KR20190001386A - Indoor Positioning Method and Apparatus Based on Bluetooth Low Energy - Google Patents

Abstract

Embodiments of the present invention provide an indoor positioning method and an indoor positioning apparatus which can accurately measure an indoor position of a user by generating a plurality of signal intensity maps in consideration of directivity of a user terminal and setting a tracking range based on a position history of the user to select a signal intensity map.

Description

TECHNICAL FIELD [0001] The present invention relates to an indoor positioning method and apparatus based on low-power Bluetooth,

Field of the Invention [0002] The present invention relates to a method and apparatus for positioning in an indoor space.

Location information using GPS (Global Positioning System) can be utilized in various fields such as vehicle navigation, disaster situation response, location based service, and the like. However, since the GPS technology is relatively weak, it is difficult to recognize the location in a building where the line of sight (LoS) environment is not guaranteed or where there is signal interference.

To replace GPS, communication technologies such as Bluetooth low energy (BLE), Zigbee, Wi-Fi, and Cellular can be applied to indoor positioning. The indoor positioning information measured by the local communication technology can be applied to various fields such as large-scale material management, amusement park, and large shopping mall.

In particular, BLE simplifies the packet structure of the classic Bluetooth protocol and is more energy efficient and more compatible with classic Bluetooth devices, making it more popular than other local communication technologies. Indoor positioning system using BLE technology uses Received Signal Strength Indicator (RSSI) transmitted from three advertisement channels of BLE. RSSI is a cause of high error rate in indoor positioning due to large variation and non-constant value due to various external factors.

In addition, existing BLE-based indoor positioning systems use BLE beacons fixed indoors. This structure is disadvantageous in terms of scalability of the location-based service, since an administrator has to configure an application for each service to be provided to a user when a large number of users exist in the same space.

The present invention aims at accurately measuring the position of a user in a room by selecting a signal intensity map by generating a plurality of signal intensity maps in consideration of the directionality of a user terminal and setting a tracking range based on the user's location history, .

Other and further objects, which are not to be described, may be further considered within the scope of the following detailed description and easily deduced from the effects thereof.

According to an aspect of the present embodiment, there is provided a method for indoor positioning by a computing device, comprising the steps of: receiving a radio signal from a plurality of second devices from a first device for map construction in a plurality of directions in an indoor space, Generating a plurality of directional signal intensity maps (RSSI Orientation Maps) divided into cells, and generating the signal strengths recorded in the plurality of directional signal intensity maps from the third device of the user, And estimating a position of the third device of the user in the indoor space by comparing the signal intensity measured by the second devices of the first device and the second device.

According to another aspect of the present invention, a signal intensity measured by a plurality of second devices from a first device for map construction is recorded for each of a plurality of directions in an indoor space, and a plurality of signal strengths per direction A signal map generator for generating RSSI Orientation Maps, and comparing the signal strength recorded in the plurality of directional signal intensity maps with a signal intensity measured by the plurality of second devices from a third device of the user And a position estimator for estimating a position of the third device of the user in the indoor space.

As described above, according to the embodiments of the present invention, a plurality of signal intensity maps are generated in consideration of the direction of a user terminal, and a signal strength map is set by setting a tracking range based on a user's location history, The position of the user can be accurately measured.

According to the embodiments of the present invention, an error of an estimated position can be minimized by estimating a position of a user by applying a weight for each direction to a position of a selected cell in a plurality of signal intensity maps.

According to embodiments of the present invention, the wireless signal receivers fixed at a specific location from the wireless signal transmitter of the user receive the wireless signals and transmit the positioning data to the service providing server, so that even if there is no separate smart device, And even if a problem occurs in a wireless signal transmitter of one user, there is an effect that it does not affect that another user receives the location-based service.

The effects described in the following specification and those obvious to those skilled in the art, which are expected to be effected by the technical features of the present invention, are handled as described in the specification of the present invention even if they are not explicitly mentioned here.

Fig. 1 (a) illustrates an active indoor positioning system, and Fig. 1 (b) illustrates a manual indoor positioning system.
FIG. 2 (a) is a diagram illustrating an RSSI distribution by beacon angle in a horizontal direction, and FIG. 2 (b) is a diagram illustrating an RSSI distribution by beacon angle in a vertical direction.
3 and 4 are block diagrams illustrating an indoor positioning apparatus according to embodiments of the present invention.
5 is a diagram illustrating how the indoor positioning apparatus according to an embodiment of the present invention sets K directions in an indoor space.
6 is a diagram illustrating how an indoor positioning apparatus according to an embodiment of the present invention generates K directional signal intensity maps.
7 is a diagram illustrating that an indoor positioning apparatus according to another embodiment of the present invention sets a tracking range.
8 and 9 are flowcharts illustrating an indoor positioning method according to another embodiment of the present invention.
10 (a) is a graph showing error distances of positioning results obtained by the embodiments of the present invention at a window size of 1s, and FIG. 10 (b) FIG.
FIG. 11A is a graph showing the error distances of results obtained by positioning beacons using the same beacon as the map building beacon according to the embodiments of the present invention. FIG. A graph showing error distances of results obtained by using beacons different from beacons.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Will be described in detail with reference to exemplary drawings.

A location based service (LBS) refers to a wireless content service providing specific information according to a changed location of a user. An indoor positioning system is needed to support location-based services in indoor space.

Fig. 1 (a) illustrates an active indoor positioning system, and Fig. 1 (b) illustrates a manual indoor positioning system.

An active indoor positioning system is structured such that a fixed receiver (scanner) receives signals from a movable beacon (advertiser), and the receiver is connected to a location based service providing server. A manually operated indoor positioning system is structured such that a fixed beacon (advertiser) is transmitted to a mobile receiver (scanner), and a receiver is connected to a location based service providing server. The indoor positioning system according to the present embodiments is implemented as an active indoor positioning system.

The indoor positioning system mainly uses the fingerprint method. In the conventional fingerprint method, the indoor space is divided into small cells, and RSSI values are collected directly from each cell, and a signal map is constructed by building a database. Then, the RSSI value received at the user's position is compared with the database, Estimate the cell showing the pattern as the location of the user. In the conventional fingerprint method, since the signal map is constructed in a certain direction without considering the direction of the wireless transceiver, there is a problem that the error rate is increased compared with the signal map.

In FIG. 2 (a), RSSI distributions of beacons in the horizontal direction are shown. In FIG. 2 (b), RSSI distributions of beacons in the vertical direction are shown. As shown in FIG. 2, the RSSI value varies depending on the directions of the devices constituting the indoor positioning system, that is, the directions of the antennas of the transmitter and the receiver. A difference in RSSI value occurs due to antenna gain of the transmission antenna and the reception antenna or multipath of the indoor environment. As a result of the simulation, the RSSI value of the beacon horizontally changed in the range of -78 dB to -84 dB, and the RSSI value of the vertically installed beacon changed in the range of -75 dB to -87 dB.

3 and 4 are block diagrams illustrating an indoor positioning apparatus according to embodiments of the present invention. 3, the indoor positioning apparatus 300 includes a signal map generating unit 310 and a position estimating unit 320. [ The indoor positioning device 300 may omit some of the various components illustrated in FIG. 3 or may further include other components. Referring to FIG. 4, the indoor positioning device 400 may further include a tracking range setting unit 420.

The signal map generators 310 and 410 record the signal strengths measured by the plurality of second devices from the first device for map construction. The plurality of second devices measure the signal intensity from the first device for building a map in a plurality of directions in the indoor space. The signal map generators 310 and 410 generate a plurality of directional signal intensity maps (RSSI Orientation Maps) divided into a plurality of cells in which signal strengths are recorded.

The signal map generators 310 and 410 receive a BLE signal from the first device in a predetermined direction to generate a plurality of signal intensity maps. The first device and the second device are in wireless communication and may use Bluetooth low energy (BLE). The first device is a BLE advertiser and the BLE advertiser is mobile. The second device is a BLE scanner and the BLE scanner is fixedly installed at a specific position in the indoor space. That is, the indoor positioning apparatus can be implemented in an active manner.

Active indoor positioning systems allow users to optimize RSSI values measured from the advertiser because they can use the same standardized advertiser. Since the active system can provide the position location data directly to the service providing server by the receiver, the user can receive the location based service without the user's smart device. An active system has the effect of not affecting the entire system because it affects only one user when a problem occurs in the advertiser, unlike a manual system.

The position estimating units 320 and 430 compare the signal strengths recorded in the plurality of directional signal intensity maps with the signal intensity measured by the plurality of second devices from the user's third device, As shown in FIG. The third device of the user and the first device for building the map can perform the function of the BLE advertiser.

Hereinafter, it is explained that the indoor positioning apparatus generates a direction-specific signal intensity map. FIG. 5 is a diagram illustrating an example in which an indoor positioning device according to an embodiment of the present invention sets K directions in an indoor space, and FIG. 6 is a diagram illustrating an indoor positioning device according to an embodiment of the present invention, Lt; RTI ID = 0.0 > maps. ≪ / RTI >

To create a signal map, the entire interior space is divided into cells having a certain size. A cell can be represented by an nxn matrix, and the coordinates (x, y) of the cell are represented by (x, y) coordinates from the reference cell. R BLE scanners are fixed at the (x, y) position of a specific cell. The BLE scanner is configured so that no more than one is located in the same cell. Each cell (x, y) in the indoor positioning system records the coordinates (x, y) of the cell and RSSI values measured by R scanners.

In order to distinguish the directionality of the BLE devices constituting the indoor positioning system, it is divided into K direction regions as shown in FIG. The direction k is a direction of the BLE device and generates a signal map for each device direction and constitutes a plurality of signal maps for each direction. The direction-specific signal map D _k is expressed by Equation 1 by the signal strength RSSI _i .

D _k denotes the direction-specific signal map (OM), which is OM = {D _k | k = 1, ..., K}.

According to Equation (1), D _k becomes larger as the number of scanners installed in the indoor positioning system increases, the number of cells increases, and the number of directions increases, and accurate indoor positioning becomes possible. An example of constructing D _k is shown in Fig. For example, the scanner (receiver) is fixed and located at the end of the indoor space, and the number of scanners R = 4. In order to construct the OM, the direction of the device is divided into K regions, and each cell existing in the signal map from the signal map (D _-1 ) in the first direction to the signal map (D _K ) (x, y) and records the RSSI all _i. When all the recording is completed, the configuration of the directional signal map (OM) is completed.

Since a plurality of directional signal maps take into consideration the directionality of the BLE device, it is possible to overcome the limitation of the conventional method of the printing of the pixels to some extent.

Hereinafter, the indoor positioning apparatus sets the tracking range. 7 is a diagram illustrating that an indoor positioning apparatus according to another embodiment of the present invention sets a tracking range.

The indoor positioning apparatus may include a tracking range setting unit that sets a tracking range that is a part of the indoor space based on the position history of the user's third device and the moving speed of the user's third device.

The tracking range is defined as a range of a fingerprinting map that can be set based on the current user's position history and moving speed to improve the accuracy of the indoor positioning. This tracking range is defined according to the time difference between the moving speed of the user and the previous position and the next position of the user.

The present embodiments can further reduce the possibility of error by setting the tracking range, thereby improving the accuracy of the indoor positioning. In the conventional fingerprinting method, when the RSSI value at the measurement position is compared with the RSSI value at the data of the fingerprinting map in the actual measurement, a cell having the RSSI value closest to the range of the entire fingerprinting map is searched. In this method, if the RSSI value of the beacon is different from the measured position, the probability of selecting a cell different from the actual position is high, which causes an error. On the other hand, the present embodiment compares the RSSI values only within the movement range of the user, which can be theoretically calculated when the RSSI values are compared in the fingerprinting map within the tracking range rather than the entire fingerprinting map. This is because the cell selection width is narrow and the probability of selecting the correct cell is relatively increased, thereby reducing the indoor positioning error. When the tracking range according to the user's position at time t is denoted by l, the moving speed of the user is denoted by v, and the position of the next time user is denoted by t ', the tracking range (1) is expressed by Equation (2).

Where x _t denotes the x-coordinate of the user's position located at time t and x _{t '} denotes the x-coordinate of the user's position at time t' when the user reaches the next position. Similarly, y _t means the y-coordinate of the user's position at time t and y _{t '} means the y-coordinate of the user's position at time t' when the user reaches the next position. Therefore, the tracking range at time t is set based on the previous position of the user, and the difference between the current position of the user and the previous position of the user is set to a range smaller than or equal to v (t - t '). The larger the indoor environment, the faster the user moves, the smaller the size of the cell, and the smaller the size of the tracking range (1).

If the user's previous position coordinate (x _t , y _t ) does not exist, it is determined that the indoor positioning is started and the tracking range is OM. That is, the OM becomes a fingerprint map for calculating the position of the user at the start of the indoor positioning. After that, when the coordinates (x _t , y _t ) of the user are grasped, the reference point of the tracking range existing in the OM is updated and the range of the tracking range (1) is set as shown in FIG. If the set range (l) the coordinates (x _{t ', yt')} measured in the position that the correct coordinates _{(x t ', y t'} ) of the user and the reference point of the trace range is updated to the user's next position calculation . If it exceeds the set range (l), it can not be the user's position. The tracking range setting unit updates the tracking range by changing the reference point of the tracking range to the current position of the user's third device. The set Tracking Area (TA) of the coordinates of all the cells (x, y) satisfying the tracking range (l) is expressed by Equation (3).

According to Equation (3), when the moving speed of the user is fast in the indoor positioning system, the distance traveled by the user is increased compared to the time, which makes accurate measurement difficult. Therefore, this may require a large range of l and may be a factor in lowering the accuracy of indoor positioning. In addition, if the difference between the previous user's location time t and the next user's location time t 'is small, a sufficient amount of data can not be collected, and thus the information is not received from all the BLE advertising channels. Therefore, the indoor positioning device should be designed in consideration of the size of the indoor positioning window, the moving speed of the user in the indoor environment, and the number of signal generation of the beacon.

Hereinafter, the indoor positioning apparatus estimates the position of the device. If the signal map generating section establishes a directional signal map to be used as the fingerprinting map before the actual indoor positioning, the position estimating section proceeds to the actual positioning. The position estimating unit determines a fingerprinting map to be compared, calculates an Euclidean distance, and calculates an Orientation Weight.

The indoor positioning device compares the RSSI value measured through the actual positioning with the RSSI value of the pre-measured comparison fingerprinting map so that the comparison fingerprinting map must be configured before the actual positioning. In this case, the indoor positioning device uses the directional signal map (OM). If there is no user's location information in the indoor positioning system, all directional signal maps (OM) are used as comparison fingerprint maps. When the previous location information of the user exists, only the directional signal map (OM) existing within the above-described tracking range is used as the comparison target fingerprinting map. That is, the position estimator selects a map in which the previous position of the user's third device is within the tracking range from among the plurality of directional signal intensity maps.

Unlike the conventional method, the present embodiments utilize the direction of the BLE device constituting the indoor positioning system and the history of the user's position, and thus show the indoor location positioning result with high accuracy.

The position estimator calculates the Euclidean distance between the signal intensity recorded in the plurality of directional signal intensity maps and the signal intensity measured by the plurality of second devices from the user's third device. The position estimating unit selects the cells having the smallest Euclidean distance in the plurality of directional signal intensity maps, and calculates the positions of the plurality of cells.

The Euclidean distance is used to set a similar measure when comparing the RSSI value of the compared fingerprint map with the actual measured RSSI value. The Euclidean distance E _k in the direction _k is calculated using RSSI _{i, axy, k} indicating the RSSI value of the corresponding cell a _xy in the defined Dk. If the measured RSSI value is MRSSI _{i, axy, k} , then Ek is expressed by Equation (4).

E _k compares the actually measured RSSI value with the RSSI value of the comparison fingerprinting map and calculates the absolute value of the difference. The finally calculated Euclidean distance value has one value for each cell in the direction k of the BLE device. The Ek calculated by this process is a measure of finding the cell with the smallest RSSI difference through comparison of RSSI values. At this time, the cell coordinate E _{min, k (axy)} of E _k having the smallest difference is expressed by Equation (5).

The position estimating unit calculates a plurality of weight values for the plurality of cells based on the Euclidean distance. The position estimating unit calculates the position of the third device of the user based on the positions of the plurality of cells by applying a plurality of weightings to the positions of the plurality of cells.

The calculated E _{min, k (axy)} Value has one value for each cell constituting the fingerprint map of each direction k. At this time, E _{min, k (axy)} The value may represent another (x, y) coordinate even in the same cell due to the directional characteristics of the device. The conventional scheme does not consider the direction, so it appears as one of the coordinates of the closest cell. However, in this embodiment, because there are coordinates for each direction, a plurality of (x, y) coordinates are integrated to calculate an accurate user position. At this time _, to integrate the coordinates of E _{min, k (axy)} , weights are weighted on each Euclidian distance, and the effect of the coordinates of the cell indicating the closest RSSI value is more reflected. Here, when the weight calculated by the direction k of each BLE device is W _k , W _k is expressed by Equation (6).

E _{min, i} and E _{min, k} denote Euclidean distance by direction. K represents the maximum number of equally divided BLE device orientations. As the Euclidean distance is shorter, it means that it corresponds to the RSSI value of the comparison object. Therefore _, the reciprocal of E _{min, k} calculated in the direction k is taken to increase the weight of the value similar to the comparison fingerprinting map. A value similar to the comparison fingerprinting map can be calculated by dividing the inverse of the Euclidean distance values in all directions K existing in the same cell. Therefore, the sum of W _K calculated in all directions K is always 1. According to Equation (6), if the Euclidean distance is small, the weight of the direction E _{min, k} increases. Conversely, if the Euclidean distance is large, the weight decreases. As a result, this can more accurately reflect the importance of the most similar cell coordinates and thus increase the indoor positioning accuracy.

Once the weight for each direction is calculated, the user's current position can be calculated. The current position P (x, y) of the user is expressed by Equation (7).

E _{min, k} calculated in the fingerprinting map composed of K directions can represent different values for each direction k. Therefore, the weight calculated in all directions K is multiplied by the corresponding coordinates, and the final user's position P (x, y) is calculated when the weight is added. The current position of the user is transmitted to the indoor positioning device for the next position calculation of the user. The indoor positioning device receives the calculated user's current position and uses it to set the tracking range and reference point at the next position calculation. Table 1 shows the total algorithm for calculating the user indoor position.

The line 1-15 in Table 1 represents the step of setting the fingerprinting map for each direction, i.e., the signal map for each direction, the line 16-22 represents the step of calculating the Euclidean distance E _k , line represents a step of finding a value representing the smallest E _k E _k of the calculation, line 27-34 represents the step of calculating the weight for E _k, line 35-39 it is based on the final user of the And calculating the coordinate P (x, y).

Although the components included in the indoor positioning device are shown separately in FIGS. 2 and 3, a plurality of components may be combined with each other and implemented with at least one module. The components are connected to a communication path connecting a software module or a hardware module inside the device and operate organically with each other. These components communicate using one or more communication buses or signal lines.

The indoor positioning device may be implemented in logic circuitry by hardware, firmware, software, or a combination thereof, and may be implemented using a general purpose or special purpose computer. The device may be implemented using a hardwired device, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or the like. Further, the device may be implemented as a System on Chip (SoC) including one or more processors and controllers.

The indoor positioning device may be mounted in a form of software, hardware, or a combination thereof to a computing device provided with a hardware element. The computing device may refer to various devices including all or part of a memory for storing data for executing a program, a microprocessor for executing and calculating a program, and the like.

8 and 9 are flowcharts illustrating an indoor positioning method according to another embodiment of the present invention. The indoor positioning method may be performed by a computing device.

In step S810, the computing device records the signal strength measured by receiving a radio signal from the first device for map construction in a plurality of directions in the indoor space, and measures a plurality of Directional signal intensity maps (RSSI Orientation Maps).

The first device, the third device, and the second device use Bluetooth low energy (BLE). Wherein the first device and the third device are a BLE advertiser and the BLE advertiser is mobile and the second device is a BLE scanner and the BLE scanner is fixed at a specific location in the indoor space Respectively.

In step S820, the computing device compares the signal strengths recorded in the plurality of directional signal intensity maps with the signal strengths measured by the plurality of second devices from the user's third device to determine the position of the user's third device .

Referring to FIG. 9, the indoor positioning method may further include a step S920 of setting a tracking range after step S910.

In step S920, the computing device sets a tracking range that is a part of the indoor space based on the position history of the user's third device and the moving speed of the user's third device. The step of setting the tracking range (S920) may update the tracking range by changing the reference point of the tracking range to the current position of the user's third device.

The step S930 of estimating the position of the third device of the user selects a map in which the previous position of the user's third device is within the tracking range from among the plurality of directional signal intensity maps.

Estimating the position of the user's third device (S930) calculates the Euclidean distance between the signal strength recorded in the plurality of directional signal intensity maps and the signal intensity measured by the plurality of second devices from the user's third device , Cells having the smallest Euclidean distance are selected from the plurality of directional signal intensity maps, and the positions of the plurality of cells are calculated.

The step of estimating the location of the third device of the user (S930) may include calculating a plurality of weight values for a plurality of directions for a plurality of cells based on the Euclidean distance, applying a plurality of weight values to the plurality of cells, The position of the third device of the user is calculated based on the position of the cell of the second device.

8 and 9 illustrate the sequential execution of the respective steps. However, those skilled in the art will appreciate that various modifications and changes may be made to the embodiments of the present invention without departing from the essential characteristics of the embodiments of the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.

The operations according to the present embodiments may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. A computer-readable medium represents any medium that participates in providing instructions to a processor for execution. The computer readable medium may include program instructions, data files, data structures, or a combination thereof. For example, there may be a magnetic medium, an optical recording medium, a memory, and the like. The computer program may be distributed and distributed on a networked computer system so that computer readable code may be stored and executed in a distributed manner. Functional programs, codes, and code segments for implementing the present embodiment may be easily deduced by programmers of the technical field to which the present embodiment belongs.

Hereinafter, simulation results will be described with reference to FIGS. 10 and 11. FIG.

10 (a) is a graph showing error distances of positioning results obtained by the embodiments of the present invention at a window size of 1s, and FIG. 10 (b) FIG.

In FIG. 10, an original scheme is an existing method, an OW scheme is an indoor positioning method considering a direction, and a TM-OW scheme is an indoor positioning method (Tracking Map Orientation Weight) considering a user's previous position and a device direction.

The error is calculated by applying each method using the RSSI value measured for each path. In this case, the Window size for the indoor positioning refers to the time for the user to measure the RSSI value from one place. Each method was divided into two cases when the window size was 1s and the indoor position was measured by each route.

The cumulative distribution function (CDF) of the TM-OW scheme contained more than 80% error within 1m of error range, and all measurements were included within the error range of about 3m, showing better performance than other schemes. On the other hand, the Original Scheme reflects a single fingerprinting map and does not take into consideration the orientation of the device and the user's previous position, so the error range is more than 80% within 4m. In addition, there is a very large error of about 10 m in the error range to accommodate all calculated measurement positions.

The larger the indoor positioning window, the more accurate indoor measurement is possible, and the present embodiments enable more accurate positioning than other indoor positioning methods.

Beacons do not use exactly the same chips in the same model, so they have different directional characteristics and different battery levels. This affects the RSSI value recorded in the indoor positioning, leading to an indoor positioning error.

11A shows error distances of results obtained by positioning beacons using the same beacon as the map building beacon. In FIG. 11B, Represents the error distance of the result of positioning using different beacons. Referring to FIG. 11, the TM-OW scheme has a higher accuracy than the original scheme even when a map beacon is not used in an actual indoor positioning.

The present embodiments are for explaining the technical idea of the present embodiment, and the scope of the technical idea of the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment should be construed according to the following claims, and all technical ideas within the scope of equivalents thereof should be construed as being included in the scope of the present invention.

300, 400: indoor positioning apparatus 310, 410: signal map generating unit
420, 430: Position estimation unit 420: Tracking range setting unit

Claims (14)

A method for indoor positioning by a computing device,
The computing device records a signal intensity measured by receiving a wireless signal from a first device for map construction in a plurality of directions in a room space and a plurality of second devices, Generating RSSI Orientation Maps; And
(I) comparing the signal strength recorded in the plurality of directional signal intensity maps with (ii) the signal strength measured by the plurality of second devices from the user's third device, and Estimating a position of the third device of the user
And an indoor positioning method. The method according to claim 1,
Wherein the first device for map construction, the third device of the user, and the second device use Bluetooth low energy (BLE), and the first device for map construction and the third device of the user use BLE Wherein the second device is a BLE scanner and the BLE scanner is fixedly installed at a specific position in the indoor space. Way. The method according to claim 1,
Further comprising the step of setting a tracking range that is a partial area of the indoor space based on the location history of the third device of the user and the moving speed of the third device of the user, Way. The method of claim 3,
The step of setting the tracking range includes:
Wherein the tracking range is updated by changing the reference point of the tracking range to the current position of the third device of the user. The method of claim 3,
Wherein estimating the location of the third device of the user comprises:
And selects a map in which a previous position of the third device of the user is within the tracking range from among the plurality of directional signal intensity maps. The method according to claim 1,
Wherein estimating the location of the third device of the user comprises:
Wherein the Euclidean distance between the signal strengths recorded in the plurality of directional signal intensity maps and the signal intensity measured by the plurality of second devices from the third device of the user is calculated, Wherein a cell having a minimum distance is selected, and a position of a plurality of cells is calculated. The method according to claim 6,
Wherein estimating the location of the third device of the user comprises:
Calculating a weight for each of a plurality of directions for the plurality of cells based on the Euclidean distance, applying a weight for each of the plurality of directions to the positions of the plurality of cells, And calculating the position of the third device. Recording the signal strength measured by the plurality of second devices from the first device for map construction for each of a plurality of directions in the indoor space and generating a plurality of signal intensity maps (RSSI Orientation Maps) A signal map generator for generating a signal map; And
Comparing the signal strength recorded in the plurality of directional signal intensity maps with a signal intensity measured by the plurality of second devices from a user's third device to estimate a position of the third device of the user in the indoor space, position estimator for
And an indoor positioning device. 9. The method of claim 8,
Wherein the first device for map construction, the third device of the user, and the second device use Bluetooth low energy (BLE), and the first device for map construction and the third device of the user use BLE Wherein the second device is a BLE scanner and the BLE scanner is fixedly installed at a specific position in the indoor space. Device. 9. The method of claim 8,
And a tracking range setting unit for setting a tracking range that is a partial area of the indoor space based on the position history of the third device of the user and the moving speed of the third device of the user Indoor positioning device. 11. The method of claim 10,
The tracking range setting unit may set,
And updates the tracking range by changing a reference point of the tracking range to a current position of the third device of the user. 11. The method of claim 10,
The position estimating unit may calculate,
And selects a map in which the previous position of the third device of the user is within the tracking range from among the plurality of directional signal intensity maps. 9. The method of claim 8,
The position estimating unit may calculate,
Wherein the Euclidean distance between the signal strengths recorded in the plurality of directional signal intensity maps and the signal intensity measured by the plurality of second devices from the third device of the user is calculated, And calculates a position of a plurality of cells by selecting cells whose distance is minimum. 14. The method of claim 13,
The position estimating unit may calculate,
Calculating a weight for each of a plurality of directions for the plurality of cells based on the Euclidean distance, applying a weight for each of the plurality of directions to the positions of the plurality of cells, And calculates the position of the third device.

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