CN102565833B - Method for estimating position of mobile user - Google Patents
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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, espespecially a kind of method can estimating mobile users position according to global positioning satellite signal and cellular network signal.
Background technology
In recent years, the service (Location-basedservices, LBS) based on position along with diversification in styles presents height sexual development, and wireless location technology is subject to attention and the attention of association area.The required signal measured of location technology can be global positioning satellite (GlobalPositioningSystem, GPS) signal, the reference signal of Radio Network System or the assist location signal of other system.The content measured because of signal is different, and has different locate modes, and in current association area, diversified location technology is proposed widely.
Based on satellite (satellite-based) navigation system on, GPS is the most known and is widely used in the navigation system in various field.GPS is through that 24 satellites be laid in space are round-the-clock transmits location signal earthward, and running gear only needs to configure suitable receiving equipment and can receive location signal any time and carry out three-dimensional space position and resolve in arbitrary place in the whole world.GPS mainly provides latitude and longitude coordinates positioning service for outdoor environment, and setting accuracy is high, and its positional information is only had an appointment the error of ten meters.But the location signal launched due to gps satellite can be subject to covering of building, therefore, also cannot use this technology in indoor.In addition, when narrow city streets or the weather condition difference of Metropolitan Area, GPS setting accuracy has the reduction of certain degree.
Based on cellular network (cellularnetwork-based) navigation system on, the most basic location technology, utilize cell base station (celltower), the i.e. cell global recognition (CellGlobalIdentity of base station, CGI) code, realizes two-dimensional spatial location and resolves.Advantage, for not need complicated location compute amount, also can use this technology in indoor, and because setting accuracy directly depends on the scope that cell base station is contained, therefore, metropolitan area is to suburb, and its positional information is about from a few hectometer to the error of tens kilometers.In cellular network navigation system, another simple and practical location technology utilizes running gear reception from the signal power strength of cell base station, i.e. received signal strength (ReceivedSignalStrength, RSS), realize two-dimensional spatial location to resolve.Localization method utilizes three or more received RSS values, the position of running gear is resolved with triangle polyester fibre algorithm, its shortcoming is, due to non-direct-view effect (non-lineofsighteffect) and the impact of covering decline (shadowfading), the measure error of RSS value causes triangle polyester fibre algorithm to resolve or to calculate great placement error value.In addition, at suburb or hills environment, the laying of cell base station is less, and the ability listening to three or more base stations is also Main Bottleneck.Except above-mentioned location technology, the location technology based on Measuring Time signal such as the time of advent (TimeofArrive, ToA) and time of advent poor (TimeDifferenceofArrive, TDoA) is also widely used method.Although have preferably positioning accurate accuracy, its topmost shortcoming needs complicated location compute amount, high signal to measure complexity, high extra computer hardware cost and needs to change the hardware structure of running gear.In addition, at suburb or hills environment, for realizing location compute, the ability listening to three or more cell base stations is also subject matter.
Summary of the invention
Use a device seamless (seamless) can capture the service based on position in different environments for meeting mobile users, the present invention proposes a kind of position estimation method being applied to device.
Estimate in example of the present invention that the method for mobile users position is for the Combination wireless network based on satellite and cellular network.At least comprise an action trainer to be used for obtaining a plurality of training data, one training data report draws together CGI code parameters and the signal strength values of a GPS location coordinate and a plurality of cell base station, and this plurality of cell base station comprises a base station in service sector and base station, at least one neighbor cell; One data operation server is used for performing the estimation of the search of above-mentioned a plurality of training data, warm (fusion) and cellular-site location; One mobile users uses a device, and this device obtains a locator data from a base station, specific cell, and this locator data comprises CGI code parameters and the signal strength values of this base station, specific cell; One positions calculations server is used for performing the search of this locator data and the estimation of mobile users position; And one signal characteristic database for storing above-mentioned a plurality of training data, the record positional information of cell base station and state, and carry out the search of described a plurality of training data and locator data for above-mentioned data operation server and positions calculations server.
In example of the present invention, position estimation method is the CGI code parameters of the base station, specific cell that foundation this action device detects, can obtain the cellular-site location information from this signal characteristic database and a plurality of training data.There is provided a base station (CGI) positioning mode based on this cellular-site location information, provide a base station to assist RSS (CGI-RSS) positioning mode based on this plurality of training data.Each positioning mode is endowed weights (priority), and the weights of this CGI-RSS are in general higher, selects the positional information of a high weight to determine the position of a mobile users.
The above-mentioned method of the present invention is pure software framework, can be laid in tangible machine through program code.When machine loading procedure code and perform time, machine becomes to carry out device of the present invention.
Accompanying drawing explanation
The present invention is further illustrated below in conjunction with the drawings and specific embodiments.
Figure 1 shows that the mobile users position estimation of the embodiment of the present invention based on satellite and cellular network simplifies configuration diagram;
Figure 2 shows that the data training configuration diagram of mobile users position estimation in the embodiment of the present invention;
Figure 3 shows that the data training framework schematic flow sheet of mobile users position estimation in the embodiment of the present invention;
Figure 4 shows that the framework schematic flow sheet of mobile users position estimation in the embodiment of the present invention;
Figure 5 shows that one carries out the framework schematic flow sheet of mobile users position estimation by training data a plurality of in this service type;
Figure 6 shows that one carries out the framework schematic flow sheet of mobile users position estimation by a plurality of training data in this neighbours' classification.
Primary clustering symbol description:
101,102,103GPS satellite 104,105,106,107 cell base station
108 action training device 109 data operation servers
110 running gear 111 positions calculations servers
112 signal characteristic databases
201 receiving element 202 data buffer units
203 data sorting unit 204 DEU data encryption units
205 back-up database 206 cellular wireless network
The warm unit of 207 data decryption unit 208 data
209 location compute unit
301 ~ 311 step 401 ~ 406 steps
501 ~ 508 step 601 ~ 608 steps
Embodiment
The technological means realized to make the present invention, creation characteristic, reaching object and effect is easy to understand, below in conjunction with concrete diagram, setting forth the present invention further.
Figure 1 shows that the mobile users position estimation of the embodiment of the present invention based on satellite and cellular network simplifies configuration diagram, comprise a plurality of gps satellite (101, 102, 103), a plurality of cell base station (104, 105, 106, 107), one action trainer 108 is as intelligent mobile phone or personal digital assistant (PDA), one data operation server 109, one running gear 110 is as mobile phone, intelligent mobile phone, PDA, notebook computer or flat computer (iPad), one positions calculations server 111 and a signal characteristic database 112.This data operation server 109, this positions calculations server 111 and this signal characteristic database 112 are be set up in high in the clouds.These gps satellites are round-the-clock transmits framing signal earthward.Each cell base station has a public control channel (commoncontrolchannel, CCH), and it can continue in cellular network, broadcast its signal to provide a unique CGI code parameters.It is noted that the number of this gps satellite and this cell base station is not limited to the number shown in Fig. 1, under the prerequisite not departing from spirit of the present invention, in different embodiments, this number can change to some extent.
Figure 2 shows that the data training configuration diagram of mobile users position estimation in the embodiment of the present invention, an action trainer 108 is equipped with receiving element 201, data buffer storage unit 202, data sorting unit 203, DEU data encryption unit 204 and a back-up database 205.This data operation server 109 is by being made up of the warm unit 208 of data decryption unit 207, data and a location compute unit 209.This action trainer 108 links through a cellular wireless network 206 and this data operation server 109.When this action trainer 108 enters the outdoor target area of this Combination network, the receiving element 201 through this action trainer 108 can obtain a plurality of training data.One training data report is drawn together as follows:
1. a GPS location coordinate.Its operation principle is roughly as follows: the gps receiver (not shown) in the receiving element 201 of this action trainer 108, the existence of at least four gps satellite signals detected, the signal measurement one ToA value of one gps satellite, calculates the GPS location coordinate of this action trainer 108 according at least four ToA values.
2. the CGI code parameters of a plurality of cell base station and signal strength values.The receiving element 201 of this action trainer 108 detects the existence of a plurality of cell base station (as shown in Figure 1 104,105 and 107) signal, one cell base station signal can be extracted a CGI code parameters and measure a signal strength values, and this plurality of cell base station comprises a base station in service sector (as shown in Figure 1 104) and base station, at least one neighbor cell (as shown in Figure 1 105,107).
As be familiar with GPS technology people known to, this GPS location coordinate upgraded once with each second usually, and therefore, the time label (timestamp) of input is set to one second.Based on this time label, the receiving element 201 through action training device 108 can obtain this GPS location coordinate once and can extract a plurality of CGI code parameters and measure a plurality of signal strength values secondary.The data buffer storage unit 202 of this action trainer 108 stores that this receiving element 201 is accessed, institute extracts and measured a plurality of training datas, and with basis, a plurality of training datas of storage is sent to this data sorting unit 203.Label interval time transmitting a lot data is set to 30 seconds.It is noted that in embodiments of the present invention, the time tag of setting and number of times are not limited to above-mentioned number, and under the prerequisite not departing from spirit of the present invention, in different embodiments, this number can change to some extent.
After the data sorting unit 203 of this action trainer 108 receives a plurality of training data, perform the class discrimination of data, in the classification of 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 data separately.Linking cellular wireless network 206 (as shown in Figure 1 104) by a plurality of training data through an application programming interface (applicationprogramminginterface, API) before being sent to this data operation server 109, by DEU data encryption unit 204, compression and encryption are performed to a plurality of training data, to form a plurality of encryption training data, and transmit a plurality of encryption training data and store to this backup database 205.Based on the transmission characteristic of wireless network, once a plurality of encryption training data transmits unsuccessfully, a plurality of encryption training data can be obtained to perform re-transmission from this backup database 205.After this data operation server 109 receives a plurality of encryption training data, the decryption unit 207 of this data operation server 109 decompresses and deciphering for performing a plurality of encryption training data, to form a plurality of deciphering training data, then, this data fusion unit 208 obtains the training data of corresponding database, to perform data fusion through search one signal characteristic database 112.At following Fig. 3, be mainly used to the step that descriptive data base search, data fusion and cellular-site location are estimated.
Figure 3 shows that the data training framework schematic flow sheet of mobile users position estimation in the embodiment of the present invention.First perform step 301, the CGI code parameters using the cell base station of extracting is the search that a key assignments (key) carries out a signal characteristic database 112.In step 302, confirm whether this CGI code parameters is an existence.
If 1. CGI code parameters is an existence, the warm unit of these data 208 obtains training data (step 303) from this signal characteristic database 112, perform these signal characteristic database training data and a plurality of training data warm, return these warm data to this signal characteristic database 112 (step 304).This signal characteristic database 112, after receiving these warm data, performs to upgrade and stores, and the positional information recording this cell base station is a more new state (step 305).
If 2. CGI code parameters is a non-existence, a plurality of training data is directly sent to this signal characteristic database 112 (step 306) by the warm unit of these data 208.After this signal characteristic database 112 receives a plurality of training data, perform storage, and the positional information recording this cell base station is a unknown state (step 307).
3. this signal characteristic database 112 inspects 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 transmits the training data of this cell base station immediately to this location compute unit 209 (step 308), if the record of this positional information is a more new state, then the regularly timing of this signal characteristic database 112 transmits the training data of this cell base station to this location compute unit 209 (step 309).This location compute unit 209 can be set up according to a plurality of training datas received and troop, and use RF ensemble set algorithm (clusteringalgorithm) executing location estimation (step 310), and this RF signal means received signal strength value.This location compute unit 209 returns this cellular-site location of being estimated to this signal characteristic database 112, this signal characteristic database 112 is after receiving this positional information, perform storage, and to record this positional information state be a known state (step 311).
Figure 4 shows that the framework schematic flow sheet of mobile users position estimation in the embodiment of the present invention, when a mobile users uses a running gear 110 to there is the target area of this Combination wireless network, when requiring a positional information between any a period of time, this action device 110 obtains a locator data (step 401) from a base station, specific cell, this locator data comprises CGI code parameters and the signal strength values of this base station, specific cell, and this base station, specific cell is a base station in service sector (as 106 in Fig. 1).
This action device 110 is through link one cellular wireless network and use an API that this locator data is sent to this positions calculations server 111 (step 402).After this positions calculations server 111 receives this locator data, the CGI code parameters using this base station in service sector is a key assignments, performs the search of this signal characteristic database 112 to obtain corresponding cellular-site location information and training data (step 403).A plurality of training data comprises two classifications: service type and neighbours' classification, whether the training data inspecting this service type exists (step 404), if the training data of this service type is an existence, then use the training data of this service type to carry out the position estimation (step 405) of mobile users, if the training data of this service type is a non-existence, then use the training data of this neighbours' classification to carry out the position estimation (step 406) of mobile users.At following Fig. 5 to Fig. 6, be mainly used in the execution mode that mobile users position estimation method of the present invention is described by a plurality of training data of this service type and a plurality of training datas of this neighbours' classification.
Figure 5 shows that one carries out the framework schematic flow sheet of mobile users position estimation by a plurality of training datas of this service type.First step 501 is performed, to this plurality of signal strength values RSS of a plurality of training datas of this service type
i, wherein i=1,2 ..., N, definition one first reference signal strength value and one second reference signal strength value.In this embodiment, use lowest signal intensity value to define one first reference signal strength value, its equation can be written as RSS
ref1=min{RSS
i; Use highest signal strength value to define one second reference signal strength value, its equation can be written as RSS
ref2=max{RSS
i.
Continue and perform step 502, a plurality of troop (cluster) is divided to a plurality of training datas of this service type.In this embodiment, a plurality of training datas of this service type divide three and troop, and wherein the individual a plurality of training datas of trooping of kth (k=1,2,3) can with gathering G
krepresent.It is noted that this number of trooping is not limited thereto, under the prerequisite not departing from spirit of the present invention, in different embodiment, this number can change to some extent.The mode of division of trooping is: according to this first reference signal strength value, this second reference signal strength value and this number definition one first signal strength signal intensity border (boundary) value 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
bsvalue defines each and troops, and for example, the signal strength values of known i-th training data is RSS
iif, RSS
ibe more than or equal to (RSS
ref2+ RSS
bs), then this training data is positioned at k=1 and troops; If RSS
ibe less than (RSS
ref2+ RSS
bs) and be more than or equal to (RSS
ref2+ 2RSS
bs), then this training data is positioned at k=2 and troops; Otherwise then this training data is positioned at k=3 and troops.
Continue and perform step 503, the signal strength values RSS of the base station in service sector detected according to this action device 110
m, troop from this plurality of cluster selection one.For example, if RSS
mbe more than or equal to (RSS
ref2+ RSS
bs), then select k=1 to troop.
Continue and perform step 504, inspect these a plurality of training data of trooping and whether exist.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 location coordinate and this plurality of signal strength values of a plurality of training datas using this to troop calculate a mobile users position, and its execution mode is: suppose a G
k, k=1 or 2 or 3, comprises n
kindividual training data, each training data has a GPS location coordinate 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 a weighted value W is calculated
g, then, use weighted average algorithm to calculate a mobile users position, its equation can be written as
X＝∑
g＝1，…，nk(W
g×X
g)/∑
g＝1，…，nkW
g
Y＝∑
g＝1，…，nk(W
g×Y
g)/∑
g＝1，…，nkW
g
In step 506, for a plurality of training datas of this service type, the signal strength values of the base station in service sector detected with this action device 110 is a base value, and calculate one similar (proximity) value to each signal strength values of each training data respectively, it can be expressed as P
i, wherein i=1,2 ..., N.
Continue and perform step 507, from this plurality of similar value definition one first with reference to similar value.In this embodiment, use maximum similar value to define, its equation can be written as P
max=min{P
i.
Continue and perform step 508, a plurality of GPS location coordinate of a plurality of training datas of this service type and this plurality of signal strength values is used to calculate a mobile users position, its execution mode is: this service type has N number of training data, the similar value that each training data has a GPS location coordinate, a signal strength measurement and calculates, 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 a weighted value W is calculated
i, then, use weighted average algorithm to calculate a mobile users position, its equation can be written as
X＝∑
i＝1，…，N(W
i×X
i)/∑
i＝1，…，NW
i
Y＝∑
i＝1，…，N(W
i×Y
i)/∑
i＝1，…，NW
i
Figure 6 shows that one carries out the framework schematic flow sheet of mobile users position estimation by a plurality of training datas of this neighbours' classification.First step 601 is performed, to a plurality of signal strength values RSS of a plurality of training datas of this neighbours' classification
j, wherein j=1,2 ..., M, definition one the 3rd reference signal strength value and one the 4th reference signal strength value.In this embodiment, use 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 highest signal strength value to define one the 4th reference signal strength value, its equation can be written as RSS
ref4=max{RSS
j.
Continue and perform step 602, a plurality of trooping is divided to a plurality of training datas of this neighbours' classification.In this embodiment, a plurality of training datas of this neighbours' classification divide three and troop, and wherein the individual a plurality of training datas of trooping of kth (k=1,2,3) can with gathering H
krepresent.It is noted that this number of trooping is not limited thereto, under the prerequisite not departing from spirit of the present invention, in different embodiments, this number can change to some extent.The mode divided 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
bnvalue defines each and troops, and for example, the signal strength values of a known jth training data is RSS
jif, RSS
jbe more than or equal to (RSS
ref4+ RSS
bn), then this training data is positioned at k=1 and troops; If RSS
jbe less than (RSS
ref4+ RSS
bn) and be more than or equal to (RSS
ref4+ 2RSS
bn), then this training data is positioned at k=2 and troops; Otherwise then this training data is positioned at k=3 and troops.
Continue and perform step 603, the signal strength values RSS of the base station in service sector detected according to this action device 110
m, troop from this plurality of cluster selection one.For example, if RSS
mbe more than or equal to (RSS
ref4+ RSS
bn), then select k=1 to troop.
Continue and perform step 604, inspect these a plurality of training datas of trooping and whether exist, if these a plurality of training datas of trooping are an existence, then proceed to step 605, otherwise, then proceed to step 606.
In step 605, a plurality of GPS location coordinate and this plurality of signal strength values of a plurality of training datas using this to troop calculate a mobile users position, and its execution mode is: suppose a H
k, k=1 or 2 or 3, comprises m
kindividual training data, each training data has a GPS location coordinate 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 a weighted value W is calculated
h, then, use weighted average algorithm to calculate a mobile users position, its equation can be written as
X＝∑
h＝1，…，mk(W
h×X
h)/∑
h＝1，…，mkW
h
Y＝∑
h＝1，…，mk(W
h×Y
h)/∑
h＝1，…，mkW
h
In step 606, for a plurality of training datas of this neighbours' classification, the signal strength values of the base station in service sector detected with this action device 110 is a base value, and calculate a similar value to each signal strength values of each training data respectively, it can be expressed as P
j, wherein j=1,2 ..., M.
Continue and perform step 607, from this plurality of similar value definition one second with reference to similar value.In this embodiment, use maximum similar value to define, its equation can be written as P
max=min{P
j.
Continue and perform step 608, a plurality of GPS location coordinate of a plurality of training datas of this neighbours' classification and this plurality of signal strength values is used to calculate a mobile users position, its execution mode is: this neighbours' classification has M training data, the similar value that each training data has a GPS location coordinate, a signal strength measurement and calculates, 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 a weighted value W is calculated
j, then, use weighted average algorithm to calculate a mobile users position, its equation can be written as
X＝∑
j＝1，…，M(W
j×X
j)/∑
j＝1，…，MW
j
Y＝∑
j＝1，…，M(W
j×Y
j)/∑
j＝1，…，MW
j
This positions calculations server 111 provides and comprises a base station (CGI) positioning mode and RSS (CGI-RSS) positioning mode is assisted in a base station.This CGI positioning mode is the position using cellular-site location information to determine a mobile users, and this CGI-RSS positioning mode is the position using the training data of this service type or neighbours' classification to estimate a positional information to determine a mobile users.Each positioning mode is endowed weights (priority), and the weights of this CGI-RSS are in general higher.This positions calculations server 111 selects the positional information of a high weight to determine the position of a mobile users.
The method of the invention described above, particular system unit or its part unit, for pure software framework, tangible media can be laid in through program code, as hard disk, disc or any electronic installation (Storage Media as intelligent mobile phone, embodied on computer readable), when machine loading procedure code and perform (as intelligent mobile phone load and perform), machine becomes to carry out device of the present invention.The method and apparatus of the invention described above also can form of program codes through some transfer mediums, as cable, optical fiber or any transmission kenel transmit, when program code is received by machine (as intelligent mobile phone), loads and perform, machine becomes to carry out device of the present invention.
Above-listed detailed description is illustrating for one of the present invention possible embodiments, but this embodiment is also not used to limit the scope of the claims of the present invention, allly do not depart from the equivalence of doing of skill of the present invention spirit and implement or change, all should be contained in the scope of the claims of this case.
Claims (10)
1. estimate a method for mobile users position, it is characterized in that, described method is used for the Combination wireless network based on satellite and cellular network, comprises the following steps:
Use a running gear to obtain a locator data from a base station, specific cell, wherein this base station, specific cell is a base station in service sector of this action device, and this locator data comprises 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, obtain corresponding cellular-site location information and training data by the search of positions calculations server executive signal property data base, and provide and comprise an architecture method and RSS positioning mode is assisted in a base station; And
Be endowed weights according to each positioning mode, select the positional information of a high weight to determine a mobile users position;
Wherein, base station assists RSS positioning mode to be use the training data of this signal characteristic database to estimate that a positional information is to determine the position of a mobile users;
The training data of described signal characteristic database comprises service type and neighbours' classification, if the training data of service type is an existence, then use the training data of this service type to carry out mobile users position estimation, otherwise, then use the training data of this neighbours' classification to carry out mobile users position estimation.
2. the method for estimation mobile users position according to claim 1, is characterized in that, described architecture method is the position using cellular-site location information to determine a mobile users.
3. the method for estimation mobile users position according to claim 1, is characterized in that, uses a plurality of training datas of this service type to carry out position estimation, comprises the following steps:
According to a plurality of signal strength values definition one first reference signal strength value and the one second reference signal strength value of this plurality of training data;
One first signal strength signal intensity boundary value is defined according to this first reference signal strength value, this second reference signal strength value and the number of clusters that predetermines;
Based on this first signal strength signal intensity boundary value, this plurality of training data is divided a plurality of trooping;
One signal strength values of the base station in service sector detected according to this action device, troops from this plurality of cluster selection one; And
Inspect the training data of trooping of this selection, if a plurality of training datas of trooping of this selection are an existence, a plurality of training datas of trooping of this selection are then used to calculate a mobile users position, otherwise, then a plurality of training datas of this service type are used to calculate a mobile users position.
4. the method for estimation mobile users position according to claim 3, is characterized in that, uses lowest signal intensity value to define the first reference signal strength value and uses highest signal strength value to define the second reference signal strength value.
5. the method for estimation mobile users position according to claim 3, it is characterized in that, a plurality of signal strength values of a plurality of GPS location coordinate and this according to a plurality of training datas of trooping of this selection uses weighted average algorithm to calculate a mobile users position.
6. the method for estimation mobile users position according to claim 3, is characterized in that, uses a plurality of training datas of this service type to calculate a mobile users position, comprises the following steps:
One signal strength values of the base station in service sector detected according to this action device, calculates a similar value to each signal strength values of each training data respectively;
From 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 location coordinate and this plurality of signal strength values of this plurality of training data, based on this first reference similar value, weighted average algorithm is used to calculate a mobile users position.
7. the method for estimation mobile users position according to claim 1, is characterized in that, uses a plurality of training datas of this neighbours' classification to carry out position estimation, comprises the following steps:
According to a plurality of signal strength values definition one the 3rd reference signal strength value and one the 4th reference signal strength value of this plurality of training data;
A secondary signal intensity boundary value is defined according to the 3rd reference signal strength value, the 4th reference signal strength value and the number of clusters that predetermines;
Based on this secondary signal intensity boundary value, this plurality of training data is divided a plurality of trooping;
One signal strength values of the base station in service sector detected according to this action device, troops from this plurality of cluster selection one; And
Inspect the training data of trooping of this selection, if a plurality of training datas of trooping of this selection are an existence, a plurality of training datas of trooping of this selection are then used to calculate a mobile users position, otherwise, then a plurality of training datas of this neighbours' classification are used to calculate a mobile users position.
8. the method for estimation mobile users position according to claim 7, is characterized in that, uses lowest signal intensity value to define the 3rd reference signal strength value and uses highest signal strength value to define the 4th reference signal strength value.
9. the method for estimation mobile users position according to claim 7, it is characterized in that, a plurality of signal strength values of a plurality of GPS location coordinate and this according to a plurality of training datas of trooping of this selection uses weighted average algorithm to calculate a mobile users position.
10. the method for estimation mobile users position according to claim 7, is characterized in that, uses a plurality of training datas of this neighbours' classification to calculate a mobile users position, comprises the following steps:
One signal strength values of the base station in service sector detected according to this action device, calculates a similar value to each signal strength values of each training data respectively;
From 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 location coordinate and this plurality of signal strength values of this plurality of training data, based on this second reference similar value, weighted average algorithm is used to calculate a mobile users position.
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| TW99144057A TWI426290B (en) | 2010-12-15 | 2010-12-15 | Method for estimating a mobile user position |
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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 |
| 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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| US7380000B2 (en) * | 2005-08-16 | 2008-05-27 | Toshiba America Research, Inc. | IP network information database in mobile devices for use with media independent information server for enhanced network |
| US7630972B2 (en) * | 2007-01-05 | 2009-12-08 | Yahoo! Inc. | Clustered search processing |
| US7873746B2 (en) * | 2007-07-27 | 2011-01-18 | Lagavulin Limited | User interface for a portable, image-processing transmitter |
| US9094880B2 (en) * | 2008-06-19 | 2015-07-28 | Qualcomm Incorporated | Access terminal assisted node identifier confusion resolution using a time gap |
| US8229440B2 (en) * | 2008-07-14 | 2012-07-24 | Qualcomm Incorporated | Systems, methods and apparatus to facilitate identification and acquisition of access points |
| US8886200B2 (en) * | 2008-09-18 | 2014-11-11 | Qualcomm Incorporated | Using signal monitoring to resolve access point identifier ambiguity |
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| 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 |
| 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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| TW201224491A (en) | 2012-06-16 |
| CN102565833A (en) | 2012-07-11 |
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