:
Step 1. environment is arranged
System at first positions the layout of environment, by positioning inductor, and the location return system, the layout design of location induction point makes up the environment of a location;
Step 2. parameter is collected
By obtaining of positional parameter, the parameter that is about in the environment be used to locate is collected, form the empirical value database of location;
Step 3. algorithm design
Position the design of algorithm, algorithm is promptly to exist when navigation system occurs, but according to different environment, different user's requests, the parameter of these algorithms need carry out a series of adjustment, is used to adapt to protean surrounding environment;
Step 4. terminal positioning
Realize the location of terminal, the environment that user terminal is arranged in the moving process neutralized system is linked up and the system service end is linked up, and by being positioned at the application program on the terminal, the pushed information that positional information is relevant with co-located information sends in the system.
The basic fixed position algorithm based on probability distribution of described WLAN (wireless local area network) indoor accurate position algorithm is: based on the terminal positioning data with by gathering the empirical value data that a large amount of Back ground Information point processings draw, computing in addition, obtain the joint probability of each positioning inductor sampled intensity on difference and the present anchor point, the empirical value point of choosing the probability maximum is as the benchmark anchor point; Its concrete job step is:
Step 1. beginning
Step 2. input sample is array S module and empirical value database-located point array ExS module as a result
Obtain the sampled result array S{rls1 of input, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement; And obtain input empirical value database-located point array ExS{x, and y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with the anchor point array ExS{x in sampled result array S and the empirical value database, y, o, ls1, ls2, ls3 ... compare, wherein x, and y, o} are empirical value point coordinates and direction, lsN is the empirical value distributed data of positioning inductor at this anchor point;
B). carry out probability calculation module based on the Bayesian network;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, the joint probability table module of o};
Step 4. sorts and chooses
A), joint probability is carried out order module
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, the y} module, and returning of probability maximum;
Step 5. finishes.
The median filtering algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is to utilize continuous sampling, chooses the intermediate value that has stable state most, carries out the method for basic vector distance computing, improves the accuracy of anchor point, reduces side-play amount; Its concrete job step is:
Step 1. beginning
Step 2. input sample is array as a result
Obtain sampled result array S1{rls11 three times, rls12, rls13 ..., S2{rls21, rls22, rls23 ..., S3{rls31, rls32, rls33 ..., wherein rlsMN is the intensity of certain positioning inductor of arriving of the M time sampled result actual measurement; Wherein:
A), input sampled result array first time S1 module;
B), input sampled result array second time S2 module;
C), import sampled result array S3 module for the third time;
Step 3. is chosen intermediate value
Choose the intermediate value module of three sampled result of each positioning inductor;
Step 4. array is calculated
Form interim sampled result array module S ' rls1 ', rls2 ', rls3 ' ..., and calculate;
Step 5. finishes.
The four-way filtering algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is: the empirical value numerical value in its empirical value database is that the numerical value of gathering the four direction of specified point draws, when carrying out basic distance vector coupling, the numerical value of four direction will be ignored direction and carry out computing, the selection of these empirical value data is by relatively, choose with current terminal positioning numerical value in immediate direction numerical value; Its concrete job step is:
Step 1. beginning
Step 2. input sample number of results pack module
Obtain the sampled result array S{rls1 of input, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement;
Step 3. obtains the anchor point array module and the module with the immediate direction numerical value of rlsN lsN is chosen in input
Obtain the anchor point array ExS1{x in the empirical value database, y, o1, ls1, ls2, ls3 ... module, the anchor point array ExS2{x in the empirical value database, y, o2, ls1, ls2, ls3 ... module, the anchor point array ExS3{x in the empirical value database, y, o3, ls1, ls2, ls3, module, the anchor point array ExS4{x in the empirical value database, y, o4, ls1, ls2, ls3 ... module; The module with the immediate direction numerical value of rlsN lsN is chosen in input, and forms interim anchor point array ExStmp{x, y, and o ', ls1 ', ls2 ', ls3 ' ... module;
Step 4. comparison
With the anchor point array ExS1{x in sampled result array S and the empirical value database, y, o1, ls1, ls2, ls3 ..., the anchor point array ExS2{x in the empirical value database, y, o2, ls1, ls2, ls3 ..., the anchor point array ExS3{x in the empirical value database, y, o3, ls1, ls2, ls3,, the anchor point array ExS4{x in the empirical value database, y, o4, ls1, ls2, ls3 ... compare { x wherein, y} is empirical value point coordinates and direction, { o1, o2, o3, o4} are the different sample direction of empirical value point, and lsN is the empirical value distributed data of positioning inductor at this anchor point;
Step 5. probability calculation
A), the output of sampled result array module and choose output with the immediate direction numerical value of rlsN lsN module and all enter probability calculation module based on the Bayesian network, calculate;
B). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in this anchor point { x, y, the joint probability table module of o};
Step 6. sorts and chooses
A), joint probability is carried out order module
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, the y} module, and returning of probability maximum;
Step 7. finishes.
The anchor point induction Weight algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is: all have a plurality of positioning inductors around each anchor point, and these inductors are incomplete same to the weight that anchor point is had in the computing of location, some positioning inductor has prior foundation to corresponding anchor point, this algorithm is optimized at this point, improves stationkeeping ability; Its concrete job step is:
Step 1. beginning
Step 2. input sample is the anchor point array ExS module of array S module and empirical value database cum rights value as a result
Obtain the sampled result array S{rls1 of input, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement; And obtain the anchor point array ExS{x that imports empirical value database cum rights value, and y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with the anchor point array ExS{x in sampled result array S and the empirical value database, y, o, ls1, ls2, ls3 ... compare { x wherein, y, o} is empirical value point coordinates and direction, and lsN is the empirical value distributed data of positioning inductor at this anchor point, and psN is the weights of positioning inductor at this point;
B). carry out probability calculation module based on Bayesian Netowrk tape weights;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, the joint probability table module of o};
Step 4. sorts and chooses
A), joint probability is carried out order module
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, the y}) module, and returning of probability maximum;
Step 5. finishes.
The invention has the beneficial effects as follows: this method is based on employed location algorithm in the terminal positioning technology on the WLAN (wireless local area network) Wireless LocalArea Network, by this algorithmic technique, make us on the WLAN (wireless local area network) stationkeeping ability, to obtain considerable raising, reach about 3-5 rice; The effect of this method is very obvious, and good location algorithm will bring the significantly raising of location technology stability, accuracy.
Description of drawings
The present invention is further described below in conjunction with description of drawings and embodiment.
Accompanying drawing 1 is an accurate positioning method flow diagram of the present invention;
Accompanying drawing 2 is the flow diagram that the present invention is based on the basic fixed position algorithm of probability distribution;
Accompanying drawing 3 is the flow diagram of median filtering algorithm of the present invention;
Accompanying drawing 4 is the flow diagram of four-way filtering algorithm of the present invention;
Accompanying drawing 5 is the flow diagram of anchor point induction Weight algorithm of the present invention;
The drawing reference numeral explanation:
The 1-positioning inductor is arranged;
2-signal passback wireless local area network (WLAN) system is arranged;
The induction point design of 3-location;
4-Design Orientation environment arrangement;
The collection of 5-positional parameter is obtained;
The design of 6-location algorithm;
The 7-terminal positioning;
8-regularly obtains current location information;
9-sends to the centrally-located server;
The Algorithm Analysis of 10-server provides positional information;
Does 11-move the position?
12-obtains reposition associated multimedia information;
15-begins;
16-sampled result array S;
17-empirical value database-located point array ExS;
18-is based on the probability calculation of Bayesian network;
19-S is at any anchor point of empirical value database { x, y, the joint probability table of o};
20-sorts to joint probability;
21-chooses anchor point { x, the y} of probability maximum;
22-finishes;
24-sampled result array S1;
25-sampled result array S2;
26-sampled result array S3;
27-chooses the intermediate value of three sampled result of each positioning inductor;
28-forms interim sampled result array;
30-chooses and the immediate direction numerical value of rlsN lsN;
Anchor point array ExS1 in the 31-empirical value database;
Anchor point array ExS2 in the 32-empirical value database;
Anchor point array ExS3 in the 33-empirical value database;
Anchor point array ExS4 in the 34-empirical value database;
The anchor point array ExS of 36-empirical value database cum rights value;
37-is based on the probability calculation of Bayesian Netowrk tape weights;
Embodiment:
See also shown in the accompanying drawing 1, the present invention is made up of systems such as localizing environment, location induction point and positioning equipments, this system comprises: positioning inductor, location return system, positioning inductor are arranged (1), signal passback wireless local area network (WLAN) system layout (2) and location induction point design technology such as (3), wherein:
Positioning inductor arranges that (1) module, signal passback wireless local area network (WLAN) system layout (2) and location induction point design (3) module are connected with Design Orientation environment arrangement (4) module respectively, and Design Orientation environment arrangement (4) module is obtained (5) module, location algorithm design (6) module and terminal positioning (7) module with the positional parameter collection successively and is connected.
The terminal positioning (7) of described WLAN (wireless local area network) indoor accurate position device comprises: regularly obtains current location information (8) module, sends (9) module, server Algorithm Analysis to the centrally-located server and provide positional information (10) module, position and move (11) module and obtain module such as reposition associated multimedia information (12) module, wherein:
Regularly obtain current location information (8) module successively with send to the centrally-located server that (9) module, server Algorithm Analysis provide positional information (10) module, the position is moved (11) module and obtained reposition associated multimedia information (12) module and is connected.
See also shown in the accompanying drawing 1,2,3,4,5, the basic principle of WLAN (wireless local area network) location algorithm is: the semaphore that WLAN (wireless local area network) is interior is at the regional level gathered, form one and be called the set of empirical value data of database, in this data acquisition system, each signaling point that need locate all has one group of data, is respectively the signal numerical value of ambient signals inductor difference projection on this four direction.In actual location, current demand signal numerical value that user terminal is sent and the numerical value in the empirical value database mate, obtain then may the probability maximum anchor point return to the user.
A kind of WLAN (wireless local area network) indoor accurate position algorithm, this WLAN (wireless local area network) location algorithm comprises: based on the basic fixed position algorithm of probability distribution, median filtering algorithm, four-way filtering algorithm and anchor point induction Weight algorithm, this algorithm semaphore that WLAN (wireless local area network) is interior is at the regional level gathered, form an empirical value data of database set, in this data acquisition system, each signaling point that need locate all has one group of data, be respectively the signal numerical value of ambient signals inductor difference projection on this four direction, and the current demand signal numerical value that user terminal is sent and the numerical value in the empirical value database mates, obtain then may the probability maximum anchor point return to the user; Its concrete job step mainly is:
Step 1. environment is arranged
System at first positions the layout of environment, by positioning inductor, and the location return system, the layout design of location induction point makes up the environment of a location;
Step 2. parameter is collected
By obtaining of positional parameter, the parameter that is about in the environment be used to locate is collected, form the empirical value database of location;
Step 3. algorithm design
Position the design of algorithm, algorithm is promptly to exist when navigation system occurs, but according to different environment, different user's requests, the parameter of these algorithms need carry out a series of adjustment, is used to adapt to protean surrounding environment;
Step 4. terminal positioning
Realize the location of terminal, the environment that user terminal is arranged in the moving process neutralized system is linked up and the system service end is linked up, and by being positioned at the application program on the terminal, the pushed information that positional information is relevant with co-located information sends in the system.
See also shown in the accompanying drawing 2, the basic fixed position algorithm based on probability distribution of described WLAN (wireless local area network) indoor accurate position algorithm is: based on the terminal positioning data with by gathering the empirical value data that a large amount of Back ground Information point processings draw, computing in addition, obtain the joint probability of each positioning inductor sampled intensity on difference and the present anchor point, the empirical value point of choosing the probability maximum is as the benchmark anchor point; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array S (16) module and empirical value database-located point array ExS (17) module as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement; And obtain the input empirical value database-located point array ExS (17) x, y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with anchor point array ExS (17) { x, y, o, the ls1 in sampled result array S (16) and the empirical value database, ls2, ls3 ... compare { x wherein, y, o} are empirical value point coordinates and direction, and lsN is the empirical value distributed data of positioning inductor at this anchor point;
B). carry out probability calculation (18) module based on the Bayesian network;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, joint probability table (19) module of o};
Step 4. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, y} (21) module, and returning of probability maximum;
Step 5. finishes (22).
See also shown in the accompanying drawing 3, the median filtering algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is to utilize continuous sampling, chooses the intermediate value that has stable state most, carries out the method for basic vector distance computing, improve the accuracy of anchor point, reduce side-play amount; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array as a result
Obtain sampled result array S1{rls11 three times, rls12, rls13 ..., S2{rls21, rls22, rls23 ..., S3{rls31, rls32, rls33 ..., wherein rlsMN is the intensity of certain positioning inductor of arriving of the M time sampled result actual measurement; Wherein:
A), input sampled result array S1 (24) the module first time;
B), input sampled result array S2 (25) the module second time;
C), import sampled result array S3 (26) module for the third time;
Step 3. is chosen intermediate value
Choose intermediate value (27) module of three sampled result of each positioning inductor;
Step 4. array is calculated
Form interim sampled result array (28) module S ' rls1 ', rls2 ', rls3 ' ..., and calculate;
Step 5. finishes (22).
See also shown in the accompanying drawing 4, the four-way filtering algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is: the empirical value numerical value in its empirical value database is that the numerical value of gathering the four direction of specified point draws, when carrying out basic distance vector coupling, the numerical value of four direction will be ignored direction and carry out computing, the selection of these empirical value data is by relatively, choose with current terminal positioning numerical value in immediate direction numerical value; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array (16) module as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement;
Step 3. obtains the anchor point array module and the module with the immediate direction numerical value of rlsN lsN (30) is chosen in input
Obtain anchor point array ExS1 (31) { x, y, o1, ls1, ls2 in the empirical value database, ls3 ... module, anchor point array ExS2 (32) { x, y, o2 in the empirical value database, ls1, ls2, ls3 ... module, anchor point array ExS3 (the 33) { x in the empirical value database, y, o3, ls1, ls2, ls3, module, anchor point array ExS4 (34) { x, y, o4 in the empirical value database, ls1, ls2, ls3 ... module; The module with the immediate direction numerical value of rlsN lsN (30) is chosen in input, and forms interim anchor point array ExStmp{x, y, and o ', ls1 ', ls2 ', ls3 ' ... module;
Step 4. comparison
With anchor point array ExS1 (31) { x, y, o1, the ls1 in sampled result array S and the empirical value database, ls2, ls3 ..., anchor point array ExS2 (the 32) { x in the empirical value database, y, o2, ls1, ls2, ls3 ..., anchor point array ExS3 (33) { x, y in the empirical value database, o3, ls1, ls2, ls3,, anchor point array ExS4 (34) { x, y, o4 in the empirical value database, ls1, ls2, ls3, compare, wherein { x, y} are empirical value point coordinates and direction, { o1, o2, o3, o4} is the different sample direction of empirical value point, and lsN is the empirical value distributed data of positioning inductor at this anchor point;
Step 5. probability calculation
A), the output of sampled result array (16) module and choose output with the immediate direction numerical value of rlsN lsN (30) module and all enter probability calculation (18) module based on the Bayesian network, calculate;
B). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in this anchor point { x, y, joint probability table (19) module of o};
Step 6. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, y} (21) module, and returning of probability maximum;
Step 7. finishes (22).
See also shown in the accompanying drawing 5, the anchor point induction Weight algorithm of described WLAN (wireless local area network) indoor accurate position algorithm is: all have a plurality of positioning inductors around each anchor point, and these inductors are incomplete same to the weight that anchor point is had in the computing of location, some positioning inductor has prior foundation to corresponding anchor point, this algorithm is optimized at this point, improves stationkeeping ability; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is anchor point array (36) module of array S (16) module and empirical value database cum rights value as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of certain positioning inductor of arriving of actual measurement; And obtain input empirical value database cum rights value anchor point array ExS (36) x, y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with anchor point array ExS (the 17) { x in sampled result array S (16) and the empirical value database, y, o, ls1, ls2, ls3 ... compare { x wherein, y, o} is empirical value point coordinates and direction, and lsN is the empirical value distributed data of positioning inductor at this anchor point, and psN is the weights of positioning inductor at this point;
B). carry out probability calculation (37) module based on Bayesian Netowrk tape weights;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, joint probability table (19) module of o};
Step 4. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose anchor point { x, y}) (21) module, and returning of probability maximum;
Step 5. finishes (22).
As a widely accepted emerging technology, the WIFI technology is the positive strength of public attention nowadays, technology constantly develops, speed constantly promotes, use it to simplify the online formality, the case that promotes the online quality can be found everywhere, continuous lifting along with the crowd of use quantity, use the increase of user's dependency degree, this wireless local area network technology has begun to come into our daily life, becomes the picture TV, electric wire, the part of the basic telecom service network that network is the same, though brought the more spaces that can give the rein to imagination to us. wireless local area network technology does not reach as yet and resembles cell phone network now, and electrical network is so general, and it is at a high speed, easy-to-use popular service ability is widely accepted, and becomes an important optional standard of next generation network.
The technology that needs are popularized, comprise the location technology that we talk about now, all be to have enough audient crowds, just can make the actual use possibility that becomes a reality, and wireless local area network technology in recent years popularize rapidly, make the localization that utilizes WLAN be positioned to for possibility, WLAN (wireless local area network) has formed one and has located the local side overlay network widely in the whole world at present, in the U.S., Japan, Korea S, China, progressively being laid to one in the bustling city at leisure can be at same GSM in future, the service network of 3G competition, this magnifies the existence of net just, has bred the user of numerous use high bandwidth local online, and these users, just can enjoy and compare GPS, CDMA 1X etc. are more flexible, and positioning accuracy is higher, the network that can use under the local environment.
Claims (7)
1, a kind of WLAN (wireless local area network) indoor accurate position device, this device has localizing environment, location induction point and positioning equipment, it is characterized in that comprising: positioning inductor, location return system, positioning inductor are arranged (1), signal passback wireless local area network (WLAN) system layout (2) and location induction point design (3), wherein:
Positioning inductor arranges that (1) module, signal passback wireless local area network (WLAN) system layout (2) and location induction point design (3) module are connected with Design Orientation environment arrangement (4) module respectively, and Design Orientation environment arrangement (4) module is obtained (5) module, location algorithm design (6) module and terminal positioning (7) module with the positional parameter collection successively and is connected.
2, WLAN (wireless local area network) indoor accurate position device according to claim 1, it is characterized in that: described terminal positioning (7) comprising: regularly obtain current location information (8) module, send to the centrally-located server that (9) module, server Algorithm Analysis provide positional information (10) module, the position is moved (11) module and obtained reposition associated multimedia information (12) module, wherein:
Regularly obtain current location information (8) module successively with send to the centrally-located server that (9) module, server Algorithm Analysis provide positional information (10) module, the position is moved (11) module and obtained reposition associated multimedia information (12) module and is connected.
3, a kind of WLAN (wireless local area network) indoor accurate position algorithm, it is characterized in that: this WLAN (wireless local area network) location algorithm comprises: based on the basic fixed position algorithm of probability distribution, median filtering algorithm, four-way filtering algorithm and anchor point induction Weight algorithm, this algorithm semaphore that WLAN (wireless local area network) is interior is at the regional level gathered, form an empirical value data of database set, in this data acquisition system, each signaling point that need locate all has one group of data, be respectively the signal numerical value of ambient signals inductor difference projection on this four direction, and the current demand signal numerical value that user terminal is sent and the numerical value in the empirical value database mates, and obtains then and may return to the user by the big anchor point of probability; Its concrete job step mainly is:
Step 1. environment is arranged
At first position the layout of environment, by positioning inductor, the location return system, the layout design of location induction point makes up the environment of a location;
Step 2. parameter is collected
By obtaining of positional parameter, the parameter that is used in the environment locate is collected, form the empirical value database of location;
Step 3. algorithm design
Position the design of algorithm, algorithm is to be to exist when navigation system occurs, according to different environment, and different user's requests, the parameter of algorithm need be adjusted;
Step 4. terminal positioning
Realize the location of terminal, the environment that user terminal is arranged in the moving process neutralized system is linked up and the system service end is linked up, and by being positioned at the application program on the terminal, the pushed information that positional information is relevant with co-located information sends in the system.
4, WLAN (wireless local area network) indoor accurate position algorithm according to claim 3, it is characterized in that: described basic fixed position algorithm based on probability distribution is: based on the terminal positioning data with by gathering the empirical value data that a large amount of Back ground Information point processings draw, computing in addition, obtain the joint probability of each positioning inductor sampled intensity on difference and the present anchor point, the empirical value point of choosing the probability maximum is as the benchmark anchor point; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array S (16) module and empirical value database-located point array ExS (17) module as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of the positioning inductor that arrives of actual measurement; And obtain the input empirical value database-located point array ExS (17) x, y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with anchor point array ExS (17) { x, y, o, the ls1 in sampled result array S (16) and the empirical value database, ls2, ls3 ... compare { x wherein, y, o} are empirical value point coordinates and direction, and lsN is the empirical value distributed data of positioning inductor at this anchor point;
B). carry out probability calculation (18) module based on the Bayesian network;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, joint probability table (19) module of o};
Step 4. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose the big anchor point of probability { x, y} (21) module, and returning;
Step 5. finishes (22).
5, WLAN (wireless local area network) indoor accurate position algorithm according to claim 3, it is characterized in that: described median filtering algorithm is to utilize continuous sampling, chooses the intermediate value with stable state, carries out the method for basic vector distance computing; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array as a result
Obtain sampled result array S1{rls11 three times, rls12, rls13 ..., S2{rls21, rls22, rls23 ..., S3{rls31, rls32, rls33 ..., wherein rlsMN is the intensity of the positioning inductor that arrives of the M time sampled result actual measurement; Wherein:
A), input sampled result array S1 (24) the module first time;
B), input sampled result array S2 (25) the module second time;
C), import sampled result array S3 (26) module for the third time;
Step 3. is chosen intermediate value
Choose intermediate value (27) module of three sampled result of each positioning inductor;
Step 4. array is calculated
Form interim sampled result array (28) module S ' rls1 ', rls2 ', rls3 ' ..., and calculate;
Step 5. finishes (22).
6, WLAN (wireless local area network) indoor accurate position algorithm according to claim 3, it is characterized in that: described four-way filtering algorithm is: the empirical value numerical value in its empirical value database is that the numerical value of gathering the four direction of specified point draws, when carrying out basic distance vector coupling, the numerical value of four direction will be ignored direction and carry out computing, the selection of these empirical value data is by relatively, choose with current terminal positioning numerical value in approaching direction numerical value; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is array (16) module as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of the positioning inductor that arrives of actual measurement;
Step 3. obtains the anchor point array module and direction numerical value lsN (30) module approaching with rlsN chosen in input
Obtain anchor point array ExS1 (31) { x, y, o1, ls1, ls2 in the empirical value database, ls3 ... module, anchor point array ExS2 (32) { x, y, o2 in the empirical value database, ls1, ls2, ls3 ... module, anchor point array ExS3 (the 33) { x in the empirical value database, y, o3, ls1, ls2, ls3, module, anchor point array ExS4 (34) { x, y, o4 in the empirical value database, ls1, ls2, ls3 ... module; Direction numerical value lsN (30) module approaching with rlsN chosen in input, forms interim anchor point array ExStmp{x, y, and o ', ls1 ', ls2 ', ls3 ' ... module;
Step 4. comparison
With anchor point array ExS1 (31) { x, y, o1, the ls1 in sampled result array S (16) and the empirical value database, ls2, ls3 ..., anchor point array ExS2 (the 32) { x in the empirical value database, y, o2, ls1, ls2, ls3 ..., anchor point array ExS3 (33) { x, y in the empirical value database, o3, ls1, ls2, ls3,, anchor point array ExS4 (34) { x, y, o4 in the empirical value database, ls1, ls2, ls3, compare, wherein { x, y} are empirical value point coordinates and direction, { o1, o2, o3, o4} is the different sample direction of empirical value point, and lsN is the empirical value distributed data of positioning inductor at this anchor point;
Step 5. probability calculation
A), the output of sampled result array (16) module and choose output with approaching direction numerical value lsN (30) module of rlsN and all enter probability calculation (18) module based on the Bayesian network, calculate;
B). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in this anchor point { x, y, joint probability table (19) module of o};
Step 6. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose the big anchor point of probability { x, y} (21) module, and returning;
Step 7. finishes (22).
7, WLAN (wireless local area network) indoor accurate position algorithm according to claim 3, it is characterized in that: described anchor point induction Weight algorithm is: all have positioning inductor around each anchor point, and these inductors are incomplete same to the weight that anchor point is had in the computing of location, positioning inductor has important basis to corresponding anchor point, and this algorithm is optimized at this point; Its concrete job step is:
Step 1. beginning (15)
Step 2. input sample is anchor point array ExS (36) module of array S (16) module and empirical value database cum rights value as a result
Obtain input sampled result array S (16) rls1, rls2, rls3 ..., wherein rlsN is the intensity of the positioning inductor that arrives of actual measurement; And obtain input empirical value database cum rights value anchor point array ExS (36) x, y, o, ls1, ls2, ls3 ...;
Step 3. comparison and calculating
A). with anchor point array ExS (the 17) { x in sampled result array S (16) and the empirical value database, y, o, ls1, ls2, ls3 ... compare { x wherein, y, o} is empirical value point coordinates and direction, and lsN is the empirical value distributed data of positioning inductor at this anchor point, and psN is the weights of positioning inductor at this point;
B). carry out probability calculation (37) module based on Bayesian Netowrk tape weights;
C). calculate array S in any anchor point of empirical value database { x, y, the joint probability of o}, and draw S in any anchor point of empirical value database { x, y, joint probability table (19) module of o};
Step 4. sorts and chooses
A), to joint probability (20) module that sorts
All array S are sorted in the joint probability of empirical value database-located point array;
B), choose the big anchor point of probability { x, y} (21) module, and returning;
Step 5. finishes (22).
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101742262A (en) * | 2009-12-25 | 2010-06-16 | 北京邮电大学 | Indoor positioning method and device |
| CN101998232A (en) * | 2009-08-19 | 2011-03-30 | 财团法人工业技术研究院 | Mobile device positioning method and equipment |
| CN102307382A (en) * | 2011-05-16 | 2012-01-04 | 苏州市职业大学 | Automatic estimation method by using received-wireless-signal strength distribution curve |
| US8330654B2 (en) | 2009-08-10 | 2012-12-11 | Industrial Technology Research Institute | Method and apparatus for positioning mobile device |
| CN102905368A (en) * | 2012-10-18 | 2013-01-30 | 无锡儒安科技有限公司 | Mobile auxiliary indoor positioning method and system based on smart phone platform |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| TWI395970B (en) * | 2009-08-10 | 2013-05-11 | Ind Tech Res Inst | Method and apparatus for positioning mobile device |
| CN101998232A (en) * | 2009-08-19 | 2011-03-30 | 财团法人工业技术研究院 | Mobile device positioning method and equipment |
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| CN101742262A (en) * | 2009-12-25 | 2010-06-16 | 北京邮电大学 | Indoor positioning method and device |
| CN102307382A (en) * | 2011-05-16 | 2012-01-04 | 苏州市职业大学 | Automatic estimation method by using received-wireless-signal strength distribution curve |
| CN102307382B (en) * | 2011-05-16 | 2014-07-16 | 苏州市职业大学 | Automatic estimation method by using received-wireless-signal strength distribution curve |
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| CN102905368B (en) * | 2012-10-18 | 2015-06-10 | 无锡儒安科技有限公司 | Mobile auxiliary indoor positioning method and system based on smart phone platform |
| CN102905368A (en) * | 2012-10-18 | 2013-01-30 | 无锡儒安科技有限公司 | Mobile auxiliary indoor positioning method and system based on smart phone platform |
| CN104284417A (en) * | 2013-07-08 | 2015-01-14 | 国际商业机器公司 | Method and network element for tracking a trajectory of a mobile device |
| CN104284417B (en) * | 2013-07-08 | 2018-04-03 | 格芯公司 | For tracking the method and network element of position of mobile equipment |
| CN103841639A (en) * | 2013-12-05 | 2014-06-04 | 镇江高科科技信息咨询有限公司 | Wireless local area network technology for indoor positioning |
| CN109444874A (en) * | 2018-09-17 | 2019-03-08 | 上海无线电设备研究所 | A kind of target range tracking |
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