WO2018101495A1

WO2018101495A1 - Rssi-based positioning method using ibeacon

Info

Publication number: WO2018101495A1
Application number: PCT/KR2016/013852
Authority: WO
Inventors: 신요안; 비덕투안; 이승우
Original assignee: 숭실대학교 산학협력단
Priority date: 2016-11-29
Filing date: 2016-11-29
Publication date: 2018-06-07

Abstract

The present invention relates to an RSSI-based positioning method using an iBeacon and comprises the steps of: allowing a user terminal to scan adjacent iBeacon nodes so as to select four iBeacon nodes in order based on the size of the RSSI value received therefrom; dividing, into four spaces having the same width, a region obtained by connecting the selected four iBeacon nodes, and mapping preset confidence limit table values to the four spaces; estimating the distance to an iBeacon node having the highest RSSI value among the four iBeacon nodes and selecting, from among the four spaces, one space corresponding to the estimated distance; and determining the position of the user terminal through RSSI values received from the remaining iBeacon nodes excluding the iBeacon node having the highest RSSI value. According to the RSSI-based positioning method using an iBeacon, of the present invention, an estimation value, which is more efficient and accurate than that of a conventional indoor positioning method, can be provided by allowing a change of RSSI from an iBeacon node to be observed.

Description

RSSI-based Positioning Method Using IBEACON

The present invention relates to an RSSI-based positioning method using iBeacon, and more particularly, to an RSSI-based positioning method using iBeacon which can estimate the position of a user terminal indoors using a received signal strength index together with iBeacon technology. It is about.

In order to provide a variety of location-based services, the location of the terminal is most important. A positioning system using a GPS satellite receiver is used to determine the location of the terminal, but such a positioning system has a disadvantage in that it is difficult to determine a location because the terminal does not receive a satellite signal when there is a terminal in a building.

In order to compensate for these disadvantages, indoor location information service is provided using location information of a wireless communication base station. However, the range of the base station is too wide, so that it is difficult to provide accurate service such as the error reaches several hundred meters. Therefore, in order to accurately determine the location of a terminal in a building, a technology for identifying a location by receiving a signal of the wireless AP and comparing and analyzing the location information of the wireless AP with the received signal strength has been studied.

Most of the existing RSSI-based positioning algorithms focus on positioning using either triangulation or fingerprinting. However, in the case of triangulation, the accuracy is lowered when used in a wide range, and in the case of finger printing, there are problems that a plurality of beacon nodes are required to obtain high accuracy. In addition, when the Bluetooth short-range signal and wireless map construction, the signal loss is very large, often out of service range.

Therefore, in order to achieve high accuracy, a technique for combining a triangulation method with a fingerprinting technique according to a divided region is required.

The background technology of the present invention is disclosed in Korean Patent Registration No. 10-1286169 (published on July 15, 2013).

An object of the present invention is to provide an RSSI-based location positioning method using iBeacon which can estimate the location of a user terminal indoors using a received signal strength index together with iBeacon technology.

According to an embodiment of the present invention for achieving the technical problem, in the RSSI-based location positioning method using iBeacon, the user terminal scans the neighboring iBeacon node, the four iBeacon in order of receiving the RSSI value Selecting a node, dividing the selected four iBeacon nodes into four spaces having the same width and width in a region connecting the four iBeacon nodes, mapping a predetermined confidence range table value to the four spaces, and the four iBeacon nodes Estimating a distance from the iBeacon node having the largest RSSI value among the four spaces, selecting one space corresponding to the estimated distance from the four spaces, and from the remaining iBeacon nodes except the iBeacon node having the largest RSSI value. Determining the location of the user terminal based on the received RSSI value.

According to the RSSI-based positioning method using iBeacon according to the present invention, by observing the change of RSSI from the iBeacon node, it is possible to provide more efficient and accurate estimates than the existing indoor positioning method.

1 is a flowchart illustrating an RSSI based location positioning method using iBeacon according to an embodiment of the present invention.

2 is an exemplary diagram showing a space between nodes divided into a grid model according to an embodiment of the present invention.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is said to "include" a certain component, it means that it can further include other components, without excluding other components unless specifically stated otherwise.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention.

The present invention proposes a method for providing positioning of a user terminal (iPhone) indoors using a reception strength index (RSSI) together with iBeacon technology.

After measuring the RSSI radio propagation model of the user terminal from a single iBeacon node, it can be used for the corresponding confidence-range characteristics of the terminal location. It can be estimated.

That is, according to an embodiment of the present invention, the unknown location of the user terminal may be estimated by measuring the RSSI of the iBeacon nodes. Here, iBeacon node is a Bluetooth 4.0 low energy device that represents small size, low cost and low power consumption, and generally broadcasts a small amount of information.

First, RSSI propagation between a user terminal and an iBeacon node is measured over time. This measured RSSI information can evaluate the confidence range of a single iBeacon node. And based on this confidence range information, a simple positioning method is established.

If the measurement cannot be made based on the confidence range information, the location is measured using the CoreLocation API using GPS or Wi-Fi signal information among APIs (Application Programming Interface) of the user terminal.

Hereinafter, it is assumed that RSSI measurement is performed by the user terminal at intervals of 5 minutes along the edge of the wall by adding 0.5m starting from 0.5m from the iBeacon node until reaching the end of the measurement space. The user terminal may receive an RSSI value from an iBeacon node at one second intervals.

First, the user terminal scans iBeacon nodes located in the vicinity, and selects four iBeacon nodes in order of the received RSSI values (S110).

That is, the user terminal selects the four closest iBeacon nodes (B _i ), and can obtain B _k through Equation 1 below.

Next, the user terminal divides the selected four iBeacon nodes into four spaces having the same width and width in the region connecting the selected iBeacon nodes, and maps the preset confidence range table values to the four spaces (S120).

That is, when iBeacon nodes B1, B2, B3, and B4 are selected, the user terminal divides the space into four spaces by connecting intermediate points with respect to the area where the four iBeacon nodes are connected. In each space, it can be divided into five areas according to the distance. In addition, a predetermined confidence range table value may be mapped to an area of each space.

Here, the confidence range table value may be represented as shown in Table 1 below.

Table 1 shows the confidence ranges recorded by the iPhone every five minutes along the edge of the wall, starting at 0.5 m from the iBeacon node and adding 0.5 m each until reaching the end of the measurement space.

That is, Table 1 shows data of receiving RSSI values from iBeacon nodes at intervals of 1 second using an iPhone, a user terminal, and storing signal strengths received from iBeacons in a database after combining time and distance measurement methods. Table.

Such a confidence range table may be divided into five regions in the space of B1 and mapped to the corresponding regions.

That is, the range of -56db to -65db at a distance of 0.5m from the iBeacon node, the range of -76db to -66db at a distance of 1m, and the range of -85db to -75db at a distance of 1.5m. As such, the confidence range table is created using the strengths of the signals received from the iBeacons, combining all the measurement results of the combination function.

Next, the user terminal estimates the distance from the iBeacon node having the largest RSSI value among the four iBeacon nodes and selects one space corresponding to the estimated distance from the four spaces (S130).

The user terminal determines the location of the user terminal through RSSI values received from the remaining iBeacon nodes except for the iBeacon node having the largest RSSI value (S140).

Assuming that the user terminal is divided into B1, B2, B3, and B4 in the order of the received RSSI value, first, select the largest space including the largest iBeacon node B1, and then the distance of the next two iBeacon B2, B3 The location of the user terminal can be determined by comparison from.

If iBeacon B2 and iBeacon B3 are outside the confidence distance, the selection of the region may be based on the comparison value.

On the other hand, if one of the three distances of d1, d2, d3 is not mapped, the user terminal may scan the iBeacon node located in the vicinity again.

However, if one of the three distances of d1, d2, and d3 is not mapped in the process of repeating the predetermined number of repetitions, an accurate value calculated by the CoreLocation API can be obtained.

As a result, if the mapping is successful, the distance of the user terminal is determined according to the location of the corresponding area. If the distance is calculated by the CoreLocation API, the distance can be obtained by triangulation.

Hereinafter, a process in which a user terminal according to an embodiment of the present invention divides an area connecting four iBeacon nodes into four spaces and divides into five groups for each space will be described.

As shown in FIG. 2, it may be assumed that beacons are installed at each corner of a square area of a 4.0m * 4.0m space, and the area is divided into a grid model and configured as a total of 16 zones.

First, the user terminal divides the restricted area connecting iBeacon nodes B1, B2, B3, and B4 into four partitions, respectively, into I, II, III, and IV. The user terminal may select an area of the iBeacon node that has received the largest signal using the strength of the signal received from the iBeacon nodes of B1, B2, B3, and B4, respectively.

As shown in FIG. 2, assuming that the space of I is selected, the space I may combine the fingerprinting technique and the confidence range table to classify the space I into 16 regions and 5 groups.

That is, an area adjacent to an iBeacon node of B1 at a distance of 0.5m is classified into a first group, and the first area is included. The second group is a part of 2 zones, 5 zones and 6 zones which are 1.0 m away from the iBeacon node of B1, and the third group is

zones

3, 6, 7, 9, which are 1.5 meters from the iBeacon node of B1. It includes 10 areas. The fourth group includes 4 zones, 8 zones, 11 zones, 13 zones, and 14 zones with a distance of 2.0 m, and the last group includes 12 zones, 15 zones, and 16 zones, measured by the coreLocation API. The measured accuracy values are used to represent the values of the "trust-range" measurable.

Therefore, when the user terminal according to the embodiment of the present invention selects the iBeacon node of B1 having the greatest RSSI strength, the user terminal selects the space I, and is divided in detail in the space I using the strengths of the RSSIs of B2 and B3. It can be estimated to be located in the area.

As described above, by observing a change in RSSI from the iBeacon node, an efficient and accurate estimate can be provided than the conventional indoor positioning method.

Although the present invention has been described with reference to the embodiments shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent other embodiments are possible. Therefore, the true technical protection scope of the present invention will be defined by the technical spirit of the appended claims.

Claims

In RSSI-based location positioning method using iBeacon,

The user terminal scans the neighboring iBeacon nodes, selecting the four iBeacon nodes in order of the received RSSI value,

Dividing the selected four iBeacon nodes into four spaces having the same width and width, and mapping a predetermined confidence range table value to the four spaces;

Estimating a distance from an iBeacon node having the largest RSSI value among the four iBeacon nodes, selecting one space corresponding to the estimated distance from the four spaces, and

RSSI-based location positioning method comprising the step of determining the location of the user terminal through the RSSI value received from the remaining iBeacon node except the iBeacon node having the largest RSSI value.