Institutionen för systemteknik

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1 Institutionen för systemteknik Department of Electrical Engineering Examensarbete 3-D Positioning in Large Warehouses using Radio-frequency identification Examensarbete utfört i Kommunikationssystem vid Tekniska högskolan vid Linköpings universitet av Jonas Karhu LiTH-ISY-EX 14/4795 SE Linköping 2014 Department of Electrical Engineering Linköpings universitet SE Linköping, Sweden Linköpings tekniska högskola Linköpings universitet Linköping

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3 3-D Positioning in Large Warehouses using Radio-frequency identification Examensarbete utfört i Kommunikationssystem vid Tekniska högskolan vid Linköpings universitet av Jonas Karhu LiTH-ISY-EX 14/4795 SE Handledare: Examinator: Vladimir Savić isy, Linköpings universitet Jonas Karlsson Syntronic Danyo Danev isy, Linköpings universitet Linköping, 18 september 2014

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5 Avdelning, Institution Division, Department Division for Communication Systems Department of Electrical Engineering SE Linköping Datum Date Språk Language Svenska/Swedish Engelska/English Rapporttyp Report category Licentiatavhandling Examensarbete C-uppsats D-uppsats Övrig rapport ISBN ISRN LiTH-ISY-EX 14/4795 SE Serietitel och serienummer Title of series, numbering ISSN URL för elektronisk version Titel Title 3-D Positionering i stora lager med hjälp av Radio-frequency identification 3-D Positioning in Large Warehouses using Radio-frequency identification Författare Author Jonas Karhu Sammanfattning Abstract In large warehouses, there are a lot of articles that needs do be kept track of. As the number of articles grows larger, the administrative complexity increases. Thus, a solution that automatically keeps track of the position of each article in real-time is of interest. That is, if an item in the warehouse is moved, no manual administration should be needed to know the new position of the item. Radio detection and ranging (RADAR) is a ranging technique that doesn t need to communicate with an object to find the distance to it, instead signals are sent and when they are reflected off the object and returned to the sender, the distance to the object may be calculated. However, you cannot tell two equally shaped objects apart purely based on RADAR techniques. There are many other techniques for ranging, sound navigation and ranging (SONAR) is another example, but they all lack the possibility of detecting the identity of the object. So, in order to find a specific item s position, some kind of communication with the item is necessary. Radiofrequency identification (RFID) is a neat technology with which this is possible. An RFID reader can send radio signals out in the air, and objects that are in the vicinity of the reader and are tagged with an RFID tag can receive that signal and respond with it s unique identification number. This way, the RFID reader can identify the RFID tagged object from a distance. There are also a variety of ways to approximate the distance between reader and tag. Unfortunately this is a rather difficult task, especially in indoor environments. There are already some existing products on the market that uses RFID for different kinds of positioning. In this thesis, the theory behind positioning, the fundamentals of RFID and different positioning solutions will be analysed and presented. A number of tests were carried out with an RFID system within the ultra-high frequency (UHF) band, which is around 866 MHz. The test system only supported range estimation based on the received signal strength indicator (RSSI) and the test results showed that narrowband RSSI measurements are highly disturbed by multipath propagation which make the overall positioning performance insufficient. Further analysis of time based range estimation techniques, such as time of arrival (TOA), time of flight (TOF) and time difference of arrival (TDOA), revealed that better positioning accuracy is possible, especially if ultra-wide bandwidth (UWB) is used. Nyckelord Keywords RFID, Positioning

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7 Abstract In large warehouses, there are a lot of articles that needs do be kept track of. As the number of articles grows larger, the administrative complexity increases. Thus, a solution that automatically keeps track of the position of each article in real-time is of interest. That is, if an item in the warehouse is moved, no manual administration should be needed to know the new position of the item. Radio detection and ranging (RADAR) is a ranging technique that doesn t need to communicate with an object to find the distance to it, instead signals are sent and when they are reflected off the object and returned to the sender, the distance to the object may be calculated. However, you cannot tell two equally shaped objects apart purely based on RADAR techniques. There are many other techniques for ranging, sound navigation and ranging (SONAR) is another example, but they all lack the possibility of detecting the identity of the object. So, in order to find a specific item s position, some kind of communication with the item is necessary. Radio-frequency identification (RFID) is a neat technology with which this is possible. An RFID reader can send radio signals out in the air, and objects that are in the vicinity of the reader and are tagged with an RFID tag can receive that signal and respond with it s unique identification number. This way, the RFID reader can identify the RFID tagged object from a distance. There are also a variety of ways to approximate the distance between reader and tag. Unfortunately this is a rather difficult task, especially in indoor environments. There are already some existing products on the market that uses RFID for different kinds of positioning. In this thesis, the theory behind positioning, the fundamentals of RFID and different positioning solutions will be analysed and presented. A number of tests were carried out with an RFID system within the ultra-high frequency (UHF) band, which is around 866 MHz. The test system only supported range estimation based on the received signal strength indicator (RSSI) and the test results showed that narrowband RSSI measurements are highly disturbed by multipath propagation which make the overall positioning performance insufficient. Further analysis of time based range estimation techniques, such as time of arrival (TOA), time of flight (TOF) and time difference of arrival (TDOA), revealed that better positioning accuracy is possible, especially if ultra-wide bandwidth (UWB) is used. iii

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9 To my family and friends. v

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11 Acknowledgments First of all I d like to thank Jonas Karlsson, my supervisor at Syntronic, for all the help you ve given me. I m also grateful for the pleasant work environment created by you and your colleagues at Syntronic. Secondly, a great thanks to Vladimir Savić, my supervisor at the university, for all the valuable insights and tips that helped me get through this thesis. Last, but not least, I want to thank Danyo Danev, my examiner at the university, for your positive attitude in general and for your help in this thesis, as well as in previous courses. Linköping, June 2014 Jonas Karhu vii

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13 You see, wire telegraph is a kind of a very, very long cat. You pull his tail in New York and his head is meowing in Los Angeles. Do you understand this? And radio operates exactly the same way: you send signals here, they receive them there. The only difference is that there is no cat. Albert Einstein. ix

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15 Contents Abbreviations Notation xv xvii 1 Introduction Background Aims Indoor Positioning Thesis Outline Related Work Positioning General Positioning Triangulation Trilateration Radio-Based Positioning Received Signal Strength Indicator (RSSI) Angle of Arrival (AOA) Time of Arrival (TOA) Time Difference of Arrival (TDOA) Time of Flight (TOF) Phase Difference of Arrival (PDOA) Summary RFID Fundamentals of RFID Coupling Magnetic Coupling Load Modulation Load Modulation with Subcarrier Electrical Coupling Electromagnetic Coupling Range xi

16 xii Contents Close Coupling Systems ( 1 cm) Remote Coupling Systems ( 1 m) Long-Range Systems (> 1 m) Tags Passive Tags Battery Powered Tags Battery Assisted Passive Tags Active Tags Modulation Amplitude Shift Keying (ASK) Frequency Shift Keying (FSK) Phase Shift Keying (PSK) Security Summary Possible RFID Positioning Solutions Positioning of Packages Multilateration RSSI-based Range Estimations PDOA-based Range Estimations TOF-based Range Estimations TOA-based Range Estimations TDOA Fingerprinting Positioning of Truck Multilateration Fingerprinting Tags in the Floor Weighted Centroid Summary Tests Hardware Reader Tags Software Positioning of Tag RSSI-based Range Estimations RSSI-based Fingerprinting Test Test Test Summary Positioning of Reader RSSI-based Fingerprinting Test

17 Contents xiii Test Test Summary Summary Conclusions 43 7 Future Work 45 List of Figures 46 List of Tables 48 Bibliography 49

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19 Abbreviations In alphabetic order Abbreviation AM AOA ASK DOS FM FSK GND GPS LOS NLOS PDOA PSK RADAR RFID RSSI SNR Rx TDOA TOA TOF Tx UHF UWB WLAN Meaning Amplitude Modulation Angle of Arrival Amplitude Shift Keying Denial of Service Frequency Modulation Frequency Shift Keying Ground potential Global Positioning System Line-of-Sight Non-Line-of-Sight Phase Difference of Arrival Phase Shift Keying Radio Detection and Ranging Radio-frequency identification Received Signal Strength Indicator Signal-to-Noise Ratio Reception Time Difference of Arrival Time of Arrival Tome of Flight Transmission Ultra-High Frequency Ultra-Wideband Wireless Local Area Network xv

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21 Notation In alphabetic order, Greek letters first Notation Meaning γ Path loss exponent Difference ɛ Positioning error Θ Measure of accuracy λ Wavelength π Pi ( ) σ Standard deviation φ The phase of a signal B Bandwidth c The speed of light ( m/s) d Actual distance from reader to tag dˆ Estimated distance from reader to tag E Electric field strength Carrier frequency of the RFID reader f S Sub-carrier frequency relative to the carrier frequency H Magnetic field strength P Power P L Path loss SNR Signal-to-noise ratio t Time t P The time it takes for the tag to process a signal and respond t RT T Round-trip-time, which is the time of flight plus the processing time at the tag t T OF The time it takes for a signal to travel from a reader to a tag and back X G Gaussian random variable with zero mean and standard deviation σ f READER xvii

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23 1 Introduction This paper is the documentation of my master thesis which is the final part of my education to become an engineer in the field of applied physics and electrical engineering. The thesis was carried out at Syntronic Software Innovations AB in Linköping, Sweden. 1.1 Background It s becoming more and more important to make production lines and product storage more effective. As warehouses grow larger, the manual handling of packages are getting less plausible. An automatic system that could keep track of the packages locations within the warehouse would be of great help to the employees that are fetching the packages. Radio-frequency identification (RFID) is a technology that has grown rapidly in popularity over the last years. It is a neat way of identifying things, that are tagged with an RFID tag, from a distance. There are several sub-sets of RFID technologies that operates over different distances, read ranges from a few millimetres up to several hundred meters can be achieved with RFID technology. RFID is used in numerous applications today, including short range applications such as key tags, animal identification, travel tickets, etc. RFID applications for larger ranges, including personal identification during sports events, car identification in toll gates, an many more, are also widely used. 1

24 2 1 Introduction 1.2 Aims The aims of this thesis is to present possible solutions for positioning in indoor environments using RFID. A complete positioning system is not the purpose of this work and will hence not be presented. Although, this document may be used as guidelines for a potential developer and/or system architect that is to build a positioning system based on RFID. 1.3 Indoor Positioning Outside our atmosphere, there are several satellites orbiting our planet and sending radio signals down to earth. These signals are utilized by devices that have support for the global positioning system (GPS) to calculate the position of that device. This way, the position relative to the earth s coordinate system can be found with pretty high accuracy (a few metres). However, since GPS uses carrier frequencies above 1 GHz, the signals don t penetrate solid materials, such as buildings, that well and therefore it doesn t work indoors. Fortunately, there are other radio based techniques, e.g. WiFi, Bluetooth and RFID, with which indoor positioning is possible. But unfortunately, the indoor environment is rather harsh against the radio wave propagation which suffers from unwanted effects such as multi-path propagation, which means that the signal bounces on walls and other objects before it reaches it s destination. Also, there might be objects in the way of the signal which could, in the worst case, result in that the signal doesn t reach it s destination at all. 1.4 Thesis Outline In this Chapter, an introduction to this thesis is presented to inform the reader of what s to come and why. Section 2 contains the theory behind positioning. General positioning methods such as triangulation, used as far back as the Greek antiquity, will be introduced and explained in detail. Other positioning methods, that are more adapted for radio communication, will be discussed as well. Since the positioning is to be based on RFID, Chapter 3 will be dedicated to this area. The essential parts of the wide area that is RFID will be described, including how it actually works from a physics perspective, how large the communication range can be, what different tags there are, and much more. After the tools at hand are introduced, some of the countless possible positioning solutions will be presented in Chapter 4. Some of the positioning solutions presented in Chapter 4 will be tested in Chapter 5 with hardware provided by Syntronic. The simulations have been done in Matlab. After all theory has been analysed, the possible positioning solutions have been presented and the tests reviewed, conclusions and final thoughts will be found in Chapter 6. On top of that, comments and recommendations regarding future

25 1.5 Related Work 3 work will be discussed in Chapter 7. Finally, a list of figures, a list of tables and the bibliography will be present in the last pages. 1.5 Related Work There are a lot of work conducted and countless papers published within the areas of indoor positioning and RFID, respectively. Although, there aren t a lot of papers on the topic of indoor positioning using RFID in the way that this thesis is niched. A paper with similar topic as this thesis, where the accuracy of an indoor positioning system is analysed, but with WiFi instead of RFID, is [Jekabsons et al., 2011]. Although it is advantageous with WiFi from an equipment point of view, i.e. if there is an existing WiFi network, it can be used as a part of a positioning system, other traffic on the network may interfere with the positioning and worsen the performance. [Ting et al., 2011] have conducted a study on using passive RFID tags for indoor positioning with, according to the authors, satisfactory results. The test area used in this paper was quite limited. If it had been larger, and possibly with obstacles, the limitations on read ranges that passive RFID tags have together with the problems with only using the RSSI values for range estimations would probably have been shown even more, and have resulted in a worse positioning performance. Furthermore, [Saab and Nakad, 2011] have proposed a Kalman filter aided indoor positioning system with passive RFID tags which performed with high accuracy. However, there was some restrictions on the geometry in which the readers and tags could be placed which simplified the problem. If it is possible to simplify the problem in this manner, which it might not be in a warehouse application, this solution seems to be a good one. [Arnitz et al., 2010] have performed an interesting study where they used ultrawide bandwidth (UWB) for an ultra-high frequency (UHF) RFID system with passive tags. The tests were carried out in a warehouse with readers mounted within a pallet gate and pallets passing the gate were tagged with RFID tags. Even though the set-up cost for the experiments were quite high, since they had to build the reader- and tag antennas by themselves, it would be a significantly lower cost if these antennas were to be mass-produced. Positioning errors less than 0.2 metres was achieved with their positioning solution.

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27 2 Positioning The term positioning is one of many terms that refers to finding someone s or some thing s position within an environment or reference frame. This is a broad field with several applications, such as finding the position of a cellular phone acting in a cellular network, navigate a ship travelling at sea or inventory tracking in a warehouse, of which the latter is the main purpose of this thesis. The Global Positioning System (GPS) is a well-known example of such a system. A GPS receiver, using signals from several satellites, is able to determine its position relative to the earth by utilizing the distances to those satellites. In this chapter, some general positioning methods will be described geometrically in Section 2.1. Since the main objective of this thesis is RFID positioning, a number of different radio based positioning techniques will be introduced in Section 2.2 and further analysed in Chapter General Positioning Triangulation Triangulation is a method for determining an objects position by modelling the problem with one or more triangles. In Figure 2.1, a simple triangulation example is depicted. If the positions A and B, the distance l between them as well as the measured angles α and β are known, the perpendicular distance d from the line AB to the object C, can be calculated. From the standard tangent formula, the following equation holds. l = d tan α + d, α, β 0. tan β 5

28 6 2 Positioning Figure 2.1: Geometrical representation of the triangulation method. Using basic algebraic manipulation and trigonometric identities, this ends up with the following expression. d = l sin α sin β, α, β 0. sin(α + β) Once d is known, the other sides of the triangle can easily be calculated and the position of C determined Trilateration Trilateration, as opposed to triangulation, uses the distances from the reference points to the object, instead of angles. To determine the position of the object, one calculates the intersection between a number of circles (or spheres, 3-D) with radii according to the distance measurements and centers at the known positions. Using three distance measurements, it is only possible to determine the objects two-dimensional position. In order to get the three-dimensional position, a fourth distance measurement is needed (in the ideal case). If there are errors in the range estimations, even more measurements are needed. As mentioned, this is used in the Global Positioning System (GPS). Consider three circles, S 1, S 2 and S 3, with radii r 1, r 2 and r 3, respectively, in the x- y-plane. Given that the centers of these circles don t form a line, the intersection I between them can be calculated. To simplify the calculations, without loss of generality, let the center of S 1 be in the origin, the center of S 2 be along the x-axis and the center of S 3 be anywhere in the x-y-plane. This is depicted in Figure 2.2. Using the facts above, the following system of equations hold. r1 2 = x 2 + y 2, r 2 = (x x 2 ) 2 + y 2, r3 2 = (x x 3 ) 2 + (y y 3 ) 2, where x 2 is the x-coordinate of the center of circle S 2, x 3, y 3 is the x, y-coordinates of the center of circle S 3 and x, y are the coordinates of the intersection I. Subtracting equation 1 from equations 2 and 3, respectively, reduces the system

29 2.2 Radio-Based Positioning 7 Figure 2.2: Geometrical representation of the trilateration method. of equations to two linear equations with two unknowns. { r 2 r1 2 = 2xx 2 + x2 2, r3 2 r2 1 = 2xx 3 2yy 3 + x3 2 + y2 3, which has the solution x = r2 1 r2 2 +x2 2 2x 2, y = r2 1 r2 3 +x2 3 +y2 3 x 3 x2 (r 2 1 r2 2 +x2 2 ) 2y 3. This may be expanded to three dimensions using spheres instead of circles. If the centers of those spheres lies in a plane, the three dimensional position can be calculated with only three spheres if it s known on which side of the plane the object is placed. In general, four spheres are needed. 2.2 Radio-Based Positioning In this section, some of the most common techniques for radio based position that exists will be introduced and briefly explained. The details of these techniques are further described and analysed in Chapter Received Signal Strength Indicator (RSSI) Since the power of a propagating signal, or signal strength, is decaying with increasing distance, the received signal strength indicator (RSSI) can be measured and used to estimate the distance from a reference point to an object. This is explained in more detail in Sections and Angle of Arrival (AOA) By utilizing directional antennas, or antenna arrays, the angle to an object, or angle of arrival (AOA), can be determined. This is done by sending signals in different directions and then sense at what direction the signals reach their maxi-

30 8 2 Positioning mum signal strength. Once the angles from the reference points to the object are determined, triangulation can be done to find the position of the object Time of Arrival (TOA) Since there is a linear relation between the propagation time and propagation distance, due to the fact that radio waves propagate at the speed of light 1, the time of arrival (TOA) can be used to find the distance from an object to a reference point. This requires that there are a number of synchronized receivers which receives the same signal at different time instances. Also, within that signal, the time that the signal was sent must be available for the receiver in order to know the propagation time. The distances are then calculated according to d = c t, where c is the speed of light ( m/s) and t is the time difference between the time of transmission and time of arrival. Once the distances from the reference points to the object are known, trilateration can be used to find the object s position. This is explained in more detail in Section Time Difference of Arrival (TDOA) Time difference of arrival (TDOA) is a positioning technique where a signal sent from an unknown position is received at multiple synchronized receivers at known positions and the time differences of the arrival times are computed. One advantage of this method is that the time that the signal was sent is not needed to be known. Although, a drawback is that the synchronization between the receivers are very important. By calculating the TDOA between two receivers at known positions, the origin of the signal will be placed on a hyperbola, [Gustafsson and Gunnarsson, 2003]. Using more measurements from other receivers, more hyperbolas are formed and the unknown position may be estimated using e.g. nonlinear least squares, [Gustafsson and Gunnarsson, 2003]. Other filtering and/or averaging may be done to further improve the accuracy. This is explained in more detail in Section Time of Flight (TOF) This technique is similar to TOA in that it uses the propagation speed of the radio signal, i.e. the speed of light, together with the time it takes for the signal to travel between a reference point and an object at an unknown position. The difference is that in time of flight (TOF), the round-trip time, i.e. the time it takes for the signal to travel from the reference point to the object at the unknown position and back, is measured. This way, only the transceiver at the reference point need to keep track of time. As in TOA, several distance estimates are calculated and trilateration is used to find the unknown position. This is explained in more detail in Section Radio waves travel at the speed of light in vacuum, the speed is negligibly slower in air.

31 2.3 Summary Phase Difference of Arrival (PDOA) Range estimation based on phase difference of arrival (PDOA) uses two or more different carrier frequencies to send signals from a reference point to an object at an unknown position. The phase of a signal will change differently depending on the distance to the object. Comparing the phase difference between the different signals makes it possible to estimate the range. This is explained in more detail in Section Summary Some of the existing techniques for positioning have been introduced here. It should be noted that this is merely a theoretical presentation that aims to explain the concept of each technique. In real scenarios the measurements will be affected by noise and the positioning will be erroneous. In Chapter 4 the severity of the noise, as well as methods for minimizing the noise, will be discussed.

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33 3RFID Radio-frecuency identification (RFID) is a very broad and increasingly popular field of study. However, this chapter aims to give a basic understanding of the physical concepts behind the RFID technique. For a more comprehensive analysis of RFID, see [Finkenzeller, 2010]. To demonstrate the diversity of RFID systems, a number of different applications are mentioned. RFID may be differentiated in many ways; different frequencies, different bandwidths, whether the tags are battery powered or not, and so on. The different frequencies used have a strong correlation to which distances RFID communication is possible. There are a lot of short range applications that uses lower frequencies, such as animal identification, access control, public transportation and sports events, to name a few. For long range applications, such as this thesis, RFID within the ultra-high frequency (UHF) or microwave frequency is favourable. Although, for the purpose of completeness, all operating frequencies for RFID systems will be considered. Most of the facts in this chapter are gathered from [Finkenzeller, 2010]. 3.1 Fundamentals of RFID The physical communication in RFID, as the name indicates, utilizes radio frequency signals to achieve wireless communication between a reader and a tag. In the simplest case, the 1-bit transponder, the tag only gives a response if it is within the read range of the reader. Thus, the tag response is binary (1 or 0), i.e. the tag is in the vicinity of the reader or it is not. Although this simple system have some clear limitations, it is widely used in retail alarm systems, e.g. clothes are tagged with an RFID tag to prevent shoplifting. All RFID tags, except the 1-bit transponder, have a memory that can store a small amount of data, which may be a tag identification number, information about the object being tagged, 11

34 12 3 RFID Figure 3.1: Magnetic field generated by the reader induces a current in the antenna coil of the tag. etcetera. 3.2 Coupling Depending on the distance the RFID system is designed for, a specific physical property is used for the coupling between reader and tag. This is done either in the near-field of the reader by magnetic coupling or electric coupling, or in the far-field of the reader antenna by electromagnetic coupling. As a rule of thumb, the transition from from the near-field to the far-field occurs at the distance λ/2π. At that distance, the electromagnetic field has formed an electromagnetic wave Magnetic Coupling Magnetic coupling, also called inductive coupling, is when an alternating magnetic field, H, are used to power up and communicate with a tag. It is based on the physical properties described by Faraday s law of induction. When the reader and tag antenna are in the form of a coil, a current flowing through the reader antenna coil will produce a magnetic field around the reader. This in turn will induce a current in the tag s antenna coil, powering the internal circuit of the tag, see Figure Load Modulation The tag can communicate with the reader, i.e. send data, by utilizing a load resistor, or modulation resistor, that is switched on and off to alter the magnetic field, which they share due to mutual inductance. By doing this, the voltage at the reader antenna is changed. If the resistor is switched on and off based on the data that are to be sent, it becomes a type of amplitude modulation. This method is called load modulation.

35 3.2 Coupling 13 Figure 3.2: Electromagnetic wave generated by the reader powers the tag Load Modulation with Subcarrier The change of voltage at the reader antenna might be difficult to detect at the tag since the coupling is rather weak, the useful signal generated by the change of voltage in the antenna are much smaller in magnitude than the antenna voltage. So instead of modulate the data by switching the load resistor on and off, it is possible to let the load resistor be switched on and off with a constant high frequency f S, f S < f READER, where f READER is the reader s frequency with which the magnetic field is generated. This can be seen as a subcarrier that appears as two spectral lines at frequencies f READER ± f S. The subcarrier may then be modulated with the data using either amplitude shift keying (ASK), frequency shift keying (FSK) or phase shift keying (PSK), which the reader can retrieve with a band-pass filter and demodulate Electrical Coupling Electrical coupling, or capacitive coupling, is similar to magnetic coupling, but instead of creating a magnetic field, the reader has a large conductive area that is given a potential which yields in a voltage between the reader antenna and the potential of the ground (GND), thus an electric field, E, is created between the reader and the GND. If a tag is placed within this electric field, it s input resistor will enable the tag to harvest energy from the electric field. Also, as in magnetic coupling, a load resistor is used to achieve data transfer from the tag to the reader by load modulation Electromagnetic Coupling In electromagnetic coupling, as opposed to magnetic and electric coupling, the tag doesn t utilize the field strength around the reader, but instead uses the energy that the propagating radio wave generated by the alternating fields contains to power the tag. This is depicted in Figure 3.2. The electromagnetic wave that reaches the tag is reflected by the tag s antenna, this is called backscatter. The backscattered signal may be modulated, as in load modulation for inductive coupling, which in this case is called modulated backscatter. This is realized, again as in load modulation for inductive coupling, with a load resistor that is switched on and off according to the data that is to be transmitted from the tag to the reader.

36 14 3 RFID 3.3 Range As mentioned earlier, there are many ways to differentiate different RFID systems. The most intuitively of which are the operating frequency, or as here, the operating distance Close Coupling Systems ( 1 cm) Systems that are referred to as close coupling systems are operating at very short distances, i.e. from a few millimetres up to a centimetre. These systems use magnetic or electrical coupling when communicating with tags Remote Coupling Systems ( 1 m) Systems within the remote coupling systems category uses mostly magnetic coupling but there are a small fraction of these that uses electrical coupling. Systems that operates on these distances are mainly systems with carrier frequencies 135 khz, MHz and MHz Long-Range Systems (> 1 m) For communication to be possible on larger distances than λ/2π, electromagnetic coupling has to be used. The electromagnetic wave that is sent from the reader are reflected, or backscattered, from the tag to the reader with it s information modulated into the backscattered wave. Systems that can be referred to as long-range systems include carrier frequencies 433 MHz, 866 MHz and 2.45 GHz within the ultra-high frequency (UHF) and 5.8 GHz and GHz within the super-high frequency (SHF). 3.4 Tags Passive Tags A passive tag is a tag that has no external battery nor power supply. All the power that is required for the tag to be operational are extracted from either the magnetic field, electric field or the electromagnetic wave from the reader. This allows the tag s chip to be very small, although the antenna of the tag has to be of sufficient size for the tag to be able to extract any energy from the field or wave. In the case of electromagnetic backscattering, higher frequencies allows for smaller antennas, since the antenna size required is related to the wavelength Battery Powered Tags In the literature, some refer to active tags only based on the fact that they do have a battery. However, there are two types of tags that are equipped with a battery that can be differentiated depending on how the transmission of data from the tag to the reader is done. These two types will be referred to as battery assisted passive tags and active tags. Moreover, battery powered tags all have in common

37 3.5 Modulation 15 that they are larger than passive tags, since they need to contain the battery. They also suffers from the drawback of necessary battery changes Battery Assisted Passive Tags Battery assisted passive, sometimes called semi-active or semi-passive, tags don t use power from the battery to communicate with the reader. Instead, they communicate the same way as passive tags, but their internal circuits are battery powered. This allows the tag to have a lower threshold for sensing the reader which in turn enables the tag to communicate with the reader at a larger range. Also, the tag may be equipped with sensors that are powered by the battery. For example, a temperature sensor may be attached to the tag and when the reader communicates with the tag it learns the temperature in the tag s environment Active Tags Active tags, as opposed to all other types of tags, have the possibility to communicate with others using it s own radio transmitter. That is, they can transmit their ID number (and/or other information) with out a request from a reader. In this case, tags may be configured to transmit certain information at a certain interval. They may be equipped with a motion sensor, enabling the tags to put themselves in an idle mode when they are fixed and transmit when they are moving. This allows for more flexibility when building and implementing a system, but this type of tags are more expensive than the others. 3.5 Modulation RFID systems uses rather simple methods for modulation of the data to be transmitted, namely amplitude shift keying (ASK), frequency shift keying (FSK) or phase shift keying (PSK) Amplitude Shift Keying (ASK) One basic characteristic of the electromagnetic wave is the amplitude. The amplitude can be changed between two values to indicate binary 0 or 1, see Figure 3.3a. The analog counterpart amplitude modulation (AM) is widely used in commercial radio Frequency Shift Keying (FSK) The frequency is another characteristic of the electromagnetic wave that can be altered to achieve modulation. By switching the frequency of the signal between two values, binary 0 and 1 are represented, see Figure 3.3b. This also has an analog counterpart, frequency modulation (FM), that is used in commercial radio as well.

38 16 3 RFID Binary 1 Binary Binary 1 Binary Amplitude [V] Amplitude [V] Time [t] (a) Amplitude shift keying Time [t] (b) Frequency shift keying Binary 1 Binary 0 1 Amplitude [V] Time [t] (c) Phase shift keying. Figure 3.3: The different modulation schemes used in RFID systems Phase Shift Keying (PSK) Another characteristic of the electromagnetic wave that may be altered is the phase. Changing the phase between two values enables representation of binary 0 and 1, see Figure 3.3c. 3.6 Security There are a lot of ways to compromise an RFID system. Attacks like eavesdropping, denial of service (DOS) attacks, interfering signal, destruction of tag, tag shielding, relay attacks and many more are possible to do if the RFID system aren t equipped with the required countermeasures. However, one should estimate the probability of those threats and weight the cost of building and implementing the necessary countermeasures versus the cost a security breach would yield. In the case of personal access cards, travelling tickets, payment applications and so on, the probability of an attack is certainly higher than for example industrial and warehouse applications.

39 3.7 Summary 17 Frequency Band Coupling Range (Approx.) Tag < 135 khz Electrical or magnetic 1 cm Passive 135 khz Mostly Magnetic 10 cm Passive MHz Mostly Magnetic 10 cm 1m Passive MHz Mostly Magnetic 10 cm 1m Passive 433 MHz Electromagnetic m Active 866 MHz (915 Electromagnetic 1 15 m Passive MHz U.S.) 2.45 GHz Electromagnetic 1 15 m Active 5.8 GHz Electromagnetic up to 200 m Active Table 3.1: Summary of different RFID systems, [Wikipedia] and [Finkenzeller, 2010]. 3.7 Summary When building an application based on RFID, there are a lot of factors to take into account. It is important that the operating distance is sufficient. Also, the possibility of interference has to be considered, so that the RFID application does not occupy radio frequencies that other applications use, since the RFID application, as well as the other application, may suffer from performance losses due to interference. Whether the tags are battery powered or not might be an important basis for the decision as well, both because battery powered tags in general are more expensive and because they require maintenance, i.e. battery changes. It is also worth mentioning that within the radio spectra, lower frequencies penetrates other mediums better than higher frequencies. Furthermore, the security aspects are important to consider. In Table 3.1, a summary of the different RFID systems on the market is listed.

40

41 4 Possible RFID Positioning Solutions The main objective of this thesis is to find the position of an object, i.e. a package, within a warehouse. The package is assumed to be tagged with an RFID tag upon arrival to the warehouse and then placed on a shelf somewhere. There are several ways to build, implement and configure a system that finds the position of the package, these will be discussed in this chapter. Different ways of positioning the packages will be discussed in Section 4.1. If the package that is to be fetched is large, or if it s just not feasible to carry the packages by hand, a truck might be necessary to be able to move the package. For several reasons, it can be interesting to be able to keep track of the truck s position. One possible application could be to draw a map of the warehouse and a possible route to the package. Methods for truck positioning will be discussed in Section Positioning of Packages Positioning of packages can be done in many ways, either a passive or active tag is placed on the package and readers are placed around the interior of the warehouse. Depending on the RFID system that is used, the read range and the accuracy of the RFID system, the needed density of readers will vary. For shorter read ranges with bad accuracy, higher density of readers is required, and vice versa Multilateration Multilateration, or trilateration as described in Section 2.1.2, requires that the range from at least four readers, at known positions, to one tag can be estimated 19

42 20 4 Possible RFID Positioning Solutions γ = 2.4, σ = 5 γ = 2.4, σ = 5 γ = 2.4, σ = 5 γ = 2.4, σ = 0 (ideal) 50 RSSI [dbm] Distance [m] Figure 4.1: Simulated log-distance path loss model (the solid black lines are generated the same way, but since there is a random variable present, the outcome varies). in order to get the tag s position. There are different ways to estimate the distance from a reader to a tag, some of which will be discussed here RSSI-based Range Estimations Range estimations based on the received signal strength indicator (RSSI) should be possible due to the fact that the signal strength fades logarithmically proportional to the distance, if the there are no multipath propagation and no obstacles. However, in indoor environments, multipath propagation will occur, there may also be obstacles that prevent line-of-sight communication between the reader and the tag. These problems with indoor environments may be severe to the overall performance of a positioning system based purely on the RSSI. In Figure 4.1, the log-distance path loss model for the RSSI is depicted with arbitrary, but nonetheless realistic, values of the parameters λ and σ. λ is the path loss exponent, which simply tells how steep the slope is, whereas σ, which is the standard deviation, reflects how much the RSSI varies. In other words, a high value on σ yields that the RSSI values cannot be translated into a unique distance. However, if the channel is good, e.g. as in an anechoic chamber, σ will be small and the RSSI value is easily translated into a distance. The formula for the logdistance path loss model is presented in Section 5.3.1, where an example with parameter values derived from an actual experiment is shown.

43 4.1 Positioning of Packages PDOA-based Range Estimations Phase difference of arrival is a method in which the reader sends signals with different frequencies to a tag and compares the phase difference of the received signals to estimate the distance to the tag. These frequencies may be two different frequencies f 1 and f 2 (f 2 > f 1 ). The phase φ of the signals will be φ i = 4πf id, (4.1) c where d is the distance between reader and tag and c is the speed of light, [Li et al., 2009]. This yields the estimated distance to the tag ˆ d = c φ 12 4π f 12, (4.2) where φ 12 = φ 2 φ 1 and f 12 = f 2 f 1. Since the phase of a signal is expressed in the interval [0, 2π), there will not be a unique distance corresponding to each phase difference. In fact, the above expression is only true if the true phase difference is within [0, 2π). This has to be taken into account if the unknown distance is unbounded. Since the true phase can be expressed as Φ 12 = φ mπ, (4.3) where m is an unknown integer, the estimated distance becomes d ˆ = c φ 12 + cm. (4.4) 4π f 12 2 f 12 It may be noted that the distance d max, for which m goes from 0 to 1, occurs when c d max =, (4.5) 2 f 12 so if the distance to the tag is bounded, i.e. smaller than d max due to limitations by the read range or physical boundaries of e.g. a building, m will be zero and (4.2) will hold. An example value of d max for the hardware presented in is d max = c = 2 f 12 2 ( ) m As an improvement to this, [Li et al., 2009] also propose a PDOA range estimation based on multiple frequencies. By utilizing frequency hopping, packets within the same message that is sent between reader and tag can be given different carrier frequencies and used for the PDOA range estimation. Averaging the phase differences over different carrier frequencies minimizes the noise and gives a better performance. PDOA is a more robust way of doing range estimations than RSSI, especially in bad conditions, [Hekimian-Williams et al., 2010]. Also, PDOA may be used to accurately track movements of tagged objects. PDOA may be used together with RSSI for an even more robust range estimation, or to reduce the number of readers needed.

44 22 4 Possible RFID Positioning Solutions TOF-based Range Estimations Time of flight is a method for range estimation where the time, t T OF, it takes for the signal to travel to and back from the tag is the variable. Since the signal travels at approximately the speed of light, the distance to the tag is simply estimated as ˆ d = ct T OF 2 = c(t RT T t P ), (4.6) 2 where t RT T is the total round-trip time, including the processing time in the tag circuit, t P, [Zhang et al., 2010]. This seems pretty straightforward, however, in severe multipath environments such as warehouses, high bandwidth is required for accurate range estimation, [Li et al., 2011]. [Li et al., 2011] further state that the achieved accuracy is inversely proportional to the bandwidth. Naturally, the accuracy is also dependent on how severe the multipath environment is, so the signal-to-noise ratio (SNR) will impact the accuracy as well. The expression for the lower bound of the accuracy, Θ, is derived to be Θ d ( 1 2B π ). SNR SNR The reason for this to be be a lower bound is that non-channel noise, e.g. imperfections in the frequency oscillator, phase-offsets, and so on, are neglected. This lower bound for the accuracy is depicted in Figure 4.2. As one can see, if a specific accuracy is wanted and there is a low SNR, then the bandwidth has to be large TOA-based Range Estimations In 2.2.3, it is described how the range estimation in time of arrival is done, which is very similar to how it is done TOF. As described in Section , higher channel bandwidth yields better time resolution. Therefore it is advantageous for the overall positioning performance to have a large bandwidth when the positioning is based on time measurements. Ultra-wideband (UWB) is a wideband transmission between transmitter and receiver that is defined as the threshold when the bandwidth exceeds either 500 MHz or 20% of the center frequency. By using UWB, the time resolution is increased, this means that the accuracy for detecting the signal also is increased. This does not, however, mean that it has to be the line-of-sight (LOS) component of the multipath signal that has the largest peak, but since the time resolution is increased it is easier to distinguish between the LOS and non-line-of-sight (NLOS) components. There are a lot of ways to implement range estimation using TOA, [Alavi and K., 2006] proposes a method for estimating a model of the distance measurement error and [Zou et al., 2010] compares different TOA implementation and proposes and implements a design of a TOA receiver. [Merz et al., 2008] have done experiments using active tags with wide band antennas together with synchronized readers which performs positioning using TOA.

45 4.1 Positioning of Packages 23 Accuracy [m] SNR = 10 db SNR = 5 db SNR = 0 db SNR = 5 db SNR = 10 db SNR = 15 db SNR = 20 db SNR = 25 db SNR = 30 db Bandwidth [MHz] Figure 4.2: Lower bound for the accuracy in range estimation based on TOF for different bandwidths. The result was promising, the positioning error was below 30 cm for 95% of the estimations TDOA As introduced in Section 2.2.4, TDOA, in the simplest case, utilizes two receivers to measure a time difference between them. The time difference that is observed will yield a hyperbola between the receivers on which the sender is located. This is depicted, with different values of the time difference, in Figure 4.3. The same demand on the time resolution, as in the TOA case discussed in Section , applies for TDOA. That is, UWB is needed in order to get the desired time resolution for accurate range estimations Fingerprinting Fingerprinting is a technique that uses reference points to fingerprint certain location. Since all of the methods for range estimation suffers from more or less problems with severe multipath propagation in indoor environments, which may result in ambiguity in the range estimation, recording the characteristics between a reader at a known position and a tag at a known position, e.g. the RSSI, TOA, and so on, may improve positioning performance in harsh environments. In the case of RSSI, which is analysed in Section 5.3.2, the positioning area can be covered with reference tags, the tags are read and the RSSI values are stored along with the positions of the tags. This is done in an off-line phase. When the actual

46 24 4 Possible RFID Positioning Solutions Figure 4.3: Hyperbolas with possible sender positions created by different time differences observed at two receivers marked. positioning of a tag is to be done, the tag is read and the RSSI value from that read is compared to the stored RSSI values, or the fingerprints. An RSSI value close to one of the stored reference values means that it is a high probability that the tag is in the vicinity of that reference values corresponding position. 4.2 Positioning of Truck Instead of using multiple readers to find the position of a tag, one reader, that is placed on the truck, can read many tags in its surrounding in order to be positioned. Of course, the truck may be positioned the same way as a package, with a tag, but since trucks generally have a power source it might be beneficial to place a reader on the truck, enabling other additional positioning techniques for improved accuracy Multilateration This is the inverse problem of positioning of packets using multilateration described in Section Instead of using several readers to locate a tag, several tags at known positions may be read by one reader, that is placed. Using one, or a combination, of the above mentioned methods for range estimation, this will become exactly the same geometrical problem. Consequently, the same solution will hold.

47 4.3 Summary Fingerprinting This will also be an inverse problem, but of the fingerprinting in Section Tags in the Floor Another way to locate a truck is to place passive tags in or on the floor on which the truck will travel. An RFID reader with low frequency that can read the tags in/on the floor may be placed under the truck. This way, since the tags are read from a relatively short distance, the truck can be positioned with high accuracy. Also, since passive tags are rather cheap, high density of tags in/on the floor would be feasible Weighted Centroid Another approach that utilizes multiple passive tags at known positions is the weighted centroid. The reader reads tags that are in the vicinity of the reader. A simple centroid algorithm calculates the centroid of all tags that are read. However, the tags that are closest will be read more times than tags that are further away from the reader, or at least the probability of that happening is greater. So, the weighted centroid is an extension of the simple centroid that takes the probability of a read into account. [Athalye et al., 2011] have performed analysis of the weighted centroid with promising results. The weighted centroid formula is ˆp Reader = p i p T agi, where ˆp Reader is the estimated position of the reader, p T agi is the position of tag i and p i is the probability of tag i being read, [Athalye et al., 2011]. 4.3 Summary As the reader of this thesis might have realized by now, there are a lot of ways to build and implement a positioning system based on RFID. The system architect have to take a lot of factors into account when designing the system. Naturally, the accuracy requirements plays a big part in this. How often items that are to be tracked are moved and if the movements should be tracked are important to consider in order to optimize the life time of possible batteries. At what distance tags are supposed to be read and if there are any other radio communication present in the environment that could worsen the performance of the system are factors that might make the choice of carrier frequency easier. There are drawbacks to every possible solution, some of which could be bad accuracy, the price for buying the equipment, the set-up costs and/or set-up complexity, the need of maintenance, e.g. battery changes, and more. Active tags together with readers that allows TOA or TDOA measurements seems to have the best potential for good accuracy, especially if UWB can be utilized. The drawbacks with this is the high cost, the maintenance, which is implementation dependent, i.e. how often the tags are active affects the battery life time, and i

48 26 4 Possible RFID Positioning Solutions also that there may be other systems operating in the same frequency band since there is quite a large spectrum occupied when using UWB.

49 5Tests In order to experience the possibilities and difficulties of RFID positioning, some tests were carried out. Syntronic provided a set of RFID hardware as a basis for testing. First, the hardware will be presented in Section 5.1, then the software used is presented in Section 5.2, finally some tag and reader positioning tests are shown in Section 5.3 and Section 5.4, respectively. 5.1 Hardware A reader, presented in Section 5.1.1, were placed in a fairly empty room and communicated with a computer via WLAN. From the computer, the tag reads were executed, presented and stored for positioning and evaluation purposes. Depending on the test that were done, the tags, presented in Section 5.1.2, were placed differently in the reader s surrounding Reader The reader used in these tests are a ThingMagic M6 reader, depicted in Figure 5.1a. The reader operates in the ultra-high frequency (UHF) band, which is around 866 MHz. See Table 5.1 for a summary of the reader parameters. In this frequency band, only passive tags have been designed, therefore, passive tags have been used in all tests that were carried out. Connected to the reader was a monostatic dipole antenna, unfortunately though, the antenna were not optimally designed for the operating frequency which could ve been the reason for the bad performance in read ranges. Passive RFID tags operating at this frequency should have a read range up to 10 meters, but in the tests, read ranges up to only 1 meter were achieved. 27

50 28 5 Tests Parameter Value Variable RF Power Output 31.5 dbm Yes Frequency Band MHz No Bandwidth 2 MHz No Table 5.1: Parameters for Thingmagic M6 Reader. (a) ThingMagic M6 reader. (b) Avery Dennison AD-843 tag. Figure 5.1: The hardware that were used to do the tests Tags As mentioned in 5.1.1, passive tags were used for testing. The tags that were used are of the brand Avery Dennison, with model number AD-843, shown in Figure 5.1b. This tag has a dipole antenna, which means that the read performance depend on which direction it is placed, since the reader also has a dipole antenna. According to the specification, the tag can be read at a distance of 6 feet, i.e. about 1.8 meters. However, as mentioned before, the read range achieved was only about 1 meter. 5.2 Software In order to be able to do anything with the reader, some software is needed. ThingMagic provided a program called Universal Reader Assistant with which it was really simple to read the tags. However, the possibility of extracting any performance measures other than the RSSI was non-existing. The evaluation of the tag reads as well as the position calculations were done in Matlab. 5.3 Positioning of Tag In order to position a tag, several readers are needed as mentioned before. Therefore, since the positioning wasn t done online, the reader was placed in one position at a time, simulating that several readers were available.

51 5.3 Positioning of Tag Measured γ = 2.0 γ = 2.4 γ = 2.8 RSSI [dbm] Distance [m] Figure 5.2: Measured path loss in test environment versus model based path losses with σ equal to zero RSSI-based Range Estimations As discussed earlier, range estimations based purely on RSSI don t work that well indoors due to severe multipath propagation. This was somewhat confirmed by attempts to use the RSSI to do range estimations with the test set-up. Figure 5.2 shows the bad performance of the RSSI in the test environment, along with a model based path loss. Based on this, further analysis of this method was not conducted. The log-distance path loss model is a model that predicts path losses for a radio signal that propagates indoors. The measured RSSI values from the tests can be compared to those from this model. The model states that P L = P TxdBm P RxdBm = P L γ log 10 d d 0 + X G, (5.1) where P L is the total path loss in decibel (db), P TxdBm is the transmitted power in decibel-milliwatts (dbm), P RxdBm is the received power in dbm, P L 0 is the path loss at the reference distance d 0, d is the distance, γ is the path loss exponent and X G is a Gaussian random variable with zero mean and standard deviation σ. In Figure 5.2 the path loss for some different path loss exponents are shown, X G is set to zero. Approximate values of the path loss exponent, γ, and the standard deviation, σ, for the test environment are shown in Table 5.2.

52 30 5 Tests Path loss exponent (γ) Standard deviation (σ) Table 5.2: Numerical values describing the path loss in the test environment. Figure 5.3: Test 1 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0, 0]. The actual tag position is marked RSSI-based Fingerprinting Based on the bad results in Section 5.3.1, another approach called Fingerprinting, described in Section 4.1.3, was tried. In the test environment, this method actually worked quite well, as can be seen in Figures But, as mentioned earlier, this method requires extensive installation, or set-up, to do the off-line phase. The reference points, or fingerprints, were measured uniformly over an area of 70 times 90 centimetres with 10 centimetres separation, which results in 63 fingerprints Test 1 In the first test, the tag was placed at [x, y] = [0.14, 0.20], the results of Test 1 can be seen in Figures Test 2 In the second test, the tag was placed at [x, y] = [0.67, 0.18], the results of Test 2 can be seen in Figures

53 5.3 Positioning of Tag 31 Figure 5.4: Test 1 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0]. The actual tag position is marked. Figure 5.5: Test 1 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0.70]. The actual tag position is marked.

54 32 5 Tests Figure 5.6: Test 1 Joint weighted probability grid with the exact tag position ( ) and the estimated tag position ( ). Figure 5.7: Test 2 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0, 0]. The actual tag position is marked.

55 5.3 Positioning of Tag 33 Figure 5.8: Test 2 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0]. The actual tag position is marked. Figure 5.9: Test 2 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0.70]. The actual tag position is marked.

56 34 5 Tests Figure 5.10: Test 2 Joint weighted probability grid with the exact tag position ( ) and the estimated tag position ( ). Test Positioning Error (ɛ) m m m Table 5.3: Positioning errors for the different tests of tag positioning using Fingerprinting Test 3 In the third test, the tag was placed at [x, y] = [0.62, 0.48], the results of Test 3 can be seen in Figures Summary As can been seen in Figures The positioning error varied quite a bit. A summary of the different positioning errors can be found in Table 5.3. The mean error was ɛ = 0.15 m.

57 5.3 Positioning of Tag 35 Figure 5.11: Test 3 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0, 0]. The actual tag position is marked. Figure 5.12: Test 3 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0]. The actual tag position is marked.

58 36 5 Tests Figure 5.13: Test 3 Weighted probability grid of tag positions based on a reader placed at [x, y] = [0.90, 0.70]. The actual tag position is marked. Figure 5.14: Test 3 Joint weighted probability grid with the exact tag position ( ) and the estimated tag position ( ).