KR20090085333A - System and method for estimating the location of a mobile node based on snooping node using a received signal strength indication - Google Patents

Abstract

A system and method for estimating the location of a mobile node based on snooping node using a received signal strength indication are provided to block an unnecessary operation with a coordinator in another indoor space. In the separated indoor space, a location of a mobile node is located based on a correction node(400) with presumption, and a mobile node(200) is determined whether it is moved from a second indoor space to a first indoor space. The mobile node receives a signal from a plurality of fixed nodes(100) and a plurality of data of each fixed node is obtained. A plurality of data of the obtained each fixed node is received from the mobile node. The representative received signal strength of each fixed node is produced by using a plurality of data of each fixed node.

Description

System and method for estimating the location of a mobile node based on snooping node using a Received Signal Strength Indication}

The present invention relates to a system and method for estimating a position of a mobile node based on a calibration node, and more particularly, to a system and method for estimating a position of a mobile node moving to an area separated by a calibration node on a sensor network. will be.

Wireless sensor networks need to operate in a variety of environments, meeting a variety of needs, including reliability, scalability, low cost, deployment environments and transmission media. The network communication method used in IEEE 802.15.4 is a configuration that is based on WPAN and is provided in a form that requires little infrastructure. The Zegbee Alliance defines the network and security layers as well, while the Zigbee Alliance defines specifications to ensure the diversity and complexity of the requirements of each business and service area.

For example, in the field of control of factory production machines and home network appliances, the issue of reliability and location of data is an important part, and these issues are reflected in the standard.

In order to detect the location of a node, techniques such as event detection, location awareness dependent computing, and geographic tracking are required. Although much research has been conducted on reliability and data reliability from the viewpoint of a sensor network, there is a need for a method and a system capable of securing the reliability of a received signal in location recognition.

On the other hand, the position estimation in the sensor network may play the same role as the Global Positioning System (GPS) in the system for position estimation using RF (Radio Frequency). In the sensor network, there is a need for a method of improving the reliability of the extracted value in order to estimate a location using a signal value received by a radio frequency (RF) without a line-of-sight.

The RF signal on the power spectral density and modulation quality (including EVM) of the transmitting node is constant, but the receiving node can obtain the value of the distorted signal due to the effects of multipath, noise, and conductors. Therefore, it is not easy to get the exact position.

In addition, in the sensor network, a small cost is required for each node to install tens to hundreds, thousands, or tens of thousands of nodes, and the battery consumption of each node needs to be reduced as much as possible to simplify maintenance of each node.

In addition, the high-rise building or a large area within the building is divided into a plurality of areas by rooms, offices, areas, etc., and distortion may be increased in transmission and reception of signals by obstacles such as partitions or walls.

Therefore, in the sensor network, there is a need for a position estimation system and method capable of robustly operating on signal distortion while reducing power consumption in order to estimate the position of a mobile node moving within the area range of the sensor network. .

According to an embodiment of the present invention, a position estimation method for estimating the position of a mobile node by activating a coordinator and a fixed node of the corresponding indoor space by introducing a correction node for the position of the mobile node moving on the separated indoor space. And to provide a system.

In addition, it is an object of the present invention to provide a location estimation method and system that can detect the multi-path interference or signal distortion, such as obstacles in the indoor space, and estimate the position of the mobile node in consideration of this.

It is also an object of the present invention to provide a position estimation method and system that can calculate a representative received signal strength from a plurality of pieces of received signal strength fluctuating in real time and increase accuracy in position estimation.

The objects of the present invention are not limited to the above-mentioned objects, and other objects that are not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, a method of estimating a position of a mobile node based on a correction node in a plurality of separate indoor spaces according to an embodiment of the present invention, wherein the mobile node is the first in the second indoor space; Determining whether to move to an indoor space; Receiving a signal from each of a plurality of fixed nodes arranged in the first indoor space when the mobile node moves to a first indoor space to obtain a plurality of data for each fixed node; Receiving from the mobile node a plurality of data for each fixed node obtained; Calculating a representative received signal strength for each fixed node using a plurality of data for each fixed node; And estimating a relative position from each fixed node relative to the mobile node using the representative received signal strength for each fixed node.

In order to achieve the above object, in a system for estimating the position of a mobile node based on a correction node in a plurality of separate indoor spaces according to another embodiment of the present invention, a signal having a constant intensity is transmitted on the first indoor space. One or more fixed nodes; A mobile node that detects a received signal strength (RSSI) transmitted from each fixed node over time to obtain a plurality of data for each fixed node; A correction node positioned in an intermediate region of a second indoor space and the first indoor space to determine whether the mobile node has moved from the second indoor space to the first indoor space; And a coordinator which receives a plurality of data for each fixed node from the mobile node and estimates the location of the mobile node.

According to an embodiment of the present invention as described above, the position of the mobile node moving on the separated indoor space by introducing a correction node to activate the coordinator and the fixed node of the corresponding indoor space to estimate the position of the mobile node by different Unnecessary operation of the coordinator and the fixed node located in the indoor space can be prevented.

In addition, by estimating the position of the mobile node in consideration of multipath interference or signal distortion, such as an obstacle in an indoor space, it is possible to increase the accuracy of the position estimation of the mobile node.

In addition, by calculating a representative received signal strength from a plurality of data of the received signal strength fluctuating in real time and performing position estimation, the accuracy of the position estimation of the mobile node can be improved.

The effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

Specific details of other embodiments are included in the detailed description and the drawings. Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various different forms, and only the embodiments make the disclosure of the present invention complete, and the general knowledge in the art to which the present invention belongs. It is provided to fully inform the person having the scope of the invention, which is defined only by the scope of the claims. Like reference numerals refer to like elements throughout.

FIG. 1A illustrates the operation of a fixed node and a mobile node in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention, and FIG. 1B measures received signal strengths according to distances indoors and outdoors. An example is shown.

Referring to FIG. 1A, the fixed node 100 may be fixedly positioned at a predetermined position. The fixed node 100 transmits a signal having a constant strength. The fixed node 100 may include any device or sensor node capable of transmitting a radio frequency (RF).

The mobile node 200 may receive a signal transmitted by the fixed node 100. The mobile node 200 may move its position in real time and may be attached to a user's body or attached to various devices. The mobile node 200 may receive the RF signal and detect the strength of the RF signal. The strength of the detected signal may be referred to as a received signal strength (RSSI).

As such, the fixed node 100 and / or the mobile node 200 may be referred to as a sensor node, and a network formed by the plurality of sensor nodes may be referred to as a sensor network. The fixed node 100, the mobile node 200, etc. in one embodiment of the present invention may transmit and receive RF signals, and thus may serve as sources and receivers.

Referring to FIG. 1B, as shown in FIG. 1A, the mobile node 200 receives a signal transmitted from the fixed node 100 while the mobile node 200 moves and detects the received signal strength RSSI.

The received signal strength detected by the mobile node 200 may be lowered with distance. As the average value of the received signal of about 15 seconds at one point is measured, it can be seen that the reduction in the strength of the received signal in the outdoor is increased as the distance increases. In this case, the received received signal strength (RSSI) value is expressed as a quantized integer from 0 to 255, and the closer to the source, the closer to 255. However, the scale is only one example and may have various scale values by the user or the system.

FIG. 1C illustrates a variation in received signal strength with distance from a room, and FIG. 1D illustrates variation in received signal strength with a distance from an outdoor location.

1C and 1D, the variation in the received signal strength received indoors is relatively greater than the variation in the signal strength received outdoors. This is because the received signal strength received indoors may be less stable than the signal strength received outdoors. Therefore, when the location estimation is performed using the signal strength received indoors, the error may be less than that of the outdoor location estimation. Can be large.

Taken as a whole, the deviation may gradually increase as the distance increases. As this deviation increases, the received signal strength may decrease with a constant trend. The form of the reduction is irregular, and the deviation of the received signal strength in the room is greater than the deviation of the received signal strength in the outdoors. If the deviation is small, a large error does not occur even when the average of the received signal strength is converted to the distance. However, if the deviation is large, the error may be large when the average of the received signal strength is changed.

As such, it can be seen that the deviation of the received signal strength in the room is relatively large in the standard deviation of the received signal strength in the outdoor. Since the variation of the received signal strength is larger in the indoor than in the outdoor, the location of the mobile node 200 cannot be reliably estimated using the received received signal strength indoors. Accordingly, there is a need for a system and method capable of reliably estimating the position of the mobile node 200 by sensing the received signal strength not only outdoors but also indoors.

2A and 2B show examples of classifying communication areas by clusters in a general coordinator-based sensor network. 3A, 3B, and 3C illustrate an example of performing communication between a mobile node and a coordinator in a communication area in a general coordinator-based sensor network.

2A and 2B, each coordinator 301; 302 has each cluster area 10; 20. Here, the cluster region is an independent region capable of estimating the position of the mobile node 200 by one coordinator, and may estimate the position of the mobile node 200 in each cluster region 10 (20).

The cluster regions may be separated from each other as shown in FIG. 2A, or the cluster regions of the cluster regions may overlap each other as shown in FIG. 2B.

3A illustrates an example in which the mobile node 200 communicates between the mobile node 200 and each coordinator 300 (301) when the mobile node 200 moves from the first cluster area 10 to the second cluster area 20 in a general cluster area. Shows.

In general, the coordinator and the mobile node 200 may communicate in a time-division manner to prevent collision or crosstalk. For example, when the mobile node 200 is in the first cluster region 10, the mobile node 200 may communicate with the first coordinator 300 in the first cluster region by dividing time. The first coordinator 300 is inactive when the mobile node 200 transmits and receives data, and the mobile node 200 is resting when the first coordinator 300 transmits and receives data. Meanwhile, in data transmission and reception, beacons may be transmitted together. Beacons indicate the existence of a sensor network and are frames that play a role in maintaining the network. The beacon may be periodically transmitted and received for channel state detection, parameter correspondence, network recognition, etc. in order for the mobile node 200 and / or coordinator 300; 301 to work correctly in the sensor network.

When the mobile node 200 moves from the first cluster region 10 to the second cluster region 20 as shown in FIG. 1, the first coordinator 300 moves the mobile node 200 to the first cluster region 10. The system server (not shown) that enters the sleep mode and determines that the mobile node 200 has moved to the second cluster area 20 or is wired or wirelessly connected to the coordinator. The mobile node 200 receives the movement of the mobile node 200 to start the operation.

The mobile node 200 moves to the second cluster area 20 to coordinate scheduling and / or scheduling beacons between the second coordinator 301 and the mobile node 200 at the start of operation of the second coordinator 301. In a state in which scheduling adjustment for the operation of the mobile node is not made, operations of the mobile node 200 and the second coordinator 301 may collide with each other.

3B illustrates an example in which the mobile node 200 communicates between the mobile node 200 and each coordinator 300 (301) when the mobile node 200 moves from the first cluster area 10 to the second cluster area 20 as shown in FIG. 2B. Shows.

In general, when the cluster regions 10 and 20 overlap each other between the coordinators 300 and 301, the coordinators 300 and 301 may communicate with each other by wire or wirelessly. Therefore, even if the mobile node 200 moves from the overlapping area to another cluster area, the location of the mobile node 200 can be estimated without collision by adjusting the operations of the coordinators 300 and 301 through the scheduler.

Meanwhile, even in the case of FIG. 3B, under the situation of FIG. 2B, communication between the first coordinator 300 and the mobile node 200 is suddenly transferred to the cluster area of the second coordinator 301 only in the absence or overlapping area of the scheduler. When the mobile node 200 moves, a collision may occur between the second coordinator 301 and the mobile node 200. This is because the second coordinator 301 does not belong to the first cluster region 10 of the first coordinator 300, so that scheduler adjustment between the first coordinator 300 and the second coordinator 301 is not performed. Accordingly, when the mobile node 200 moves to the second cluster area 20, scheduler adjustment is not performed between the second coordinator 301 and the mobile node 200, and thus a collision may occur in data transmission and reception.

 3C shows an example of performing channel initialization for collision prevention. Referring to FIG. 3, when the mobile node 200 moves out of the first cluster area 10 of the first coordinator 300 to the second cluster area 20, the second coordinator 301 and the mobile node 200 are moved. Channels can be initialized first in order to prevent collisions in data transmission and reception. The channel initialization may perform a reconnection process in which the mobile node 200 sets up a channel in the new cluster region with respect to the movement to the new cluster region.

During a predetermined time interval of the reconnection process, the position estimation and / or data transmission and reception of the mobile node 200 moved to another cluster area is not possible. Therefore, in a state in which the mobile node 200 continuously moves, the position trajectory of the mobile node 200 cannot be tracked for a predetermined time interval, and the mobile node substantially undergoes channel setup during the reconnection process. The transmission / reception sampling of data required for the position estimation of 200 may be reduced, thereby reducing the reliability of the data.

Therefore, in one embodiment of the present invention, discontinuity and system performance deterioration in estimation of the position of the mobile node 200 due to collision or initialization setup that may occur when the mobile node 200 moves out of a predetermined cluster area to another cluster area. In order to reduce this, a snooping node may be introduced. Due to the introduction of the correction node, when the mobile node 200 frequently moves to each cluster area on the plurality of cluster areas, position estimation of the mobile node 200 can be continuously performed, and time delay due to channel initialization can be reduced. Can be.

4A and 4B schematically illustrate a cluster region in which a correction node is introduced in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention.

Referring to FIG. 4A, in the case where the correction node 400 is introduced in an intermediate region deviating from the first cluster region 10 and the second cluster region 20, the first coordinator 300 and the first coordinator 300 and the first coordinator 300 may be formed. The area where the second coordinator 301 cannot cover can be reduced. Therefore, even before the mobile node 200 moves out of the first cluster region 10 to the second cluster region 20, the movement of the mobile node 200 may be tracked using the correction node 400.

Referring to FIG. 4B, in the region where the first cluster region 10 and the second cluster region 20 overlap, the correction node 400 moves from the first coordinator 300 or the second coordinator 301 to the mobile node 200. By receiving the position information or the movement trajectory information of, the mobile node 200 can perform the position estimation of the mobile node 200 immediately when moving to another cluster area.

As described above, the position estimation of the mobile node 200 by continuously transmitting and receiving data without a channel initialization process while preventing the mobile node 200 and the coordinator 300 (301) from coming in by introducing the correction node 400. can do.

5 illustrates a communication process of a correction node, a coordinator, and a mobile node for estimating the position of the mobile node in the position estimation system of the mobile node based on the correction node according to an embodiment of the present invention. In FIG. 5, the mobile node 200 moves from the first cluster region 10 to the second cluster region 20 of FIGS. 4A and 4B.

When the mobile node 200 is located in the first cluster area 10, the correction node 400, the first coordinator 300, and the mobile node 200 may transmit and receive data through time-divided channels, respectively. At this time, the second coordinator 301 located in the second cluster area 20 is in a sleep mode and is simply in a state of receiving data. Meanwhile, a channel to be time-divided for a relatively short time is also allocated to the correction node 400 so that the mobile node 200 is located near or near the boundary between the first cluster region 10 and the second cluster region 20. It may be detected whether the proximity to the correction node 400 is located.

When the mobile node 200 moves from the first cluster area 10 to the second cluster area 20, the correction node 400 detects whether the mobile node 200 enters the second cluster area 20. When entering the second cluster area 20, the location information and the channel information of the mobile node 200 in the first cluster area 10 may be transmitted to the second coordinator 301 by wire or wirelessly. Accordingly, data may be transmitted and received at different times through time-division channels sequentially allocated to the mobile node 200, the second coordinator 301, and the correction node 400 respectively moved to the second cluster area 200. Can be.

As described above, even when the mobile node 200 moves out of the cluster area managed by the existing coordinator 300 to another cluster area by introducing the correction node 400 as in the embodiment of the present invention, the initialization node 400 is not initialized. The position of the mobile node may be estimated continuously, and the time-division region may be continuously allocated in advance by the correction node 400 to prevent collisions in data transmission and reception between each component.

Meanwhile, in the following description of an embodiment of the present invention, the cluster regions 10 and 20 may be referred to as separate indoor spaces in the room, and each coordinator may be referred to as the mobile node 200 in each separate indoor space. The location can be estimated.

6A is a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention, and FIG. 6B illustrates an operation of a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention. Show the situation.

6A and 6B, the position estimation system of a mobile node based on a correction node according to an embodiment of the present invention includes a fixed node 100, a mobile node 200, a correction node 400, and a coordinator ( 300).

The fixed node 100 is one or more fixed nodes 110 (120; 130) as sensor nodes that are spaced at regular intervals or randomly spaced apart. The fixed node 100 may transmit a signal of a constant intensity to the mobile node 200, the correction node 400, or the coordinator 300 to serve as a `` x ''. In addition, the fixed node 100 may transmit information to the mobile node 200, the correction node 400, or the coordinator 300.

The fixed node 100 may be located in each of a plurality of indoor spaces. For example, as shown in FIG. 6B, a room, a corridor, and a room may be divided into a first indoor space, a second indoor space, and a third indoor space, respectively. Each indoor space may include one or more fixed nodes (110; 120; 130; 140). In an embodiment of the present invention, a set of fixed nodes 100 used to estimate the position of the mobile node 200 may vary according to the indoor space where the mobile node 200 is located. Therefore, in a situation where the position of the mobile node 200 is moved in real time, the indoor space in which the mobile node 200 is located is determined to activate only the fixed node 100 in the corresponding indoor space, and the other fixed node is in a human state. You can leave it in (Sleep mode). For example, when the mobile node 200 is located in the second indoor space, the fifth fixed node F ₅ , the sixth fixed node F ₆ , the seventh fixed node F ₇ , and the eighth fixed node. F ₈ may be activated and used to estimate the position of the mobile node 200. When the mobile node 200 moves to the first indoor space, the first fixed node (F ₁ ; 110), the second fixed node (F ₂ ; 120), the third fixed node (F ₃ ; 130), and the fourth The fixed node F ₄ 140 may be activated and used for position estimation of the mobile node 200. Therefore, when the space in which the mobile node 200 moves is changed, unnecessary fixed nodes are left in the human state and only necessary fixed nodes are activated to efficiently use the entire system, and unnecessary power consumption can be reduced.

The mobile node 200 is a sensor node whose position can be moved. The mobile node 200 obtains a received signal strength indication (RSSI) by sensing the strength of the signal transmitted from the fixed node 100. The mobile node 200 senses the strength of the signal transmitted from each of the fixed nodes 110; 120; 130; 140 disposed around the mobile node 100, and thus receives a plurality of received signal strengths for the fixed nodes. (RSSI) can be obtained. The mobile node 200 continuously detects the strength of the signal from each fixed node 100 over time, and transmits a plurality of received signal strength data acquired over time to the coordinator 300.

On the other hand, the mobile node 200 may change the position in the plurality of separate indoor space. For example, the mobile node 200 may move from the second indoor space of the living room to the first indoor space of the room. Alternatively, the second indoor space may move from the second indoor space to the third indoor space. As such, in an embodiment of the present invention, the location of the mobile node may be determined for each indoor space, and the location of the mobile node 200 may be estimated as a relative position at each fixed node in the corresponding indoor space.

As shown in FIG. 6B, the fixed node 100 is composed of one or more (110, 120, 130, 140), the mobile node 200 is the strength of the signal from each fixed node (110; 120; 130; 140) Receive continuous signal strength over time. Here, the received signal strength data, which is the strength of the signal transmitted from each fixed node by the mobile node 200, is a plurality of data continuously detected according to time, and the 'data' or 'received' mentioned in one embodiment of the present invention. Signal strength data 'refers to the value of the received signal strength as the strength of the attenuated signal detected by the mobile node 200 for the signal transmitted from the fixed node 100. In addition, a signal transmitted for each fixed node 100 is converted into 'data' or 'received signal strength data' detected by the mobile node 200, 'data for each fixed node' or 'received signal for each fixed node. Intensity data '.

The correction node 400 is located in the middle region of the plurality of separated indoor spaces, and determines whether the mobile node 200 moves on the indoor space. For example, when the mobile node 200 moves from the second indoor space to the first indoor space, whether the mobile node 200 moves to the first indoor space in an intermediate region between the first indoor space and the second indoor space. Determine whether or not.

The correction node 400 detects the received signal strength of the signal transmitted from the mobile node 200 so that the mobile node 200 detects the distance from the correction node 400. Meanwhile, the correction node 400 may obtain the position information or the movement trajectory information at the previous time of the mobile node 200 from the coordinator 300. Therefore, the correction node 400 is a mobile node 200 by using the received signal strength of the signal received from the mobile node 200 and the position information or the movement trajectory information of the mobile node 200 transmitted from the coordinator 300. Whether it is moved to another indoor space or to the indoor space can be determined. For example, when the mobile node 200 moves from the second indoor space to the first indoor space, the correction node 400 receives the received signal strength from the mobile node 200 and the previous time from the second coordinator 301. It is possible to determine whether to move to the first indoor space of the mobile node 200 by using the location information of the mobile node 200 in.

The correction node 400 transfers the movement information of the mobile node 200 to the coordinator 300 when the mobile node 200 moves to the indoor space of the new area. At this time, the correction node 400 transmits the movement information of the mobile node 200 to the coordinator for estimating the position of the mobile node 200 in the indoor space where the mobile node 200 has moved. Therefore, the correction node 400 receives the received signal strength detected by the mobile node 200 and previous position information of the mobile node 200 from the coordinator in the previous indoor space to determine whether the mobile node 200 is moved. . When the correction node 400 determines that the mobile node 200 has moved to the new indoor space, the correction node 400 transmits the movement information of the mobile node 200 to a new coordinator in charge of the new indoor space.

The coordinator 300 estimates a relative position of the mobile node 200 by using a plurality of received signal strength data for each fixed node transmitted from the mobile node 200. Here, the relative position is a relative position of the mobile node 200 from each fixed node (110; 120; 130; 140), and if the position of each fixed node (110; 120; 130; 140) is known, the mobile node The position of 200 may be estimated. The positions of each fixed node (110; 120; 130; 140) and the correction node 400 are predefined positions so that the coordinator 300 may provide absolute positions of each fixed node and correction node.

The coordinator 300 converts the plurality of received signal strength data detected by the mobile node 200 into the representative received signal strength for each fixed node 110; 120; 130; 140, and uses the same to determine the representative received signal strength of the mobile node 200. The relative position can be estimated. A representative received signal strength for each fixed node (110; 120; 130; 140) will be referred to as a representative received signal strength for each fixed node, and the representative representative received signal strength for each fixed node is fixed by the mobile node (200). One representative value calculated for position estimation among the plurality of received signal strength data detected by the node 100.

The coordinator 300 may include a population generator 310, a representative value calculator 320, and a position estimator 330.

The population generator 310 uses the plurality of received signal strength data of each fixed node 110; 120; 130; 140 received from the mobile node 200, respectively. Create a confidence population for. The population generator 310 first receives received signal strength data of each fixed node 110 (120; 130; 140) detected by the mobile node 200 from the mobile node 200 according to time. Receive a plurality of data for 110; 120; 130; 140. The population generator 310 calculates a moving average value for each fixed node (110; 120; 130; 140) from the plurality of received data, and uses each of the fixed nodes (110; 120) by using the calculated moving average distribution. 130; 140 creates a confidence population. Here, the confidence population for each fixed node is substantially valid in the data set of the plurality of received signal strengths for each fixed node (110; 120; 130; 140) detected by the mobile node 200 and transmitted to the coordinator. A group of data that is judged. Since the confidence population for each fixed node is extracted from the data of the received signal strength received by the mobile node 200 from each fixed node 100, the number of trust populations may be generated as many as the number of the fixed nodes 100.

The method of calculating the moving average by the population generator 330 is as follows. The mobile node 200 sequentially detects the received signal strength from a predetermined fixed node 100 over time, and the mobile node 200 sequentially transmits the received signal strength to the coordinator 300. The average received signal strength is obtained by sequentially setting the signal strength data transmitted in a predetermined number or at a predetermined time unit, and the average received signal strength is obtained by sequentially shifting the first data of the data set one by one. For example, if a plurality of data that is received signal strength data is {v ₀ , v ₁ , v ₂ , v ₃ , v ₄ , v ₅ , v ₆ , v ₇ , v ₈ , v ₉ }, each of three If we want to find one average reception strength, we can compare {(v ₀ + v ₁ + v ₂ ) / 3, (v ₁ + v ₂ + v ₃ ) / 3, (v ₂ + v ₃ + v ₄ ) / 3, ( v ₃ + v ₄ + v ₅ ) / 3, (v ₄ + v ₅ + v ₆ ) / 3, (v ₅ + v ₆ + v ₇ ) / 3, (v ₆ + v ₇ + v ₉ ) / 3 , (v ₇ + v ₈ + v ₉ ) / 3} can be obtained. As such, a value obtained by shifting an average of a data set including a certain number of data according to time or sequentially according to data is referred to as a moving average.

The representative value calculator 320 calculates a representative received signal strength for each fixed node by using the generated confidence population for each fixed node. Here, the representative received signal strength refers to one value that the mobile node 200 detects a plurality of received signal strengths from each fixed node and is extracted based on the data of the plurality of received signal strengths. The representative received signal strength can be calculated by the number of each fixed node, and thus each is referred to as a representative received signal strength for each fixed node.

The representative value calculator 320 calculates a representative received signal strength of each fixed node from the confidence population of each fixed node. For example, the representative value calculator 320 first selects a predetermined trust population and extracts one piece of data arbitrarily from the selected trust population. The distance between one extracted data and all other data in the confidence population is averaged. When the obtained average value is less than or equal to the threshold value, the sum of the selected value and the average value may be calculated as the representative received signal strength. In addition, the method for generating the representative received signal strength in the confidence population may be a method for obtaining the average of the corresponding population, such as the average value, the weighted average, etc., the representative received signal by a person of ordinary skill in the art Various ways of selecting the strength are possible.

The position estimator 340 estimates the relative position of the mobile node 200 from each fixed node 100 using the estimated representative signal strength for each fixed node. The position estimator 340 may estimate a relative position from each fixed node by using the representative received signal strength of the received signal strength of each fixed node. Also, the position estimator may determine the position from each fixed node more precisely by weighting a representative received signal strength with respect to the received signal strength of each fixed node.

As described above, according to an embodiment of the present invention, the coordinator 300 and the fixed node 110 of the corresponding indoor space are introduced by introducing the correction node 400 to the position of the mobile node 200 moving on the separated indoor space. By activating the 120; 130; 140 to estimate the position of the mobile node, unnecessary operation of the coordinator and the fixed node located in the other indoor space can be prevented.

In addition, it is possible to relatively accurately estimate the position of the mobile node 200 by securing a reliable population through the moving average. In addition, by introducing a kind of k-means algorithm, the representative received signal strength in the confidence population can be accurately calculated with a small amount of computation, thereby increasing the efficiency in position estimation.

7A shows a distribution of a population obtained by a moving average for 5 seconds according to an embodiment of the present invention, and FIG. 7B shows a population obtained by a moving average for 15 seconds according to an embodiment of the present invention. Shows the distribution of.

The moving average is a value obtained by sequentially shifting an average of a data set including a certain number of data over time. For example, while the mobile node 200 receives signals sequentially from a predetermined j-th fixed node 100 in time, 100 received signal strengths (v _{0 , j} , v _{1 , j} , v _{2 , j} , ..., v _{99 , j} ). When 10 is the number of intervals in the data set, the moving average may be calculated as in the following equation.

Where v _{i , j} is the received signal strength at which the signal transmitted from the j-th fixed node 100 is detected at the i-th time step, s _{i , j} represents the moving average, and the subscript is sequentially calculated Received from the order of the moving average and j-th fixed node. As described above, the moving average is a value obtained by averaging a certain number of data sets for a predetermined time, and a single moving average value can be obtained as a whole even though a somewhat unstable reception signal strength is detected for a predetermined time.

In addition, since the moving average value is quantized and displayed as an integer of 0 to 255 steps, the obtained moving average value may overlap. As described above, a plurality of moving average values may be obtained based on the plurality of received signal strengths detected over time, and the obtained plurality of moving average values may be represented by the number of times of overlapping, similar to a normal distribution as illustrated in FIG. 7A or 7B. The distribution of moving average values can be obtained.

Using the obtained distribution of the moving average values, a confidence population, which is a reliable data group, may be extracted from the plurality of received signal strength data. For example, when the distribution of moving average values is the same as that of FIG. 7A or 7B, the data set of the received signal strength in the region where the magnitude of the moving average differs by 'h' around the maximum value is trusted. Can be extracted as a population. Alternatively, a data set of received signal strength located in a region belonging to a predetermined confidence range based on the average value in the distribution of the moving average may be extracted as a confidence population. For example, in the range of 60% confidence range, a statistical region in which 60% of data may be located based on the mean value in the distribution of the moving average may be extracted, and a confidence population may be extracted therefrom.

On the other hand, as the number of received signal strengths detected as time increases, the number of moving average values also increases, so that the coordinator 300 may take a load on processing of the plurality of received signal strength data. In addition, when the mobile node 200 moves, the plurality of received signal strength data previously detected may not be necessary to estimate the current position of the mobile node 200. Accordingly, moving average values may be calculated using a received signal strength up to a certain time before the current time point, and a confidence population may be generated, and the time reference may be set by a user or by an experimental result or per unit time. The number of times of data reception may be determined.

8 is a flowchart illustrating a k-means algorithm applied in a system for estimating a position of a mobile node based on a correction node according to an embodiment of the present invention.

Referring to FIG. 8, first, a confidence population for the 1-th fixed node is selected (S700). A confidence population for each fixed node can be generated by the signals received from each fixed node. Thus, generating a representative received signal strength for each confidence population is by the k-means algorithm, where 'k' is the number of fixed nodes.

In the selected confidence population, predetermined received signal strength data is selected (S710). One receive signal strength data is randomly selected from the confidence population. For example, the confidence population for the j-th fixed node 100 may be defined as follows. As described above, the group which extracts the days belonging to the confidence range region through the moving average among the plurality of data received from the j-th fixed node 100 becomes the confidence population for the j-th fixed node 100.

를 선택했다고 가정한다. Where arbitrarily receive signal strength

Assume that is selected.

When one received signal strength is selected, an average value of distances between the selected received signal strength and all other received signal strengths of the confidence population is obtained (S720). The distance average value is an average value of Euclidean distance between the selected received signal strength and the remaining received signal strength, and can be expressed by the following equation.

Where Eu _j is the average value of Euclidean distance for the j-th node. Therefore, Eu _j may have a large distance mean value when the selected received signal strength is located near the edge of the remaining confidence population, and may be low when located at the center of the confidence population.

After calculating the distance average value, it is determined whether the calculated distance average value is equal to or less than a threshold value (S730). The threshold is the maximum allowable value of the average deviation of the representative received signal strength in the confidence population, and may be set to an experimental or theoretical value considering the magnitude, number, or error range of the received signal strength. Therefore, the threshold is preferably set to a deviation value such that the calculated distance average value can guarantee the representativeness of the confidence population.

If the calculated distance average value is less than or equal to the threshold value, the selected received signal strength and the calculated distance average value are added together to calculate the representative received signal strength for the j-th fixed node (S740). If the calculated distance average value is greater than or equal to the threshold value, another predetermined received signal strength may be selected from the confidence population, and the above-described process may be repeated and calculated as the representative received signal strength for the j-th fixed node (S710, S720, S730). ).

If the representative received signal strength for the j-th fixed node is calculated, it is checked whether the representative received signal strength of the confidence population for all fixed nodes is calculated (S750). If not calculated, the process can be repeated by selecting a trust population of the next fixed node (S760, S710, S720, S730).

As described above, in one embodiment of the present invention, by introducing the k-means algorithm to calculate the representative value in the confidence population, a relatively accurate estimation value can be calculated with a small amount of computation in calculating the representative received signal strength. In addition, by generating a confidence population based on a moving average and extracting a representative value from the generated population, a good representative value can be obtained robustly even for unstable data. Therefore, by extracting the reliable population by the moving average, the reliable data is first extracted, and the representative received signal strength is calculated by the k-means method, so that the accuracy of estimating the representative received signal strength can be relatively increased.

9 shows a schematic diagram of a position estimation of a mobile node in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention.

The position estimator 330 of the coordinator 300 may calculate the position of the mobile node 200 using the representative received signal strength of the surrounding fixed nodes 110 (120; 130). Here, the position of the mobile node 200 is a relative position from the position of the known fixed nodes 110 (120; 130) around.

For example, n fixed nodes 110 (120; 130) are located around the mobile node 200, and n represents a representative received signal strength of received signal strengths for the n fixed nodes. For each r _i , the position of the mobile node can be obtained by the following equation.

Where n is the number of surrounding fixed nodes 100, A is the maximum value of signal strength that can be received from the fixed node, and r _i Is the representative received signal strength estimated from the plurality of received signal strength data detected from the i-th fixed node obtained in accordance with one embodiment of the present invention.

On the other hand, while applying Equation 4, an error may occur due to a deviation in a transmission distance and a space of a signal from each fixed node 100. Therefore, in estimating the distance based on the (Ar _i ) value of Equation 4, the following equation may be introduced.

Κ is a constant determined by the fixed node 100 and the system of the present invention, and β denotes a distance index. Therefore, in one embodiment of the present invention, the distance index (real number 1 or more) may be calculated as the received signal strength decreases with distance according to an experimental or theoretical value.

For example, when the distance from the fixed node 100 is within 5m, the distance index β may be between 1.0 and 1.5, and when the distance is 5m or more, the distance index may be between 1.5 and 2.0. Alternatively, if the distance from the fixed node is within 10m by experimental repetition, the distance index may be designated as a variable range of value from 1.4 to 1.6. The increase in the distance index means that the distance between the fixed node 100 and the mobile node 200 increases, so that the reception signal strength decreases relatively.

In addition, given a value of (Ar _i ), the distance from the i-th fixed node may be known through reference data. The reference data is data in which a received signal strength (RSSI) corresponding to a predetermined distance is predefined, and compared with the representative received signal strength for the i-th fixed node.

Therefore, by substituting Equation 5 into Equation 4 and substituting Equation 5 into the value of (Ar _i ), the error caused by the deviation of the transmission distance and the space can be corrected. This may be interpreted as having the same effect as giving weights (W _i ) to (Ar _i ) values of Equation 4, respectively.

As described above, the position of the mobile node 200 can be easily obtained from the plurality of received signal strength data sensed by the surrounding fixed node 100.

10A is a schematic diagram of detecting signal distortion detection by a correction node in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention. Referring to FIG. 10A, the correction node 400 detects a received signal strength, which is the strength of a received signal, from each of the fixed nodes 110; 120; 130; 140 located in a separate indoor space. The absolute position of the calibration node 400 and each fixed node 110; 120; 130; 140 is given from the coordinator 300 or the position coordinates are set when each node 110; 120; 130; 140; 400 is installed. Can be mounted in a given state.

Accordingly, the correction node 400 senses the received signal strength for each fixed node from each of the fixed nodes 110; 120; 130; 140, so that the correction node 400 and each of the fixed nodes 110; 120; 130; 140 may sense the distance from the devices. Given the positions of the correction node and each fixed node, the absolute distance between the correction node 400 and each fixed node can be known, and the correction node 400 detects the received signal strength from each fixed node to detect each fixed node. Known sensed distances from 110; 120; 130; 140 are known.

Correction node 400 is representative of the received signal strength from each fixed node (110; 120; 130; 140) r _i; In this case, the distance index in Equation 5 may be calculated by comparing the sensed winding distances from the respective fixed nodes and the absolute distances of the fixed nodes. Thus, by using the representative received signal strength r _i for each fixed node, a distance index for each fixed node can be calculated, and the distance index can correct for signal distortion in space. By applying Equation 5 applying the calculated distance index to each fixed node to Equation 4, it is possible to efficiently correct signal distortion due to obstacles or multiple paths in the indoor space in estimating the position of the mobile node 200. have.

10B is a schematic diagram of detecting a spatial movement of a mobile node by a correction node in a position estimation system of the mobile node based on the correction node according to an embodiment of the present invention. Referring to FIG. 10B, the correction node 400 determines whether the mobile node 200 moves on the separated indoor space, and receives the received signal strength detected from the mobile node 200 and the mobile node 200 received from the previous coordinator 301. Can be determined using the position information or the movement trajectory of the "

For example, a case in which the mobile node 200 moves from the second indoor space to the first indoor space will be described. First, when the mobile node 200 moves in the second indoor space, the previous coordinator 301 estimates the position of the mobile node 200. The mobile node 200 located in the second indoor space senses the received signal strength from each of the fixed nodes 150; 160; 170; 180 activated in the second indoor space, and then detects the detected representative received signal strength from the previous coordinator. Send to 301. The previous coordinator 301 may estimate the location of the mobile node 200 using the information transmitted from the mobile node 200.

Meanwhile, the mobile node 200 may move from the second indoor space to the first indoor space. At this time, the correction node 400 may be located between the space separating the first indoor space and the second indoor space, and the correction node 400 senses the received signal strength transmitted from the mobile node 200. The correction node 400 is located in the middle area of the separated space and moves across the area of the indoor space of the mobile node 200. The correction node 400 increases and decreases the received signal strength transmitted from the mobile node 200. Can be determined through Also, the correction node 400 may obtain position information of the mobile node 200 from the previous coordinator 301. The correction node 400 utilizes the movement trajectory of the mobile node 200 from the previous coordinator 301 and the received signal strength of the transmitted signal from the mobile node 200 to allow the mobile node 200 to generate the second indoor space. 1 Can accurately determine moving to the indoor space.

When the mobile node 200 moves across the separated indoor space, the correction node 400 may transmit the movement information to the new coordinator 300. When the new coordinator 300 receives movement information indicating that the mobile node 200 has moved to the first indoor space from the correction node 400, each of the fixed nodes 110; 120; 130; 140 is located in the first indoor space. Send alarm message in sleep mode. Each fixed node (110; 120; 130; 140) receives an alarm message, switches from a human state to a wake up mode, and starts operation.

In this way, by introducing the correction node 400, the movement information of the mobile node 200 moving across the separated indoor space is grasped and transmitted to the coordinator 300 to induce individual operation of each separated indoor space. can do. Therefore, while preventing unnecessary operation of the fixed node in the indoor space, by operating the fixed node and the coordinator of the indoor space in which the mobile node 200 is located can reduce the power consumption to ensure long-term operation.

11 is a flowchart illustrating a method for estimating a location of a mobile node using received signal strength according to an embodiment of the present invention. Referring to FIG. 11, first, it is determined whether the mobile node 200 moves from the second indoor space to the first indoor space (S700). This is because the correction node 400 detects the received signal strength of the signal transmitted from the mobile node 200 and uses the position information or the movement trajectory of the mobile node 200 received from the previous coordinator 301. Movement information as to whether or not it has moved across the other indoor space of 200 can be obtained.

If it is determined that the mobile node 200 has moved to the first indoor space, the correction node 400 transmits the movement information to the coordinator 300 of the first indoor space. The coordinator 300 of the first indoor space wakes up by sending an alarm message to one or more fixed nodes 110; 120; 130; 140 that are disposed in the first indoor space in a sleep mode. .

One or more fixed nodes (110; 120; 130; 140) receiving the alarm message continuously transmit a signal to the mobile node 200 with a constant intensity. The mobile node 200 detects the received signal strength of the signal transmitted from each fixed node over time to obtain a plurality of data for each fixed node (S710). The mobile node 200 transmits the obtained data to the coordinator 300 in real time.

Meanwhile, the correction node 400 may detect the received signal strength of the signal transmitted from each of the fixed nodes 110; 120; 130; 140 and correct the distance error according to the signal distortion in the first indoor space. . In the state where the distance between the correction node 400 and each of the fixed nodes is already known, the distance index of Equation 5 is calculated by comparing the estimated distance using the detected received signal strength and reflected in Equation 4. can do.

The coordinator 300 calculates a representative received signal strength for a plurality of data obtained from each fixed node while acquiring a plurality of data for each fixed node from the mobile node 200 (S720). The representative received signal strength is calculated by obtaining a plurality of moving average values from a plurality of data for each fixed node, extracting a confidence population using the obtained distribution of the moving average values, and then extracting one representative received signal strength from the extracted confidence population. By obtaining the representative signal strength for each fixed node can be calculated.

Meanwhile, a detailed method of calculating the representative received signal strength is as follows.

(1) A plurality of moving average values for each fixed node are obtained from the plurality of data for each fixed node. The moving average is an average obtained by averaging a data set made up of a certain number of data or data for a predetermined time period and shifting the data one by one to make a small change in the data set.

(2) When a plurality of moving average values for each fixed node are obtained, a confidence population for received signal strength data received from each fixed node is extracted using the obtained distribution of the moving average values. By displaying the obtained plurality of moving average values in frequency, a distribution similar to the normal distribution can be obtained. Therefore, by extracting the data located at a constant distance from the center of the distribution average of the moving average, the data located at the area recognized as a trusted area by the statistics of the normal distribution, or the data located at a constant distance from the position having the maximum frequency, etc. Populations are available. Here, the data refers to the data of the received signal strength detected by the mobile node 200.

(3) When the confidence population for each fixed node is obtained, the representative received signal strength of the received signal strength received from each fixed node 100 is calculated. Here, the representative received signal strength refers to a value optimized by the mobile node 200 among the received signal strength values of the signal transmitted from the fixed node. Accordingly, one representative value is calculated from each fixed node 100, which is referred to as a representative received signal strength for each fixed node.

For example, a method of extracting one representative value extracts predetermined data from the extracted confidence population, and when a mean value of the distance between the predetermined data and other data belonging to the confidence population is less than or equal to a threshold value, the predetermined data value. The sum of the mean values of and distances can be calculated as a representative value.

Finally, when one representative received signal strength is calculated from each fixed node 110; 120; 130; 140, the representative received signal strength for each fixed node 110; 120; 130; 140 is moved. The relative position of the node 200 may be estimated (S730). Here, the relative position of the mobile node 200 refers to a position that is relatively determined from the known position of the fixed node 100. On the other hand, since the absolute position of each fixed node (110; 120; 130; 140) is already known, the absolute position of the mobile node 200 can also be estimated.

On the other hand, when the mobile node 200 leaves the first indoor space, it transmits a message to each fixed node (110; 120; 130; 140) to convert to a human state (S740). Accordingly, each of the fixed nodes 110; 120; 130; 140 disposed in the first indoor space may be converted into a sleep mode to reduce power consumption.

As described above, according to an embodiment of the present invention, it is possible to reliably estimate the position of the mobile node moving across spaces separated from the indoor space. In addition, the fixed nodes disposed in the separated space are placed in the human state and the operating state according to the position of the mobile node, thereby efficiently using power to ensure long-term operation. In addition, by correcting signal distortion caused by obstacles such as furniture or partitions located in the indoor space, it is possible to increase the accuracy of the position estimation of the mobile node in the indoor space.

Although embodiments of the present invention have been described above with reference to the accompanying drawings, those skilled in the art to which the present invention pertains have various permutations, modifications, and modifications without departing from the spirit or essential features of the present invention. It is to be understood that modifications may be made and other embodiments may be embodied. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

1A is a diagram illustrating an example of measuring received signal strength according to a distance according to an embodiment of the present invention.

1B is a diagram illustrating magnitude values according to distances of received signal strengths according to an embodiment of the present invention.

FIG. 1C is a diagram illustrating variation of received signal strength according to distance in a room.

FIG. 1D is a diagram illustrating a variation in received signal strength according to a distance outdoors.

2A and 2B are diagrams illustrating an example of classifying communication areas by clusters in a general coordinator-based sensor network.

3A, 3B, and 3C illustrate examples of performing communication between a mobile node and a coordinator in a communication area in a general coordinator-based sensor network.

4A and 4B are diagrams schematically illustrating a cluster region in which a correction node is introduced in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention.

FIG. 5 is a diagram illustrating a communication process of a correction node, a coordinator, and a mobile node for estimating the position of the mobile node in the position estimation system of the mobile node based on the correction node according to an embodiment of the present invention.

6A is a block diagram of a location estimation system of a mobile node using received signal strength according to an embodiment of the present invention.

6B is a diagram illustrating a space in which a system for estimating a location of a mobile node using received signal strength according to an embodiment of the present invention is operated.

FIG. 7A illustrates a distribution of a population obtained by a moving average for 5 seconds according to an embodiment of the present invention. FIG.

7B is a diagram showing a distribution of a population obtained by a moving average for 15 seconds according to an embodiment of the present invention.

8 is a flowchart illustrating a k-means algorithm applied to a location estimation system of a mobile node using received signal strength according to an embodiment of the present invention.

9 is a schematic diagram of position estimation in a location estimation system of a mobile node using received signal strength according to an embodiment of the present invention.

10A is a schematic diagram of detecting signal distortion detected by a correction node in a position estimation system of a mobile node based on a correction node according to an embodiment of the present invention.

10B is a schematic diagram of detecting spatial movement of a mobile node by a correction node in a position estimation system of the mobile node based on the correction node according to an embodiment of the present invention.

11 is a flowchart of a method for estimating a location of a mobile node using received signal strength according to an embodiment of the present invention.

* Description of the main parts of the drawings *

10, 20: cluster zone

100: fixed node

200: mobile node

300, 301: Coordinator

310: population generation unit 320: representative value calculation unit

330: location estimation unit

400: correction node

Claims (10)

A method of estimating the position of a mobile node based on a correction node in a plurality of separated indoor spaces, Determining whether the mobile node moves from a second indoor space to a first indoor space; Receiving a signal from each of the plurality of fixed nodes arranged in the first indoor space when the mobile node moves to the first indoor space to obtain a plurality of data for each fixed node; Receiving from the mobile node a plurality of data for each fixed node obtained; Calculating a representative received signal strength for each fixed node using a plurality of data for each fixed node; And Estimating a relative position from each fixed node relative to the mobile node using a representative received signal strength for each fixed node. The method of claim 1, further comprising: determining whether to move to the first indoor space. If the mobile node is determined to have moved to the first indoor space, further comprising waking up the plurality of fixed nodes disposed in the first indoor space; Way. The method of claim 1, wherein the determining of the movement A correction node, based on the correction node, for determining whether the mobile node has moved to the first indoor space using the received signal strength of the signal transmitted from the mobile node and the position information of the mobile node in a previous coordinator. Method for estimating the position of a mobile node. The method of claim 1, wherein calculating the representative received signal strength Obtaining a plurality of moving average values for each fixed node with respect to the plurality of data for each fixed node; Extracting a confidence population for each fixed node using a plurality of moving average values for each fixed node; And Calculating a representative received signal strength for each fixed node using a k-means algorithm in the confidence population for each fixed node. The method of claim 1, wherein estimating relative positions from each fixed node comprises: Receiving, by the correction node, a plurality of pieces of data obtained by receiving signals transmitted from each of the plurality of fixed nodes from the correction node, and detecting signal distortion in the first indoor space; Estimating a relative position from each fixed node by converting the sensed signal distortion into a distance index. The method of claim 1, And transmitting a sleep message to each of the plurality of fixed nodes when the mobile node leaves the first indoor space. A system for estimating a position of a mobile node based on a correction node in a plurality of separated indoor spaces, At least one fixed node for transmitting a signal of a constant intensity on the first indoor space; A mobile node that detects a received signal strength (RSSI) transmitted from each fixed node over time to obtain a plurality of data for each fixed node; A correction node positioned in an intermediate region of a second indoor space and the first indoor space to determine whether the mobile node has moved from the second indoor space to the first indoor space; And And a coordinator for receiving a plurality of data for each fixed node from the mobile node and estimating the position of the mobile node. 8. The method of claim 7, wherein the correction node is And a correction node for detecting signal distortion in the first indoor space using received signal strength of signals transmitted from the one or more fixed nodes. The method of claim 7, wherein the coordinator is And estimating the relative position from each fixed node by converting the sensed signal distortion into a distance index. The method of claim 7, wherein the coordinator is A population generation unit configured to generate a confidence population for each fixed node by calculating a plurality of moving average values for each fixed node from the plurality of data for each fixed node; A representative value calculator configured to calculate a representative received signal strength for a fixed node representing a plurality of data to each fixed node by using the generated confidence population for each fixed node; And And a position estimator for estimating a relative position from each fixed node using the calculated representative received signal strength for each fixed node.

Images