KR101964509B1 - Method of positioning indoor and apparatuses performing the same - Google Patents

Abstract

An indoor positioning method and apparatus for performing the same are disclosed. An indoor positioning apparatus according to an exemplary embodiment of the present invention includes a filtering unit for filtering a plurality of signal strength values transmitted from each of a plurality of reference nodes and a filtering unit for filtering the optimal average signal strength value of the plurality of reference nodes based on the filtered signal strength values And a determination unit for determining an indoor positioning of the target node receiving the plurality of signal strength values based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of reference nodes.

Description

Field of the Invention The present invention relates to an indoor positioning method,

The following embodiments relate to an indoor positioning method and apparatuses for performing the same.

Location-based technology is a technology that acquires physical, geographical, or logical location information of an object placed in a specific location and reacts accordingly.

As the positioning method, there are a triangulation method of measuring the position by measuring the difference of the distance between objects, the angle or the azimuth angle, the scene analysis method using the scenery seen from the specific point of view (Vantage Point) .

In addition, the position measurement technique may be variously used, such as a position measurement technique using a global positioning system, a position measurement technique using a received signal intensity of a radio signal, and a position measurement technique using a short distance wireless communication.

GPS positioning technology is a technique for measuring the distance to a satellite by measuring the phase of a carrier signal transmitted from a GPS satellite (or absolute positioning) or tracking a code of a carrier signal (or relative positioning). Therefore, although GPS positioning technology is widely used at present, it is possible to provide stable service through a fixed satellite with a wide signal radius. However, it can not be serviced in a room or a shaded area where accuracy is low and reception of GPS satellite signals is difficult, .

The location measurement technique using mobile communication is a technology for obtaining geographical location information of a mobile terminal by triangulation using a currently established mobile communication system. A terminal based method in which a terminal having a GPS receiver transmits position information to a network separately from a base station, and a hybrid method in which both are mixed. In this case, the location measurement technology using the above method does not need a separate infrastructure and is widely utilized as a macro location positioning technique because it has a wide service area like GPS.

Embodiments can provide a technique for filtering a plurality of signal strength values transmitted at each of a plurality of reference nodes.

Embodiments can also provide a technique for calculating an optimal average signal strength value of a plurality of reference nodes based on filtered signal strength values.

Embodiments may also provide a technique for determining indoor positioning for a target node that has received a plurality of signal strength values based on position information of a plurality of reference nodes and an optimal average signal strength value of a plurality of reference nodes .

An indoor positioning method according to an embodiment includes filtering a plurality of signal strength values transmitted at each of a plurality of reference nodes, calculating an optimal average signal strength value of the plurality of reference nodes based on the filtered signal strength values And determining an indoor positioning for a target node that has received the plurality of signal strength values based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of reference nodes.

The filtering may include obtaining at least one of the 30 signal strength values per second transmitted at each of the plurality of reference nodes.

Wherein the calculating includes selecting signal strength values for calculating an optimal average signal strength value of the plurality of reference nodes from among the filtered signal strength values based on the time of obtaining the filtered signal strength values .

Wherein the determining comprises: determining a number of the plurality of reference nodes; configuring the plurality of reference nodes as a plurality of subsets based on the number of the plurality of reference nodes; Calculating an average signal strength value of the plurality of sub-sets based on the average signal strength value of the plurality of sub-sets based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of sub- And determining and determining indoor positioning for the plurality of subsets.

The step of verifying the indoor location may include determining a Non Line Of Sight (NLOS) based on the maximum likelihood function value and the NLOS error distance for the plurality of subsets.

The determining may further include delivering a notification of the indoor positioning to the target node.

An indoor positioning apparatus according to an exemplary embodiment of the present invention includes a filtering unit for filtering a plurality of signal strength values transmitted from each of a plurality of reference nodes and a filtering unit for filtering the optimal average signal strength value of the plurality of reference nodes based on the filtered signal strength values And a determination unit for determining an indoor positioning of the target node receiving the plurality of signal strength values based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of reference nodes.

The filtering unit may obtain at least one of 30 signal strength values per second transmitted from each of the plurality of reference nodes.

The determining unit may select signal strength values for calculating an optimal average signal strength value of the plurality of reference nodes from among the filtered signal strength values based on the acquisition time of the filtered signal intensity values.

Wherein the determining unit determines the number of the plurality of reference nodes, configures the plurality of reference nodes as a plurality of sub-sets based on the number of the plurality of reference nodes, Based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of sub-sets, and calculating the optimal average signal strength value of the plurality of sub- Can be determined and determined.

The determination unit may determine Non Line Of Sight (NLOS) based on the maximum likelihood function value and the NLOS error distance for the plurality of subsets.

And the determination unit may notify the target node of the indoor positioning.

1 shows a block diagram of an indoor positioning system according to an embodiment.
Fig. 2 shows a block diagram of the indoor positioning apparatus shown in Fig. 1. Fig.
3A to 3C show examples illustrating indoor positioning.
Figures 4A and 4B show examples of signal strength values and filtered signal strength values.
Figures 5A through 5C show examples for determining the average signal strength value.
6A to 6G show examples of judging NLOS.
7 is a flowchart illustrating an operation method of an indoor positioning system according to an embodiment.

It is to be understood that the specific structural or functional descriptions of embodiments of the present invention disclosed herein are presented for the purpose of describing embodiments only in accordance with the concepts of the present invention, May be embodied in various forms and are not limited to the embodiments described herein.

Embodiments in accordance with the concepts of the present invention are capable of various modifications and may take various forms, so that the embodiments are illustrated in the drawings and described in detail herein. However, it is not intended to limit the embodiments according to the concepts of the present invention to the specific disclosure forms, but includes changes, equivalents, or alternatives falling within the spirit and scope of the present invention.

The terms first, second, or the like may be used to describe various elements, but the elements should not be limited by the terms. The terms may be named for the purpose of distinguishing one element from another, for example without departing from the scope of the right according to the concept of the present invention, the first element being referred to as the second element, Similarly, the second component may also be referred to as the first component.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between. Expressions that describe the relationship between components, such as "between" and "between" or "neighboring to" and "directly adjacent to" should be interpreted as well.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. It will be understood that, in this specification, the terms " comprises ", or " having ", and the like are to be construed as including the presence of stated features, integers, But do not preclude the presence or addition of steps, operations, elements, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the meaning of the context in the relevant art and, unless explicitly defined herein, are to be interpreted as ideal or overly formal Do not.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the patent application is not limited or limited by these embodiments. Like reference symbols in the drawings denote like elements.

1 shows a block diagram of an indoor positioning system according to an embodiment.

Referring to FIG. 1, the indoor positioning system 10 includes a plurality of reference nodes 100, an indoor positioning device 200, and a target node 300.

Each of the plurality of reference nodes 100 may communicate with the indoor positioning device 200 and the target node 300. Thus, each of the plurality of reference nodes 100 may transmit packets for the plurality of reference nodes 100 to the indoor device 200 and the target node 300.

The indoor positioning device 200 may be attached to the target node 300 or attached at a distance from the target node 300 to receive the packets.

For example, when the indoor positioning apparatus 200 is attached to the target node 300, the indoor positioning apparatus 200 receives packets for the plurality of reference nodes 100 from the plurality of reference nodes 100 .

The indoor positioning apparatus 200 may be configured such that the plurality of reference nodes 300 received by the target node 300 from the target node 300 are allocated to the indoor positioning apparatus 200, Lt; RTI ID = 0.0 > 100 < / RTI >

The indoor positioning device 200 can determine the indoor positioning (or the recognition position) with respect to the target node 300. In addition, the indoor positioning device 200 can consider the maximum distance from the minimum distance that the target node 300 moves in the indoor environment during the indoor positioning period in the movement of the target node 300.

The indoor positioning device 200 communicates with the target node 300. Accordingly, the indoor positioning device 200 can receive the packets received by the target node 300. [ In addition, the indoor positioning device 200 can transmit a notification to the target node.

The target node 300 may receive notifications and packets. Thus, the target node 300 may display a notification. In addition, the target node 300 may transmit the packets to the indoor positioning device 200. At this time, the target node 300 may store the notification in an internal memory (not shown).

The target node 300 may be implemented as a portable electronic device. For example, the portable electronic device may be a laptop computer, a mobile phone, a smart phone, a tablet PC, a mobile internet device (MID), a personal digital assistant (PDA) an enterprise digital assistant, a digital still camera, a digital video camera, a portable multimedia player (PMP), a personal navigation device or a portable navigation device (PND), a handheld game console, , an e-book, or a smart device. At this time, the smart device can be implemented as a smart watch or a smart band.

Also, the target node 300 may be implemented in a portable electronic device.

Hereinafter, the configuration and operation of the indoor positioning device 200 will be described in detail with reference to FIG.

Fig. 2 shows a block diagram of the indoor positioning apparatus shown in Fig. 1. Fig.

2, the indoor positioning device 200 includes a transmission / reception module 210, a controller 230, and a memory 250.

The transmission / reception module 210 receives packets from the plurality of reference nodes 100 and the target node 300. At this time, the packets may include location information (or coordinates) of each of the plurality of reference nodes 100, identification information, and signal strength value in the building.

The transceiver module 210 may send a notification to the target node 300. In this case, the notification may be indoor positioning information for the target node 300 and surrounding information about the position of the target node 300.

Thus, the transceiver module 210 may communicate with the plurality of reference nodes 100 and the target node 300.

The transmission / reception module 210 can perform communication based on various types of infrastructure such as an Internet communication network, an intranet, a local area network (LAN), a wireless LAN, an IEEE 802.15.4 based Zigbee, Wi-Fi, LF, Xbee, Zigbee, BlueTooth and Beacon have.

The controller 230 controls the overall operation of the indoor positioning device 200. For example, the controller 230 may control the operation of each configuration 210 and 250.

The controller 230 may obtain the packets received via the transmission / reception module 210. [ At this time, the controller 230 can store and manage the obtained packets in the memory 250. [

In addition, the controller 230 may calculate an optimal average signal strength value of a plurality of existing nodes using a plurality of signal strength values transmitted from each of the plurality of reference nodes, and determine, based on the optimal average signal strength value, Can be determined. The controller 230 includes a filtering unit 231 and a determination unit 233.

The filtering unit 231 may obtain at least one of the signal strength values included in the obtained packets. For example, the filtering unit 231 may obtain at least one of 30 signal strength values per second transmitted from each of the plurality of reference nodes 100. [

The filtering unit 231 filters at least one obtained. For example, the filtering unit 231 may filter at least one using a Kalman filter. That is, the filtering unit 231 may filter the signal strength values using the Kalman filter to minimize and continuously estimate the variability of the signal strength values due to the unstable channel environment. In this case, the unstable channel environment may be various, such as human motion, interference due to propagation signals of other networks, multipath propagation and obstacles. The Kalman filter may also be a model that considers only univariate factors for signal strength values to minimize consideration factors other than variability in signal strength values.

Therefore, the filtering unit 231 can reduce the indoor positioning error of the target node 300 using the Kalman filter to generate an optimal signal intensity value.

The filtering unit 231 may transmit at least one filtered signal to the determining unit 233 immediately after filtering the at least one obtained. At this time, the filtering unit 231 can store and manage the filtered at least one in the memory 250.

The Kalman gain, the signal strength value, and the variance value of the signal strength can be expressed by Equations (1), (2) and (3).

), 측정 잡음 분산 상수(

) 및 시스템 잡음 분산 상수(

)를 통해 계산될 수 있다. 또한, 복수의 기준 노드들(100) 및 타깃 노드(300)의 물리적 구성 특성과 환경적 요소를 고려하여 시스템 잡음 분산 상수는 0.001로 설정하고, 측정 잡음 분산 상수는 0.4로 설정할 수 있다.
The Kalman gain K in Equation (1) is the previous received signal variance value

), The measurement noise dispersion constant (

) And the system noise variance constant (

). ≪ / RTI > In addition, the system noise variance constant may be set to 0.001 and the measured noise variance constant may be set to 0.4 in consideration of physical configuration characteristics and environmental factors of the plurality of reference nodes 100 and the target node 300. [

), 이전 신호 세기 값(

) 및 수학식 1에서 계산된 K에 기초하여 계산할 수 있다.
The currently estimated signal strength value P in Equation (2) is the measured signal strength value (

), The previous signal strength value (

) And K calculated in Equation (1).

)을 계산할 수 있다. 또한, 실내 측위가 결정된 후 P 및 신호 세기의 분산값

은

및

로 바뀌어 다음 계산 과정에 활용될 수 있다.Equation (3) is based on equations (1) and (2)

) Can be calculated. Further, after the indoor positioning is determined, the P and the variance of the signal intensity

silver

And

And can be used in the next calculation process.

The determination unit 233 can calculate an optimal average signal strength value. For example, the determination unit 233 may calculate the optimal average signal strength value of each of the plurality of reference nodes 100 based on the acquisition time of the filtered signal strength values.

Specifically, the determination unit 233 obtains the filtered signal strength values, and selects signal strength values for calculating the optimum average signal strength value among the filtered signal strength values based on the acquisition time of the filtered signal strength values . That is, the determination unit 233 can select the signal strength values of the specific number that are most recently acquired.

The determining unit 233 may calculate an optimal average signal strength value of the plurality of reference nodes 100 based on the selected signal intensity values.

In order to statistically utilize the filtered signal strength values, a result obtained by averaging the most recently received specific number of packets can be expressed by Equation (4).

The determination unit 233 can perform the primary indoor positioning with respect to the target node 300. [ For example, the determination unit 233 can perform indoor positioning on the target node 300 based on the position information on the plurality of reference nodes 100 and the filtered and averaged signal intensity values. In addition, the indoor positioning for the target node 300 may be the position coordinate with the greatest probability.

는 신호 세기 기댓값일 수 있다.
The maximum likelihood function formula based on the Log-distance Path Loss Model and Equation (4) can be expressed by Equation (5). At this time,

May be an expected signal strength value.

Equation (5) can be expressed as Equation (6) to calculate position coordinates having the greatest probability after applying Equation (5) to all predictable position coordinates.

The determination unit 233 can determine the indoor positioning for the target node 300. [ For example, the determination unit 233 can determine the indoor positioning for the target node 300 when it is determined that the indoor positioning is not the Non-Line Of Sight (NLOS) channel environment. Therefore, when the determination unit 233 determines the indoor positioning for the target node 300, the determination unit 233 can determine the NLOS.

Specifically, after the determination unit 233 performs the indoor positioning of the target node 300, the number of the plurality of reference nodes 100 can be confirmed.

개의 집합으로 구성할 수 있다.In addition, the determination unit 233 may configure the plurality of reference nodes 100 as a plurality of subsets based on the number of the plurality of reference nodes 100. For example, when the plurality of reference nodes 100 are n, the determination unit 233 determines a plurality of sub-

Can be composed of two sets.

The determining unit 233 may calculate the optimal average signal strength value of the plurality of sub-sets based on the optimal average signal strength value of the plurality of reference nodes 100. [ For example, the determination unit 233 may calculate the optimal average signal strength value of the plurality of sub-sets based on the optimal average signal strength value of the plurality of reference nodes 100 using the triangulation method.

In addition, the determination unit 233 can perform secondary indoor positioning with respect to the target node 300. For example, the determination unit 233 can perform indoor positioning on the target node 300 based on positional information for a plurality of subsets and an optimal average signal strength value of a plurality of subsets.

Therefore, the determination unit 233 can determine the maximum likelihood function value based on the primary indoor positioning and the secondary indoor positioning. Also, the determination unit 233 can determine the NLOS error distance based on the secondary indoor positioning.

The determination unit 233 may determine the NLOS based on the maximum likelihood function value and the NLOS error distance, and determine the indoor positioning of the target node 300 according to the NLOS determination result.

For example, the determination unit 233 may determine the indoor positioning of the target node 300 when it is determined that the NLOS is not the NLOS.

As another example, if the determination unit 233 determines that the NLOS is not the NLOS, the determination unit 233 can re-determine the maximum likelihood function value and the NLOS error distance by reconstructing the plurality of subsets until it is determined that the NLOS is not the NLOS. At this time, the decision unit 233 can reconstruct a plurality of subsets with subsets of the maximum likelihood function value.

Accordingly, the determination unit 233 can determine the indoor positioning for the target node 300 based on the recursively determined maximum likelihood function value and the NLOS error distance. Accordingly, the determination unit 233 can determine the NLOS through the recursive approach and avoid the positioning error of the indoor positioning with respect to the target node.

The NLOS error distance for two points that are the farthest from each other among the positional coordinates for the plurality of subsets can be expressed by Equation (7).

는 기준 노드

를 제외한 하위 집합에서 엊은 부분 실내 측위 좌표이다. 또한, D 값이 임계값 이상일 경우 NLOS, 아닐 경우 LOS(Line of Sight)로 판단할 수 있다. 이때, 임계값은 실내 측위 시스템이 구분하고자 하는 측위 거리(Resolution)로서 설정될 수 있다.D in the equation (7) is the NLOS error distance,

The reference node

Is a partial indoor positioning coordinate. If the D value is greater than or equal to the threshold value, it can be determined to be NLOS or LOS (Line of Sight). At this time, the threshold value may be set as a positioning distance that the indoor positioning system desires to distinguish.

The determination unit 233 may transmit the notification of the indoor positioning to the target node 300 when the indoor positioning is determined.

A module in this specification may mean hardware capable of performing the functions and operations according to the respective names described in this specification and may mean computer program codes capable of performing specific functions and operations , Or an electronic recording medium, e.g., a processor or a microprocessor, equipped with computer program code capable of performing certain functions and operations.

In other words, a module may mean a functional and / or structural combination of hardware for carrying out the technical idea of the present invention and / or software for driving the hardware.

3A to 3C show examples illustrating indoor positioning.

3A to 3C, a description will be given taking into consideration a plurality of reference nodes 100, a target node 300, a recognition position, a recognition position radius, an interference, and signal propagation.

Referring to FIG. 3A, when performing indoor positioning in a wireless channel environment in a stable LOS state, the recognized position radius may be narrowly formed by forming a recognition position close to the target node 300.

Referring to FIG. 3B, in FIG. 3B, it is possible to check the variability of unstable signal intensity values in a channel environment receiving external interference from another network. At this time, the recognition position in FIG. 3B may be sporadically formed at a distance from the target node 300 in the indoor positioning. Thus, the recognition position radius can be made wider. In addition, the reason for the variability may be a complex problem such as irregular movement of the user, multipath problem of the signal and interference of other network signals.

Referring to FIG. 3C, the signal strength value may be attenuated by the presence of a direct obstacle on the path of propagation from one reference node to the target node 300. That is, although the recognition position of FIG. 3C is formed within a certain range, the NLOS problem may occur and may be formed away from the target node 300.

Figures 4A and 4B show examples of signal strength values and filtered signal strength values.

Figures 4A and 4B show the filtering results of the signal strength values through the Kalman filter when the target node 300 receives the packet from one reference node. At this time, the target node 300 of FIGS. 4A and 4B switches from the stop state to the moving state with time in about 15 seconds, and the moving direction and the position condition may be the same.

FIG. 4A can show the signal strength value and the filtered signal strength value in a stable LOS channel environment.

FIG. 4B shows the signal strength value and the filtered signal strength value in an unstable channel environment. Therefore. The signal intensity value of FIG. 4B is unstable as compared with FIG. 4A, and may be more unstable when the state of fluctuation is severe. In addition, the reason for the variability in Fig. 4B may be various, such as packet loss, peak noise, and antenna shake.

5A to 5C show examples for determining an average received signal strength value.

In Figures 5a-5c, as soon as the target node 300 moving at a fixed and fixed speed arrives at 2 m, it can receive 30 packets per second from the base node. 5A-5C also show signal strength values and filtered values under a stable LOS channel and unstable channel conditions. 5A to 5C also show statistically utilized packets.

5A shows a case (CASE1) receiving 30 packets per second when the stationary target node 300 is 2 m away from the reference node. The graph 511 represents a signal strength graph, the graph 513 represents a filtered signal strength graph, the graph 515 represents a graph obtained by averaging two packets at the target node 300, A graph of averaging 5 packets in the target node 300 and a graph 519 shows a graph of averaging 30 packets in the target node 300. [ Therefore, when the graph 515, the graph 517, and the graph 519 are considered, the utilization of the packet in the stopped state can utilize the signal strength information of the received packet at the initial reception time.

FIG. 5B shows a case (CASE 2) in which 30 packets per second are received from the reference node when the target node 300 moving at 0.5 m / sec moves for 1 second and arrives at a distance of 2 m. The graph 531 represents a signal strength graph, the graph 533 represents a filtered signal strength graph, the graph 535 represents a graph obtained by averaging two packets at the target node 300, 5A shows a graph obtained by averaging five packets in the target node 300 and a graph 539 shows a graph obtained by averaging 30 packets in the target node 300. FIG. Considering the graph 535, the graph 537 and the graph 539, it may be necessary to utilize the optimum number of packets in the state of moving at 0.5 m / sec.

FIG. 5C shows a case (CASE 3) in which 30 packets per second are received from the reference node when the target node 300 moving at 1.2 m / sec moves for 1 second and arrives at a distance of 2 m. A graph 553 represents a filtered signal strength graph, a graph 555 represents a graph obtained by averaging two packets at the target node 300, A graph of averaging five packets at the target node 300 and a graph 559 showing a graph of averaging 30 packets at the target node 300. [

Considering the graph 555, the graph 557 and the graph 559, it may be necessary to utilize the optimum number of packets in the state of moving at 1.2 m / sec. For example, based on minimizing the variability, the optimal number of packets for Fig. 5C may be five.

In the case of the graph 535 and the graph 555 in which a deficient packet is utilized for indoor positioning, the positioning error may be affected by the variability of the signal intensity, and too many packets necessary for the indoor positioning In the case of the graph 539 and the graph 559, since the signal strength information at the previous time is used, the positioning result may be the same as before, or an error may occur, and the reliability of the positioning result may be low.

6A to 6G show examples of judging NLOS.

6A shows an example of determining NLOS.

6A shows a positioning error due to the NLOS channel at the position 630 and the position 650 during movement of the target nodes 300 in an indoor environment in which 13 reference nodes are arranged on a ceiling of 12 m * 12 m. Specifically, location 630 may receive an NLOS signal from node 13 and position 650 may receive an NLOS signal from nodes 8 and 13.

6B shows another example of determining NLOS.

FIG. 6B shows indoor positioning for the target node 300 at location 610 in FIG. 6A. That is, FIG. 6B shows whether the target node 300 is indoors when it is determined that the target node 300 is not NLOS.

및

로부터 타겟 노드(300)에 대한 실내 측위를 실시할 수 있다(611). 이때,

및

는 기준 노드일 수 있다.For example, the indoor positioning device 200

And

(611) to the target node (300). At this time,

And

May be a reference node.

= {

},

= {

},

= {

} 및

= {

}로 하위 집합들을 형성할 수 있다(613).The indoor positioning device 200

= {

},

= {

},

= {

} And

= {

(613). ≪ / RTI >

The indoor positioning device 200 can perform indoor positioning on the sub-sets (615). Accordingly, the indoor positioning device 200 can generate recognition positions for the sub-sets.

The indoor positioning apparatus 200 can determine the NLOS from the recognition positions (617). At this time, the indoor pseudo device 200 can determine the NLOS based on the NLOS error distance.

The indoor positioning apparatus 200 can determine the indoor position for the target node 100 by determining the position 610 as LOS (619).

Figures 6C and 6D show another example of determining NLOS.

Referring to FIG. 6C, FIG. 6C shows a case where the indoor positioning is determined to be NLOS when determining the indoor positioning for the target node 300 at the position 630.

및

로부터 타깃 노드(300)에 대한 실내 측위를 실시할 수 있다(630-1). 이때,

및

는 기준 노드일 수 있다.For example, the indoor positioning device 200

And

(630-1) from the target node (300). At this time,

And

May be a reference node.

= {

},

= {

},

= {

},

= {

} 및

= {

}로 하위 집합들을 형성할 수 있다(630-2).The indoor positioning device 200

= {

},

= {

},

= {

},

= {

} And

= {

} To form subsets (630-2).

The indoor positioning device 200 may perform indoor positioning on the subset (630-3). Accordingly, the indoor positioning device 200 can generate recognition positions for the sub-sets.

The indoor positioning device 200 can determine the NLOS from the recognition positions (630-4). At this time, the indoor pseudo device 200 can determine the NLOS based on the NLOS error distance.

The indoor positioning apparatus 200 can determine the location 630 as NLOS and perform the first recursive process without determining the indoor positioning of the target node 100 (630-5). At this time, the maximum likelihood function value may be 0.89.

Referring to FIG. 6D, when it is determined from FIG. 6C that NLOS is determined, FIG. 6D shows a process of determining LOS by performing indoor positioning through a first recursive process.

및

로부터 타겟 노드(300)에 대한 1차 재귀적 실내 측위를 실시할 수 있다(630-6). 이때,

및

는 기준 노드일 수 있다. 즉, 실내 측위 장치(200)는 최대 우도 함수값을 가진 하위 집합의 기준 노드들에 기초하여 기준 노드들을 선택할 수 있다.For example, the indoor positioning device 200

And

The first recursive indoor positioning of the target node 300 may be performed (630-6). At this time,

And

May be a reference node. That is, the indoor positioning device 200 can select the reference nodes based on the subset of the reference nodes having the maximum likelihood function value.

= {

},

= {

},

= {

} 및

= {

}로 1차 재귀적 하위 집합들을 형성할 수 있다(630-7).The indoor positioning device 200

= {

},

= {

},

= {

} And

= {

} Can form primary recursive subsets (630-7).

The indoor positioning device 200 may perform the indoor positioning for the first recursive subsets (630-8). Accordingly, the indoor positioning device 200 can generate the first recursive recognition positions for the first recursive subsets.

The indoor positioning device 200 may determine the NLOS from the primary recursive recognition locations (630-9). At this time, the indoor addressable device 200 can determine the NLOS based on the first recursive NLOS error distance and the maximum likelihood function value.

The indoor positioning apparatus 200 may determine the indoor position for the target node 100 by determining the position 630 as the LOS (630-10).

Figures 6E, 6F and 6G show another example of determining NLOS.

Referring to FIG. 6E, FIG. 6E shows a case where indoor positioning is determined to be NLOS when determining indoor positioning for a target node 300 at a location 650. FIG.

및

로부터 타겟 노드(300)에 대한 실내 측위를 실시할 수 있다(650-1). 이때,

및

는 기준 노드일 수 있다.For example, the indoor positioning device 200

And

(650-1) to the target node 300 from the indoor location. At this time,

And

May be a reference node.

= {

},

= {

},

= {

},

= {

},

= {

} 및

= {

}로 하위 집합들을 형성할 수 있다(650-2).The indoor positioning device 200

= {

},

= {

},

= {

},

= {

},

= {

} And

= {

} (650-2). ≪ / RTI >

The indoor positioning apparatus 200 can perform indoor positioning on the subset (650-3). Accordingly, the indoor positioning device 200 can generate recognition positions for the sub-sets.

The indoor positioning apparatus 200 can determine the NLOS from the recognition positions (650-4). At this time, the indoor pseudo device 200 can determine the NLOS based on the NLOS error distance.

The indoor positioning apparatus 200 may determine the location 650 as NLOS and perform the first recursive process without determining the indoor positioning for the target node 100 (650-5). At this time, the maximum likelihood function value may be 0.52.

Referring to FIG. 6F, when it is determined from FIG. 6E that NLOS is determined, FIG. 6F shows a process of performing NLOS by performing indoor positioning through a first recursive process.

및

로부터 타겟 노드(300)에 대한 1차 재귀적 실내 측위를 실시할 수 있다(650-6). 이때,

및

는 기준 노드일 수 있다. 즉, 실내 측위 장치(200)는 최대 우도 함수값을 가진 하위 집합의 기준 노드들에 기초하여 기준 노드들을 선택할 수 있다.For example, the indoor positioning device 200

And

The first recursive indoor positioning of the target node 300 can be performed (650-6). At this time,

And

May be a reference node. That is, the indoor positioning device 200 can select the reference nodes based on the subset of the reference nodes having the maximum likelihood function value.

= {

},

= {

},

= {

},

= {

} 및

= {

}로 1차 재귀적 하위 집합들을 형성할 수 있다(650-7).The indoor positioning device 200

= {

},

= {

},

= {

},

= {

} And

= {

} Can form primary recursive subsets (650-7).

The indoor positioning device 200 may perform the indoor positioning for the first recursive subsets 650-8. Accordingly, the indoor positioning device 200 can generate the first recursive recognition positions for the first recursive subsets.

The indoor positioning device 200 may determine the NLOS from the primary recursive recognition locations (650-9). At this time, the indoor addressable device 200 can determine the NLOS based on the first recursive NLOS error distance and the maximum likelihood function value.

The indoor positioning apparatus 200 may determine the location 650 as NLOS and perform the second recursive process without determining the indoor positioning of the target node 100 (650-10). At this time, the maximum likelihood function value may be 0.86.

Referring to FIG. 6G, if it is determined from FIG. 6F that NLOS is determined, FIG. 6G shows a process of determining LOS by performing indoor positioning through a second recursive process.

및

로부터 타겟 노드(300)에 대한 2차 재귀적 실내 측위를 실시할 수 있다(650-11). 이때,

및

는 기준 노드일 수 있다. 즉, 실내 측위 장치(200)는 최대 우도 함수값을 가진 하위 집합의 기준 노드들에 기초하여 기준 노드들을 선택할 수 있다.For example, the indoor positioning device 200

And

A second recursive indoor positioning can be performed on the target node 300 (650-11). At this time,

And

May be a reference node. That is, the indoor positioning device 200 can select the reference nodes based on the subset of the reference nodes having the maximum likelihood function value.

= {

},

= {

},

= {

} 및

= {

}로 2차 재귀적 하위 집합들을 형성할 수 있다(650-12).The indoor positioning device 200

= {

},

= {

},

= {

} And

= {

} Can form secondary recursive subsets (650-12).

The indoor positioning device 200 may perform the indoor positioning for the second recursive subsets 650-13. Accordingly, the indoor positioning device 200 can generate the second recursive recognition positions for the second recursive subsets.

The indoor positioning device 200 may determine the NLOS from the secondary recursive recognition locations (650-14). At this time, the indoor addressable device 200 can determine the NLOS based on the second recursive NLOS error distance and the maximum likelihood function value.

The indoor positioning device 200 can determine the indoor position for the target node 100 by determining the location 650 as LOS (650-15).

7 is a flowchart illustrating an operation method of an indoor positioning system according to an embodiment.

Referring to FIG. 7, the indoor positioning apparatus 200 may filter and average the signal strengths of the plurality of reference nodes 100 (S710).

The indoor positioning apparatus 200 can perform the first indoor positioning with respect to the target node 300 (S720).

The indoor positioning apparatus 200 can confirm the number of the plurality of reference nodes 100 (S730).

The indoor positioning apparatus 200 may configure a plurality of reference nodes 100 as a plurality of subsets (S740).

The indoor positioning apparatus 200 can perform secondary indoor positioning with respect to the target node 300 (S750).

The indoor positioning apparatus 200 can determine the maximum likelihood function value and the NLOS error distance (S760).

The indoor positioning apparatus 200 can determine the NLOS (S770).

If it is determined that the indoor positioning apparatus 200 is NLOS, a plurality of subsets may be reconfigured (S780).

If it is determined that the indoor positioning apparatus 200 is not the NLOS, the indoor positioning apparatus 200 may determine the indoor positioning for the target node 300 (S790).

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA) , A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, 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 produced 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 devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (12)

Filtering a plurality of signal strength values transmitted at each of a plurality of reference nodes;
Calculating an optimal average signal strength value of the plurality of reference nodes based on the filtered signal strength values; And
Determining an indoor positioning for a target node that has received the plurality of signal strength values based on the position information of the plurality of reference nodes and the optimal average signal strength value of the plurality of reference nodes
Lt; / RTI >
Wherein the calculating step comprises:
Selecting signal strength values for calculating an optimal average signal strength value of the plurality of reference nodes from the filtered signal strength values based on the time of obtaining the filtered signal strength values
And an indoor positioning method.
The method according to claim 1,
Wherein the filtering comprises:
Obtaining at least one of 30 signal strength values per second transmitted at each of the plurality of reference nodes
And an indoor positioning method.
delete The method according to claim 1,
Wherein the determining comprises:
Confirming the number of the plurality of reference nodes;
Configuring the plurality of reference nodes as a plurality of subsets based on the number of the plurality of reference nodes;
Calculating an optimal average signal strength value of the plurality of subsets based on an optimal average signal strength value of the plurality of reference nodes; And
Determining and determining indoor positioning for the plurality of subsets based on location information of the plurality of reference nodes and an optimal average signal strength value of the plurality of subsets
And an indoor positioning method.
5. The method of claim 4,
Wherein the step of confirming the indoor positioning comprises:
Determining a Non Line Of Sight (NLOS) based on a maximum likelihood function value and an NLOS error distance for the plurality of subsets
And an indoor positioning method.
The method according to claim 1,
Wherein the determining comprises:
And notifying the target node of the indoor positioning
And an indoor positioning method.
A filtering unit filtering a plurality of signal strength values transmitted from each of the plurality of reference nodes;
Calculating an optimal average signal strength value of the plurality of reference nodes based on the filtered signal strength values,
Determining a room location for a target node that has received the plurality of signal strength values based on the location information of the plurality of reference nodes and the optimal average signal strength value of the plurality of reference nodes,
Lt; / RTI >
Wherein,
And selects signal strength values for calculating an optimal average signal strength value of the plurality of reference nodes from among the filtered signal strength values based on the acquisition time of the filtered signal strength values.
8. The method of claim 7,
Wherein the filtering unit comprises:
And acquires at least one of 30 signal strength values per second transmitted at each of the plurality of reference nodes.
delete 8. The method of claim 7,
Wherein,
Checking the number of the plurality of reference nodes,
The plurality of reference nodes are configured as a plurality of subsets based on the number of the plurality of reference nodes,
Calculating an optimal average signal strength value of the plurality of sub-sets based on the optimal average signal strength value of the plurality of reference nodes,
And determine and determine indoor positioning for the plurality of subsets based on location information of the plurality of reference nodes and an optimal average signal strength value of the plurality of subsets.
11. The method of claim 10,
Wherein,
And determines NLOS (Non Line Of Sight) based on the maximum likelihood function value and the NLOS error distance for the plurality of subsets.
8. The method of claim 7,
Wherein,
And notifies the target node of the notification of the indoor positioning.

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