TWI411806B - A method of positioning a rfid tag using spatial mesh algorithm - Google Patents

A method of positioning a rfid tag using spatial mesh algorithm Download PDF

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Publication number
TWI411806B
TWI411806B TW99102400A TW99102400A TWI411806B TW I411806 B TWI411806 B TW I411806B TW 99102400 A TW99102400 A TW 99102400A TW 99102400 A TW99102400 A TW 99102400A TW I411806 B TWI411806 B TW I411806B
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Taiwan
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antennas
error
grid
grids
distance
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TW99102400A
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Chinese (zh)
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TW201126194A (en
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Chien Ho Ko
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Univ Nat Pingtung Sci & Tech
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Abstract

A method of positioning a RFID tag using spatial mesh algorithm is disclosed. Radio Frequency Identification (RFID) readers are arranged in a space having a RFID tag therein to be positioned. To position the RFID tag, the space is then divided into a plurality of rectangular spatial boxes. Calculating each distance between a center of rectangular spatial box and each RFID reader is followed to obtain a set of distances for each RFID reader. The differences between the set of distances by calculation for each reader and the distance by measurement are compared and analyzed to find a set of rectangular spatial boxes having minimum differences for each reader. By comparing the set of rectangular spatial boxes having minimum differences for each reader, the position of the RFID tag is determined.

Description

RFID tag positioning calculation method

The invention relates to a radio frequency identification (RFID) tag, in particular to an algorithm for RFID tag positioning.

In the 21st century, wireless communication technology is widely used in daily life, which brings us great convenience. In addition to communication, wireless technology can be used for positioning technology. The commonly used positioning technology includes GPS and Cell. ID, infrared, IEEE 802.11, ultrasonic, ultra-wideband, Zig Bee and Radio Frequency Identification (RFID). Although GPS can be accurately positioned and low cost, this technology is suitable for outdoor positioning; Cell ID and ultra-wideband are suitable for large-scale regional positioning; infrared is susceptible to interference and construction is high; IEEE 802.11 and Zig Bee are less effective than expected; The installation of the sound wave system is costly.

The RFID wireless identification tag is a non-contact automatic identification system that uses radio waves to transmit identification data. A group of radio frequency identification systems consists of tags and readers. The tags are equipped with circuits, and the readers are intermittently separated from a distance. The energy is transmitted to the tag reader to exchange messages. The tag is basically a simple antenna mounted on a silicon wafer and then packaged in glass or plastic components.

The RFID indoor positioning system was proposed by HighTower and Borriello in 2001. This research develops the SpotON positioning system to verify the feasibility of RFID in indoor positioning. In the SpotON method, the positioning of unknown objects does not go through the process of central control of the system. It is done by other sensing points with the same hardware specifications in a decentralized manner. These sensing points scattered in the sensing environment will collect and report the received signal strength (RSSI) data, and finally locate them. The algorithm calculates the predicted position of the unknown object.

The RFID antenna positioning is suitable for indoor use and the construction cost is low. However, if only a single RFID antenna is used for positioning in the three-dimensional space, the obtained positioning target position is a spherical surface. If an RFID antenna is added, the positioning target position can be limited to two. The intersection of the spheres is a circular arc. Adding a third antenna according to the wireless sensing network will have two intersections with the arc. These two points represent the two possible positions of the positioning target. It is understood that generally 4 antennas are required.

As shown in Fig. 1, the positioning concept requires at least three signal transmitting towers and the position of the transmitting tower is known. It is assumed that the signal sent by each node is the range covered by the circle in the figure, and the coordinates of the signal transmitting tower are respectively (X=0). , Y=0), (X=1, Y=0) and (X=3, Y=0), the three nodes cover the range r1, r2 and r3, and the unknown range can be calculated by using the three nodes. The location of the object, if this concept is applied to more than four signal transmission towers, is called Multilateration.

The algorithm proposed in the prior patent application 97113617 is based on the concept of spatial position correction, first measuring the distance of each RFID antenna to the target tag, and then generating a starting point in the positioning space, and calculating the starting point to each RFID antenna. Straight line distance. Then calculate the Root Mean Square Error (RMSE) of all antennas and target tags. If the root mean square error is less than the preset value, the iterative correction is performed. The iterative correction is obtained by using the initial coordinate value local gradient, initial coordinate and adjustment rate calculation.

Next, calculate the Root Mean Square Error (RMSE) of all antennas and target tags. If the root mean square error is less than the preset value, it ends, otherwise iterative correction is continued.

It is an object of the present invention to provide an RFID tag positioning algorithm that can be applied to two-dimensional or three-dimensional space.

The invention relates to a method for positioning radio frequency identification (RFID) tags, which comprises at least the following steps: (a) providing three antennas and respectively measuring the measured distances s k of the antennas to a target tag (k=1- 3); (b) cutting a positioning space containing the target label into n grids; (c) calculating a linear distance S jk (j=1-n, respectively, from the center point of the n grids of the three antennas; k = 1-3), the actual distance from the 3n antennas to the center of the grid is obtained; (d) the error e jk is calculated, which are the measured distances s k of the antennas for the target label, respectively. The error of the straight line distance S jk of the grid centers, that is, e jk = s k -S jk (j = 1 - n, k = 1-3); (e) for the error value calculated for each antenna Comparing, three sets of meshes with the smallest error value are obtained, and the error values of the plurality of meshes in each group are the same; and (f) comparing the meshes with the smallest error values in different groups, and selecting from them The grid of intersections is the location of the target tag.

The invention also provides another method for positioning radio frequency identification (RFID) tags, comprising at least the following steps: (a) providing three antennas and respectively measuring the measured distances s k of the antennas to a target tag (k= 1-3); (b) cutting a three-axis pair of a positioning space into an N-block grid; (c) calculating a linear distance S jk (j=1-N, respectively, from the center point of the n grids of the three antennas; k = 1-3), the actual distance from the 3N antennas to the center of the grid is obtained; (d) the error e jk is calculated, which is the measured distance s k made by the antennas and the center of the grids The error of the straight line distance S jk , ie e jk = s k -S jk (j = 1 - N, k = 1-3); (e) Comparing the error values calculated for each antenna, three groups can be obtained The grid with the smallest error value has the same error value of multiple grids in each group; (f) compare the grids with the smallest error values in different groups, and select the grid of mutual intersections from The grid is then further cut into M-block grids, and the steps (c) to (f) are repeated until the number of iterations or/and the average error of the selected grid positions is less than a set value, and the position of the target label is determined.

The invention will be further understood by the following detailed description of the invention and the appended claims.

A radio frequency identification (RFID) reader includes an antenna that can be used to read the radio received signal strength (hereinafter referred to as RSSI) of the RFID tag. The RSSI can calculate the distance, but the location of the RFID target tag is still unknown. Therefore, as described in the prior art, at least three antennas are required to acquire the position (but there are still two possible positions). For the sake of understanding, the embodiment of the present invention uses the fourth antenna to obtain a three-dimensional space. The unique location in which to target.

The method of the present invention is called Spatial Positioning Algorithm 2.0 (SPA 2.0), which searches for the positioning space one by one by the exhaustive method, cuts the positioning space into a plurality of grids, and calculates the error of each grid sequentially, and the selection error is minimum. The target tag location. For an embodiment of the present invention, reference may be made to the flowchart shown in FIG. 2.

Step 100: arranging a plurality of reference tags and four antennas in a positioning space containing the target tag. In order to cover various signals in the calculation process, the RFID antennas are uniformly distributed, and are disposed in different positions in the positioning space as much as possible. The RSSI is obtained to reduce the error. In addition, the antenna price is higher, and the uniform distribution can reduce the number of antenna arrangements and reduce the cost of the wireless sensing network.

Step 105: Since the positions of all the reference tags are known, and the positions of the antennas are also known, the radio wave received signal strength (RSSI) values of the reference tags of the antennas and known locations are measured one by one, and then The RSSI value of the antennas and the distances of the reference labels are used to generate an RSSI value-distance relationship diagram, that is, a wireless signal attenuation curve. Because RFID signal influenced by environmental factors, the relationship between RSSI and the distance with the ambient condition change, it is necessary to obtain the relationship between RSSI and the distance of a particular environment, and thus the measurement curve and the target RFID tag antenna measurement of distance s k (k =1-4). In one embodiment, the specific relationship between RSSI and distance is plotted with nine reference labels, as shown in FIG.

Step 110: Divide the positioning space into three squares, cut into n square cubes, or cut the positioning space into n positive cube grids. If there is any remaining space, it is regarded as a grid, which is preset according to the user. The predetermined average error tolerance value determines the magnitude of n, wherein the predetermined average error tolerance value may use the root mean square error value as a reference;

Step 115: Calculate the linear distance S jk (j=1-n, k=1-4) of the four antennas from the center points of the n grids respectively, and obtain the actual distance between the antennas and the center of the grid by 4n antennas;

Step 120: Calculate the error e jk , which is the error of the measured distance s k of the antenna for the target label and the linear distance S jk of the grid centers, that is, e jk =s k -S Jk (j=1-n, k=1-4)

Step 125: Comparing the error values calculated by each antenna, the four grids with the smallest error value are obtained, and the error values of the plurality of grids in each group may be the smallest;

Step 130: Align the meshes with the smallest error values in the different groups, and select the mesh that intersects each other as the position of the target tag.

Another alternative is to calculate the average error ε j , and the grid with the smallest selection error is the target label position. In the embodiment of the present invention, it is a root mean square error (RMSE), and the formula is as follows:

Where m is the number of RFID antennas in the positioning space, s k is the measured distance of the target label measured by the kth antenna, and S jk is the calculated linear distance from the kth antenna to the jth grid center. In fact, the grid with the smallest root mean square error is the grid described in the former way that intersects after the comparison.

The present invention further modifies this embodiment, and derives a spatial positioning algorithm 2.1 (ie, SPA 2.1). Previously, SPA 2.0 calculated the target label position in an exhaustive manner, and it takes a lot of time when the positioning space is large, although it can be enlarged through the grid. The way to shorten the calculation time, but the results of large grid calculations will reduce the accuracy, and the exhaustive way will spend most of the time calculating the irrelevant area and reducing the search function.

Therefore, the SPA 2.1 calculus improves the way SPA 2.0 searches all possible locations of the space in an exhaustive way. Unlike SPA 2.0, SPA 2.1 first divides the overall space into N blocks, N is about 4~8, and calculates the center point of each block. After the error, the block with the smallest selection error is further divided into M blocks, where M is not necessarily equal to N. In the embodiment of the present invention, the overall space is equally divided into eight blocks, and the flow is as shown in FIG. 4 .

Step 200: Using the wireless signal attenuation curve as depicted in step 110, the measured distance s k (k=1-4) of the k-th RFID antenna and the target tag position is obtained;

Step 205: First, the space three-axis pair is cut into eight grids;

Step 210: Calculate the linear distance S jk (j=1-8, k=1-4) of the four antennas from the center point of the eight grids respectively, and obtain the actual distance between the 32 antennas and the center of the grid;

Step 215: Calculate the error e jk , which is the error between the measured distance s k made by the antennas and the linear distance S jk of the grid centers, that is, e jk =s k -S jk (j=1 -8, k = 1-4);

Step 220: Comparing the error values calculated by each antenna, obtaining four grids with the smallest error value, and the error values of the plurality of grids in each group may be the smallest;

Step 225: Align the meshes with the smallest error values in the different groups, select the meshes that intersect each other, and return to step 205, and then finely cut the mesh into eight meshes, and repeat steps 205-225 above. Until the number of iterations or / and the selected root mean square error ε j of the grid j is less than a set value, then the position of the target label is determined as the position of the selected grid j, wherein the calculation of the root mean square error In the same formula as above, the number of iterations is the number of times of repeating steps 205 to 225.

Another alternative is to directly calculate the root mean square error ε j , select the grid with the smallest root mean square error, and return to step 205 to finely cut the grid into eight grids, and repeat steps 205 to 220. when the iteration number or / and the center position of the root mean square error ε j selected grid j is less than a predetermined value, it is determined that the target position of the tab j of the position of the grid is selected.

Setting the number of iterations ensures that the positioning is completed within a certain time, and the average error is less than the set value to ensure a specific positioning accuracy, which can be selected by the user as needed.

In order to verify the feasibility of the above spatial positioning algorithms 2.0 and 2.1 (SPA 2.0 and SPA 2.1), the present invention uses a practical case simulation calculation process, and the positioning space used is 926 cm long, 535 cm high and 211 cm high, and the actual position of the target tag is ( 694cm, 400cm, 75cm).

When using SPA 2.0 calculus, firstly, use the exhaustive method to cut the space into a grid. In this experiment, each grid is cut into a cube of 30cm, 30cm wide and 30cm high. The positioning space is 31 chips long and 18 square wide. 8 grids high, total 4464 cubes, the minimum error after calculation is 0.4; if the grid is enlarged, the calculation time can be shortened, but the error is also enlarged. The grid is 100cm long, 100cm wide and 100cm high. The total length is 10 grids, 6 grids wide and 3 grids high, totaling 180 cubes. The minimum error after calculation is 1.5.

Using SPA 2.1, the positioning space is first cut into eight blocks, and the error value is calculated by the center point of each block. Then, the block closest to the positioning target is selected in the eight blocks and then cut into eight blocks until the error is less than a certain value. The value stops. This algorithm can improve the calculation speed of SPA 2.0. Because SPA 2.1 only needs to cut eight blocks at a time, the convergence speed is faster. The invention uses SPA 2.1 to locate eight spatial centroids after positioning the space, as shown in Fig. 5, after calculating the error, the error rate of the central point of the seventh block is minimum, as shown in Fig. 6. If the error satisfies the stop condition, it stops. If the stop condition has not been met, the seventh block is further cut into eight meshes until the stop condition is satisfied. The convergence curve of SPA 2.1 is shown in Fig. 7.

The above is only the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention; all other equivalent changes or modifications which are not departing from the spirit of the present invention should be included in the following. Within the scope of the patent application.

Figure 1: Schematic diagram showing three-dimensional spatial positioning of RFID; Figure 2: Flowchart of Spatial Positioning Algorithm 2.0 (SPA 2.0) algorithm according to the present invention.

Figure 3 shows the antenna wireless signal attenuation curve.

4 is a flow chart of a spatial positioning algorithm 2.1 (SPA 2.1) algorithm in accordance with the present invention.

Figure 5 shows the spatial positioning algorithm 2.1 grid coordinates.

Figure 6 shows the grid errors of the spatial positioning algorithm 2.1 of the present invention.

Figure 7 shows the convergence trajectory of the spatial positioning algorithm 2.1 of the present invention, the initial position being in one corner of the positioning space.

Claims (12)

  1. A method for positioning radio frequency identification (RFID) tags includes at least the following steps: (a) providing three antennas and respectively measuring the measured distances s k (k=1-3) of the antennas to a target tag; (b) cutting a positioning space containing the target label into n grids; (c) calculating a linear distance S jk of the three antennas from the center points of the n grids (j=1-n, k=1 -3), the actual distance from the 3n antennas to the center of the grid is obtained; (d) the error e jk is calculated, which are the measured distances s k of the antennas for the target label and the networks The error of the straight line distance S jk of the lattice center, ie e jk = s k -S jk (j = 1 - n, k = 1-3); (e) compare the error values calculated for each antenna, Obtaining three sets of meshes with the smallest error value, the error values of the complex meshes in each group are the same; and (f) comparing the meshes with the smallest error values in different groups, and selecting the mutual intersections from them The grid is the location of the target tag.
  2. The method of claim 1, wherein before the step (a), the method further comprises the steps of: arranging a plurality of reference tags and a plurality of antennas in a positioning space containing the target tag, wherein the antennas Distributed in the positioning space in a uniform manner, and disposed at different positions, obtaining the RSSI value of the reference label or the target label in different orientations; measuring the radio wave receiving of the antennas and the reference labels of the known positions one by one a signal strength (RSSI) value, and then an RSSI value-distance relationship map is generated according to the RSSI values of the antennas and the distances of the reference labels; The measured distance of the target tag is obtained according to the RSSI value of the target tag measured by the antennas, and according to the RSSI value-distance relationship map corresponding to the antennas.
  3. The method of claim 1, wherein when the positioning space is cut into n grids, the three axes of the positioning space can be equally divided into n square grids, or cut into n squares. The cube grid, if there is any remaining space, is regarded as a grid, and the number of grids of the positioning space in the step (b) is determined according to the tolerance of one of the root mean square errors preset by the user.
  4. For example, in the method described in claim 1, the target label position in the step (f) is also the grid with the smallest error after calculating the root mean square error.
  5. For example, in the method described in claim 1, after selecting the position of the grid with the smallest error as the position of the target label, the method further includes the following steps: (g) finely cutting the selected grid into m grids, Where m is not necessarily equal to n, steps (c) to (g) are repeated until the selected grid position is within an average error ε j or / in the space and the number of iterations is less than a set value.
  6. The method of claim 5, wherein the average error ε j in the step (g) is a root mean square error.
  7. The method of claim 1, wherein a fourth antenna is further provided, and the steps of (a) to (f) are further performed to further determine the position of the target tag.
  8. A method for positioning a radio frequency identification (RFID) tag includes at least the following steps: (a) providing three antennas and respectively measuring the measured distances s k (k=1-3) of the antennas to a target tag; (b) cutting a three-axis pair of a positioning space into an N-block grid; (c) calculating a straight-line distance S jk of the three antennas from the center points of the N grids (j=1-N, k=1-3 ), the actual distance from the 3N antennas to the center of the grid is obtained; (d) the error e jk is calculated, which is the measured distance s k made by the antennas and the linear distance S jk of the centers of the grids Error, ie e jk = s k -S jk (j = 1 - N, k = 1-3); (e) Comparing the error values calculated for each antenna, the three groups with the smallest error value can be obtained. a grid, in which each of the plurality of grids has the same error value; and (f) compares the grids with the smallest error values in the different groups, and selects the grids of the intersections, and returns to the step (b) And then finely cutting the mesh into M-blocks, and repeating steps (c) to (f) until the number of iterations or / and the average error of the selected grid positions is less than a set value, determining the target label position.
  9. The method of claim 8, wherein the step (a) further comprises the steps of: arranging a plurality of reference tags and a plurality of antennas in a positioning space containing the target tags, wherein the antennas are distributed in a uniform manner In the positioning space, and at different positions, obtaining the RSSI value of the reference label or the target label in different directions; measuring the radio wave receiving signal strength (RSSI) of the antenna and the reference labels of the known positions one by one a value, and then according to the RSSI value of each antenna and the distance of the reference labels to generate an RSSI value-distance relationship diagram; and the RSSI value of the target tag measured according to the antenna, and then according to the RSSI value-distance relationship The graph obtains the measured distance s k of the target tag.
  10. For example, in the method of claim 8, wherein a fourth antenna is further provided, according to steps (a) to (f), the position of the target tag is further determined.
  11. The method of claim 8, wherein the average error is a root mean square error.
  12. For example, in the method described in claim 8, the target label position in the step (f) is also the grid with the smallest error after calculating the root mean square error.
TW99102400A 2010-01-28 2010-01-28 A method of positioning a rfid tag using spatial mesh algorithm TWI411806B (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050285793A1 (en) * 2004-06-23 2005-12-29 Sugar Gary L Self-calibrated path loss position estimation and zone of impact determination
CN101349745A (en) * 2008-09-06 2009-01-21 黄以华 Wireless radio frequency positioning method using region partitioning algorithm
TW200928417A (en) * 2007-12-28 2009-07-01 Prec Machinery Res & Dev Ct Method for real-time positioning by radio frequency identification devices

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050285793A1 (en) * 2004-06-23 2005-12-29 Sugar Gary L Self-calibrated path loss position estimation and zone of impact determination
TW200928417A (en) * 2007-12-28 2009-07-01 Prec Machinery Res & Dev Ct Method for real-time positioning by radio frequency identification devices
CN101349745A (en) * 2008-09-06 2009-01-21 黄以华 Wireless radio frequency positioning method using region partitioning algorithm

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
孫瑜 等,射頻識別技術及其在室內定位中的應用,計算機應用,第25卷第5期,2005.05 *
朱娟 等,基於RFID的室內定位算法,微計算機信息,第25卷第8-2期,2009, *
鄧輝舫 等,使用無線射頻識別(RFID)技術進行室內定位,計算機應用,第28卷第7期,2008.07 *

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