USOO7433693B2
`
`(12) United States Patent
`Sheynblat
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 7.433,693 B2
`Oct. 7, 2008
`
`(54) LOCATION-SENSITIVE CALIBRATION DATA
`
`(75) Inventor: Leonid Sheynblat, Hillsborough, CA
`(US)
`
`(73) Assignee: gym Incorporated, San Diego,
`
`8, 2002 Calvert et al.
`2002/0102989 A1
`1/2003 Perez-Breva et al.
`2003, OOO8668 A1
`2004/0203904 A1* 10, 2004 Gwon et al. ............. 455,456.1
`2005/001265.6 A1
`1/2005 Reisman et al. ............. 342,118
`2005/0032531 A1* 2/2005 Gong et al. .......
`... 455,456.5
`2005/0040968 A1
`2/2005 Damarla et al. ........ 340,825.49
`2005/0246334 A1* 11/2005 Tao et al. ....................... 707/5
`
`(*) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 458 days.
`
`WO
`
`FOREIGN PATENT DOCUMENTS
`
`O31.01140 A1 12/2003
`OTHER PUBLICATIONS
`
`(21) Appl. No.: 11/000,702
`
`(22) Filed:
`
`Nov.30, 2004
`
`(65)
`
`Prior Publication Data
`
`US 2006/OO891.53 A1
`
`Apr. 27, 2006
`
`Related U.S. Application Data
`(60) Provisional application No. 60/622,884, filed on Oct.
`27, 2004.
`s
`(51) Int. Cl.
`(2006.01)
`H04O 7/20
`(52) U.S. Cl. .............. 455/456.1; 455/456.2:455/456.5;
`455/404.2: 342/118; 342/357.02
`(58) Field of Classification Search .............. 455/4.56.1,
`455/4562, 456.5, 404.2: 342/1 18,357.02
`See application file for complete search history.
`References Cited
`
`(56)
`
`U.S. PATENT DOCUMENTS
`
`6, 195,556 B1* 2/2001 Reudink et al. .......... 455,456.2
`6,716,101 B1 * 4/2004 Meadows et al. ........ 455,456.1
`7,116,996 B2 * 10/2006 Lazaro et al. ............... 455,466
`7,130,646 B2 * 10/2006 Wang ...................... 455,456.5
`
`Wang S.S.P. et al. E-911 Location Standards and Location Standars
`Services: Emerging Technology Symposium: Braodband, Wireless
`Internet Access, 2000 IEEE Apr. 10-11, 2000, Piscaway, NJ. USA,
`IEEE, Apr. 10, 2000, pp. 1-5.
`Kunczier H. et al: "Enhanced Cell ID Based Terminal Location for
`Urban Area Location Based Applications' Consumer Communica
`tions and Networking Conference, 2004. CCNC 2004. First IEEE
`Las Vegas, NV, USA, IEEE, Jan.5, 2004 Piscataway, NJ,USA, IEEE,
`Jan. 5, 2004, pp. 595-599.
`* cited by examiner
`Primary Examiner Sanh D Phu
`(74) Attorney, Agent, or Firm—Richard A. Bachard; Linda G.
`Gunderson; Thomas R. Rouse
`
`ABSTRACT
`(57)
`A system, method and device are provided for determining
`the position of a mobile station through the identification of
`an approximate position of the mobile station. Thereafter
`received signal strength (RSSI) fingerprint data for the
`approximate position is requested and retrieved. The finger
`print data and received signal strength data collected at the
`mobile station are compared in connection with fixing the
`position of the mobile station.
`
`24 Claims, 4 Drawing Sheets
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`RSS
`NDICATOR
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`LOCATION
`ESTIMATOR
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`FINGERPRINT
`REGUESTOR
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`FINGERPRINT
`COMPARATOR
`50
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`NETWORK
`54
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`LOCATION
`DISPLAY
`52
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`Page 1 of 9
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`SAMSUNG EX-1062
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`U.S. Patent
`U.S. Patent
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`Oct. 7, 2008
`Oct. 7, 2008
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`Sheet 1 of 4
`Sheet 1 of 4
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`US 7.433,693 B2
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`Fig. 1
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`U.S. Patent
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`Oct. 7, 2008
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`Sheet 2 of 4
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`US 7.433,693 B2
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`MOBILE STATION
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`Fig. 2
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`LOCATION
`APPROX.
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`MEMORY
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`Sheet 3 of 4
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`US 7.433,693 B2
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`RSS
`INDICATOR
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`LOCATION
`ESTIMATOR
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`FINGERPRINT
`REQUESTOR
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`FINGERPRINT
`COMPARATOR
`50
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`NETWORK
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`Fig. 4
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`LOCATION
`DISPLAY
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`TOWER
`TOWER TOWER INTES
`on RSSITOKEN LOCATION
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`Oct. 7, 2008
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`Sheet 4 of 4
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`US 7.433,693 B2
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`76
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`60
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`COLLECT RSS
`DATA ATMS
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`62
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`DETERMINE APPROXIMATE
`MSLOCATION
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`SELECT LOOK-UP TOKEN ON
`THE BASIS OF APPROXIMATE
`MSLOCATION
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`COMPARE LOOK-UP TOKEN
`DATA TO RSS
`DATA COLLECTED
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`FIND CORRELATION OF
`RSS DATA WITH
`LOOK-UPDATA
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`70
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`SELECT TOKEN WITH
`HIGHEST CORRELATION
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`CORRELATION
`ABOVE A SET
`THRESHOLD
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`Fig. 6
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`US 7,433,693 B2
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`1.
`LOCATION-SENSTIVE CALIBRATION DATA
`
`CROSS-REFERENCE TO RELATED
`APPLICATION
`
`This application claims priority from copending provi
`sional patent application 60/622,884, filed Oct. 27, 2004.
`
`BACKGROUND
`
`2
`system, especially in heavily trafficked networks. While not
`Subject to many of the problems associated with other posi
`tion identifying technologies, fingerprinting requires Sub
`stantial work in data collection and is most feasible in highly
`populated, highly concentrated metropolitan areas. However,
`fingerprinting benefits from the collection of multi-path sig
`nal data which arises through indirect signal paths from trans
`mitter to receiver. A need exists to seize on the benefits of
`fingerprinting in a manner that improves current RSSI posi
`tion measurement techniques.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 is a diagram of a mobile station and several BTSs
`organized in a grid, with each grid division being assigned a
`token look-up, indicated by a subscripted “T”.
`FIG. 2 is a block diagram of an embodiment of a commu
`nication system.
`FIG. 3 is a block diagram of mobile station.
`FIG. 4 illustrates a functional block diagram of a mobile
`station position location system.
`FIG. 5 is a chart illustrating the type of data which can be
`maintained in fingerprint database.
`FIG. 6 is a flowchart of a method for determining a position
`of a mobile station.
`
`DETAILED DESCRIPTION
`
`An improved position determination method, system, and
`device are provided for a mobile station, especially for use in
`highly populated areas exhibiting multi-path signal patterns.
`Familiar locations having such multi-path signal patterns
`include, for example, the Chicago, Manhattan, or San-Fran
`cisco financial districts.
`In one position determination aspect, fingerprint data is
`stored in a network database, and relevant portions of the
`database are downloaded to the mobile station in connection
`with identifying an approximate signal reception area in
`which the mobile station lies. The fingerprint database
`includes RSSI data.
`With reference to FIG. 1, which illustrates a diagram
`including mobile station 2 (Suggesting a car phone) and sev
`eral transmitting receiving sites, such as BTSS organized in
`grid 5, each grid division is assigned a token look-up indi
`cated by a subscripted “T”. The subscripts refer to the row and
`column of grid 5.
`The embodiments can be used in conjunction with several
`different radio access channel systems, including, for
`example, code division multiple access (CDMA), time divi
`sion multiple access (TDMA), frequency division multiple
`access (FDMA), space division multiple access (SDMA), or
`like systems.
`In the case of CDMA systems, signals are spread over a
`frequency and coded. Such characteristics contribute to sig
`nal properties allowing privacy andjamming resistance. Cod
`ing is accomplished using code resembling noise, which is
`referred to as pseudorandom scrambling code or pseudo
`noise. Whereas other mobile systems regard multipath signal
`characteristics as being undesirable, with CDMA, a multipath
`signal has some desirable aspects in that the multi-path sig
`nals can be used to increase the quality of a signal. This is
`made possible because the wideband nature of CDMA sig
`nals. Each BTS site 4 transmits a pseudo noise (PN) code
`having a unique code sequence, (including a base station
`identification (BASE-ID) which mobile station 2 can distin
`guish in the BTS's pilot signal on the forward link (commu
`nication from a BTS to mobile station) pilot channel. The
`
`10
`
`15
`
`Locating people, vehicles employees, etc. has become a
`matter of increased importance over the last several years,
`especially through the medium of a mobile phone. Much
`interest in determining mobile phone position was prompted
`by the Federal Communications Commission (FCC) through
`its edict to create the wireless Enhanced 911 system (E911)
`by November 2005.
`Several technologies are available and have been proposed
`for mobile station (e.g. mobile phone, personal digital assis
`tant (PDA) with telecommunications capability, portable
`computer with telecommunications capability, pager etc.)
`position determination ranging from use of the global posi
`tioning systems (GPS) to phone network-based solutions.
`Fingerprinting provides another approach to determining the
`position of a mobile station.
`Radio frequency signal characteristics associated with
`various regions in a signal transmission area are collected in
`a database. Each grouping of signal characteristics for a
`region is known as a fingerprint. Typically, the position of a
`mobile station is determined by comparing a RF data sample
`collected by the mobile station to fingerprint data in the data
`base. The mobile station’s position is determined to lie in the
`area corresponding to a fingerprint data point of highest cor
`relation to the RF data sample.
`The comparison is made by a server holding the fingerprint
`data. If the comparison were to be accomplished at a mobile
`station, in accordance with conventional practices, a signifi
`cant amount of data would have to be downloaded from a
`network-based database to the mobile station. Fingerprinting
`requires multiple measurements to be taken from different
`base stations or cell sites, e.g., base station transceivers
`(BTSs), at different times of day to capture short-term signal
`variation (Rayleigh fading, etc.) and variations in network
`load (capacity) in an effort to capture each fingerprint cali
`bration point for a fingerprint database. Consequently, down
`45
`loading the fingerprint database to the mobile station would
`likely be infeasible.
`Received signal strength indicator (RSSI) has been used in
`connection with network planning and fingerprinting by Eka
`hau, Inc. Radio network sample points are collected from
`different site locations. Each sample point contains RSSI data
`together with related map coordinates which are stored in a
`database for position tracking of persons, assets, equipment,
`etc. within a Wi-Fi network (802.11a/b/g).
`However, this Wi-Fi based Ekahau system is for small
`applications wherein a program run on a server calculates
`position determinations and interacts with a client device
`(i.e., laptop computer, personal digital assistant (PDA), Wi-Fi
`Tag, etc.) in connection with an application program for
`recording field data (e.g., RSSI data). The position determi
`nation data returned can include the speed, heading, building
`floor and grid location of client device. For larger scale appli
`cations, several U.S. wireless carriers determine a mobile
`phone's location using RSSI measurements made from and
`by nearby BTSs.
`Triangulation techniques can result in duplicative calcula
`tions at a network server which can unnecessarily burden the
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`US 7,433,693 B2
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`4
`gies. The level of accuracy is increased over basic cell-ID. For
`example, in GSM networks, the additional technologies for
`combination can include Timing Advance (which measures
`handset range from the base station, including whether or not
`the handset is connected to the nearest cell) and RSSI.
`Table 1 below summarizes the expected performance in
`terms of average accuracies of position determination accord
`ing to the method indicated to obtain a location approxima
`tion. The accuracies define the search regions for RSSI
`matching and reduce significantly the number of grids to be
`provided to and examined by the mobile station.
`
`10
`
`TABLE 1
`
`15
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`Location Approximation
`Method
`
`AFLT
`
`Enhanced
`Cell-ID
`
`Cell-ID
`
`Average Accuracy of
`Position Determination
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`100 to 200 m 150 to 1000 m 750 m to
`3-5 km
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`3
`pilot channel constantly transmits signal 7 which mobile sta
`tion 2 uses to acquire the communication system. After
`mobile station 2 has acquired the system, pilot signal 7 is used
`for signal strength measurement.
`The strength of the pilot signal from a BTS to a mobile
`station is used to determine the power required to properly
`adjust the strength of a mobile station's signal transmission.
`Additionally, according to one aspect, the pilot signal
`strength can be used to identify transmitting BTSs in an effort
`to define relevant look-up tokens from a network database
`(not shown) which contains pertinent RSSI database infor
`mation for comparison with the RSSI data measured at
`mobile station 2.
`The relevant look-up token information can be determined
`from a single BTS. For instance, BTS 4A can be circum
`scribed within circle 12 (shown partially) defining a transmit
`ting radius 10. Look-up token data within circle 12 of a given
`radius 10 can be downloaded to mobile station 2. Radius 10
`can be of a predetermined length, a parameter selection char
`acteristic that is especially Suitable for multi-path signal envi
`ronments. Alternatively, the length of radius 10 can be tai
`lored as a function of pilot signal strength. For instance, the
`stronger the signal, the Smaller the radius length needed since
`a closer proximity to a BTS may be inferred and a fewer
`number of look-up tokens analyzed.
`Mobile station 2 compares the downloaded look-up token
`information based on a single BTS 4 with RSSI data mea
`Sured at its position to assess its location. Since each look-up
`token T corresponds to a mapped location, choosing the look
`up token with closest correlation to the measured RSSI data
`allows a position fix at location corresponding to that look-up
`token. As can be judged from FIG. 1's grid 5 of look-up
`tokens, more look-up tokens over a given area will allow
`tighter grid spacing and thus provide a better basis for a more
`accurate position determination.
`In an alternative embodiment, the pilot signals from two
`BTSs are used to determine the relevant look-up token data
`for analysis. As shown in FIG. 1, intersecting radii 10 from
`BTSs 4A and 4C, respectively, define a region of intersection
`6 on grid 5. Consequently, the affected areas in region 6 relate
`to look-up tokens which include T.T.T.T.s, and T22.
`The look-up tokens within the region of intersection 6 are
`downloaded to mobile station 2. By using two BTSs to define
`the relevant look-up tokens, fewer look-up tokens may have
`to be analyzed as compared with look-up tokens within a
`transmission radius of a single BTS 4. As with the previous
`embodiment, radius 10 can be of a predetermined length or it
`can be tailored to represent a function of pilot signal strength
`from each BTS. Accordingly, each radius 10 associated with
`a given BTS 4 need not be the same length.
`In another alternative embodiment, other methods of deter
`mining the relevant look-up token data for analysis, and there
`fore an approximate location for the mobile station, may be
`used. For instance the pilot signal from yet a third BTS, BTS
`4B, can be used to establish another intersecting circle (not
`shown) in a manner employing advanced forward link trilat
`eration (AFLT). With AFLT, the mobile station takes RSSI
`measurements of signals from nearby cellular base stations
`(towers) in addition to the relative times of arrival (TOA)
`measurements, and uses these readings to trilaterate an
`approximate location of the handset.
`Additionally, pertinent RSSI fingerprint data for download
`to the mobile station can also be based on a cell-ID (cellular
`identifiers) information, or enhanced cell-ID through the
`identification of cellular base station masts proximate the
`mobile station. Enhanced Cell-ID is a network technology
`that combines cell-ID with one or more additional technolo
`
`FIG. 2 is a block diagram showing a system in which the
`interaction of mobile station 2 with BTS 4 and database 8 can
`be located remotely from mobile station 2 and BTS 4. Inter
`action is such that a request, denoted by the outgoing end of
`double arrow 16, to a BTS 4 (having the strongest pilot signal
`strength indication), for selected look-up tokens can be made
`by mobile station 2 in connection with analyzing signal
`strength data received from BTSs. Look-up token informa
`tion can be received by the same BTS 4 from database 8 in
`connection with a request to a server 11 at which the database
`is resident. Alternatively, database 8 information can be for
`warded to mobile station 2 through another BTS (not shown)
`as indicated by dotted lined arrow 20.
`In an alternative embodiment, other unique cellular iden
`tifiers in addition to the base station identification (BASE-ID)
`can be used to identify an area of interest in connection with
`downloading the pertinent fingerprint data. These identifiers
`include the system identification (SID)/network identifica
`tion (NID)/BASE-ID and SID/mobile switching center iden
`tification (MSC-ID)/BASE-ID.
`FIG. 3 is a block diagram of mobile station 2. As shown,
`mobile station 2 includes a location approximation identifier
`section 30 which identifies the pertinent portion of the finger
`print database to download to mobile station 2 in accordance
`with one of the location approximation methods discussed
`herein, i.e. AFLT, enhanced Cell-ID, etc. RSSI section 32
`determines RSSI measurements at mobile station 2 working
`in conjunction with a radio frequency communication section
`34 for providing mobile communications and processor 36
`for processing data within mobile station 2. The RSSI mea
`Surements, request for pertinent fingerprint data and determi
`nation of mobile station position occur in connection with
`software 42 held in memory 40.
`FIG. 4 is a functional block diagram of a mobile station
`position location system. As shown, location estimator 46
`identifies an approximate location of the mobile station
`according to one of methods discussed herein. Alternatively,
`location estimator can be implemented in the network 54.
`Fingerprint requestor 48 requests and obtains the pertinent
`fingerprint data for the approximate location identified by
`location estimator 46. Fingerprint comparator 50 compares
`the measured RSSI data as determined by RSSI indicator 51
`with the fingerprint data received from network 54 through
`fingerprint requestor 48 in connection with requestor 48’s
`fingerprint request.
`A mobile station's position is determined by fingerprint
`comparator 50 in connection with choosing a look-up token
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`with highest correlation to the RSSI data measured by RSSI
`indicator 51. The area corresponding to the look-up token is
`chosen as the position of the mobile station. The mobile
`station's location is displayed on location display 52. The
`location can be displayed in terms of latitude and longitude 5
`readings. Additionally, or alternatively, the location can
`include a representative street address. Alternatively, location
`display step may entail mapping and displaying location on
`the digital map. In yet another embodiment the location can
`be provided to an application internal or external to the 10
`mobile station for further processing and display.
`FIG. 5 is a chart illustrating the type of data which can be
`maintained in fingerprint database 8 that is used to determine
`the position of the mobile station. As shown, database 8 can
`hold tower entries indicating the identity of towers for defin- 15
`ing the areas of look-up token interest. FIG. 5 show an
`example of two tower entries. However, more tower entries
`can be used to define a look-up token area. For further refine
`ment of the look-up token area, the intersecting areas between
`two towers can be documented as determined by a specified 20
`radius, defining BTS antenna coverage orantenna range, out
`from each BTS. Note, however, that it is useful to maintain
`single tower entries in database 8 to account for circum
`stances where a single tower is sufficient to define the look-up
`token area and where only a single tower reception is relevant. 25
`RSSI tokens as defined by the tower intersection area or
`single tower, can be maintained in database 8. Location as
`defined by latitude and longitude readings, among other mea
`Sures, can also be maintained in database 8.
`FIG. 6 is a flowchart showing a method for position deter- 30
`mination of a mobile station. As shown, RSSI data is collected
`by the mobile station, 60. Thereafter, an approximate location
`of the mobile station is determined, 62. The approximate
`location of the mobile station can be determined according to
`one of the foregoing discussed techniques. For instance, in 35
`one aspect, the mobile station determines the nearest BTS site
`based on pilot signal strength from the transmitted pilot signal
`on the received pilot channel. A second and next nearest BTS
`tower is identified based on the 2" and next strongest pilot
`signal. Based on the intersection of overlapping reception 40
`areas from the two or more identified BTS sites, an area of
`interest of relevant look-up tokens is defined and supplied to
`the mobile station.
`In another aspect, look-up token data is defined corre
`sponding to an area identified as being proximate to the 45
`mobile station, 64. These look-up tokens are compared, pref
`erably at a server holding the look-up token database, with the
`RSSI data collected by the mobile station, 66. A correlation is
`calculated between each look-up token data point in the
`defined area of interest, 68. The look-up token with the high- 50
`est correlation to the collected RSSI data is selected, 70, and
`compared with a predetermined correlation threshold, 72. For
`instance, should an 80% correlation between the look-up
`token and collected RSSI data be sufficient then the selected
`look-up token is chosen indicative of a corresponding posi- 55
`tion location (street address, longitudinal and latitudinal indi
`cation, etc.) of the mobile station, 74. If the selected look-up
`token of highest correlation fails to meet the threshold value,
`the method is restarted, starting with collection of RSSI data
`by the mobile station, 60, in an effort to obtain a position fix 60
`for the mobile station. The use of many known algorithms
`related to nearest neighbor search and signal pattern matching
`is also contemplated herein. These techniques can be
`employed to further refine the location estimate.
`Although a description has been given with reference to 65
`particular embodiments, it is to be understood that these
`embodiments are merely illustrative of the principles and
`
`6
`applications. It is therefore to be understood that numerous
`modifications may be made to the illustrative embodiments
`and that other arrangements may be devised without depart
`ing from the spirit and scope as defined by the appended
`claims.
`The invention claimed is:
`1. A system for determining the position of a mobile station
`comprising:
`a location estimator for identifying an approximate posi
`tion of the mobile station;
`a fingerprint requestor for requesting and obtaining,
`through radio channel access, pertinent location finger
`print data from a fingerprint database remote from said
`mobile station, said pertinent location fingerprint data
`being indicative of the approximate position of the
`mobile station; and
`a fingerprint comparator for comparing measured RSSI
`data at said mobile station with said pertinent location
`fingerprint data in order to determine a position of the
`mobile station.
`2. A system for determining the position of a mobile station
`as recited in claim 1 further comprising a display, said display
`being operable to indicate the position of the mobile station.
`3. A system for determining the position of a mobile station
`as recited in claim 1 wherein said radio channel access is
`provided through a technique selected from the group of
`radio-channel access schemes consisting of CDMA, TDMA,
`FDMA, SDMA, and a combination thereof.
`4. A system for determining the position of a mobile station
`as recited in claim 1 wherein said remote fingerprint database
`contains RSSI data.
`5. A system as recited in claim 1 wherein said mobile
`station is a mobile communications device selected from the
`group consisting of a mobile phone, a personal digital assis
`tant with wireless communications capability, a portable
`computer with wireless communications capability and a
`pager.
`6. A mobile station comprising:
`a location approximation identification section being oper
`able to identify and download to said mobile station a
`pertinent portion of a remote fingerprint database, the
`pertinent portion of a remote fingerprint database corre
`sponding to a vicinity of said mobile station;
`a RSSI section for making RSSI measurements at said
`mobile station;
`a memory;
`a processor;
`Software held in memory and run in said processor for
`determining a position of said mobile station by com
`paring said pertinent portion of said remote fingerprint
`database corresponding to the vicinity of said mobile
`station with said RSSI measurements made at said
`mobile station.
`7. A mobile station as recited in claim 6 wherein said
`location approximation identification section identifies a per
`tinent portion of a remote fingerprint database, corresponding
`to a vicinity of said mobile station by a method of advanced
`forward link trilateration.
`8. A mobile station as recited in claim 6 wherein said
`location approximation identification section identifies a per
`tinent portion of a remote fingerprint database through iden
`tification of a base station site in the vicinity of said mobile
`station by measuring base station pilot signal strength.
`9. A mobile station as recited in claim 6 wherein said
`location approximation identification section identifies a per
`tinent portion of a remote fingerprint database, corresponding
`to a vicinity of said mobile station by a method using cell-ID
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`7
`through the identification of a cellular base station located
`proximate said mobile station.
`10. A mobile station as recited in claim 6 wherein said
`location approximation identification section identifies a per
`tinent portion of a remote fingerprint database, corresponding
`to a vicinity of said mobile station by a method using
`enhanced cell-ID.
`11. A system for determining the position of a mobile
`station comprising:
`a fingerprint database including RSSI data;
`a mobile station including a location estimator for identi
`fying an approximate position of said mobile station;
`a fingerprint requestor for requesting and obtaining,
`through radio channel access, pertinent location finger
`print data from a fingerprint database remote from said
`mobile station, said pertinent location fingerprint data
`being indicative of the approximate position of the
`mobile station; and
`a fingerprint comparator for comparing measured RSSI
`data at said mobile station with said pertinent location
`fingerprint data in order to determine a position of said
`mobile station.
`12. A method of determining the position of a mobile
`station comprising:
`collecting RSSI data at a mobile station;
`determining an approximate location of said mobile sta
`tion;
`Selecting fingerprint look-up token data, from a database
`located remote from said mobile station, corresponding
`to said approximate location of said mobile station;
`comparing said fingerprint look-up token data selected
`from the database corresponding to said approximate
`location of said mobile station with said RSSI data col
`lected at said mobile station; and
`determining a position of said mobile station in accordance
`with finding said fingerprint look-up token data of high
`est correlation with said RSSI data.
`13. A method of determining the position of a mobile
`station as recited in claim 12 further including determining
`whether said highest correlation meets a predetermined
`threshold.
`14. A method of determining the position of a mobile
`station as recited in claim 13 wherein said method is reiterated
`should said highest correlation fail to meet said predeter
`mined threshold.
`
`10
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`15
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`25
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`30
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`US 7,433,693 B2
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`8
`15. A method of determining the position of a mobile
`station as recited in claim 12 wherein said fingerprint look-up
`token data includes RSSI data.
`16. A method of determining the position of a mobile
`station as recited in claim 12 wherein determining the
`approximate location of said mobile station is accomplished
`using a method of AFLT.
`17. A method of determining the position of a mobile
`station as recited in claim 12 wherein determining the
`approximate location of said mobile station is accomplished
`through identification of a base station site in the vicinity of
`said mobile station measuring base station pilot signal
`strength.
`18. A method of determining the position of a mobile
`station as recited in claim 12 wherein determining the
`approximate location of said mobile station is accomplished
`through identification of a cellular base station antenna
`located proximate said mobile station.
`19. A method of determining the position of a mobile
`station as recited in claim 12 which further includes display
`ing said mobile station location.
`20. A method of determining the position of a mobile
`station as recited in claim 19 wherein the display of said
`mobile station location includes longitudinal and latitudinal
`readings.
`21. A method of determining the position of a mobile
`station as recited in claim 19 wherein the display of said
`mobile station location includes street location information.
`22. A system for determining the position of a mobile
`station comprising:
`means for estimating an approximate position of the
`mobile station;
`means for requesting and obtaining pertinent location fin
`gerprint data from a fingerprint database, said pertinent
`location fingerprint data being indicative of the approxi
`mate position of the mobile station from the means for
`estimating; and
`means for comparing measured RSSI data at said mobile
`station with said pertinent location fingerprint data to
`determine the position of said mobile station.
`23. The system for determining of claim 22 wherein the
`fingerprint database contains RSSI data.
`24. The system for determining of claim 22 wherein the
`means for requesting and obtaining comprises radio channel
`aCCCSS,
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