CN102565833A - Method for estimating position of mobile user - Google Patents
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- CN102565833A CN102565833A CN2011104108312A CN201110410831A CN102565833A CN 102565833 A CN102565833 A CN 102565833A CN 2011104108312 A CN2011104108312 A CN 2011104108312A CN 201110410831 A CN201110410831 A CN 201110410831A CN 102565833 A CN102565833 A CN 102565833A
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Abstract
The invention discloses a method for estimating the position of a mobile user. Signals are acquired from a plurality of satellites and a plurality of cell base stations through a mobile training device, and a signal feature database is established based on the signals. A mobile user uses a device to acquire signals from a particular cell site, performs a database search based on the signal characteristics, and estimates the location of the mobile user based on the data in the characteristics database.
Description
Technical field
The present invention relates to the method for position estimation, refer to a kind of method that can estimate the action customer location according to global positioning satellite signal and cellular network signal especially.
Background technology
In recent years, along with diversification in styles with the position be the basis service (Location-based services, LBS) appear the height sexual development, wireless location technology receives the attention and the attention of association area.The signal of the required measurement of location technology can be global positioning satellite (Global Positioning System, GPS) the assist location signal of the reference signal of signal, Radio Network System or other system.The content of measuring because of signal is different, and different locator meamss is arranged, and diversified location technology is proposed widely in the association area at present.
On the positioning system that with the satellite is basis (satellite-based), GPS is the most popular positioning system of knowing and be widely used in various fields.GPS sees through the round-the-clock location signal that transmits earthward of 24 satellites that are laid in the space, and running gear only need dispose suitable receiving equipment and can receive the location signal any time and carry out three-dimensional space position and resolve in arbitrary place in the whole world.GPS provides the latitude and longitude coordinates positioning service to outdoor environment, and setting accuracy is high, only have an appointment ten meters error of its positional information.Yet, because the location signal launched of gps satellite can receive covering of buildings, therefore, indoor and can't use this technology.In addition, under the situation of the narrow city street in city district or weather condition difference, the GPS setting accuracy has the reduction of certain degree.
On the positioning system that with the cellular network is basis (cellular network-based); The most basic location technology is to utilize cell base station (cell tower), i.e. the cell of base station overall situation identification (Cell Global Identity; CGI) sign indicating number is realized the two-dimensional space location compute.Advantage also can be used this technology for not needing complicated location compute amount indoor, because setting accuracy directly depends on the scope that cell base station is contained, therefore, the metropolitan area is to the suburb, and its positional information is approximately from the error of several hectometers to tens kilometer.In the cellular network positioning system, the location technology that another is simple and practical is to utilize running gear to receive the signal power strength from cell base station, and (Received Signal Strength RSS), realizes the two-dimensional space location compute promptly to receive signal intensity.Localization method be utilize three or more than received RSS value; Resolve the position of running gear with the triangle location algorithm; Its shortcoming does; Because non-direct-view effect (non-line of sight effect) and the influence of covering decline (shadow fading), the measuring error of RSS value causes the triangle location algorithm can't resolve or calculate great placement error value.In addition, in the suburb or the hills environment, the laying of cell base station is less, and the ability of listening to three or above base station also is main bottleneck.Except above-mentioned location technology, location technology that is the basis with the Measuring Time signal such as time of arrival, (Time of Arrive was ToA) with time of arrival, poor (Time Difference of Arrive TDoA) also was widely used method.Though have the preferred positioning precision, its topmost shortcoming is to need complicated location compute amount, high signal measuring complex degree, high extra computer hardware cost and the hardware structure that needs the change running gear.In addition, in the suburb or the hills environment, for realizing location compute, the ability of listening to three or above cell base station also is a subject matter.
Summary of the invention
For satisfied action user uses a device can seamless in varying environment (seamless) acquisition be the service on basis with the position, and the present invention proposes a kind of position estimation method that is applied to device.
The method of estimation action customer location is to be used for the Combination wireless network that is the basis with satellite and cellular network in the instance of the present invention.At least comprise that an action trainer is used for obtaining a plurality of training datas; One training data newspaper is drawn together the CGI code parameters and the signal strength values of a GPS position coordinates and a plurality of cell base stations, and these a plurality of cell base stations comprise a base station in service sector and at least one neighbor cell base station; One data operation server is used for carrying out the estimation of the search of above-mentioned a plurality of training datas, warm (fusion) and cellular-site location; Delegation employs the family and uses a device, and this device obtains a locator data from a specific cell base station, and this locator data comprises the CGI code parameters and the signal strength values of this specific cell base station; Certain bit arithmetic server is used for carrying out the search of this locator data and the estimation of action customer location; And one the signal characteristic database be used to store the positional information and the state of above-mentioned a plurality of training data, record cell base station, and supply above-mentioned data operation server and location calculation server to carry out the search of said a plurality of training data and locator data.
Position estimation method is the CGI code parameters according to the detected specific cell of this action device base station in the instance of the present invention, can obtain cellular-site location information and a plurality of training data from this signal characteristic database.Based on this cellular-site location information one base station (CGI) localization method is provided, provides a base station to assist RSS (CGI-RSS) localization method based on these a plurality of training datas.Each localization method is endowed weights (priority), and the weights of this CGI-RSS are in general higher, selects the positional information of a high weight to confirm that delegation employs the position at family.
The above-mentioned method of the present invention is the pure software framework, can see through program code and be laid in the entity machine.When machine loading procedure code and execution, machine becomes in order to carry out device of the present invention.
Description of drawings
Further specify the present invention below in conjunction with accompanying drawing and embodiment.
Shown in Figure 1 is that the embodiment of the invention is simplified configuration diagram with the action customer location estimation that satellite and cellular network are the basis;
Shown in Figure 2 is the data training configuration diagram of action customer location estimation in the embodiment of the invention;
Shown in Figure 3 is the data training framework schematic flow sheet of action customer location estimation in the embodiment of the invention;
Shown in Figure 4 is the framework schematic flow sheet of action customer location estimation in the embodiment of the invention;
Shown in Figure 5 is one by the take action framework schematic flow sheet of customer location estimation of a plurality of training datas in this service type;
Shown in Figure 6 is one by the take action framework schematic flow sheet of customer location estimation of a plurality of training datas in this neighbours' classification.
The primary clustering symbol description:
101,102,103 gps satellites, 104,105,106,107 cell base stations
108 action training devices, 109 data operation servers
110 running gears, 111 location calculation servers
112 signal characteristic databases
201 receiving elements, 202 data buffer units
203 data qualification unit, 204 DEU data encryption units
205 back-up databases, 206 cellular wireless network
The warm unit of 207 data decryption unit, 208 data
209 location compute unit
301～311 steps 401～406 steps
501～508 steps 601～608 steps
Embodiment
For technological means, creation characteristic that the present invention is realized, reach purpose and effect and be easy to understand and understand, below in conjunction with concrete diagram, further set forth the present invention.
Shown in Figure 1 is that the embodiment of the invention is simplified configuration diagram with the action customer location estimation that satellite and cellular network are the basis; Comprise a plurality of gps satellites (101; 102; 103), a plurality of cell base stations (104; 105,106,107), action trainer 108 as intelligent mobile phone or PDA(Personal Digital Assistant), a data operation server 109, an action device 110 are like mobile phone, intelligent mobile phone, PDA, notebook computer or flat computer (iPad), necessarily a bit arithmetic server 111 and a signal characteristic database 112.This data operation server 109, this location calculation server 111 and this signal characteristic database 112 are to be set up in high in the clouds.The round-the-clock positioning signal that transmits earthward of these gps satellites.Each cell base station has a public control channel, and (common control channel, CCH), it can continue, and its signal of broadcasting provides a unique CGI code parameters in cellular network.Be noted that the number of this gps satellite and this cell base station is not limited to number shown in Figure 1, not being contrary under the prerequisite of spirit of the present invention, in different embodiment, this number can change to some extent.
Shown in Figure 2 is the data training configuration diagram of action customer location estimation in the embodiment of the invention, and an action trainer 108 is equipped with a receiving element 201, a data buffer storage unit 202, a data qualification unit 203, a DEU data encryption unit 204 and a back-up database 205.This data operation server 109 is by being made up of a data decryption unit 207, the warm unit 208 of data and a location compute unit 209.This action trainer 108 sees through a cellular wireless network 206 and links with this data operation server 109.When this action trainer 108 got into the outdoor target area of this Combination network, the receiving element 201 that sees through this action trainer 108 can obtain a plurality of training datas.One training data newspaper is drawn together as follows:
1. a GPS position coordinates.Its principle of work is roughly following: the gps receiver (not shown) in the receiving element 201 of this action trainer 108; Detect the existence of at least four gps satellite signals; The signal measurement one ToA value of one gps satellite, at least four ToA values of foundation calculate the GPS position coordinates of this action trainer 108.
2. the CGI code parameters and the signal strength values of a plurality of cell base stations.The receiving element 201 of this action trainer 108 detects the existence of a plurality of cell base stations (as shown in fig. 1 104,105 and 107) signal; Can extract a CGI code parameters and measure a signal strength values of one cell base station signal, and these a plurality of cell base stations comprise a base station in service sector (as shown in fig. 1 104) and at least one neighbor cell base station (as shown in fig. 1 105,107).
As be familiar with people institute knowledges of GPS technology, usually this GPS position coordinates with each renewal second once, therefore, the time label of input (time stamp) was made as one second.Based on this time label, the receiving element 201 that sees through action training device 108 can obtain this GPS position coordinates once and can extract a plurality of CGI code parameters with measure a plurality of signal strength values secondaries.The data buffer storage unit 202 of this action trainer 108 stores that this receiving element is 201 accessed, extract to measured a plurality of training datas, and be sent to this data qualification unit 203 with a plurality of training datas that batch mode will store.Label interval time that transmits a lot data was made as 30 seconds.Be noted that in embodiments of the present invention, the time tag of setting and number of times are not limited to above-mentioned number, not being contrary under the prerequisite of spirit of the present invention, in different embodiment, this number can change to some extent.
The data qualification unit 203 of this action trainer 108 receives after a plurality of training datas; Carry out the class discrimination of data; Classification in data; Can divide into a service type and neighbours' classification to same CGI code parameters, and a service type and neighbours' classification comprise a plurality of training datas separately.In link cellular wireless network 206 (as shown in fig. 1 104) a plurality of training datas are seen through an API (application programming interface; API) be sent to before this data operation server 109; Carry out compression and encryption by 204 pairs of a plurality of training datas of DEU data encryption unit; Forming a plurality of encryption training datas, and transmit a plurality of encryption training datas to this backup database 205 and store.Based on the transport property of wireless network,, can obtain a plurality of encryption training datas from this backup database 205 and carry out re-transmission in case a plurality of encryption training data transmits failure.After this data operation server 109 receives a plurality of encryption training datas; The decrypting device 207 of this data operation server 109 is used for a plurality of encryption training datas are carried out decompression and deciphering; To form a plurality of deciphering training datas; Then, this data fusion unit 208 sees through searches the training data that a signal characteristic database 112 obtains corresponding database, to carry out data fusion.At following Fig. 3, mainly be used to the step of descriptive data base search, data fusion and cellular-site location estimation.
Shown in Figure 3 is the data training framework schematic flow sheet of action customer location estimation in the embodiment of the invention.At first execution in step 301, and using the CGI code parameters of the cell base station of extracting is that a key assignments (key) carries out the search of a signal characteristic database 112.In step 302, confirm whether this CGI code parameters is an existence.
1. if the CGI code parameters is an existence, the warm unit 208 of these data from this signal characteristic database 112 obtain training data (step 303), carry out this signal characteristic database training data and a plurality of training datas warm, the passback these warm data to this signal characteristic database 112 (step 304).This signal characteristic database 112 carry out to upgrade stores after receiving these warm data, and the positional information that writes down this cell base station is a update mode (step 305).
2. if the CGI code parameters is an existence not, the warm unit 208 of these data directly is sent to this signal characteristic database 112 (step 306) with a plurality of training datas.After this signal characteristic database 112 receives a plurality of training datas, carry out to store, and the positional information that writes down this cell base station is a unknown state (step 307).
3. this signal characteristic database 112 is inspected the positional information state of this cell base station.If the record of this positional information is a unknown state; Then this signal characteristic database 112 transmit this cell base station immediately training data to this location compute unit 209 (step 308); If the record of this positional information is a update mode, then these signal characteristic database 112 regular training datas that regularly transmit this cell base station are to this location compute unit 209 (step 309).This location compute unit 209 can be set up according to a plurality of training datas that receive and troop, and uses RF ensemble set algorithm (clustering algorithm) executing location estimation (step 310), and this RF signal means the reception signal strength values.This cellular-site location that 209 passbacks of this location compute unit are estimated to is to this signal characteristic database 112, and this signal characteristic database 112 carries out storing after receiving this positional information, and to write down this positional information state be a known state (step 311).
Shown in Figure 4 is the framework schematic flow sheet of action customer location estimation in the embodiment of the invention; When employing the family, delegation use an action device 110 to have the target area of this Combination wireless network; When between any a period of time, requiring a positional information; This action device 110 obtains a locator data (step 401) from a specific cell base station, and this locator data comprises the CGI code parameters and the signal strength values of this specific cell base station, and this specific cell base station is a base station in service sector (like 106 among Fig. 1).
This action device 110 sees through link one cellular wireless network and uses an API that this locator data is sent to this location calculation server 111 (step 402).This location calculation server 111 receives after this locator data, and using the CGI code parameters of this base station in service sector is a key assignments, carries out the search of this signal characteristic database 112 and obtains corresponding cellular-site location information and training data (step 403).A plurality of training datas comprise two classifications: service type and neighbours' classification; Whether the training data of inspecting this service type exists (step 404); If the training data of this service type is an existence; Then use take action user's position estimation (step 405) of the training data of this service type,, then use take action user's position estimation (step 406) of the training data of this neighbours' classification if the training data of this service type is an existence not.At following Fig. 5 to Fig. 6, be mainly used in the embodiment that action customer location evaluation method of the present invention is described by a plurality of training datas of a plurality of training datas of this service type and this neighbours' classification.
Shown in Figure 5 is one by the take action framework schematic flow sheet of customer location estimation of a plurality of training datas of this service type.At first execution in step 501, to these a plurality of signal strength values RSS of a plurality of training datas of this service type
i, i=1 wherein, 2 ..., N defines one first reference signal strength value and one second reference signal strength value.In this embodiment, use the lowest signal intensity value to define one first reference signal strength value, its equation can be written as RSS
Ref1=min{RSS
i; Use the highest signal strength value to define one second reference signal strength value, its equation can be written as RSS
Ref2=max{RSS
i.
The execution in step 502 that continues is divided a plurality of trooping (cluster) to a plurality of training datas of this service type.In this embodiment, a plurality of training datas of this service type are divided three and are trooped, and wherein the individual a plurality of training datas of trooping of k (k=1,2,3) can be used set G
kRepresent.Be noted that this number of trooping is not limited thereto, not being contrary under the prerequisite of spirit of the present invention, in different embodiment, this number can change to some extent.The mode of division of trooping is: define one first signal intensity border (boundary) value according to this first reference signal strength value, this second reference signal strength value and this number of trooping, its equation can be written as RSS
Bs=(RSS
Ref1-RSS
Ref2)/K, wherein K is the number of trooping.Based on this RSS
BsEach troops value defined, and for example, the signal strength values of known i training data is RSS
i, if RSS
iMore than or equal to (RSS
Ref2+ RSS
Bs), then should the training data be positioned at k=1 and troop; If RSS
iLess than (RSS
Ref2+ RSS
Bs) and more than or equal to (RSS
Ref2+ 2RSS
Bs), then should the training data be positioned at k=2 and troop; Otherwise, then should the training data be positioned at k=3 and troop.
The execution in step 503 that continues is according to the signal strength values RSS of this action device 110 detected base station in service sector
m, these a plurality of cluster selection one are trooped certainly.For example, if RSS
mMore than or equal to (RSS
Ref2+ RSS
Bs), then select k=1 to troop.
Whether the execution in step 504 that continues is inspected these a plurality of training data of trooping and is existed.If these a plurality of training datas of trooping are an existence, then proceed to step 505, otherwise, then proceed to step 506.
In step 505, a plurality of GPS position coordinateses that use these a plurality of training datas of trooping calculate delegation with these a plurality of signal strength values and employ the position, family, and its embodiment is: suppose a G
k, k=1 or 2 or 3 comprises n
kIndividual training data, each training data have a GPS position coordinates and a signal strength measurement, if this signal strength measurement equals RSS
m, then weighted value is W
g=1, if this signal strength measurement is not equal to RSS
m, then calculate a weighted value W
g, then, using the weight average algorithm to calculate delegation and employ the position, family, its equation can be written as
X＝∑
g＝1，…，nk(W
g×X
g)/∑
g＝1，…，nk?W
g
Y＝∑
g＝1，…，nk(W
g×Y
g)/∑
g＝1，…，nk?W
g
In step 506; A plurality of training datas to this service type; Signal strength values with this action device 110 detected base station in service sector is a base value, and each signal strength values to each training data calculates one similar (proximity) value respectively, and it can be expressed as P
i, i=1 wherein, 2 ..., N.
The execution in step 507 that continues, these a plurality of similar value define one first with reference to similar value certainly.In this embodiment, use maximum similar value to define, its equation can be written as P
Max=min{P
i.
Execution in step 508 continues; Use a plurality of GPS position coordinateses and these a plurality of signal strength values of a plurality of training datas of this service type to calculate delegation and employ the position, family; Its embodiment is: this service type has N training data; The similar value that each training data has a GPS position coordinates, a signal strength measurement and to calculate is if this similar value is not equal to P
Max, then weighted value is W
i=1, if this similar value equals P
Max, then calculate a weighted value W
i, then, using the weight average algorithm to calculate delegation and employ the position, family, its equation can be written as
X＝∑
i＝1，…，N(W
i×X
i)/∑
i＝1，…，N?W
i
Y＝∑
i＝1，…，N(W
i×Y
i)/∑
i＝1，…，N?W
i
Shown in Figure 6 is one by the take action framework schematic flow sheet of customer location estimation of a plurality of training datas of this neighbours' classification.At first execution in step 601, to a plurality of signal strength values RSS of a plurality of training datas of this neighbours' classification
j, j=1 wherein, 2 ..., M defines one the 3rd reference signal strength value and one the 4th reference signal strength value.In this embodiment, use the lowest signal intensity value to define one the 3rd reference signal strength value, its equation can be written as RSS
Ref3=min{RSS
j; Use the highest signal strength value to define one the 4th reference signal strength value, its equation can be written as RSS
Ref4=max{RSS
j.
The execution in step 602 that continues is divided a plurality of trooping to a plurality of training datas of this neighbours' classification.In this embodiment, a plurality of training datas of this neighbours' classification are divided three and are trooped, and wherein the individual a plurality of training datas of trooping of k (k=1,2,3) can be used set H
kRepresent.Be noted that this number of trooping is not limited thereto, not being contrary under the prerequisite of spirit of the present invention, in different embodiment, this number can change to some extent.The mode of dividing of trooping is: define a secondary signal intensity boundary value according to the 3rd reference signal strength value, the 4th reference signal strength value and this number of trooping, its equation can be written as RSS
Bn=(RSS
Ref3-RSS
Ref4)/K, the wherein number of K for trooping.Based on this RSS
BnEach troops value defined, and for example, the signal strength values of known j training data is RSS
j, if RSS
jMore than or equal to (RSS
Ref4+ RSS
Bn), then should the training data be positioned at k=1 and troop; If RSS
jLess than (RSS
Ref4+ RSS
Bn) and more than or equal to (RSS
Ref4+ 2RSS
Bn), then should the training data be positioned at k=2 and troop; Otherwise, then should the training data be positioned at k=3 and troop.
The execution in step 603 that continues is according to the signal strength values RSS of this action device 110 detected base station in service sector
m, these a plurality of cluster selection one are trooped certainly.For example, if RSS
mMore than or equal to (RSS
Ref4+ RSS
Bn), then select k=1 to troop.
Whether the execution in step 604 that continues is inspected these a plurality of training datas of trooping and is existed, if these a plurality of training datas of trooping are an existence, then proceeds to step 605, otherwise, then proceed to step 606.
In step 605, a plurality of GPS position coordinateses that use these a plurality of training datas of trooping calculate delegation with these a plurality of signal strength values and employ the position, family, and its embodiment is: suppose a H
k, k=1 or 2 or 3 comprises m
kIndividual training data, each training data have a GPS position coordinates and a signal strength measurement, if this signal strength measurement equals RSS
m, then weighted value is W
h=1, if this signal strength measurement is not equal to RSS
m, then calculate a weighted value W
h, then, using the weight average algorithm to calculate delegation and employ the position, family, its equation can be written as
X＝∑
h＝1，…，mk(W
h×X
h)/∑
h＝1，…，mk?W
h
Y＝∑
h＝1，…，mk(W
h×Y
h)/∑
h＝1，…，mk?W
h
In step 606, to a plurality of training datas of this neighbours' classification, be a base value with the signal strength values of this action device 110 detected base station in service sector, each signal strength values to each training data calculates a similar value respectively, and it can be expressed as P
j, j=1 wherein, 2 ..., M.
The execution in step 607 that continues, these a plurality of similar value define one second with reference to similar value certainly.In this embodiment, use maximum similar value to define, its equation can be written as P
Max=min{P
j.
Execution in step 608 continues; Use a plurality of GPS position coordinateses and these a plurality of signal strength values of a plurality of training datas of this neighbours' classification to calculate delegation and employ the position, family; Its embodiment is: this neighbours' classification has M training data; The similar value that each training data has a GPS position coordinates, a signal strength measurement and to calculate is if this similar value is not equal to P
Max, then weighted value is W
j=1, if this similar value equals P
Max, then calculate a weighted value W
j, then, using the weight average algorithm to calculate delegation and employ the position, family, its equation can be written as
X＝∑
j＝1，…，M(W
j×X
j)/∑
j＝1，…，M?W
j
Y＝∑
j＝1，…，M(W
j×Y
j)/∑
j＝1，…，M?W
j
This location calculation server 111 provides and comprises auxiliary RSS (CGI-RSS) localization method of a base station (CGI) localization method and a base station.This CGI location genealogy of law confirms that for using cellular-site location information delegation employs the position at family, and this CGI-RSS location genealogy of law is estimated a positional information for the training data of this service type of use or neighbours' classification and confirmed that delegation employs the position at family.Each localization method is endowed weights (priority), and the weights of this CGI-RSS are in general higher.This location calculation server 111 selects the positional information of a high weight to confirm that delegation employs the position at family.
The method of the invention described above; Or particular system unit or its part unit; Be the pure software framework, can see through program code and be laid in tangible media, like hard disk, discs or any electronic installation (like the Storage Media of intelligent mobile phone, embodied on computer readable); When machine loading procedure code and execution (load and carry out like intelligent mobile phone), machine becomes in order to carry out device of the present invention.The method and apparatus of the invention described above also can the program code kenel see through some transfer mediums; Transmit like cable, optical fiber or any transmission kenel; When program code is received, loads and carry out by machine (like intelligent mobile phone), machine becomes in order to carry out device of the present invention.
Above-listed detailed description is specifying to one of the present invention possible embodiments; But this embodiment is not in order to limit claim of the present invention; Allly do not break away from the equivalence that skill spirit of the present invention does and implement or change, all should be contained in the claim of this case.
Claims (12)
1. a method of estimating the action customer location is characterized in that, said method is used for the Combination wireless network that is the basis with satellite and cellular network, comprises the following steps:
Use an action device to obtain a location data from a specific cell base station, wherein this specific cell base station is a base station in service sector of this action device, and this locator data can comprise a CGI code parameters and a signal strength values of this base station in service sector;
According to a CGI code parameters of this base station in service sector, this location calculation server is carried out the search of this signal characteristic database and is obtained corresponding cellular-site location information and training data, and provides and comprise that a base station localization method and a base station assist the RSS localization method; And
Be endowed weights according to each localization method, select the positional information of a high weight to confirm that delegation employs the position, family.
2. the method for estimation action customer location according to claim 1 is characterized in that said base station localization method is to use cellular-site location information to confirm that delegation employs the position at family.
3. the method for estimation according to claim 1 action customer location is characterized in that, the auxiliary RSS localization method in said base station is to use the training data of this signal characteristic database to estimate that a positional information employs the position at family to confirm delegation.
4. the method for estimation action customer location according to claim 3; It is characterized in that; The training data of said signal characteristic database comprises service type and neighbours' classification, if the training data of service type is an existence, then uses the customer location estimation of taking action of the training data of this service type; Otherwise, then use the customer location estimation of taking action of the training data of this neighbours' classification.
5. the method for estimation according to claim 4 action customer location is characterized in that, use this service type a plurality of training datas carry out position estimation, comprise the following steps:
A plurality of signal intensity value defineds one first reference signal strength value and one second reference signal strength value according to these a plurality of training datas;
Define one first signal intensity boundary value according to this first reference signal strength value, this second reference signal strength value and the number of clusters that is predetermined;
Should a plurality of training data divide a plurality of trooping based on this first signal intensity boundary value;
According to a signal strength values of the detected base station in service sector of this action device, these a plurality of cluster selection one are trooped certainly; And
Inspect the training data that this is trooped; If these a plurality of training datas of trooping are an existence; Then use these a plurality of training datas to calculate delegation and employ the position, family, otherwise, then use a plurality of training datas of this service type to calculate delegation and employ the position, family.
6. the method for estimation action customer location according to claim 5 is characterized in that, use lowest signal intensity value defines the first reference signal strength value and uses the highest signal strength value to define the second reference signal strength value.
7. the method for estimation action customer location according to claim 5 is characterized in that, calculates delegation according to a plurality of signal strength values use of a plurality of GPS position coordinateses and this of these a plurality of training data of trooping weight average algorithm and employs the position, family.
8. the method for estimation according to claim 5 action customer location is characterized in that, uses a plurality of training datas of this service type to calculate delegation and employs the position, family, comprises the following steps:
According to a signal strength values of the detected base station in service sector of this action device, each signal strength values to each training data calculates a similar value respectively;
From these a plurality of similar value, use maximum similar value to define one first with reference to similar value; And
According to a plurality of GPS position coordinateses of this a plurality of training data and these a plurality of signal strength values, first with reference to similar value, use weight average algorithm calculates delegation and employs the position, family based on this.
9. the method for estimation action customer location according to claim 4 is characterized in that, uses a plurality of training datas of this neighbours' classification to carry out position estimation, comprises the following steps:
A plurality of signal intensity value defineds 1 the 3rd reference signal strength value and one the 4th reference signal strength value according to these a plurality of training datas;
Define a secondary signal intensity boundary value according to the 3rd reference signal strength value, the 4th reference signal strength value and the number of clusters that is predetermined;
Should a plurality of training data divide a plurality of trooping based on this secondary signal intensity boundary value;
According to a signal strength values of the detected base station in service sector of this action device, these a plurality of cluster selection one are trooped certainly; And
Inspect the training data that this is trooped; If these a plurality of training datas of trooping are an existence; Then use these a plurality of training datas to calculate delegation and employ the position, family, otherwise, then use a plurality of training datas of this neighbours' classification to calculate delegation and employ the position, family.
10. the method for estimation action customer location according to claim 9 is characterized in that, use lowest signal intensity value defines the 3rd reference signal strength value and uses the highest signal strength value to define the 4th reference signal strength value.
11. the method for estimation action customer location according to claim 9 is characterized in that, calculates delegation according to a plurality of signal strength values use of a plurality of GPS position coordinateses and this of these a plurality of training data of trooping weight average algorithm and employs the position, family.
12. the method for estimation according to claim 9 action customer location is characterized in that, uses a plurality of training datas of this neighbours' classification to calculate delegation and employs the position, family, comprises the following steps:
According to a signal strength values of the detected base station in service sector of this action device, each signal strength values to each training data calculates a similar value respectively;
From these a plurality of similar value, use maximum similar value to define one second with reference to similar value; And
According to a plurality of GPS position coordinateses of this a plurality of training data and these a plurality of signal strength values, second with reference to similar value, use weight average algorithm calculates delegation and employs the position, family based on this.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW099144057 | 2010-12-15 | ||
| TW99144057A TWI426290B (en) | 2010-12-15 | 2010-12-15 | Method for estimating a mobile user position |
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| CN102565833A true CN102565833A (en) | 2012-07-11 |
| CN102565833B CN102565833B (en) | 2016-01-13 |
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| CN1668936A (en) * | 2002-09-06 | 2005-09-14 | 诺基亚公司 | Method and system for estimating position of mobile device |
| CN1846454A (en) * | 2003-07-28 | 2006-10-11 | 高通股份有限公司 | Location determination of a local transmitter using a database |
| US20070041344A1 (en) * | 2005-08-16 | 2007-02-22 | Toshiba America Research, Inc. | Ip network information database in mobile devices for use with media independent information server |
| CN101895812A (en) * | 2009-03-12 | 2010-11-24 | 上海爱维特信息技术有限责任公司 | Method for positioning most matched signal intensity in cellular network |
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| US7630972B2 (en) * | 2007-01-05 | 2009-12-08 | Yahoo! Inc. | Clustered search processing |
| US9131078B2 (en) * | 2007-07-27 | 2015-09-08 | Lagavulin Limited | Apparatuses, methods, and systems for a portable, image-processing transmitter |
| US9585069B2 (en) * | 2008-06-19 | 2017-02-28 | Qualcomm Incorporated | Access terminal assisted node identifier confusion resolution |
| US8229440B2 (en) * | 2008-07-14 | 2012-07-24 | Qualcomm Incorporated | Systems, methods and apparatus to facilitate identification and acquisition of access points |
| US8379512B2 (en) * | 2008-09-18 | 2013-02-19 | Qualcomm Incorporated | Using identifier mapping to resolve access point identifier ambiguity |
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2010
- 2010-12-15 TW TW99144057A patent/TWI426290B/en active
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1668936A (en) * | 2002-09-06 | 2005-09-14 | 诺基亚公司 | Method and system for estimating position of mobile device |
| CN1846454A (en) * | 2003-07-28 | 2006-10-11 | 高通股份有限公司 | Location determination of a local transmitter using a database |
| US20070041344A1 (en) * | 2005-08-16 | 2007-02-22 | Toshiba America Research, Inc. | Ip network information database in mobile devices for use with media independent information server |
| CN101895812A (en) * | 2009-03-12 | 2010-11-24 | 上海爱维特信息技术有限责任公司 | Method for positioning most matched signal intensity in cellular network |
Also Published As
| Publication number | Publication date |
|---|---|
| TWI426290B (en) | 2014-02-11 |
| CN102565833B (en) | 2016-01-13 |
| TW201224491A (en) | 2012-06-16 |
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