KR20180079901A - Location data correction apparatus for location based service and method and location data providing system using the same - Google Patents

Abstract

According to one embodiment of the present invention, the present invention provides an apparatus for correcting positioning data for a location based service, which comprises: a collected coordinate analysis unit analyzing a distribution of collected coordinates of collected data collected by a dynamic collection apparatus; a representative point generating unit generating representative points based on the distribution of the collected coordinates, and mapping the collected data to each of the representative points to generate a data set corresponding to each of the representative points; a first collected data correction unit determining incorrectly collected data among the collected data, and correcting the incorrectly collected data; and a second collected data correction unit determining whether the number of collected data exceeds a predetermined reference data number for each of the data sets, and correcting data sets for which the number of collected data does not exceed the reference data number. According to the present invention, instead of directly using the data adjacent to the representative point to generate a positioning database, various machining processes such as correction are performed on the data, thereby generating a relatively accurate positioning database.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a positioning data correction apparatus and method for a location-based service, and a positioning data providing system using the positioning data correction apparatus and method.

BACKGROUND OF THE INVENTION 1. Field of the Invention [0002] The present invention relates to a positioning apparatus for positioning information that is dynamically collected for a location based service (LBS), a method thereof, and a positioning data providing system using the same.

Recently, short-range wireless communication devices such as Wi-Fi (Wireless Fidelity) and Bluetooth Low Energy (BLE) have been rapidly spreading and users of smart devices such as smartphones and tablets are exploding. Accordingly, a variety of applications are being developed. Among them, a location based service (LBS) that provides additional services based on the location of users is attracting attention. In providing LBS, technologies are being developed to precisely provide a user's location for high-quality services, particularly in indoor environments where satellite signals can not be received. Among many research results, the location recognition technique which shows high accuracy is to collect positioning information such as the wireless communication signal or the geomagnetic field (geomagnetism) at various points in the room to construct a positioning DB, When the information is acquired, the location of the user is calculated by comparing the location information with the DB.

In order to collect environmental information in the process of establishing a positioning DB, a static collection method has been used in which an indoor space is divided into several points and then the information is collected for a sufficient time at the corresponding points and processed. However, this method has a problem that too much time and cost are generated in collection and positioning DB generation, and a dynamic collection method that can solve this problem has been proposed.

In the case of acquiring the positioning environment information by using the dynamic collection, since the collector continuously moves and collects the positioning environment information, it often occurs that sufficient data for the statistical value calculation is not obtained, There is a problem that accurate DB construction for probability based location recognition is difficult and accuracy of position recognition is lowered.

The above-described background technology is technical information that the inventor holds for the derivation of the present invention or acquired in the process of deriving the present invention, and can not necessarily be a known technology disclosed to the general public prior to the filing of the present invention.

Korean Patent Laid-Open No. 10-2010-0045355

Embodiments of the present invention provide a positioning data correction apparatus and method for a location-based service that generates a more accurate positioning database by performing various machining processes such as correction instead of directly using data adjacent to a representative point to generate a positioning database. And provides a positioning data providing system.

In addition, the embodiments of the present invention may further include determining positioning data correction for location-based services that remove noise within a range in which reliable data is maintained, by determining whether or not to remove the collected data according to the number of data included in the data set. Apparatus, method, and positioning data providing system using the same.

Further, in the embodiments of the present invention, when the data set is not supplemented by data correction, the data set itself is excluded from the positioning statistic calculation target, and thereby, the position where the noise is removed within the range where the reliable data is maintained A positioning data correction apparatus and method for a base service, and a positioning data providing system using the same.

An embodiment of the present invention includes: a collection coordinate analyzer for analyzing a distribution of collected coordinates of collected data collected by a dynamic collection device; A representative point generation unit that generates representative points based on the distribution of the collected coordinates, maps the collected data to each of the representative points, and generates data sets corresponding to each of the representative points; A first collection data correction unit for determining the collection data among the collection data and correcting the collection data; And for each of the data sets, determining whether the number of collected data exceeds a predetermined reference number of data, and if the number of collected data is less than the reference data number, And a positioning data correction unit for correcting the positioning data.

The first collection data corrector may perform clustering based on a predetermined data clustering criterion for the collected data, and may determine data not belonging to the cluster among the collected data as the mis-collected data.

Wherein the data clustering criterion is a reception strength of the collected data, and the first collected data corrector corrects the reception of the o collected data so that the o collected data belongs to the cluster when performing the clustering again based on the data clustering criterion. The intensity can be corrected.

Wherein the first collection data correction unit determines whether or not the number of collected data excluding the false collection data exceeds the number of reference data for each of the data sets and if the number of collected data excluding the false collection data is the number of the reference data May exclude the erroneous collection data from the data set exceeding the threshold.

The second collection data corrector may add virtual data generated by at least one of interpolation and data modeling to the data sets whose number of collected data does not exceed the reference data count.

The second collection data correction unit may transmit to the dynamic collection apparatus feedback information including area information corresponding to data sets in which the number of collected data does not exceed the reference data number.

Wherein the second collection data correction unit determines whether the additional collected data collected by the feedback is overlapped with the existing collected data, and if the number of the collected data excluding the additional collected data determined to be duplicated is equal to the reference data number It can be determined that the data sets that are not exceeded are not subject to the positioning statistics calculation.

And the positioning data correction device may further include a positioning database generation unit for calculating positioning statistics for the representative points based on the data sets.

The positioning database generation unit may further use collection data mapped to another representative point adjacent to each of the representative points, for each representative point corresponding to data sets for which the number of collected data does not exceed the reference data number The positioning statistics can be calculated.

According to another embodiment of the present invention, the collecting coordinate analyzing unit analyzes the distribution of collected coordinates of the collected data collected by the dynamic collecting apparatus; Generating representative points based on the distribution of the collected coordinates and mapping the collected data to each of the representative points to generate data sets corresponding to each of the representative points; Wherein the first collection data correction unit includes: determining a collection data of the collection data and correcting the collection data; And a second collection data correction unit for determining, for each of the data sets, whether or not the number of collected data exceeds a predetermined reference number of data, and wherein the number of collected data sets And a calibration step of calibrating the positioning data for the location-based service.

Wherein the correcting of the erroneous collection data comprises: the first collecting data correcting section performing clustering based on a data clustering reference preset for the collected data; .

Wherein the data clustering criterion is a reception intensity of the collected data, and the correcting of the erroneous collected data is performed when the first collected data correcting unit performs the re-clustering based on the data clustering criterion, The reception intensity of the false collection data can be corrected.

Wherein the first collected data correction unit determines whether or not the number of collected data excluding the false collection data for each of the data sets exceeds the number of reference data, May be excluded from the data set in which the number of collected data exceeds the number of reference data.

The step of correcting the data sets may include generating the second collection data by at least one of interpolation and data modeling for the data sets whose number of collected data does not exceed the reference data number Virtual data can be added.

The step of correcting the data sets may comprise the step of transmitting the feedback information including the area information corresponding to the data sets whose number of collected data does not exceed the reference data number to the dynamic collection device, .

The step of correcting the data sets may include a step of determining whether the additional collected data collected by the feedback is overlapped with the existing collected data, It can be determined that the data sets for which the number of collected data does not exceed the number of reference data are not the objects for calculation of positioning statistics.

The positioning data correction method may further comprise the positioning database generation unit calculating positioning statistics for the representative points based on the data sets.

Wherein the positioning statistics generating step includes a step of generating the positioning statistics based on a result of the comparison by the positioning database generating unit to calculate the positional statistics based on the positional data of each of the representative points corresponding to the data sets, It is possible to calculate the positioning statistics by further using the collected data mapped to the point.

Yet another embodiment of the present invention provides a computer program stored on a medium for executing the method using a computer.

Another embodiment of the present invention is a dynamic collection apparatus that generates collection data including positional environment information and positional information periodically on the move; Analyzing a distribution of collected coordinates of collected data transmitted from the dynamic collection device, generating representative points based on the distribution of the collected coordinates, mapping the collected data to each of the representative points, Determining whether or not the number of collected data exceeds the predetermined reference number of data, determining whether the number of collected data exceeds a predetermined reference number of data A positioning data correction device that corrects data sets in which the number of collected data does not exceed the reference data number; And a location database generation device for calculating positioning statistics for the representative points based on the data sets.

Other aspects, features, and advantages will become apparent from the following drawings, claims, and detailed description of the invention.

The positioning data correcting apparatus and method for location-based services according to embodiments of the present invention and the positioning data providing system using the positioning data correcting apparatus do not directly use the data adjacent to the representative point to generate the positioning database, It is possible to generate a more accurate positioning database.

In addition, according to the positioning data correction apparatus and method for location-based services according to the embodiments of the present invention and the positioning data providing system using the same, it is possible to determine whether or not to remove the collected data according to the number of data included in the data set , Noise can be removed to the extent that reliable data is maintained.

In addition, according to the positioning data correction apparatus and method for a location-based service according to embodiments of the present invention and the positioning data providing system using the positioning data correction method, when the data set is not supplemented by data correction, By excluding from the statistical value calculation target, noise can be removed within a range where reliable data can be maintained.

1 is a diagram illustrating a configuration of a positioning data providing system for a location-based service according to an embodiment of the present invention.
2 is a block diagram showing an example of the configuration of the dynamic collection device shown in FIG.
3 is a block diagram showing an example of the configuration of the positioning data correction apparatus shown in Fig.
4 is a flowchart illustrating a positioning data correction method according to an embodiment of the present invention.
FIG. 5 is a view showing an example of the collected coordinate analysis step and representative point generating step shown in FIG.
FIG. 6 is a diagram showing an example of a step of correcting the collected data shown in FIG.
FIG. 7 is a view showing another example of the step of correcting the collected data shown in FIG.
FIG. 8 is a diagram illustrating an example of correcting the data sets shown in FIG.
FIG. 9 is a diagram showing an example of a Wi-Fi RSSI measurement result.

BRIEF DESCRIPTION OF THE DRAWINGS The present invention is capable of various modifications and various embodiments, and specific embodiments are illustrated in the drawings and described in detail in the detailed description. The effects and features of the present invention and methods of achieving them will be apparent with reference to the embodiments described in detail below with reference to the drawings. However, the present invention is not limited to the embodiments described below, but may be implemented in various forms. In the following embodiments, the terms first, second, and the like are used for the purpose of distinguishing one element from another element, not the limitative meaning. Also, the singular expressions include plural expressions unless the context clearly dictates otherwise. Also, the terms include, including, etc. mean that there is a feature, or element, recited in the specification and does not preclude the possibility that one or more other features or components may be added.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to like or corresponding components throughout the drawings, and a duplicate description thereof will be omitted .

1 is a diagram illustrating a configuration of a positioning data providing system for a location-based service according to an embodiment of the present invention.

1, a positioning data providing system for a location-based service according to an embodiment of the present invention includes a dynamic collection apparatus 101, a collection database 102, a positioning data correction apparatus 103, a positioning database generation apparatus 104 and a positioning database 105.

In particular, the dynamic collection device 101 is interconnected with the collection database 102 and the positioning data correction device 103, and the positioning data correction device 103 comprises a dynamic collection device 101, a collection database 102, And the positioning database generation device 104 is interconnected with the positioning data correction device 103 and the positioning database 105. [

The dynamic collection device 101 of the present invention has a function of automatically setting a path to be collected by a collector on a map in order to automatically collect positioning environment information of a plurality of indoor spaces, A function of automatically collecting one or more positioning environment information periodically on the move, a function of generating collected data by linking the positions of the automatically calculated collectors at the time of collecting the positioning environment information, And a function of transmitting data to the collection database.

The collection database 102 includes collector information and positioning environment information.

Here, the positioning environment information may include an identifier of a wireless access point, measurement time information, azimuth information, signal strength and precision evaluation index, and the like.

Here, the collection database 102 may be a separate database physically separated from the dynamic collection apparatus 101, or may be a database conceptually separated from the dynamic collection apparatus 101 only.

The positioning data correction device 103 analyzes the collected coordinates to create a point (representative point) to generate a positioning database, a function to analyze the collected data based on the adjacent collected data at the representative point, A function of removing or correcting the collected data, a function of providing feedback to the collector requesting additional collection when the collected data is insufficient based on the first correction result, or adding the virtual collected data when the collected data is not sufficient And a function of making it possible to further utilize the data of the adjacent points when the collected data is insufficient.

At this time, the analysis and calibration processes are mutually independent and can be changed in order. Further, the functions relating to the data correction are not limited to the contents or functions described above, and various correction functions can be included so that workers in the industry can create accurate positioning databases to improve the performance of the positioning database.

The positioning database generation device 104 calculates statistical values capable of modeling environment information mathematically using the corrected data.

Here, the statistics may include a standard deviation and a global variance related to positioning.

The positioning database generation device 104 may be a separate device physically separated from the positioning data correction device 103 or may be a device that is conceptually separated only from the positioning data correction device 103, (103).

The positioning database 105 includes representative point information and positioning data generated corresponding to the representative point.

The location database 105 may be used to calculate the location of the user through probability matching with the user's location information measurements in location based services.

Here, the positioning database 105 may be a separate database physically separated from the positioning database generating apparatus 104, or may be a database conceptually separated only from the positioning database generating apparatus 104.

2 is a block diagram showing an example of the configuration of the dynamic acquisition apparatus 101 shown in FIG.

1, the dynamic collection apparatus 101 includes a collection position calculation unit 201, a positioning environment information collection unit 202, a collection data generation unit 203, and a collection data transmission unit 204, . Furthermore, it may further include a map information processing unit and a collection information display unit (not shown) for displaying information related to the collection or the map to the collector.

The collection position calculation unit 201 can calculate the positions of the collectors by estimating the stride and movement direction of the collector. To this end, the collection position calculation unit 201 may include at least one of an acceleration meter capable of detecting the user's stride and a gyroscope and a geomagnetic sensor capable of estimating the direction. The method and apparatus for calculating the collection position are not limited to the above embodiment.

The positioning environment information collecting unit 202 collects the positioning infrastructures that can be used as identifiers for distinguishing the respective points at the time of the positioning by displaying different measured values according to indoor points. The positioning infrastructure includes Wi-Fi, BLE, LTE Such as cellular networks, Ultra Wide-Band (UWB), Radio Frequency Identification (RFID), geomagnetism, barometric pressure, sound, ultrasonic waves, and the like. In addition, the information collected for each infrastructure usually uses the strength of received measurements (Wi-Fi, Received Signal Strength Indicator (RSSI) for BLE, 3-axis geomagnetic values for geomagnetism, etc.). Examples of representative measurement information, not the intensity of the measured value, include RTT (Round Trip Time) or ToA (Time of Arrival) information of the wireless communication infrastructure, and Angle of Arrival (AoA).

The collection data generation unit 203 creates collection data to be transmitted to the collection database by grouping the collected positioning environment information and the real-time location. The information included at this time may include collected coordinates, positioning environment information collected at the coordinates, auxiliary information that can be used as a reference in generating the positioning database such as the collection time and the type of the collection terminal.

The collection data transfer unit 204 utilizes and transfers collected data to the collection database 102. In this case, the data transmission method can utilize wired / wireless communication, but it is not limited thereto, and if communication is not possible, the collected data can be stored and transferred manually through the mobile storage device. Therefore, the data transfer time is not necessarily limited to real time.

3 is a block diagram showing an example of the configuration of the positioning data correction apparatus 103 shown in Fig.

Referring to FIG. 3, the positioning data correction apparatus 103 shown in FIG. 1 includes a collection coordinate analysis unit 301, a representative point generation unit 302, a first collection data correction unit 303, (304).

The collection coordinate analysis unit 301 analyzes the distribution of the collected coordinates of the collected data collected by the dynamic collection apparatus (see 101 in FIG. 1).

The representative point generating unit 302 generates a representative point based on the collected coordinate analysis result.

The first collection data correction unit 303 analyzes data collected near the representative point and removes or corrects data that is determined to have been collected.

The first collection data correcting unit 303 may perform clustering based on a predetermined data clustering criterion with respect to the collected data, and may determine that data not belonging to the cluster among the collected data is mis-collected data.

Here, the data clustering criterion may be the reception strength of the collected data.

That is, the first collection data correcting unit 303 may perform clustering based on the data clustering criterion, and may determine the data not belonging to the cluster among the collected data as false collection data.

In an alternative embodiment, the first collection data corrector 303 may correct the mis-collected data so that the mis-collected data belongs to the cluster when performing the re-clustering based on the data clustering criterion.

For example, when the data clustering criterion is the reception strength of the collected data, the first collected data corrector 303 may correct the reception strength of the collected data and perform the clustering again so that the collected data is included in the corresponding cluster .

The second collection data corrector 304 generates virtual collection data for a point at which it is determined that the analysis result data is not sufficiently collected or requests additional collection through feedback to the collection device or makes use of adjacent data.

That is, for each data set, the second collection data correction unit 304 determines whether or not the number of collected data exceeds the preset reference data count, and if the number of collected data does not exceed the reference data count Can be corrected.

In an alternative embodiment, the second collection data correction unit 304 determines whether or not the number of collected data excluding the false collection data exceeds the number of reference data, and if the number of collected data excluding the false collection data exceeds the reference data number You can exclude mis-collected data from the dataset.

Accordingly, it is possible to remove noise (for example, collected data) within a range in which reliable data is maintained by the positioning data correction apparatus for location-based services according to an embodiment of the present invention.

In an alternate embodiment, the second collection data corrector 304 may be configured to perform, for data sets for which the number of collected data does not exceed the reference data count, the virtual data generated by at least one of interpolation and data modeling Can be added.

As an alternative embodiment, virtual data may be added using a method such as bootstrap sampling or sampling with replacement.

In an alternative embodiment, the second collection data corrector 304 may be configured to provide the dynamic collection device (see 101 in FIG. 1) with feedback including area information corresponding to data sets for which the number of collected data does not exceed the reference data number Information can be transmitted.

Accordingly, additional data can be collected from the dynamic collection device for the area where data is insufficient by the positioning data correction device for location-based services according to an embodiment of the present invention.

In an alternative embodiment, the second collection data correction unit 304 determines whether the additional collected data collected by the feedback is overlapped with the existing collected data, and if the number of collected data excluding the additional collected data determined to be duplicated It can be determined that the data sets that do not exceed the reference data count are not to be subjected to the positioning statistics calculation.

Accordingly, when data is not supplemented by the positioning data correcting apparatus for location-based services according to an embodiment of the present invention, Statistic with zero deviation) can be removed.

Although not shown in FIG. 3, the positioning data correction apparatus 103 may further include a positioning database generation unit (not shown) for calculating positioning statistics for representative points based on the data sets.

The positioning database creation unit (not shown) further uses, for each representative point corresponding to the data sets whose number of collected data does not exceed the number of reference data, the collected data mapped to another representative point adjacent to each representative point And the positioning statistics of the representative point can be set as the preset statistics.

In addition, the positioning database generation unit (not shown) may set the global dispersion for the plurality of representative points as the positioning statistics.

On the other hand, the data correction method of the positioning data correction apparatus 103 shown in Fig. 1 is not limited to the above method. That is, as described above, it is also possible to preprocess the processing for the area where the collected data is insufficient before the second collected data correcting unit 304 before. In addition, the data correction method may include various correction methods that improve the performance of the other positioning database, not limited to the processing of the data where the number of data and the data is not sufficient.

4 is a flowchart illustrating a positioning data correction method according to an embodiment of the present invention.

4, in the positioning data correction method according to the embodiment of the present invention, the collection coordinate analysis unit (see 301 in FIG. 3) analyzes the distribution of the collected coordinates of the collected data collected by the dynamic collection device S410).

In addition, the positioning data correction method according to the embodiment of the present invention is characterized in that the representative point generation unit (see 302 in FIG. 3) generates representative points based on the coordinate distribution, maps the collected data to each representative point, And generates data sets corresponding to representative points (S420).

Further, in the positioning data correction method according to the embodiment of the present invention, the first collection data correction unit (see 303 in FIG. 3) determines the wrong collection data among the collected data and corrects the collected data ).

In step S430, the first collection data correction unit (see 303 in FIG. 3) performs clustering based on the data clustering criterion previously set for the collected data, and the data not belonging to the cluster among the collected data is regarded as the collected data It can be judged.

In step S430, the data clustering criterion may be the received intensity of the collected data, and when the first collected data corrector (see 303 in FIG. 3) performs the re-clustering based on the data clustering criterion, The reception strength of the collected data can be corrected.

In step S430, the first collected data correction unit (see 303 in FIG. 3) determines whether or not the number of collected data excluding the collected data exceeds the number of reference data for each of the data sets, You can exclude misleading data from a dataset where the number of collected data that you excluded exceeds the number of reference data.

In the positioning data correction method according to the embodiment of the present invention, the second collected data correction section (see 304 in FIG. 2) determines whether or not the number of collected data exceeds the preset reference data number And corrects the data sets for which the number of collected data does not exceed the reference data number (S440).

In step S430, the second collected data correction unit (see 304 in FIG. 3) determines whether the number of collected data does not exceed the number of reference data for at least one of interpolation and data modeling The virtual data generated by the user can be added.

In step S430, the second collection data correction unit (see 304 in FIG. 3) sends feedback information including area information corresponding to data sets whose number of collected data does not exceed the number of reference data to the dynamic collection apparatus Lt; / RTI >

In step S430, the second collected data correction unit (see 304 in FIG. 3) determines whether the additional collected data collected by the feedback is overlapped with the existing collected data, and determines whether additional collected data It can be judged that the data sets for which the number of collected collected data does not exceed the number of reference data are not to be subjected to the positioning statistics calculation.

Further, in the positioning data correction method according to the embodiment of the present invention, the positioning database generation unit (not shown) can calculate the positioning statistics for the representative points based on the data sets.

In the step of calculating the positioning statistics, the positioning database generator (not shown) calculates, for each representative point corresponding to the data sets whose number of collected data does not exceed the number of reference data, Can be further used to calculate positioning statistics.

FIG. 5 is a view showing an example of the collected coordinate analysis step (S410) and representative point generation step (S420) shown in FIG.

Referring to FIG. 5, the thick curve 501 indicates a route through which the acquirer acquires collected data in an environment in which a positioning infrastructure 505 such as a Wi-Fi AP is installed. The rectangle 502 indicates the position at which the dynamic collection device 101 acquired the collected data while the collector moved, and the star 503 indicates the representative point generated accordingly. A circle 504 centered on the location of the representative point represents the range of data that is utilized when creating the location database at the representative point. That is, the data in the circle 504 is utilized in generating the positioning database of the representative point 503.

The path 501 of the collector is not limited to any particular form and may vary depending on the collection scenario.

The data collection timing in the dynamic collection apparatus 101 may be periodic or variable.

Here, even if the data collection timing of the dynamic collection apparatus 101 is constant, since the positioning infrastructure information may sometimes be collected depending on the collector's variable moving speed or communication state, the distribution of the collection coordinates 502 may also be variable have.

The location of the representative point 503 and the range of data 504 mapped to the representative point may also be variable.

Since the location database is generated by processing it based on the collected data, the distribution of the collected data and the collected coordinates directly affects the quality of the location database. For this reason, the representative point 503 can be created at even intervals or at non-equidistant points in order to prevent the performance degradation of the positioning database according to the distribution of the collected coordinates 502.

FIG. 6 is a view showing an example of the step of correcting the collected data (S430) shown in FIG.

FIG. 6 is a diagram illustrating RSSI values of a Wi-Fi signal collected in a stationary state. Referring to FIG. 6, an embodiment of correcting false data using data clustering will be described as follows.

In general, there are a plurality of observation values of collected data of a specific infrastructure. For example, a Wi-Fi signal transmitted from a particular AP may be received in multiple zones within the indoor space and thus observed at multiple acquisition points. Based on such data, clustering is performed on various collected data bundled at the generated representative points so that the missing data can not be bundled into the cluster, and the missing data is interpreted as the collected data and corrected or filtered. That is to say, it confirms the collected data (refer to 502 in FIG. 5) mapped to the representative point (see 503 in FIG. 5) and performs clustering based on the received signals transmitted from the specific AP.

In an actual collection situation, the measurement value of the signal may be received weakly due to the appearance of an unexpected sudden wave disturbance source. For example, there may be a situation in which passengers have unexpectedly passed around in the collection process and have experienced severe attenuation of radio waves.

That is, most of the signals 601 have a similar value before and after -40DBm, but may receive a signal 602 that is received at some extremely low intensity. These values are signals that have experienced sudden attenuation due to various factors as described above. However, this signal intensity is not a universal situation that the user would expect to experience during the actual positioning. Therefore, if the positioning database is created based on this data, it may serve as a positioning error factor. According to an embodiment of the present invention, this error factor can be removed through data clustering.

Meanwhile, the data clustering method according to an embodiment of the present invention is not limited to a specific method, and may include various clustering methods applicable to positioning environment information.

FIG. 7 is a view showing another example of the step of correcting the collected data (S430) shown in FIG.

FIG. 7 is a diagram illustrating the strength of a signal transmitted from an AP in an environment in which a specific Wi-Fi AP is installed in a typical office building. Referring to FIG. 7, an example of correcting the collected data using data modeling is described below. Explain as follows.

Observations of a particular infrastructure may be spread over several points within the collection space. For example, the gray point represents the entire representative points of the collection in the building, where the AP signals are measured in different colors, wherein the color of each representative point represents the intensity of the received signal.

In the case of Wi-Fi, if a signal transmitted from a specific AP is received only once at a specific representative point, the standard deviation of the average and standard deviation used for mathematical modeling is usually 0, In case of difficult and Gaussian modeling, the denominator becomes zero and the probability becomes infinite, so it acts as an error factor in the probability-based positioning.

As shown in FIG. 7, the observed values of the collected data show a tendency. By modeling such tendency, sudden observations that largely deviate from the observed values can be judged as badly collected data. For such data, it is possible to correct the existing tendency to follow well, or to remove the corresponding data, thereby building a more accurate positioning database.

FIG. 8 is a diagram illustrating an example of correcting the data sets shown in FIG. 4 (S440).

8 illustrates a method of collecting received signal strengths of a collector positioning infrastructure resource 801 (assuming it is a Wi-Fi AP) along a specific collection path 802, and then, in a situation where data collection is performed at the locations of the squares 803, 808, , A black star 805 represents a place where one or more data are included in a representative point 804 of representative points to be created, and the other is a transparent star 806 and 807.

In such a situation, the database generated at the representative point 806 has a standard deviation value of 0, so that correct probability modeling is impossible. Therefore, virtual data can be generated by performing interpolation using collected data 808 and 809 in the vicinity. It is also possible to predict and generate virtual data through data modeling using data of other neighborhood.

That is, in the step of correcting the data sets shown in FIG. 4 (S440), the second collected data correcting unit (see 304 in FIG. 3) If the data is small, the data may be created virtually for the purpose of calculating the statistical value, or additional data may be acquired through feedback to the collection device, or the signal data set lacking the collected data may be completely removed, It is filtered so that a positioning database in which an inaccurate statistic value is calculated is not generated.

On the other hand, the statistics to be estimated by applying the correction are not necessarily limited to the standard deviation, and all the statistics necessary for the mathematical model for generating the positioning database may be applicable.

As an alternative embodiment, when a statistical value, particularly a standard deviation of a mathematical model, can not be accurately calculated because the collected data is not sufficiently secured, an arbitrary standard deviation value can be assigned at the time of generating the positioning database. The value assigned at this time can be arbitrarily set by the operator, or the neighboring data can be utilized.

As an alternative embodiment, the same observations may be collected even if the collected data is collected multiple times by sending a feedback signal to the dynamic collection device (see 101 in FIG. 1). For example, location database data at points 806 and 807 or collection data duplicated at point 805 may be collected. In this case, since the standard deviation is calculated as 0, it is possible to use a previously set value as the standard deviation value or to exclude the data set itself from being used for calculating the positioning data.

In the case of replacing with a preset value, the value may be a value measured through a separate experiment or a commonly known value. For example, a sufficient amount of RSSI data set can be acquired from a neighboring location of a representative point and a standard deviation of the RSSI data set can be obtained. In case of wireless signal such as Wi-Fi, as shown in FIG. 9, the measured value changes by a maximum of 5DBm from the average due to normal noise. Therefore, the standard deviation can be set by referring to this value.

In the embodiment using neighboring data, it is possible to utilize statistically generated values at the adjacent points as it is, assuming that the signal characteristics are similar at the points adjacent to the representative point. In other words, in the case of FIG. 8, the standard deviation value of the representative point 806 can be replaced with the value of the representative point 805 and used.

As an alternative embodiment, the standard deviation can be calculated by further utilizing the data mapped to the representative point adjacent to the specific representative point, under the assumption that the distribution characteristics of the signal, such as the standard deviation, remain relatively close in the adjacent space. That is, when calculating the statistics of the representative point 806, a more significant value can be calculated by using the data of the adjacent points 808 and 809, instead of using only the data mapped to the representative point, to further calculate the statistic.

As an alternative embodiment, it may be possible to use additional collecting points at selected representative points or at separate points at predetermined intervals as statistical values of adjacent representative points by extending the assumption that the signal characteristics are similar at the adjacent points. That is, instead of calculating the standard deviation for each representative point, the signal is collected through the static collection for a sufficient time at the representative point 810 at the center point, and then the standard deviation is calculated, and this value is used as the standard deviation Can be used as a value. On the other hand, the point of additional collection may be the representative point or the non-representative point.

As an alternative embodiment, a global variance may be calculated. The standard deviation in the normal positioning database is obtained by averaging based on the data mapped to each representative point and calculating how the data is distributed around the average.

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는

번째 관측값,

는 관측값의 평균을 의미한다. 정확한 측위 데이터베이스 생성을 위해서는 이 표준편차가 물리적 참값과 가깝게 추정하는 것이 중요하다. 하지만 상기와 같이 동적 수집을 기반으로 하는 측위 데이터베이스 생성에서는 수집자가 한 지점에서 꾸준히 데이터를 받지 않고 경로를 계속해서 이동하면서 자동으로 데이터를 수집하기 때문에 대표 지점에 매핑되는 충분한 수집 데이터를 확보하기 어려워 이러한 표준편차를 구해내는 것이 어려운 실정이다.here

Is the standard deviation,

The number of data,

The

The second observation,

Means the average of the observations. For accurate positioning database generation, it is important to estimate this standard deviation to be close to the physical true value. However, as described above, in the creation of the location database based on the dynamic collection, it is difficult for the collector to acquire enough collected data to be mapped to the representative point because the data is automatically collected while the route continues moving without receiving the data continuously at one point. It is difficult to obtain standard deviation.

In this case, since signals are transmitted through a similar environment in an indoor space, assuming that the characteristics of signals due to noise are similar, it is possible to utilize a large amount of data in a certain space instead of calculating standard deviation using only data bound to representative points The standard deviation can be calculated, and it is possible to generate a more meaningful positioning database by using it in common at several points. The detailed formula for this is as follows.

&Quot; (2) "

는 j 번째 대표 지점에서 수집된 i 번째 관측값,

는 j 번째 대표 지점의 관측값의 평균,

는 j 번째 대표 지점에 매핑되어 있는 관측값의 개수, l 은 대표 지점의 개수, p는 전체 관측값의 수를 의미한다.Where j is an index indicating each representative point,

Is the i-th observation value collected at the j-th representative point,

Is the mean of the observations at the jth representative point,

Is the number of observations mapped to the jth representative point, l is the number of representative points, and p is the total number of observations.

This method assumes that the channel environment or attenuation experienced through the similar space in the course of transmitting the l data is also similar to each other, so that the standard deviation value is calculated by using the difference between the average value and the observation value of the data bound at each representative point It is calculated.

As an alternative embodiment, more data may be obtained by requesting additional collection via direct feedback to the dynamic collection device (see 101 in FIG. 1).

In other words, additional collection may be requested to the collection device for points where the collected data is insufficient to accurately estimate the statistical value, such as standard deviation, so that sufficient data can be acquired through limited additional collection only for that area.

To this end, the positioning data correction device (see 103 in FIG. 1) examines the entire positioning database to identify points where accurate statistics can not be calculated because there is only one piece of data collected from a specific infrastructure, This may include collecting data from the area where the collector has requested after requesting additional collection.

The embodiments of the present invention described above can be implemented in the form of program instructions that can be executed through various computer components and recorded in a computer-readable recording medium. The computer-readable recording medium may include program commands, data files, data structures, and the like, alone or in combination. The program instructions recorded on the computer-readable recording medium may be those specifically designed and configured for the present invention or may be those known and used by those skilled in the computer software arts. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CD-ROM and DVD, magneto-optical media such as floptical disks, medium, and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code, such as those generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be modified into one or more software modules for performing the processing according to the present invention, and vice versa.

The specific acts described in the present invention are, by way of example, not intended to limit the scope of the invention in any way. For brevity of description, descriptions of conventional electronic configurations, control systems, software, and other functional aspects of such systems may be omitted. Also, the connections or connecting members of the lines between the components shown in the figures are illustrative of functional connections and / or physical or circuit connections, which may be replaced or additionally provided by a variety of functional connections, physical Connection, or circuit connections. Also, unless explicitly mentioned, such as " essential ", " importantly ", etc., it may not be a necessary component for application of the present invention.

Accordingly, the spirit of the present invention should not be construed as being limited to the above-described embodiments, and all ranges that are equivalent to or equivalent to the claims of the present invention as well as the claims .

101: dynamic collection device 102: collection database
103: positioning data correction device 104: positioning database generation device
105: positioning database 201: collection position calculation unit
202: positioning environment information collection unit 203: collection data generation unit
204: collected data transmitting unit 301: collected coordinate analyzing unit
302: representative point generation unit 303: first collected data correction unit
304: second collected data correction unit

Claims (20)

A collection coordinate analyzer for analyzing the distribution of the collected coordinates of the collected data collected by the dynamic collection device;
A representative point generation unit that generates representative points based on the distribution of the collected coordinates, maps the collected data to each of the representative points, and generates data sets corresponding to each of the representative points;
A first collection data correction unit for determining the collection data among the collection data and correcting the collection data; And
For each of the data sets, determines whether or not the number of collected data exceeds a preset reference data number, and corrects data sets for which the number of collected data does not exceed the reference data number, ;
Based on the location data. The method according to claim 1,
The first collection data correction unit
Based on a data clustering criterion set for the collected data, clustering is performed based on a predetermined data clustering criterion, and data not belonging to the cluster among the collected data is judged as the collected data. . The method of claim 2,
The data clustering criterion is
The reception strength of the collected data,
The first collection data correction unit
And corrects the reception intensity of the collected data so that the collected data belongs to the cluster when the clustering is performed based on the data clustering criterion. The method of claim 2,
The first collection data correction unit
Determining whether or not the number of collected data excluding the false collection data exceeds the number of reference data for each of the data sets and if the number of collected data excluding the false collection data exceeds the reference data number, Wherein the positioning data correction unit excludes miscounted data. The method of claim 2,
The second acquisition data correction unit
Characterized in that virtual data generated by at least one of interpolation and data modeling is added to data sets for which the number of collected data does not exceed the number of reference data. Positioning data correction device. The method of claim 2,
The second acquisition data correction unit
Wherein the dynamic collection device transmits feedback information including area information corresponding to data sets whose number of collected data does not exceed the reference data number. The method of claim 6,
The second acquisition data correction unit
Determining whether or not the additional collected data collected by the feedback overlaps with the existing collected data, and determining whether or not the collected data other than the additional collected data determined to be duplicated exceeds the reference data number Is determined not to be a target for positioning statistics calculation. The method of claim 2,
The positioning data correction device
A positioning database generation unit for calculating positioning statistics for the representative points based on the data sets;
Further comprising a location data correction unit for determining location data of the location based service. The method of claim 8,
The positioning database generation unit
For each of representative points corresponding to data sets for which the number of collected data does not exceed the number of reference data, further using collected data mapped to another representative point adjacent to each of the representative points, Based on the positional information of the position-based service. Analyzing the distribution of the collected coordinates of the collected data collected by the dynamic collection device;
Generating representative points based on the distribution of the collected coordinates and mapping the collected data to each of the representative points to generate data sets corresponding to each of the representative points;
Wherein the first collection data correction unit includes: determining a collection data of the collection data and correcting the collection data; And
The second collection data correction unit determines whether or not the number of collected data exceeds the preset reference data number for each of the data sets and corrects the data sets whose number of collected data does not exceed the reference data number ;
Wherein the location data comprises at least one of the following: < RTI ID = 0.0 > 1, < / RTI > The method of claim 10,
The step of correcting the erroneous collection data
Wherein the first collection data correction unit performs clustering based on a data clustering reference preset for the collected data and determines data not belonging to the cluster among the collected data as the miscollected data. A method of calibrating positioning data for a base service. The method of claim 11,
The data clustering criterion is
The reception strength of the collected data,
The step of correcting the erroneous collection data
Wherein the first collection data correction unit corrects the reception intensity of the miscollected data so that the miscollected data belongs to the cluster if the first collected data correction unit performs the re-clustering based on the data clustering criterion. / RTI > The method of claim 11,
The step of correcting the erroneous collection data
Wherein the first collection data correction unit determines whether or not the number of collected data excluding the false collection data exceeds the number of reference data for each of the data sets, Wherein said data collection means excludes said miscounted data in a data set exceeding a predetermined number. The method of claim 11,
The step of calibrating the data sets
Wherein the second collection data correction unit adds virtual data generated by at least one of interpolation and data modeling to data sets whose number of collected data does not exceed the reference data count Wherein the location data comprises at least one of: The method of claim 11,
The step of calibrating the data sets
Wherein the second collection data correction unit transmits to the dynamic collection apparatus feedback information including region information corresponding to data sets for which the number of collected data does not exceed the reference data number, A method of calibrating positioning data for a service. 16. The method of claim 15,
The step of calibrating the data sets
Wherein the second collection data correction unit determines whether the additional collected data collected by the feedback is overlapped with the existing collected data, and if the number of the collected data excluding the additional collected data determined to be duplicated is the number of the reference data Is not to be calculated for the positioning data for the data sets that do not exceed the predetermined threshold value. The method of claim 11,
The positioning data correction method
Wherein the positioning database generation unit comprises: calculating positioning statistics for the representative points based on the data sets;
Wherein the location data comprises at least one of the following: < RTI ID = 0.0 > 1, < / RTI > 18. The method of claim 17,
The step of calculating the positioning statistics
Wherein the positioning database generation unit further uses collection data mapped to another representative point adjacent to each of the representative points, for each representative point corresponding to data sets for which the number of collected data does not exceed the reference data number And calculating the positioning statistics based on the measured positioning data. 18. A computer program stored in a medium for executing the method of any one of claims 10 to 18 using a computer. A dynamic collection device that periodically generates collected data including positional environment information and positional information on the move;
Analyzing a distribution of collected coordinates of collected data transmitted from the dynamic collection device, generating representative points based on the distribution of the collected coordinates, mapping the collected data to each of the representative points, Determining whether or not the number of collected data exceeds the predetermined reference number of data, determining whether the number of collected data exceeds a predetermined reference number of data A positioning data correction device that corrects data sets in which the number of collected data does not exceed the reference data number; And
A positioning database generation device for calculating positioning statistics for the representative points based on the data sets;
Wherein the positioning data providing system comprises:

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