EP2440947A1

EP2440947A1 - Geolocation of a mobile station of a wireless telephony network

Info

Publication number: EP2440947A1
Application number: EP10724778A
Authority: EP
Inventors: Bruce Denby; Gérard Dreyfus; Yacine Oussar; Iness Ahriz
Original assignee: Universite Pierre et Marie Curie Paris 6
Current assignee: Universite Pierre et Marie Curie Paris 6
Priority date: 2009-06-12
Filing date: 2010-06-04
Publication date: 2012-04-18
Also published as: WO2010142615A1; FR2946825B1; FR2946825A1; US20120115510A1; JP2012529635A; KR20120034195A

Abstract

The invention relates to a method for locating a mobile station inside an area covered by a wireless telephony cellular network in which the mobile station operates. The method comprises using the mobile station to measure the received power (P_LX) on at least seven different communication channels of the network (step 200) and then locating the station according to said measurements and relevant predetermined information of the correspondence between received power on said channels and location within the covered area (step 210). The predetermined information can comprise power levels (P_LiMj) previously measured on said channels at different locations (Li) and stored in a database (BD1), in which case the station is located by comparing the measurements (P_LX) with the contents of the database (BD1). The method also enables greater locating accuracy, even inside buildings.

Description

GEOLOCATION OF A MOBILE STATION OF A NETWORK OF

WIRELESS TELEPHONY

The present invention relates to the field of geolocation, more particularly the geolocation of a mobile station operating in at least one mobile telephone network.

It may be desirable to be able to accurately locate a person or objects outside or inside buildings.

Mobile station location systems from radio signals in a cellular network have already been proposed. These mobile station location systems are notably implemented for locations in an external environment. These systems, however, locate a mobile station to the extent of its home cell.

These systems are therefore relatively inaccurate.

However, it is possible to obtain a better accuracy of these systems by comparing the signals of the nearest base stations (the so-called

"Fmgerprint"). The accuracy thus obtained remains weak since it is of the order of a hundred meters. Such inaccuracy is of course incompatible with a location inside buildings, to determine in which room of the building is the mobile station. Thus, the adaptations of such systems to the location inside buildings do not give complete satisfaction.

Furthermore, it is known mobile stations equipped with a global positioning receiver associated with a global positioning system or GPS (acronym for "Global Positioning System"). This GPS receiver is adapted to receive radio synchronization signals broadcast by satellites. These signals allow the receiver to determine its location (longitude, latitude and altitude), regardless of weather conditions.

The GPS receiver of a motor vehicle is also generally adapted to implement a so-called "dead reckoning" process. Such a method makes it possible to locate the vehicle even when it is in a tunnel or an urban environment, where the number of satellites is insufficient to achieve the location of the vehicle by means of the single reception of the signals broadcast by the satellites. Such a "dead reckoning" method estimates the position of the motor vehicle from the location data previously received from the satellites.

A "pedestrian" mode is usually available on GPS receivers. This "pedestrian" mode extends the GPS service to the location of people. However, the accuracy of this mode "pedestrian" is significantly less satisfactory. Indeed, a pedestrian moves much more slowly than a vehicle. In addition, a pedestrian is likely to remain long - sometimes even permanently - in areas that do not allow good reception of the signals emitted by the satellites. This is especially true inside buildings. In such a case, synchronization of the GPS receiver with the satellites is quickly lost. The location accuracy is greatly degraded compared to the accuracy that can be obtained in an area well covered by GPS satellites.

In addition, the GPS system provides no information on the position of a person inside a building.

There are also radio-based closed-loop location systems implemented in Wi-Fi networks (defined by IEEE 802.11 standards). The "fingerprint" process is still implemented in this type of system. Wi-Fi access points play the role of cellular base stations. Precisions of about 2 meters have been cited in the literature for the location in corridors of large commercial buildings with multiple Wi-Fi access points.

However, Wi-Fi does not lend itself well to home environments, storage warehouses, etc. Indeed, Wi-Fi networks are less common, less dense when they are deployed. These Wi-Fi networks can be very variable from the point of view of the positioning of the access points. In addition, the frequency used in Wi-Fi, (2.4 GHz or 5 GHz as appropriate), does not lend itself to good location because the signals in this frequency range are too weakened by the partitions that we found in buildings. Systems implemented in Wi-Fi networks also imply that the person or object to be located has a Wi-Fi enabled device. This is rarely the case. There is therefore a need for a location method that is simple to implement while being efficient and accurate in any location, and particularly within one or more buildings.

To this end, according to a first aspect, the invention proposes a method of providing information that can be used to locate a mobile station within a given area covered by at least one cellular wireless telephone network. wherein the mobile station operates, the method comprising: for one or more given locations within the given area, providing for each given location at least one set of N values, each of the values corresponding to one level measured reception power on a respective one of N different and predetermined communication channels of the at least one wireless telephony cellular network, N being a fixed integer greater than or equal to 7; and creating a first database associating with each set of N values the given location of corresponding measurement. According to a first preferred embodiment, the method further comprises: for each of one or more given locations within the given area, defining a set of R predetermined value (s) which is specific to this given place, R being an integer greater than or equal to 1, this set of R predetermined value (s) being associated with each set of N values provided for the corresponding given place in the first database; and the determination by statistical learning from the first database of a set of R function (s) able to provide, from each set of N values, a set of R value (s) which is an approximation of the set of R predetermined value (s) associated with this set of N values. According to a second preferred embodiment, the method further comprises: - providing Q different function (s), Q being an integer greater than or equal to 1 and less than N, and the creation of a second database from the first database by applying to each set of N values, the one or more Q function (s) to provide a set of Q value (s) corresponding, the set of Q value (s) being associated in the second a database at the given location of corresponding measurement, in which the Q functions (s) are chosen so that, for any pair of sets of N values different from the database, the two sets of Q values obtained by application of these Q functions to this pair of games of N values, are different from each other. It is advantageous for the Q function (s) to be provided either by principal component analysis, independent component analysis, or the Q function (s) respectively providing the mean value, the standard deviation, and other moments. of higher order of the set of N values. In addition, it is advantageous that the method comprises: for each of one or more given locations within the given area, the definition of a set of R predetermined value (s) which is specific to that area; given location, R being an integer greater than or equal to 1, this set of R predetermined value (s) being associated with each set of Q values provided for the corresponding given location in the second database; and determining by statistical learning from the second database a set of R function (s) capable of providing, from each set of Q value (s), a set of R value (s) which is an approximation of the set of R predetermined value (s) associated with this set of Q value (s). According to a third preferred embodiment, the method comprises for each given location, the determination by statistical learning from either the first database or the second database, of a function able to supply, respectively from of the set of N values or the set of Q value (s) obtained by applying the Q function (s) to the set of N values, an estimate of the probability that the measurement was made at that given location.

According to a second aspect, the invention proposes a method for locating a mobile station within a given area covered by at least one cellular wireless telephone network in which the mobile station operates, the method comprising the steps of: a) measuring by the mobile station of the reception power level on each of N different and predetermined communication channels of the at least one cellular wireless telephone network, N being an integer greater than or equal to 7, and b) location of the mobile station based on the levels measured in step a) and predetermined significant information of the match between receive power level on each of the N channels and location within the given area. .

According to a preferred embodiment, it is provided that for one or more given locations within the given area, the predetermined information comprises for each given location at least one associated set of W predetermined value (s) which is significant of a reception power level on each of the N channels at the corresponding given location, where W is an integer greater than or equal to 1; and step b) comprises locating the mobile station by analyzing the levels measured in step a) with respect to the set (x) of W predetermined value (s).

It can be expected that W is equal to N, the W predetermined values of each set being each representative of a reception power level on a respective one of the N channels; and the analysis in step b) comprises comparing the levels measured in step a) with the set (s) of W predetermined values. In this case, the set (s) of W predetermined values may be the set (s) of N values of the first database created with the information supply method according to the first aspect of the invention defined above. Alternatively, it can be expected that W is less than N, in which case the analysis in step b) comprises: (i) applying W different predetermined function (s) to the levels measured in step a) to provide a set of W value (s) which is significant of the levels measured in step a) in a manner homogeneous with the (s) set (x) of W predetermined value (s); and (ii) comparing the set of W value (s) thus provided with the set (s) of W predetermined values.

In this case, the set (s) of W value (s) and the W predetermined function (s) can be those provided, respectively created according to the second embodiment of the method of providing information according to the first aspect of the invention. According to another preferred embodiment, the predetermined information comprises for each of one or more given locations within the given area, an associated set of R predetermined value (s) which is specific to that given place. , R being an integer greater than or equal to 1, and a set of R predetermined functions (s) intended to provide, from the receiving power levels measured at any given location on the N channels and after a possible pretreatment of these measured levels, a set of R value (s) which is an approximation of the set of R predetermined value (s) corresponding to this given place. In addition, step b) comprises: (i) providing a set of R value (s) by means of the set of R predetermined function (s) from the levels measured at step a) and pretreated where appropriate; and (ii) locating the mobile station by comparing the set of R value (s) supplied with the set (s) of R predetermined value (s).

According to yet another preferred embodiment, the predetermined information comprises a set of R predetermined functions (s) intended to provide, from the reception power levels, measured at any location inside. of the given zone, on the N channels and after a possible pretreatment of these measured levels, a set of R value (s) which is an approximation of the coordinates of the measurement location, and the step b) comprises: (i) the providing a set of R value (s) by means of the set of R predetermined function (s) from the levels measured in step a) and pretreated if necessary; and (ii) the location of the mobile station at the coordinates expressed by the set of R value (s) provided.

According to yet another preferred embodiment, the predetermined information comprises a set of R predetermined functions (s) intended to provide, from the reception power levels, measured at any location inside. of the given zone, on the N channels and after a possible pretreatment of these measured levels, a set of R value (s) which is an approximation of the reference of the measurement location in a system of referencing places within the given area; and step b) comprises: (i) providing a set of R value (s) by means of the set R predetermined function (s) from the levels measured in step a) and pretreated if necessary; and (ii) locating the mobile station at the approximated location reference by the set of R value (s) provided.

In these various embodiments in which the predetermined information comprises a set of R predetermined function (s), this set of R predetermined function (s) can be determined by implementing the first embodiment. of the information providing method according to the first aspect of the invention.

According to yet another preferred embodiment, the predetermined information comprises for each of one or more given locations, an associated function intended to provide, from the reception power levels measured on the N channels and after a possible preprocessing of these measured levels, an estimate of the probability that the measurement was made at that location, and step b) includes the location of the mobile station based on the probability estimate provided by all or part of the functions from levels measured in step a) and pretreated if necessary. In this case, the function (s) can be provided by the third embodiment of the information providing method according to the first aspect of the invention.

In these various embodiments in which the predetermined information comprises one or more functions, it can be provided in step (i) that the levels measured in step a) are pretreated by the application of W functions. different predetermined values to provide a set of W value (s), W being an integer greater than or equal to 1 and less than N. In particular, it can be provided that the W function (s) are the Q function (s) provided respectively, that the predetermined R functions (s) are determined according to the second embodiment of the information supply method according to the first aspect of the invention.

More generally, it is advantageous for the location method to be implemented to locate the mobile station inside one or more buildings. It is also advantageous that the predetermined information is established on the basis of reception power measurements made on the N channels at different locations within the given area with the same mobile station to be located.

Finally, it is also advantageous - both in the process of providing information and in the context of the locating method - that N is greater than or equal to 20, preferably greater than or equal to 50 and more preferably greater than or equal to 200.

According to a third aspect, the invention proposes a software for a mobile station intended to operate in at least one cellular wireless telephone network, which software is provided for executing by the mobile station the localization method according to the invention.

According to a fourth aspect, the invention proposes computer software, intended to make the computer implement the following steps: (a) reception by the computer of a measurement made by a mobile station of the power level of receiving on each channel among N different and predetermined communication channels at least one wireless telephony cellular network, N being an integer greater than or equal to 7, and (b) locating the mobile station by implementing step b) of the localization method according to the invention.

According to a fifth aspect, the invention proposes a mobile station capable of operating in at least one cellular wireless telephone network, which is intended to execute the localization method according to the invention.

Other features and advantages of the invention will appear on reading the following detailed description of the embodiments of the invention, given by way of example only and with reference to the appended drawing, comprising:

FIGS. 1 to 3 illustrating a first embodiment,

FIGS. 4 to 6 illustrating a second embodiment, and

- Figures 7 to 10 illustrating a third embodiment. The invention proposes a method of locating a mobile station, for example a mobile phone, within a given area - called in the following location area - covered by at least one cellular wireless telephone network in which operates the mobile station. According to the method, the mobile station measures the reception power level on each channel among N different and predetermined communication channels of the at least one cellular wireless telephone network, N being an integer greater than or equal to 7 The mobile station is then located on the basis of the power levels previously measured on the N channels, as well as significant predetermined information on the correspondence between the reception power level on each of the N channels and the location on the N channels. inside the localization area.

The mobile station may be not only a mobile phone, but any other element capable of communicating with the cellular type wireless telephone network. In particular, the network may be a GSM network (acronym for Global System for Mobile Communication). It can also be a CDMA network (acronym for Code Division Multiple Access) or WCDMA (acronym for Wideband Code Division Multiple Access), especially a UMTS network (acronym for universal mobile telecommunication system) or CDMA2000. The network can also be a network PMR (acronym for Professional Mobile Radio, also called Private Mobile Radio) also called LMR network (acronym for Land Mobile Radio), or a network PAMR (acronym for Public Access Mobile Radio). The use of a cellular wireless telephone network is advantageous because the radio waves of the network penetrate inside the buildings, which makes it possible to locate inside buildings.

The communication channels are the different carriers contained in the frequency band used by the cellular wireless telephone network. The electromagnetic powers of the reception channels have the advantage of being easily measurable by a mobile station since it is already provided as standard to perform this type of measurement. In addition, measurements can be performed without the need to obtain authorization from the network owner. Furthermore, any communication channel can be used, whatever its function in the communication between the mobile station and the base station of the network: transmission of voice, any data such as sound, image, data, data, data signaling and control of the network, etc.

If within the location area, a same carrier used in reception by the mobile station is shared by several base stations of the network, it is advantageous to report the measurement not only to the carrier concerned, but also to the station basis of which the measure was made. In this case, a channel within the meaning of the invention is understood as referring both to the carrier concerned and to the base station concerned by the measurement of the reception power achieved by the mobile station. In other words, the same carrier can in fact be considered as defining as many communication channels as there are base stations transmitting on this carrier in the location area.

In the case of a GSM network, the reception power levels of the different channels are typically the RSSIs of the concerned carriers of the GSM network for given BSICs. For memory; the RSSI (Acronym for Received Signal Strength Indicator) is the electric field strength value of a carrier and the BSIC (Base Station Identity Code) is the identifier of a base station.

In the case of a UMTS network (acronym for Universal Mobile Telecommunications System), the reception power levels of the different channels may be the RSCP (acronym for Received Signal Code Power) of a predetermined number of pilot channels (CIPCH acronym for Common Pilot Channel). In the following, the examples described will relate more particularly to a GSM network, but they are adaptable to any other type of cellular wireless telephone network, including a UMTS or CDMA2000 network.

The use of power measurements over at least 7 channels is advantageous against all odds because this improves the accuracy of the location. Indeed, a technical bias prevailed until today, according to which there would be a strong redundancy of information provided by the reception powers of the different channels and that there would therefore be a saturation effect with the number of channels. As a result, in geo-ionization applications based on the reception power measurement, it was considered unnecessary to multiply the measurements on many different channels. But the invention made it possible to establish that this prejudice was false.

On the contrary, it has been unexpectedly found that the greater the number N of channels on which the measurements are made, the better the accuracy and reliability of the location. As a result, the number N of channels is chosen to be greater than or equal to 7. More preferably, the number N of channels is chosen to be greater than 10, more advantageously greater than 20, more advantageously even greater than 50 and even more advantageously superior The number N of channels can even correspond to the total number of channels available on the network. A GSM network can typically comprise more than 500 channels.

In the case where the number N of channels is limited, it is advantageous to make a preliminary study of the reception power on all the channels of the network in the location area to select N channels providing a good discrimination of places according power levels measured on these N channels. Although not necessary, it can be done so in any situation where the number N of channels is chosen lower than the total number of channels of the network, but this becomes particularly advantageous when the number N of channels is less than 100 and more s' it is less than 20. By way of example and in a nonlimiting manner, one way of making this selection is to choose the N channels of the network which have, on average, the strongest reception power in a certain number of regions. locations throughout the location area.

The accuracy of the location is all the more reliable as the measurements of the reception power level on the N channels - used to locate the mobile station - are made by the mobile station substantially at the same location. In practice, the measurements of the reception power level on the N channels are not performed simultaneously, but successively in time since the mobile station must each time tune to the channel to be measured. As a result, the reliability of the localization may be less if the measurements are done while the mobile station is moving. But this is not a problem in most applications where the mobile station moves at a low speed or is frequently stopped or in the case where it is necessary to detect that the mobile station remains abnormally long at the same time. in law. In practice, the measurement time of the reception power level on a channel is small, generally much less than the second. As a result, the time required to perform the measurements of the reception power level on the N channels, even if N is high, for example 200 or more, remains limited. For example, the measurement of the reception power level by a standard GSM telephone on about 500 channels remains less than one minute. Alternatively, it is possible to use a smaller number N of channels, for example less than 20, to reduce the time required to carry out the measurements. This makes it possible to ensure a sufficient reliability of location even if the mobile station is moving during the measurements, since the speed of movement remains limited. In addition, there are also products on the market that allow measurements to be made much more quickly, for example the product marketed under the name TEMS ™ POCKET by Ascom Network Testing Inc., Reston, VA, USA for WCDMA networks and GSM. The latter makes it possible to measure 500 channels in less than one second, which provides a reliable location while the mobile station is moving at a relatively high speed, for example a pedestrian walking rapidly, or even Running.

As mentioned above, after the measurement of the reception power level on the N channels by the mobile station, the location of the mobile station is carried out on the basis of the power levels previously measured on the N channels and predetermined information. significant of the correspondence between reception power level on each of the N channels and location within the location area.

Because it is significant of the correspondence between reception power level on each of the N channels and place within the location area, the predetermined information makes it possible to make a deduction as to the place where the station is located. mobile within the location area in view of the power levels measured by it on the N channels.

This predetermined information can be of any nature since it allows this deduction to be realized. For example, it is a database providing a map of the reception power level on the N channels in different locations within the location area. The deduction then takes place on the basis of a comparison of the measured reception power levels on the N channels by the mobile station with the power levels of the different places contained in the database. In other words, it is a form matching localization technique. The mesh size of the places - which is not necessarily constant - is chosen to provide a satisfactory accuracy for the location, and will depend in fact on the nature of the places: exterior / interior of the buildings, density of the communication network, etc. It is advantageous that this mapping is established by measuring the reception power levels in these different locations with the mobile station which will then be used to operate the geolocation. This ensures that the reliability of the location is not degraded due to the variability of measurements provided by different devices.

In another example, the predetermined information includes one or more mathematical functions providing a relationship between the receiving power levels on the N channels and the corresponding location. Thus, this or these functions provide, from the reception power levels on the N channels measured by the mobile station, either directly the location of the mobile station, or one or more data from which the location is deduced. This or these functions can in particular be defined by studying the above-mentioned database, in particular by artificial or statistical learning. This solution generally provides a more accurate location than the shape matching techniques. In the context of the invention, the location may be provided by the method in the form of a point location defined in any coordinate system. The coordinate system can be two-dimensional such as longitude and latitude, or three-dimensional such as longitude, latitude, and altitude. Alternatively, the location may be provided in the form of a location consisting of a predetermined geographical volume, for example a room within a building, or a predetermined geographical area which is of a surface nature, for example at outside buildings.

The location method is simple to deploy and almost universal, considering that it can be implemented in any location area when it is in the coverage of a mobile telephone network and that the majority today people have a mobile phone or other device communicating with a mobile phone network. The location process is all the more advantageous as it also works inside buildings or other places not covered by GPS signals. In addition, the method does not use information on the architecture of the cellular wireless telephone network, such as the position of antennas or base stations. In particular, synchronization interaction procedures, exchange of frames with the network that are not generally freely accessible, are not used. This makes it possible to avoid depending on the operator or operators for the implementation of the method.

The localization method can be implemented easily. Indeed, it can be implemented on a standard mobile station - for example a mobile phone - without any material modification of it. Just load it with software to execute the steps of the localization process that concerns it. Such software may be provided on any computer storage medium such as a CD-ROM or a hard disk of a server on a computer network - for example the Internet - from which it may be downloaded to the mobile station either directly or indirectly via a computer.

It can be provided that the mobile station performs the step of measuring the power level on the N channels of the network and that it sends, via the wireless communication network, for example, to a computer or server the levels thus measured. The step of locating the mobile station based on these measurements and the predetermined information is then performed by this computer or server. The predetermined information is in this case stored in the computer or server or any storage means to which it has access. This is advantageous in that the server generally has more powerful computing means than the mobile station and more storage means for storing the predetermined information. In another embodiment, both the measurement step and the localization method localization step can be implemented by the mobile station itself. In this case, the mobile station may be provided for sending, for example via the mobile telephone network, the result of the location to a computer or server or any other device such as another mobile station operating in the mobile telephone network .

Concerning the creation of the predetermined information using a database containing a map of the reception power level on the N channels in different given locations within the location area, the measurements to constitute this mapping can be done by the mobile station, and preferably by that used in the localization method.

If this database is constitutive of the predetermined information used in the location process, it is stored in the mobile station in the case where it will implement all the localization process. The implementation is easy since it is sufficient to load the mobile station with software to implement both the method of providing the predetermined information according to the invention and the location method. On the other hand, if the location step is performed by a server or a computer, the measures to constitute this mapping are sent to the server, for example via the network. The mobile station can send them for example each time it has measured the N levels on the N channels in one place, or store them to send them at once after all the measurements in the different places have been made.

This can also be the case if the predetermined information used in the localization process is obtained by studying the database, in particular by size reduction and / or artificial or statistical learning. In this case, it is actually preferable that the study is done using a computer or server that has more powerful computing means. The predetermined information thus obtained can then be sent, via the wireless telecommunications network, to the mobile station if it implements the entire localization process. Alternatively, the predetermined information can be loaded into the mobile station at the same time that it is loaded with the software to implement the location method. Whether during the implementation of the location method or for the establishment of the database containing the mapping of the reception power level on the N channels in different given locations within the location area, it It is advantageous for the mobile station to take measurements of the reception power level on the N channels when it is in standby mode. The fact that the mobile station performs the power measurements in standby mode, without the need to establish a communication, is advantageous in terms of energy consumption. Since a user spends an average of 3.3% of his time in telephone communication, the mobile station has all the time necessary to make the power measurements out of the communication time. This also prevents the mobile station from taking these measurements while remaining synchronous with the base station concerned for the current communication if these measurements were made during a communication in progress.

In all cases, the location method is well suited to be implemented in the context of the surveillance of objects or people. This concerns in particular elderly or medicalized people living alone - for example with Alzheimer's disease -, unattended children, or anyone in need of careful monitoring of their daily movements for reasons of health or safety. .

The result of the location can be transmitted by the mobile station or the server as appropriate to a third party, for example on a mobile station of its own, for example his mobile phone. Thus the third party can be informed at any time of the position of the mobile station. The result of the localization can also be transmitted to a dedicated server. The latter can record the successive location information and thus makes it possible to follow the movement of the monitored person. The server may also issue an alert, if necessary.

If the location is performed by the mobile station itself, it may be expected that the result of the location is transmitted to a third party who may be a relative, a neighbor or a security agency. The transmission can be done by SMS or MMS or via ftp on a server that can be consulted on the Internet by using the functionalities of the mobile station. Location updates can occur automatically at predetermined, programmable time intervals. A software application running on the mobile station can provide such updates. The supervisor or the third party can thus at any time consult the movements of the person or the object followed via a remote Internet application.

It can also be expected that the mobile station sends an alert message to the third party when the location has remained the same for a period longer than a specified period. This allows to realize an apparent immobility of the person or the object followed during an abnormally long period. In the case where the person needs to be rescued, the duration of intervention can be shortened which improves the safety of the person.

Other types of alarms are however possible. Thus, an alarm can be triggered manually or when the mobile station receives a signal from an implanted system (defibrillator, pacemaker, motion detector, etc.) sent by Bluetooth® or another communication protocol. low power / short range. Such alarms can be routed to a supervisor or monitoring agency by SMS or telephone call sent from the mobile station of the person or object being tracked.

The localization method is also applicable in the field of inter-machine communication, also called "Machine-to-Machine" or M2M. The M2M thus makes it possible to manage communications between any device that can be moved more or less frequently and whose movements must be followed remotely. This may include machinery, vehicles, measuring equipment, medical instruments, distributors of various products. In such a case, the method is preferably used in a GSM or UMTS standard M2M chip. Other protocols are nevertheless possible.

We will now describe with reference to Figures 1 to 3 a first embodiment in which the localization method uses a form matching technique. Fig. 1 is a flowchart illustrating the method for providing the predetermined significant information of the correspondence between reception power level on each of the N channels and location within the location area, which information will then be used by the locating method according to this first embodiment.

The method includes a first step 100 of measuring the reception power level on each of the N predetermined network channels, at each of a plurality of given locations. These measurements are preferably made with the mobile station used subsequently in the localization method. These locations may each correspond to a point location defined in any two-dimensional or three-dimensional coordinate system. Alternatively, they may each correspond to a predetermined geographical volume - for example a room within a building or a given part within such a room - or a predetermined geographical area of a surface nature, for example to the room. outside buildings.

The measurement operation on the N channels can be repeated several times at the same place, but at different times to provide several sets of measurements. This reduces the effects of measurement noise and disturbances that locally and temporarily affect the electromagnetic field. In the case where the given locations correspond to a predetermined volume or a surface area, the measurement operation on the N channels can also be repeated several times at different locations within the given location to provide several sets of measurements. This makes it possible to account for the variation of the reception power levels on the N channels inside the place. We will designate in the following by

L ₁ : each of the given locations, i being an integer taking the values from 1 to T, T being an integer greater than or equal to 1;

Mj: each series of measurements providing a set of measurements, j being an integer taking values from 1 to an integer which is the number of series of measurements made at the place L ₁ considered;

- C _k : each of the N communication channels, k being an integer taking values from 1 to N;

- PLiM _j Ck: the reception power level measured on the channel Ck during the measurement series M _j instead L ₁ ; - P _L1M,: the set consisting of the N power levels measured respectively on the N channels during the series of measurements M _j instead L ₁ , ie the set consisting of (PLIMJCI, • .PLiMjCk, .- - PLIMJCN). Each set P _UM , is comparable to the coordinates of a point or the components of a vector.

The method then comprises a second step 110 for creating a database BD1 which associates each set P _LIMJ to the corresponding location L ₁ .

In the database BD 1, the locations L ₁ are referenced by any identification system. It may be the coordinates of the places L ₁ in the case where the places Li correspond to a point location. In the case where the locations L ₁ correspond to a predetermined volume or to a surface area, they may for example be referenced by a sequence number, a code or the name of the part or zone concerned.

The database BD1 therefore takes the form of an array of the following type:

It will be understood that steps 100 and 110 are not necessarily successive, but may be concurrent.

In step 100, it can be provided that the user enters the reference of the location L ₁ concerned in the mobile station which is used in step 110 for the creation of the database. This has the advantage of being simple to implement.

The creation of the database can thus take the form of a game, during which the mobile station, once acquired a P _UMJ game, uses a voice synthesizer to ask the user for his current position, for example the name or number of the room in the building. The user then provides it on the keyboard of the mobile station, or by voice recognition. Voice synthesis and recognition systems are already common on mobile phones.

FIG. 2 is a flowchart illustrating the localization method in the context of this first embodiment.

The locating method comprises a first step 200 of measurement, by the mobile station, of the reception power level on each of the channels Ck. These measurements are made at the moment when it is desired to locate the mobile station, that is to say to determine the place in which it is located, which is noted in the sequence L _x . It is so provided N receiving power levels, each corresponding to a respective channel C _k , and which are noted in the following PLXCI, - • -I ³ LxCk, .. -PLXCN-

These N reception power levels define a set noted P _LX . This set P _LX can be considered as defining the coordinates of a point in the same coordinate system or the components of a vector in the same base as the

The locating method then comprises a second step 210 for comparing the set P _LX with the sets P _LIMJ in the database BD1. The place L _x is identified on the basis of this comparison. The comparison can be made on the basis of the distance separating the point defined by P _Lx to each of the points P _UM , which is determined by calculation.

The distance is preferably the Euclidean distance, which is calculated with the following formula:

Nevertheless, any other type of distance can be used, such as a distance L \ or a distance L ₀₀ .

The place Lx can be identified as the place L ₁ which corresponds to the point PLIM _J which has the lowest distance with the point PL _X. It may be envisaged not to carry out the comparison for all the sets P _UM , of the base BD1. For example, the comparisons can be stopped as soon as a game P _UMJ has provided a distance less than a predetermined threshold, in which case the place Lx is considered to correspond to the place Li of this game PLIM _J -

Alternatively, it may be planned to locate the location L _x at the centroid of a subset of several locations L ₁ . The locations L ₁ of this subset may be those which have a distance less than a predetermined threshold. As a variant, the subset of places L ₁ can be determined by a number B of places L ₁ which have the smallest distances. The number B can be predetermined or depend on the distances calculated for the different PLIM _J - In the calculation of the center of gravity, each place L ₁ retained is assigned the same weight.

Alternatively, each location L ₁ selected is weighted according to the distance or the distances of the different P _UM , of this place Li. It can be in particular a weighting in 1 / d.

The fact of resorting to a center of gravity calculation makes it possible to improve the precision of the localization. This solution applies preferably in the case where the places correspond to specific locations referenced in the database BD1 by coordinates.

Figure 3 illustrates an example of application of the first embodiment. For the sake of simplicity, the location area is in this example limited to 3 locations, respectively referenced L ₁ , L ₂ and L ₃ . In other words, T takes the values 1, 2 and 3. The number N of channels is in this case 10.

It is first implemented the method of providing the predetermined information in the form of database BD1 as described in connection with Figure 1. It is carried out at each location L ₁ , L ₂ and L ₃ to four series of separate measurements of the power level received on the ten channels considered in accordance with step 100 of the method: cf. FIG. 1. The measurement series for each locus L ₁ are referenced M ₁ , M ₂ , M ₃ and M ₄ , that is, 'j' takes the values 1, 2, 3 and 4. The database BD 1 is created according to FIG. step 110 of the method by associating with each set P _LIMJ the place L ₁ corresponding.

The power levels PnM _j Ck are represented in FIG. 3 by the vertical bars inside the corresponding frames.

The locating method is then implemented using the database BD 1 thus constituted, as described with reference to FIG. 2. More particularly, when it is desired to locate the mobile station, the latter performs the measurements. the receive power over the 10 channels to provide the P _{LX set} according to step 200. L _x is then determined by comparing this set P _LX to the sets P _L1M , in the database BD1 in accordance with step 210 of the process.

In this case, the place Lx is considered to be the place L ₃ because the game P _L3M3 is that of the set of games P _UM , which has the lowest Euclidean distance with the game P _Lx .

We will now describe with reference to Figures 4 to 6 a second embodiment which is based on the first embodiment, but which also uses a pretreatment of the data.

FIG. 4 is a flowchart illustrating the method for providing the predetermined significant information of the match between receive power level on each of the N channels and location within the location area, which information will then be used by the locating method according to this first embodiment.

As can be seen in the flow chart, the method comprises the same steps 100 and 110 as the method according to the first embodiment described in FIG. Referring to Figure 1. The entire description of these two steps in the context of the first embodiment is applicable to the identical to this second embodiment and will not be repeated here.

The method according to this second embodiment however comprises additional steps 120, 130 and 140. These additional steps are intended to provide a second database BD2 from a preprocessing of the first database BD1 obtained at step 110.

This pretreatment has the function of providing a second database BD2 which is smaller than the first database BD1.

Thus, step 120 consists in providing Q functions - each denoted by each - which together define a transformation denoted by 'f, where Q is an integer greater than or equal to 1 and less than N and p is an integer taking values from 1 to Q .

In step 130, this transformation 'f is applied to each set P _UM , of the first database BD1 to provide a new set of corresponding values V _LIMJ - In other words, each function%' is applied to the set P _UM , to provide a respective value - denoted VLIM _J , _P - of the value set (s) VHM _J , which can be summarized as follows:

VLIMJ - f (PLiMj)

= [fl (PLiMj), • • •, fp (PLiMj), -. . , fQ (PLiMj)] = [VLIMJ, 1, • • •, VLIMJ, P, • • •, VLIMJ, Q]

The method then comprises a step 140 of creating a second database BD2 which associates each set V _LIMJ to the place L ₁ corresponding.

It will be appreciated that steps 120 to 140 of the method are not necessarily consecutive, but may be nested within each other.

In the second database BD2, the locations L ₁ are preferably referenced in the same manner as in the first database BD1.

The database BD2 thus takes the form of an array of the following type:

Similar to the P _LIMJ games, each V _{LIMJ set} is also comparable to the coordinates of a point or the components of a vector.

The transformation f is preferably chosen so that the set (s) of value (s)

V _LIMJ associated with the places L _{1 is} discriminating (s) for the place Li corresponding to the value sets (s) obtained by 'f which are associated with the other places.

In other words, the functions% 'are chosen so that, for any pair of games P _UMJ different from the database BD1, the transformation of each of these two games

PLIM _J gives two sets VLIM _J which are different from each other, and preferably which are as different as possible to provide the best possible discrimination.

To this end, to define the functions 'f _p ', it can be resorted to any statistical method known per se, applied to the database BDl. For example, this is Principal Component Analysis (PCA) or independent component analysis. In these two cases, we can retain the first components that are discriminating for all sets of P _LIMJ values.

The transformation f may be a linear combination of the measured receive power levels PnM _j Ck, as is the case for a principal component analysis, or a nonlinear combination as may be the case for an independent component analysis . Another possibility is to define each function 'f _p ' as providing a given moment of the distribution of the levels PLiM _j Ck constituting a game P _LIMJ , such as the mean, the standard deviation and possibly other moments of order higher. In this case, it is possible to retain the lowest order moments that are discriminating for all sets of PLIM values. _J - The preprocessing transformation can also be a function composed of several transformations obtained by the techniques mentioned above.

Fig. 5 is a flowchart illustrating the locating method in the context of this second embodiment.

The first step 200 of the method is identical to that of the first embodiment. This is the measurement, by the mobile station, of the reception power level on each of the channels Ck to provide a set P _LX of N power levels PLXCI, - • -PLxCk, - • -PLXCN as it has been described for the first embodiment.

Unlike the first embodiment, the game P _LX is pre-processed - at step

220 - to make it homogeneous with the games V _HMJ in the second database BD2. For this, the transformation 'f' is applied to the game P _LX to provide a set of value (s) noted V _LX . In other words, each function 'f _p ' is applied to the set P _LX for supply a respective value - denoted V _LX , _P - of the value set (s) V _LX , which can be summarized as follows:

V _Lx = f (P _Lx ) = [f! (P _Lx ), ..., f _p (P _Lx ), ..., f _Q (P _Lx )]

⁼ [VL _X , i, ..., VL _X , _P , ..., VL _X , Q]

This game V _LX can also be considered as defining the coordinates of a point in the same coordinate system or the components of a vector in the same base as the games VLIM _J.

The locating method then comprises a step 230 for comparing the set V _LX with the sets V _LIMJ in the second database BD2 to identify the place Lx. This comparison step is performed in a manner similar to that of step 210 in the context of the first embodiment, except that it is done on the basis of the game V _LX and games V _LIMJ . Thus, the identification can be done by determining a minimum distance or by calculating a center of gravity. The entire description made with respect to step 210 of the first embodiment applies mutatis mutandis to this step 230 of the second embodiment and will therefore not be repeated here.

In the locating method according to the second embodiment, the first database is not used, but only the second database BD2. The fact of resorting to a pretreatment to provide a second BD2 database which is smaller than the first database BD1 is advantageous both because of the savings in terms of storage space and the simplification of the data processing operations. comparison to step 230. This is particularly the case if the location method is implemented by the mobile station itself.

Figure 6 illustrates an example of application of the second embodiment.

It is based on the example described with reference to FIG. 3. The creation of database BD1 is carried out by applying steps 100 and 110 of the method, as was described for FIG. 3 in the context of the first mode. of realization. The first database BD1 is not shown in FIG. 6 since it is that represented in FIG. 3.

In this example, a transformation f obtained by analysis of the main components of the database BD1 was chosen in step 120. In this case, it has been retained functions 'fi' and 'f ₂ ' corresponding to the first two main components because they provide the desirable discrimination between the different sets of values V _LIMJ - Q is equal to 2 and 'p' takes the values 1 and 2. In accordance with steps 130 and 140, the sets V _LIMJ are calculated and associated with the corresponding locations L ₁ within a second database BD2, with 'i' taking the values 1, 2 and 3 and 'j' taking the values 1, 2, 3 and 4. The sets V _LIMJ are the transforms of each set P _LIMJ by the functions 'fi' and 'f ₂ ' and therefore each comprise two values VLIM _J .I and VLIM ,, 2. In other words,

VLIMJ ⁼ f (PLiMj)

= [fl (P _Ll Mj), f ₂ (P _Ll Mj)] = [VLIMJ.IJ VLIMJ, 2]

The values VLIM _J .I and VLIM ,, 2 of each set VLIM _J are represented in FIG. 6 by the vertical bars inside the corresponding frames.

The locating method is then implemented using the second database BD2 thus constituted, as described with reference to FIG. 5. More particularly, when it is desired to locate the mobile station, the mobile station performs the following functions: receiving power measurements on the 10 channels to provide the P _{LX set} according to step 200. Then the set V _LX is calculated which is the P _LX transform by f. In other words,

V _Lx = f (P _Lx )

= [V _LXil , V _LX , ₂ ]

The values VL _X , i and VL _X , ₂ of the set VL _X are shown in FIG. 6. The locus L _x is then determined by comparing the set V _LX with the sets V _LIMJ in the second database BD2 according to FIG. step 230 of the method.

In this case, the place Lx is considered again to be the place L3 because the game VL3M3 is that of the set of games VLIM _J which has the lowest Euclidean distance with the game VL _X.

We will now describe with reference to Figures 7 to 10 a third embodiment that uses a statistical or artificial learning. This third embodiment is preferred in that it provides better location accuracy than the first and second embodiments. Fig. 7 is a flowchart illustrating the method for providing the predetermined significant information of the correspondence between reception power level on each of the N channels and location within the location, which information will then be used by the location method according to this third embodiment.

The method according to this third embodiment comprises steps 150 and 160 which apply in combination with those of the method described with reference to FIG. 1 of the first embodiment, or from the method described with reference to FIG. 4 of the second embodiment. embodiment.

With regard to its application in combination with the method described with reference to FIG. 1 of the first embodiment, this means that the method comprises the same steps 100 and 110 as the method according to the first embodiment described with reference to FIG. Figure 1. The entire description of these two steps in the context of the first embodiment is applicable to the identical to this second embodiment and therefore will not be repeated here.

Step 150 consists in defining for each location L ₁ a set of R predetermined value (s) which is specific to this location, R being an identical fixed integer number for all places L ₁ and which is greater than or equal to 1. This set of values will be noted Y _L1 in the following. Each of the values constituting the set Y _L1 will be noted Yn, a, with 'a' an integer taking the values from 1 to R. Here again, each set Y _L1 is comparable to the coordinates of a point or a vector.

Preferably, these sets Y _L1 serve to identify the different locations L ₁ in the database BDl. In other words, the P _UMJ games are each associated with the corresponding game Y _L1 in the database BD1. Step 150 is not necessarily successive to steps 100 and 110, but can be nested with them.

The database BD1 therefore takes the form of an array of the following type:

By way of example, the sets Y _L1 comprise only one value - that is to say R is equal to 1 - which corresponds to a number assigned to the place L ₁ , for example the number of the corresponding coin in a building. According to another example, the sets Y _L1 can comprise two values, respectively three values - that is to say R is equal to 2, respectively 3 - which correspond to the coordinates of the place Li in a system of three-dimensional coordinates, respectively three-dimensional. These examples are of course not limiting.

Step 160 is to determine by statistical or machine learning from the BDl database a set of function R (s) - each rated 'g _a' - adapted to supply, from each set P _LIMJ, a game - noted Z _HM , - R value (s) which is an approximation of the game Yn associated with the game P _LIMJ in the database BDl. This set of R function (s) 'g _a ' defines a transformation denoted hereinafter 'g'.

This transformation 'g' constitutes in this third embodiment the predetermined significant information of the correspondence between the reception power level on each of the N channels and the location within the location zone, which will then be used in the context of the localization process.

With regard to the application of steps 150 and 160 in combination with the method described with reference to FIG. 4 of the second embodiment, this means that the method comprises the same steps 100 to 140 as the method according to the second embodiment of FIG. embodiment described with reference to Figure 4. Therefore, the entire description of these steps 100 to 140 in the context of the second embodiment is applicable to the identical to this third embodiment and therefore will not be repeated here. Step 150 is identical to the previous variant of implementation in combination with the method described with reference to Figure 1 of the first embodiment. As a result, the description made of step 150 for the preceding variant also applies here, except that, preferentially, the sets Y _L serve to identify the different locations L ₁ in the second database. BD2. In other words, the games V _HM , are each associated with the corresponding game Yn in the second database BD2. Therefore, step 150 is not necessarily successive to steps 100 to 140, but can be nested with them.

The second database BD2 therefore takes the form of an array of the following type:

In this variant, step 160 consists of determining by statistical or artificial learning from the second database BD2 (instead of the first database BD1) a set of R function (s) - also denoted each _a '- able to provide, from each game VLIM _J (instead of PLIM _J ), a game - also noted ZLIM _J - of R value (s) which is an approximation of the game Yn associated with the game VLIM _J in the second database BD2 (instead of the first database BD1). As in the preceding variant, this set of R function (s) 'g _a ' defines a transformation denoted hereinafter 'g' and constitutes the predetermined significant information of the correspondence between the reception power level on each of the N channels and place within the location area, which will then be used as part of the location process.

In general, artificial or statistical learning is known per se. It consists in establishing a predictive model whose parameters are determined from the data themselves, rather than by knowledge or assumptions a priori.

The conventional steps in the learning analysis of a system include but are not limited to: the establishment of learning and validation bases that ensure the best possible representation of these bases; optionally, the extraction of optimal characteristic features from the raw data, in particular but not exclusively by principal component analysis or independent component analysis as described in the context of the second embodiment; the selection of the most significant features, including but not limited to the probe variable method; the construction of classification or regression architectures powered by these features, in particular by the so-called nearest neighbor K method, use of a neural network, or kernel classifiers such as SVM or TSVM support vector machines; - the choice of the best model via cross-validation techniques.

Artificial or statistical learning is more fully described, for example, in Neural Networks: Methodology and Applications by Gerard Dreyfus, Springer, 2004, which is incorporated by reference in the present description.

In this third embodiment, the localization method is implemented using the transformation 'g' previously obtained, as described in relation with FIG. 8. The first step 200 of the method is identical to that of the first embodiment. This is the measurement, by the mobile station, of the receive power level on each of the Ck channels to provide a P _{LX set} of N power levels.

PLXCI, - • -PLxCk, - • -PLXCN as described for the first embodiment. If, in order to establish the transformation 'g', the variant of the third embodiment of applying steps 150 and 160 in combination with the method described with reference to FIG. 4 of the second embodiment has been chosen, then apply step 220 preprocessing, that is to say the application to the game PL _X transformation 'P to provide the game V _LX . This step 220 is that already described in the context of the second embodiment.

In step 240, the transformation 'g' is applied to the set V _LX to obtain a set ZL _X.

In other words :

Z _Lx = g (V _Lx )

= [gi (V _Lx ), ..., g _a (V _Lx ), ..., g _R (V _Lx )]

If, in order to establish the transformation 'g', the variant of applying steps 150 and 160 in combination with the method described with reference to FIG. 1 of the first embodiment has been chosen, then the preprocessing step 220 is omitted. In this case, in step 240, the transformation 'g' is applied to the set P _LX to obtain the set Z _LX .

In other words :

Z _Lx = g (PL _X )

= [gl (P _Lx ), ..., ga (P _Lx ), ..., g _R (P _Lx )]

In both variants, the method then comprises a step 250 of locating the mobile station on the basis of the game Z _LX . It is possible to make this location by comparing the game Z _LX with Yu games (alternatively, with games Z _L i) to identify the location Lx. This comparison step may consist in finding the set Yn (respectively Zn) which has the minimum distance with Z _LX . This comparison can then be executed in a manner similar to that described for step 210 in the context of the first embodiment, except that it is made on the basis of the game Z _Lx and games Yn instead of the game P _LX and PLIM games ,. But according to an advantageous implementation, the location is provided on the basis of the game Z _LX alone, that is to say without recourse to a comparison with the games Yn, or with the games Z _Ll . There is therefore no need then to have the Yn or Zn games available to implement the localization process. For example, this is the case when the component values Yn sets are the coordinates of the place L ₁ in any coordinate system. In this case, the set Z _LX provides an approximation of the location Lx in this same coordinate system. Therefore, the set Z _LX is considered to be the location of L _x given in this coordinate system. As a variant, in the case where the given locations L ₁ each correspond to a predetermined volume or surface area, the system for referencing the locations L ₁ by the sets Yn can be chosen so that the location L _x can be identified on the basis of the game Z _Ll without comparison operation with the Yn games. For example, if each value composing the sets Yn is chosen in the form of an integer, then it is sufficient to round each value of the game Z _Lx to the nearest integer to obtain the location L ₁ of location. This method is particularly reliable in the case where the sets Yn have only one value, that is to say the case where R is equal to 1.

Fig. 9 illustrates an exemplary application of the third embodiment, in its application variant combined with the first embodiment. It is based on the example described with reference to FIG. 3. The creation of database BD1 is carried out by applying steps 100 and 110 of the method, as was described for FIG. 3 in the context of the first mode. of realization. The database BD1 is represented again in FIG. 9. In application of step 150, the following sets Yn have been defined:

for L ₁ , the set Y _L1 defined by (1,0,0);

for L ₂ , the set Y _L2 defined by (0,1,0);

for L3, the set Y _L3 defined by (0,0,1). In other words, R is 3 in this example. The transformation 'g' is obtained by statistical or artificial learning from database BD1 by application of step 160.

In our example, the transformation 'g' can be looked for in the form of three functions gi, g ₂ and g ₃ which respectively provide an estimation of the probability of location of the mobile station at places L ₁ , L ₂ and L ₃ , this probability being expressed between 0 and 1. In this case, Z _LX can be expressed as:

Z _Lx , i = gi (PLx) = σ (Σbi, _k .P _Lx ck) Z _Lx , ₂ = g ₂ (Pn0 = σ (Σb ₂ , _k .PL _x ck)

Z _Lx , 3 = g3 (PL _X ) = σ (Σb ₃ , k-PL _X Ck) with:

- ZLX, I, ZLX, 2 and ZLX, 3: the constituent values of the game ZL _X;

- bi, k, b ₂ , k and b3, k: coefficients determined by statistical learning from the first database BD1 which are the multiplicative coefficients of power levels PLxCk measured on the different channels Ck instead Lx, the summation being performed for the index k integer taking values from 1 to N;

- σ (x) = 1 / (1 + e ^"x ); and - gi (PLx): an estimate of the probability that the measurement P _LX was carried out at the place L ₁ .

The localization method is then implemented using the transformation 'g' thus obtained, as described with reference to FIG. 8. More particularly, when it is desired to locate the mobile station, the latter performs the measurements of the reception power on the 10 channels to provide the set P _LX according to step 200. In application of step 240, it is then calculated the set Z _LX which is the transform of P _LX by 'g'. The constituent values of the set Z _LX are represented by vertical bars in FIG. 9. By application of step 250, the location Lx is determined by comparing the set Z _LX with the sets Yn. In this case, it is the game Y _L3 which presents the distance - for example the Euclidean distance - the weakest with the game Z _LX . Therefore, the mobile station is considered to be localized instead of L3.

In the context of this example, the determination of the location L _x can be done other than by the comparison step 250. In this case, the determination of the place L _x can be done by rounding each of the values Z _LX , _I , Z _LX , ₂ and Z _LX , ₃ constituting the game Z _Lx to the nearest integer. The set thus obtained is the set Yn which corresponds to the place Lx. In this case, it is apparent from the graphical representation of the constituent values of Z _Lx in FIG. 9 that we obtain the set (0, 0, 1), that is to say the set Y _L3 . According to another advantageous possibility, the place Lx can be determined by considering that it corresponds to the place L ₁ for which the corresponding function g! - applied to the game P _LX - provided the highest probability, ie L3 in our example as shown in Figure 9. Of course, this example of Figure 9 can be generalized to any number of places Li, that is, for any integer number T.

Fig. 10 illustrates an exemplary application of the third embodiment, in its application variant combined with the second embodiment. He is based in the example described with reference to Figure 6. The creation of the first database BD1, then the second database BD2 is performed as described for Figure 6 of the second embodiment. Only the second database BD2 is represented in FIG. 10. In application of step 150, the same sets Y _L have been defined as in the context of the example of FIG. 9, namely:

for L ₁ , the set Y _L1 defined by (1,0,0);

for L ₂ , the set Y _L2 defined by (0,1,0);

for L ₃ , the set Y _L3 defined by (0,0,1). In application of step 160, the transformation 'g' is obtained this time by statistical or artificial learning from the second database BD2.

Here again, the transformation 'g' can be sought in the form of three functions gi, g ₂ and g ₃ which respectively provide an estimation of the probability of location of the mobile station at the locations L ₁ , L ₂ and L ₃ , this probability being expressed between 0 and 1. In this case, Z _LX can be expressed as:

Z _Lx , i = gi (V _Lx ) = σ (Σbi, _p .V _Lx , p) Z _Lx , ₂ = g ₂ (V _Lx ) = σ (Σb ₂ , pV _Lx , p) Z _Lx , ₃ = g3 (V _Lx ) = σ (Σb ₃ , pV _Lx , p)

with:

- ZL _X , i, ZL _X , ₂ and ZL _X , ₃ : the constituent values of the game ZL _X;

- bi, _p , b ₂ , _p , b ₃ , _p : coefficients determined by statistical learning from the second database BD2 which are the multiplicative coefficients of the values V _LX , _P , the summation being carried out for the index p integer taking values from 1 to Q; and

σ (x) = 1 / (1 + e ^"x ), and

- gi (VLx): an estimate of the probability that the measurement P _LX was carried out at the place L ₁ .

The localization method is then implemented using the transformation 'g' thus obtained, as described with reference to FIG. 8. More particularly, when it is desired to locate the mobile station, the latter performs the measurements of the receive power on the 10 channels to provide the P _{LX set} according to step 200, then, in accordance with step 220, the set V _LX is calculated by applying the transformation f. In application of step 240, it is then calculated the set Z _LX which is the transform of V _LX by 'g'. The constituent values of the game Z _LX are represented by vertical bars in FIG.

By applying step 250, the location Lx is determined by comparing the game Z _LX with the games Yu in a manner similar to the case of FIG. 9. In this case, it is also the game Y _L3 which presents the distance. weaker with the game Z _LX . Therefore, the mobile station is considered to be localized instead of L3. As in the previous case, the determination of the place L _x can be done by rounding each of the constituent values of the game Z _Lx to the nearest integer, which provides the set Yn corresponding to the location Lx. Or alternatively, the place L _x can also be considered as the place L ₁ for which the corresponding function g! - applied to the game P _LX - provided the highest probability, ie L3 in our example as shown in Figure 10. Of course, this example can also be generalized to any number of places Li, c that is, for any integer number T. Of course, the present invention is not limited to the examples and to the embodiment described and shown, but it is capable of numerous variants accessible to those skilled in the art.

Claims

1. Method for providing information capable of being used to locate a mobile station within a given area covered by at least one wireless cellular telephone network in which the mobile station operates, the method comprising: for one or more given places (L ₁ ) within the given zone, the provision for each of the given places (L ₁ ) of at least one set of N values (P _LIMJ ), each of the values corresponding to a measured level of reception power on a respective channel among N different and predetermined communication channels (Ck) of the at least one wireless cellular telephone network, N being a fixed integer which is greater than or equal to 7; and - the creation of a first database (BDl) associating the corresponding given measurement location with each set of N values.

2. Method according to claim 1, comprising:

- for each of one or more given places (Li) within the given zone, definition of a set of R predetermined value(s) (Yu) which is specific to this given place (Li), R being an integer greater than or equal to 1, this set of R predetermined value(s) being associated with each set of N values provided for the corresponding given location in the first database, - determination by statistical learning from the first database of a set of R function(s) ('g') capable of providing, from each set of N values (PLIM _J ), a set of R value(s) (Z _Ll ) which is an approximation of the set of R predetermined value(s) (Yn) associated with this set of N values.

3. Method according to claim 1, comprising: providing Q different function(s) (T), Q being an integer greater than or equal to 1 and less than N; and creating a second database (BD2) from the first database (BDl) by applying to each set of N values (PLIM _J ), the Q function(s) to provide a set of Q corresponding value(s) (VLIM _J ), the set of Q value(s) being associated in the second database with the corresponding given measurement location (L ₁ ) in which the Q function(s) are chosen so that, for any pair of sets of N values (PLIM _J ) different from the database (BDl), the two sets of Q values (V _LIMJ ) obtained by applying these Q functions to this pair of sets of N values (PLIM _J ), are different one from the other.

4. Method according to claim 3, in which: the Q function(s) (T) are provided either by a principal component analysis or by an independent component analysis; or the Q function(s) (T) respectively provide the mean value, the standard deviation and other higher order moments of the set of N values.

5. Method according to claim 3 or 4, comprising: for each of one or more given places (Li) inside the given zone, the definition of a set of R predetermined value(s) (Yn ) which is specific to this given location (Li), R being an integer greater than or equal to 1, this set of R predetermined value(s) being associated with each set of Q values (V _LIMJ ) provided for the corresponding given location in the second database (BD2); and the determination by statistical learning from the second database (BD2) of a set of R function(s) ('g') capable of providing, from each set of Q value(s) (VHM _J ), a set of R value(s) (Zn) which is an approximation of the set of R predetermined value(s) (Yn) associated with this set of Q value(s).

6. Method according to claim 1, 3 or 4, comprising:

- for each given location (Li), the determination by statistical learning from either the first database (BDl) or the second database (BD2), of a function capable of providing, from respectively the set of N values (PLIM _J ) OR the set of Q value(s) (VnM _j ) obtained by applying the Q function(s) to the set of N values, an estimate of the probability that the measurement was made in this given place (L ₁ ).

7. Method for locating a mobile station within a given area covered by at least one cellular wireless telephone network in which the mobile station operates, the method comprising the steps of: a) measurement by the station mobile reception power level (PLxCk) on each channel among N different and predetermined communication channels (Ck) of the at least one wireless cellular telephone network, N being an integer greater than or equal to 7, and b ) location of the mobile station on the basis of the levels measured in step a) and predetermined information (BDl; BD2; 'g') significant of the correspondence between reception power level on each of the N channels and location at inside the given area.

8. Method according to claim 7, in which: for one or more given places (Li) inside the given zone, the predetermined information comprises for each given place at least one associated set of W predetermined value(s) (s) (PLIM _J ; VLIM _J ) which is significant of a reception power level on each of the N channels at the corresponding given location, W being an integer greater than or equal to l; and - step b) comprises the location of the mobile station by analysis of the levels measured in step a) in relation to the set(s) of W predetermined value(s).

9. Method according to claim 8, in which: - W is equal to N, the W predetermined values of each set (P _LIMJ ) each being representative of a reception power level on a respective channel (Ck) among the N canals ; and the analysis in step b) comprises the comparison of the levels measured in step a) with the set(s) of W predetermined values.

10. Method according to claim 9, in which the set(s) of W predetermined values is/are the set(s) of N values of the first database (BDl) created with the method according to claim 1 .

11. Method according to claim 8, in which: W is less than N; and the analysis in step b) includes: (i) the application of W different predetermined function(s) (T) to the levels measured in step a) to provide a set of W value(s) (V _LIMJ ) which is significant of the levels measured in step a) homogeneously with the set(s) of W predetermined value(s); and (ii) the comparison of the set of W value(s) thus provided with the set(s) of

W predetermined values.

12. Method according to claim 11, in which the set(s) of W value(s) (V _LIMJ ) and the W predetermined function(s) (T) are those provided, respectively created with the process according to claim 3 or 4.

13. Method according to claim 7, in which: the predetermined information comprises: for each of one or more given places (Li) inside the given zone, an associated set of R predetermined value(s) (Yn) which is specific to this given location (Li), R being an integer greater than or equal to 1, and a set of R predetermined function(s) ('g') intended to provide, from the reception power levels measured at any given location (Li) on the N channels and after possible preprocessing of these measured levels, a set of R value(s)

(Zu) which is an approximation of the set of R predetermined value(s)

(Yu) corresponding to this given location; and step b) comprises: (i) providing a set of R value(s) (Z _Lx ) using the set of

R predetermined function(s) ('g') from the levels (P _LX ; V _LX ) measured in step a) and preprocessed if necessary; and (ii) the location of the mobile station by comparison of the set of R value(s) provided (Z _Lx ) with the set(s) of R predetermined value(s) (Yu).

14. Method according to claim 7, in which: the predetermined information comprises: a set of R predetermined function(s) intended to provide, from the reception power levels, measured at any location at inside the given zone, on the N channels and after a possible preprocessing of these measured levels, a set of R value(s) which is an approximation of the coordinates of the measurement location; and - step b) includes:

(i) providing a set of R value(s) (Z _LX ) by means of the set of R predetermined function(s) ('g') from the levels measured in step a ) and pre-treated if necessary; And

(ii) the location of the mobile station at the coordinates expressed by the set of R value(s) provided (Z _LX ).

15. Method according to claim 7, in which: the predetermined information comprises: a set of R predetermined function(s) intended to provide, from the reception power levels, measured at any location at inside the given zone, on the N channels and after possible preprocessing of these measured levels, a set of R value(s) which is an approximation of the reference of the measurement location in a location referencing system at the 'inside the given area; and step b) includes:

(i) providing a set of R value(s) (Z _Lx ) using the set of R predetermined function(s) ('g') from the levels measured in step a ) and pre-treated if necessary; And

(ii) the location of the mobile station at the place reference approximated by the set of R value(s) provided (Z _Lx ).

16. Method according to any one of claims 13 to 15, in which all of the R predetermined function(s) ('g') are determined by the method of claim 2.

17. Method according to claim 7, in which: - the predetermined information comprises:

- for each of one or more given locations (Li), an associated function ('g _a ') intended to provide, from the reception power levels measured on the N channels and after possible preprocessing of these measured levels, a estimation of the probability that the measurement was made at this given location; And step b) includes the location of the mobile station on the basis of the probability estimate provided by all or part of the functions from the levels measured in step a) and preprocessed if necessary.

18. Method according to claim 17, wherein the function(s) ('g _a ') are provided according to the method of claim 6.

19. Method according to any one of claims 13 to 18, wherein, in step (i), the levels measured in step a) are preprocessed by the application of W different predetermined functions (T) to provide a set of W value(s), W being an integer greater than or equal to 1 and less than N.

20. Method according to claim 19, in which the W function(s) (T) are the Q function(s) provided by the method according to claim 3 or 4 and the R predetermined function(s) are determined by the process of the claim

5.

21. Method according to any one of claims 7 to 20, implemented to locate the mobile station inside one or more buildings.

22. Method according to any one of claims 7 to 21, in which the predetermined information is established on the basis of reception power measurements made on the N channels in different locations within the given zone with the same mobile station that needs to be located.

23. Method according to any one of claims 1 to 22, in which N is greater than or equal to 20, preferably 50 and more advantageously 200.

24. Software for a mobile station intended to operate in at least one cellular wireless telephone network, which software is intended to cause the mobile station to execute the location method according to any one of claims

7 to 23.

25. Computer software, designed to have the computer implement the following steps: a) reception by the computer of a measurement made by a mobile station of the reception power level (PLxCk) on each channel among N canals different and predetermined communication channels (Ck) of at least one wireless cellular telephone network, N being an integer greater than or equal to 7,; and b) locating the mobile station by implementing step b) of the method according to any one of claims 7 to 23.

26. Mobile station capable of operating in at least one cellular wireless telephone network, which is intended to execute the location method according to any one of claims 7 to 23.