KR101213397B1 - Method for estimating the location of the node in sensor network - Google Patents

Abstract

The present invention relates to a method for enabling a position measurement for a specific node in a sensor network using an RF (Radio Frequency) signal, and in particular, a link quality indication (LQI) of an RF signal received at a specific node is a key axis of the position measurement. It is about how a specific node itself can measure its own location by using it as information.
The position measuring method disclosed in the present specification comprises the steps of: (a) requesting the provision of the related information to a neighboring node that holds the position related information by a position measurement target node (specific node) in the sensor network; (b) the neighboring node providing the related information to the specific node; And (c) directly measuring the position of the specific node based on the received related information and the actual strength of the radio frequency (RF) signal received from the neighboring node. .

Description

Method for estimating the location of the node in sensor network}

The present invention relates to a method for measuring a position of a specific node in a sensor network (SN), and more particularly, to a method for enabling position measurement for a specific node using a radio frequency (RF) signal. In particular, the present invention relates to a method for enabling a specific node to measure its own location by using LQI (Link Quality Indication) of an RF signal received at a specific node as key information for location measurement.

Recently, various services based on location measurement (hereafter referred to as 'location awareness') are being implemented, followed by wireless sensor networks for logistics automation, security, industrial automation and control, building automation, robotics, It is expected that applications of location-aware technologies will spread to a variety of areas, including child protection, soldier positioning in combat, rescue of firefighters isolated or missing during evolution, and medical care.

On the other hand, the sensor network (SN) is connected to the network in real time by the sensor node (sensor node) equipped with a sensor that can detect the recognition information about the object or the surrounding environment information to the network in real time By managing the, to give the computing and communication functions to all things to implement an environment that can be anytime anywhere (anytime anywhere) communication. In particular, in response to the current situation in which mobile computing environments are becoming more active, the utilization of SN is on the rise. In addition, the service range based on location awareness of sensor nodes is expected to increase exponentially in consideration of the situation that the application is widely applied recently and the utilization of SN is increasing.

Most of the current location recognition is done using the Global Positioning System (GPS) .In this case, the location recognition (location measurement) object is located in an area (shading area) where satellite propagation is not reached, such as underground or inside a building. There is a problem that location measurement itself is impossible, and the cost of building an infrastructure is very expensive.

On the other hand, the ubiquitous computing environment is increasing recently. As the sensor network can be implemented at low cost in realizing such a ubiquitous computing environment, it is expected to play a very important role in the construction of the ubiquitous computing environment. Sensor nodes forming a sensor network transmit and receive data by using RF signals.In order to meet the general trend of ubiquitous computing environment, sensor nodes use RF signals rather than GPS to measure the position of specific nodes in the sensor network. Therefore, a plan that can be effectively implemented is needed.

The present invention was developed to meet the above needs, and the problem to be solved by the present invention is to enable the position measurement for a particular node by using a radio frequency (RF) signal in a (ubiquitous) sensor network, in particular a specific node By using the LQI of the RF signal received in the position information as the axis information of the position measurement is proposed a method that enables a specific node itself to measure its own position.

In order to solve the above problems, the position measuring method disclosed in the present specification is

(a) requesting to provide the relevant information to a neighboring node that holds the location related information by a location measurement target node (specific node) in the sensor network; (b) the neighboring node providing the related information to the specific node; And (c) directly measuring the position of the specific node based on the received related information and the strength of a radio frequency (RF) signal received from the neighboring node.

At this time, the strength of the RF signal is preferably LQI (Link Quality Indication) to solve the problem of the present invention.

The present invention measures the position of a specific node by using an RF signal and LQI, and allows a specific node to measure its own position and gives reliability to the measured position by itself. In a sensor network that can dramatically improve reliability and provide superior cost and time in the construction and operation of a location-aware system and can be operated at low power, it is possible to use RF signals without additional modules for position measurement. It can greatly contribute to the expansion of services that use measurement.

1 is a view showing an example of the relationship information between the LQI and the distance.
FIG. 2 is an example of a graph presented to explain one method of calculating the relationship between LQI and distance and the reliability of LQI level.
3 is a diagram showing an example of a sensor network to which the present invention is applied.
4 is a view showing the flow of the present invention.
5 is a diagram showing an example of a data format of position measurement related information LI.
FIG. 6 is a diagram illustrating an example of information collected from a neighboring RN or SRN by a specific node for measuring its location.
FIG. 7 is a diagram illustrating an example of elements necessary for measuring a location of a specific node when receiving two response messages.
8 to 16 are

Prior to the description of the concrete contents for carrying out the present invention, for the sake of understanding, an outline of a solution to the problem to be solved by the present invention is firstly presented.

The location measurement method using GPS is recognized as a very reliable method because the accuracy of the measurement result is guaranteed. However, in the case of shaded area, it is impossible to implement the location measurement method using GPS, and even if the area of the satellite wave is reached, the construction cost and time of the system for location measurement are very high. It is an obstacle to the activation of all services.

Accordingly, the present invention provides an alternative method to overcome the above-mentioned problem of the location measuring method using GPS, enabling the measurement of the location of a specific node by using a radio frequency (RF) signal in a sensor network, and in particular, receiving at a specific node. By using the LQI of the RF signal that is used as the base information of the position measurement, it proposes a method for enabling a specific node to measure its own position.

That is, the present invention measures the position of a specific node using the RF signal and LQI, so that a specific node can measure its own position. The measurement of the position of a particular node is not done by 'passive' measurement by other nodes, but by 'active' measurement of a specific node itself. To this end, a specific node is provided with base information (location measurement related information) for measuring its location from a neighboring reference node (Reference Node: RN, which will be described in detail later), and the received location measurement related information. The position of the person is measured by comparing with the predetermined information (described in detail below) that he has.

The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention are shown. In the following description, It is to be noted that the same reference numerals are given to the drawings and that elements of other drawings can be cited when necessary in the description of the drawings. In the following description, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

In the case of measuring the position of a specific node by using the RF signal in the sensor network, a module for communication (RF signal transmission / reception module) does not need to be provided with a separate module (eg, an ultrasonic wave or an infrared ray) for position measurement. The position can be measured as it is. In this case, position measurement may be performed using Link Quality Indication (LQI), which is an indicator indicating the strength of an RF signal received by a specific node. The LQI corresponds to an average of Received Signal Strength Indication (RSSI). In the present invention, in determining the distance between a reference node and a specific node (in measuring the position of a specific node), it is used as key axis information.

On the other hand, existing and current general methods for measuring the position of a specific node using an RF signal indicate that the strength of the RF signal and the distance between the reference node and the specific node (hereinafter, abbreviated as 'distance') satisfy a certain equation. It is based on the fact. That is, the position of a specific node is measured by finding an equation that defines the specific relationship, assuming that 'LQI and distance have a specific relationship'. However, it is very difficult to find an equation that defines the specific relationship, because the RF signal strength (LQI) may have various values even under the same conditions depending on the external environmental factors and the type of antenna. Because of the lack of accuracy of the location results, the distance between the LQI and the LQI is not really tied to any particular relationship. In other words, the relationship between LQI and distance is unspecified (uncertain), which is the greatest weakness of existing or current location measurement methods using RF signals when compared to the location measurement method using GPS, which may undermine the nature of location measurement. It acts as a point.

However, in a sensor network that is superior in terms of cost and time and low power operation, measuring position using RF signals without additional modules for position measurement has sufficient potential in terms of expanding the overall service utilizing position measurement. have. In order to achieve this potential, it is ultimately necessary to minimize the uncertainty relationship (lack of accuracy or reliability) between LQI and distance.

To this end, the present invention builds the relationship information (hereinafter referred to as 'relation information') between the LQI and the distance as an adaptive relationship according to a multivariate environment through several actual measurement or simulations, rather than a specific relationship as before. In addition, the reliability of the measured position value is increased by giving reliability to the constructed relationship information. The reliability of relational information increases as the number of actual simulations (simulations) increases, and the results of the simulations (simulations) for obtaining relational information vary depending on the environment, and in particular, depending on the location (environmental site (ES)) where the simulation is performed. . Therefore, the measurement (simulation) for as many places and as many times as possible can improve the reliability of the relationship information.

The relationship information obtained according to the above-described measurement (simulation) is implemented in all types of nodes mentioned below. An example of the implemented relationship information is shown in FIG. This information is used as the basis for measuring the location of specific nodes in the sensor network. Referring to the various information presented in Figure 1 as follows.

The LQI Level refers to a level assigned to each segment by dividing the range of the strength that the LQI can have into segments. The number of levels increases, indicating that the strength of the RF signal is weak. LQI _min is the minimum LQI value of the corresponding LQI Level, and LQI _max is The maximum LQI value of the LQI Level, D _min is the minimum value of the distance at the LQI Level, D _max is the maximum value of the distance at the LQI Level, and D _aver is The mean value of the distance at the corresponding LQI level (= [D _max + D _min ] / 2). Error is the range of error (distance) that can occur at that LQI Level. Error = D _max -D _aver . C is the reliability of the above-mentioned various information related to the LQI Level and the LQI Level.

Here, the reliability C can be obtained as follows, for example (see FIG. 2).

LQI is an indicator indicating the strength of a received signal and has a characteristic of decreasing as the distance increases. Therefore, the LQI Level is specified by partitioning a distance and specifying a range of LQI (expressed in bytes) that is allowed for each partitioned distance unit. After all, the LQI Level is given by considering the strength and distance of the received signal at the same time. 1 and 2 show Level 1, Level 2, and Level 3 as examples of LQI Levels specified by these criteria, and each Level is divided into rectangles. Of course, these compartments are not necessarily rectangular.

The basis for obtaining the reliability (C) is the number of received signal components outside the range of LQI that can be taken (allowed) by the corresponding LQI level in each partitioned distance unit, and the LQI allowed by that LQI Level. The number of received signal components within the range of, but beyond the distance that the LQI Level can take, and the more received signal components, the lower the reliability of the LQI level and the reliability of various information related to the LQI level. Can be.

Referring to the example of obtaining the reliability based on the graph shown in FIG. 2 and the reliability-related matters described above, the reliability of LQI level 1 (Level 1) is the area corresponding to OA 1, OA 2, OA 3 compared to the square area of level 1 The ratio of the area excluding. The received signal corresponding to OA 1 is in the range of distances that LQI Level 1 can have (allowed), but its strength (its LQI) is greater than the minimum LQI strength (80 bytes) of LQI Level 1 (Level 1). Since it is small, it cannot be seen as LQI of LQI level 1, and the received signal corresponding to OA 2 and OA 3 has its strength (its LQI) greater than the minimum LQI of LQI level 1, but LQI level 1 It is beyond the range of distance it can have and cannot be seen as a level 1 LQI.

This is true for other LQI levels. Therefore, the reliability of LQI Level 2 is the ratio of the area of Leve1 2 to the areas excluding OA 2, OA 3, OA 4, OA 5, and the reliability of LQI Level 3 is Level 3 The ratio of the area to the area excluding the areas corresponding to OA 4 and OA 5.

An ES (Environmental Site) is a place where the above-mentioned actual measurement (simulation) is performed, and finally, an environment in which nodes are actually located. For example, Type 1 (indoor), Type 2 (cave), Type 3 (outdoor-grass), Type 4 (outdoor-parking, frequent obstacles), Type 5 (unknown space),. It may be variously specified. According to the present example, the reliability C for each LQI level according to ES is smaller as the number of types of ES is smaller.

On the other hand, according to the existing position measurement method, a specific node is provided with a calculated value of its own position value and the measured position value error from a satellite or a reference node. In consideration of the current communication environment, the position value and its error range and the reliability thereof are calculated. According to the conventional method, even though the measured position value is out of the error range, it cannot be corrected (but the measured position value can be used as it is), but the present invention calculates a specific node even if the measured position value is out of the error. This means that the reliability can be provided to an application or user (hereinafter referred to as 'user side') that utilizes the measured position information to obtain an opportunity to correct it (the user side decides whether or not to use the measured position value as it is). Can be).

FIG. 3 is a diagram illustrating an example of a sensor network SN in which a location measuring method of a specific node is implemented according to the present invention.

A Reference Node (RN) is a node that already holds (establishes) Location Information (LI), including its location, and that is capable of providing it to other nodes. In the sense of the sensor network, it can be regarded as a node corresponding to a coordinator node. The Second Reference Node (SRN) is a node that can receive its LI from the RN, measure its location, build its own LI, and provide its own LI to other nodes. SRN is equivalent to RN in that it can provide its LI to other nodes.

KN (Known Node) receives the LI provided by RN or SRN to measure its location, and UN (Unknown Node) requests LI from neighboring RN or SRN to view the node as its desired node. A node corresponding to a specific node to which a position measuring method according to the present invention is applied, N (Node) is a node (an node that is not related to position measuring) that is driven by an application different from the current position measuring system. Therefore, it means a node that can be a specific node (UN). That is, RN or SRN is a node that can provide the information (LI) necessary to measure the position of a specific node (UN).

Based on the several facts mentioned above, it will be described in detail how the position measurement for a particular node (UN) is made by the present invention.

4 to 7 are diagrams for explaining the implementation process of the present invention.

The specific node (UN) requests neighboring RNs and SRNs to provide the LIs they have (Location Information-Request: LI-REQ, S41). RN and SRN receiving LI's request to build LI based on LQI Level and information related to LQI Level as shown in FIG. 1 possessed by LI, and send response message reflecting LI to specific node (UN) (Location Information-Reply: LI-REP, S42).

Detailed description of the above-mentioned position measurement information (LI) is as follows.

Position measurement related information (LI) is implemented based on the relationship information between the LQI and the distance shown in Figure 1, in the case of a specific node (UN) receives a response message from the RN or SRN to measure their own location only LI's position is changed to KN.

5 is a diagram showing an example of a data format of LI.

LI is information that the RN, SRN, or specific node (UN) has or will have. In the case of an RN, it is already (or already) equipped; or in the case of an SRN, a specific node (UN) is Based on the response message, you will be able to measure your own location and have it ready.

ID is the ID of the RN or SRN sending the response message.

CN is a type of node. For example, CN 1 (node that already has accurate location information, RN corresponds to this), CN 2 (node that measured its location by information of two CN 1 nodes. CN 3 (node whose location is measured by information of one CN 1 node and one CN 2 node or whose location is measured by information of two CN 2 nodes, KN corresponds to this), CN 4 (A node that does not know its location may be classified as a specific node.)

(X, Y) means the position of the node in the XY-plane when the zone forming one sensor network SN is viewed in the XY-plane, and the origin of the XY-plane, that is, (0, 0) is For example, it can be one of RNs.

C _{(X, Y)} is the reliability of (X, Y). In the case of CN 1 node, the reliability of position value itself (90 [%] ~ 100 [%]), and in the case of CN 2 node, reliability of position value itself Or the minimum of the reliability of the position value itself, 1/2 of the minimum value of the reliability of the position value itself in the case of CN 3 node, and 0 [%] in the case of the CN 4 node.

Error _{(X, Y)} represents an error of (X, Y). This value may be provided in advance or obtained by calculation. In the case of calculation, it can be obtained as described above based on the information shown in FIG. 1 and the example shown in FIG. 2.

C _error is the reliability of Error _{(X, Y)} . In the case of CN 1 node _, the reliability of Error _{(X, Y)} itself (90 [%] ~ 100 [%]), in the case of CN 2 node, is the reliability of the error itself or the minimum of the error itself. 1/2 of the minimum of the reliability of the error itself, and 0 [%] for CN 4 nodes.

ES is the actual site environment where the node is located and is the same as the ES shown in FIG.

The specific node (UN) collects a response message (which reflects LI) transmitted by the RN and the SRN and measures its position by comparing the response message with the relationship information held by the specific node (S43). An example of response messages collected by a specific node (UN) is shown in FIG. 6. The information about each information is the same as the case shown in FIG. 5, and the LQI _rec is the actual LQI of the signal received at the specific node (UN) from the RN or SRN transmitting the response message collected by the specific node (UN).

The specific node (UN) measures its position is specifically as follows.

<Case 1>: When a specific node does not receive a response message

In this case, no response message has been collected from the neighboring RN or SRN (meaning that none of the neighboring nodes of the UN correspond to the RN and SRN). In this case, the neighboring nodes (RN and SRN) Ask the LI to provide LI again.

<Case 2>: When a specific node receives only one response message

In this case, a specific node (UN) collects only one piece of positioning information (LI) from the neighboring RN or SRN, LQI _rec is the RN or SRN of the RN or SRN transmitted a response message collected by the specific node (UN) Actual LQI, (X, Y) is the position of RN or SRN, and C _{(X, Y)} is the reliability of (X, Y).

Error _{(X, Y)} uses LQI _rec to indicate the corresponding D _max , in the relationship information between LQI-distances (UN) of a particular node (UN). Find and obtain D _aver . Error _{(X, Y)} = D _max -D _aver .

C and the _error ES is also used by the LQI _rec is obtained by finding the closest LQI Level C and the _error in the ES that LQI- distance between related information (Fig. 1) to the LQI _rec.

<Case 3>: When a specific node receives two response messages

In this case, two location measurement-related information (LI) is collected from a neighboring RN or SRN, the location measurement of a specific node (UN) in this case can be made as follows, for example.

FIG. 7 is a view showing elements necessary for measuring the position of a specific node (UN) in the case of <Case 3>.

The two circle groups each represent an aspect of the transmission range of the RF signal from the RN or SRN that sent the response message to a particular node (UN). In this case, the combination of the original group may be an RN-RN combination, an RN-SRN combination, or a SRN-SRN combination.

First, A and B are the positions of the RN or SRN that sent the response message, and the radius of the small circle (SR _A , SR _B ) and the radius of the large circle (LR _A , LR _B ) are the LQIs of the node that sent the response message. It is determined by D _min and D _max included in the distance relationship information (FIG. 1), respectively, and circles SC _A and LC _A and circles SC _B and LC _B have various positional relationships to be described below.

Hereinafter, the position (X _E , Y _E ), C of a specific node (UN) according to various positional relations between the circles (SC _A , LC _A ) and the circles (SC _B , LC _B ) in the case of <Case 3> Explains how to calculate _{(X, Y)} , Error _{(X, Y),} and C _error . With reference to the table shown in Figures 8 to 16 below the positional relationship corresponding to [1] to [4] below, the position of the specific node and related information (error range, reliability, etc.) are calculated. The calculation (calculation) formulas for the various types of information shown in FIGS. 8 to 16 below are stored in advance in a specific node (UN), and FIGS. 8 to 16 are presented as separate tables for convenience and are not separate tables. Say.

[1] The sun in the transmission range is a pair of large and small circles (case [1]). That is, SC _A and LC _B.

The positional relationship of the circle in case [1] is summarized as follows.

a) LR _B + SR _A <d: Circle LC _B and circle SC _A are separated (no intersection).

b) LR _B + SR _A = d: Circle LC _B and circle SC _A are circumscribed (one point of intersection).

c) LR _B -SR _A <d <LR _B + SR _A : Circle LC _B and circle SC _A intersect at two points.

d) LR _B -SR _A = d: Circle SC _A is inscribed to circle LC _B (one point of intersection).

e) LR _B -SR _A > d: original LC _B contains SC _A inside (no intersection).

f) SR _A -LR _B = d: Circle LC _B is inscribed to circle SC _A (one point of intersection).

g) SR _A -LR _B > d: Circle SC _A contains circle LC _B inside (no intersection).

h) d = 0: Circle LC _B and circle SC _A are concentric circles.

[2] The sun in the transmission range is a pair of large circles and large circles (case [2]). That is, LC _A and LC _B.

The positional relationship of the circle in case [2] is summarized as follows.

a) LR _A + LR _B <d: Circle LC _B and Circle LC _A are separated (no intersection).

b) LR _A + LR _B = d: Circle LC _B and circle LC _A are circumscribed (one point of intersection).

c) LR _A -LR _B <d <LR _A + LR _B : Circle LC _B and circle LC _A intersect at two points.

d) LR _A -LR _B = d: Circle LC _B is inscribed to circle LC _A (intersection is one point).

e) LR _A -LR _B > d: original LC _A contains original LC _B inside (no intersection).

f) LR _B -LR _A = d: Circle LC _A is inscribed to circle LC _B (one point of intersection).

g) LR _B -LR _A > d: original LC _B contains original LC _A inside (no intersection).

h) d = 0: Circle LC _B and Circle LC _A are concentric circles.

[3] The sun in the transmission range is a pair of large and small circles (case [3]). That is, LC _A and SC _B.

The positional relationship of the circle in case [3] is summarized as follows.

a) LR _A + SR _B <d: Circle LC _A and circle SC _B are separated (no intersection).

b) LR _A + SR _B = d: Circle LC _A and circle SC _B are circumscribed (one point of intersection).

c) LR _A -SR _B <d <LR _A + SR _B : Circle LC _A and circle SC _B intersect at two points.

d) LR _A -SR _B = d: Circle SC _B is inscribed to circle LC _A (with one point of intersection).

e) LR _A -SR _B > d: Circle SC _B is included inside circle LC _A (no intersection).

f) SR _B -LR _A = d: Circle LC _A inscribed to circle SC _B (one point of intersection).

g) SR _B -LR _A > d: The original LC _A is included inside the original SC _B (no intersection).

h) d = 0: Circle LC _A Circle and circle SC _B are concentric circles.

[4] The sun in the transmission range is a pair of small circles and small circles (case [4]). That is, SC _A and SC _B.

The positional relationship of the circle in case [4] is summarized as follows.

a) SR _A + SR _B <d: Circle SC _B and circle SC _A are separated (no intersection).

b) SR _A + SR _B = d: Circle SC _B and circle SC _A are circumscribed (one point of intersection).

c) SR _A -SR _B <d <SR _A + SR _B : Circle SC _B and circle SC _A intersect (two points of intersection).

d) SR _A -SR _B = d: Circle SC _B and circle SC _A are inscribed (one point of intersection).

e) SR _A -SR _B > d: circle SC _B is contained inside circle SC _A (no intersection).

f) SR _B -SR _A = d: Circle SC _B and circle SC _A are inscribed (one point of intersection).

g) SR _B -SR _A > d: circle SC _B contains circle SC _A inside (no intersection).

h) d = 0: Circle SC _B and circle SC _A are concentric circles.

According to the positional relationship of the circles shown in [1] to [4], a specific node (UN) may have information shown in FIG. 1 which it possesses, various information included in two response messages transmitted from RN or SRN, and FIG. 8. To their own position based on the table shown in FIG. 16.

<Case 4>: When a specific node receives three or more response messages

In this case, at least three location information LIs are collected from neighboring RNs or SRNs. In this case, the location measurement of a specific node (UN) may be performed as follows. Among them, specific LI information is selected (priority of LI information) to measure position, and the selection may be performed as follows, for example.

First, select a node with a low CN number among nodes that provide LI information.

Second, select a node with a low ES type number of LI information.

Third, select a high LQI _rec value of LI information.

Fourth, the C _{(X, Y)} of LI information is selected in the order of high reliability of reference position.

Fifth, it is selected that Error _{(X, Y)} of LI information is small and C _error is high (in order of small error range and high reliability of error).

If the results of the selection based on the above five criteria are all the same, any LI information may be selected. By selecting two pieces of LI information with high priority, the location of a specific node (UN) is measured in the same way as in <Case 3>.

The method of the present invention can also be embodied as computer readable code on a computer readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and also implemented in the form of a carrier wave (for example, transmission over a wired or wireless network) . The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.

The present invention has been described above with reference to preferred embodiments thereof. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

Claims (7)

(a) requesting to provide the relevant information to a neighboring node that holds the location related information by a location measurement target node (specific node) in the sensor network;
(b) the neighboring node providing the related information to the specific node; And
(c) the specific node directly measuring its position based on the received related information and the actual strength of a radio frequency (RF) signal received from the neighboring node;
The relevant information
And at least one of a position value of the neighbor node, a reliability of the position value, an error of the position value, a reliability of the error, and an environment in which the neighbor node is located. . The method of claim 1, wherein the specific node is
It divides the range of the strength of the RF signal received by the user into segments and holds the relationship between the intensity level and the distance giving the level to each segment, and provides the related information and the actual intensity of the RF signal. The method of measuring the position of a specific node in the sensor network, characterized in that for measuring its position by contrast with the relationship information.
Herein, the distance means a distance between the specific node and the neighboring node. delete The method of claim 2,
The relationship information is built up in the specific node through a plurality of measurements (simulation),
The intensity level, the maximum and minimum of the intensity at the intensity level, the maximum and minimum of the distance at the intensity level, the average of the maximum and minimum of the distance, and the error of the distance that may occur at the intensity level. And a reliability of the corresponding intensity level. The method of claim 4, wherein the reliability of the corresponding intensity level is
A sensor network which is out of the maximum and minimum values of the intensity at the corresponding intensity level and is determined according to how many RF signal components exist having the intensity at the corresponding intensity level but outside the maximum and minimum values of the distance. How to measure the position of a specific node in the. 6. The method of claim 1, 2, 4 or 5, wherein the strength of the RF signal is
Link Quality Indication (LQI) characterized in that the location measurement method of a specific node in the sensor network. A computer-readable recording medium having recorded thereon a program for executing the method of claim 6 on a computer.

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