Patent Publication Number: US-9898633-B2

Title: Method and system for determining the position and movement of items using radio frequency data

Description:
BACKGROUND 
     The field of the present disclosure relates generally to systems and methods for item checkout and in certain aspects to retail or other checkout stands (e.g., a parcel distribution station) that incorporate data readers and other electronic devices. The field of the present disclosure further relates to systems and methods for determining the position and movement of multiple items on a conveying system using radio frequency identification (RFID) tags on the items. 
     Radio frequency identification is the wireless use of electromagnetic fields to transfer data, primarily for the purposes of automatically identifying and tracking tags attached to various objects. The tags contain identifier codes and other electronically stored information that is accessible and readable by an RFID reader. RFID technology is used in a wide variety of fields, such as, for example, in the retail industry for tracking packages and goods during an automated checkout process or in inventory, the medical industry to track medicines and pharmaceuticals, and the manufacturing industry to track progress of parts through assembly lines. 
     In the retail industry, items may be identified, tracked, and decoded using a variety of systems and methods. For example, items may have RFID tags and/or optical codes (such as barcodes), and various types of systems may be used to transport the items toward a data reading device to capture the target data. In a semi-automatic system, either checker-assisted or self-checkout, objects bearing RFID tags and/or optical codes are moved one at a time by the user into or through the read region of the data reading device, at which the device captures the data from the object. In an automated system (e.g., a tunnel or portal scanner), an object is automatically moved via a transportation or conveying system through the read region, at which the reader automatically captures data from the object when the object passes through the read region. 
     The present inventors have identified certain disadvantages with conventional checkout systems that use RFID technology to identify and track objects. For example, many checkout systems assume that the conveyor belt speed and trajectory of the RFID-tagged objects are known and constant parameters. On the contrary, the present inventors have identified that these parameters are typically variable in real-life scenarios since the conveyor belt speed may change for any number of reasons and the relative position of the RFID tags may be different from item to item due to the size, shape, and/or placement of the tagged items on the conveyor belt. 
     In addition, many methods developed for identifying RFID location present several drawbacks. For example, some RFID locating methods rely on very directive antenna and/or antenna arrays, which significantly increases the cost and complexity of the system. As another example, some RFID location processes are based on the intensity of the received signal (RSSI), which indicates the strength of the signal sent from an RFID tag to an RFID reader. RSSI is typically used for estimating the distance between the RFID tag and RFID reader (a stronger signal indicates an item closer to the RFID reader), and identifying movement direction of the item bearing the RFID tag based on the strength of the signal. However, using RSSI alone tends to result in imprecise and inaccurate readings because environmental variables largely affect the strength of the signal from the RFID tag. This issue may be especially problematic in a retail setting because many of the retail items themselves affect RSSI data. For example, items with metallic or other reflecting materials (such as soda cans, canned foods, etc.) may cause signals to bounce uncontrollably, thereby weakening the signal and making the RFID tagged item appear further away from the RFID reader. In addition, liquids (such as milk, water, etc.) may absorb a portion of the signal, or larger items may obstruct the signal from smaller items, thereby causing the signal to appear weaker and resulting in an inaccurate estimation of an item&#39;s location. 
     The present inventors have, therefore, determined that it would be desirable to have a simple and streamlined system with improved performance features for accurately locating RFID tags while taking into account the variable speed of the conveyor system and the changing trajectory of the tagged items. Additional aspects and advantages of such data reading systems will be apparent from the following detailed description of example embodiments, which proceed with reference to the accompanying drawings. 
     Understanding that the drawings depict only certain embodiments and are not, therefore, to be considered limiting in nature, these embodiments will be described and explained with additional specificity and detail with reference to the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an isometric view of an automated data reading system, according to one embodiment. 
         FIG. 2  is a simplified schematic of a data reading system illustrating a one-dimensional (1-D) data-reading scenario, according to one embodiment. 
         FIG. 3  is a graph illustrating phase history and phase samples as a function of tag position for the data reading system of  FIG. 2 . 
         FIGS. 4A, 4B, and 4C  are graphs illustrating phase and nominal histories as a function of tag initial position for the data reading system of  FIG. 2 . 
         FIG. 5  is a graph illustrating a normalized correlation curve as a function of tag position for the data reading system of  FIG. 2 . 
         FIGS. 6 and 7  are simplified schematics of a data reading system illustrating a three-dimensional (3-D) data-reading scenario, according to one embodiment. 
         FIG. 8  is a schematic illustrating one embodiment of an object-sorting method for the data reading system of  FIGS. 6 and 7 . 
         FIG. 9  is a schematic illustrating another embodiment of an object-sorting method for the data reading system of  FIGS. 6 and 7 . 
         FIG. 10  is a flowchart illustrating an example method of data reading performed by the automated data reading system. 
     
    
    
     DETAILED DESCRIPTION OF DISCLOSED EMBODIMENTS 
     With reference to the drawings, this section describes particular embodiments and their detailed construction and operation. The embodiments described herein are set forth by way of illustration only and not limitation. The described features, structures, characteristics, and methods of operation may be combined in any suitable manner in one or more embodiments. In view of the disclosure herein, those skilled in the art will recognize that the various embodiments can be practiced without one or more of the specific details or with other methods, components, materials, or the like. In other instances, well-known structures, materials, or methods of operation are not shown or not described in detail to avoid obscuring more pertinent aspects of the embodiments. 
     In the following description of the figures and any example embodiments, it should be understood that an automated checkout system in a retail establishment is merely one use for such a system and should not be considered as limiting. An automated checkout system with the characteristics and features described herein may alternatively be used, for example, in an industrial location such as a parcel distribution center (e.g., postal), warehouse, luggage distribution center, manufacturing assembly lines, or in a retail goods distribution center. 
       FIGS. 1-10  collectively illustrate embodiments of an automated data reading system  10 ,  100  and various methods for locating and tracking RFID-tagged items  46 ,  146  (such as a first item  42  shown as a package/box and/or second item  44  shown as a can). It should be understood that in certain instances, item(s)  46 ,  146  may refer to a single item or multiple items being transported and processed in the system  10 ,  100 . As is discussed in further detail below, the system  10 ,  100  may be used to identify and track items  46 ,  146  during a checkout process in a supermarket or other retail establishment. In some embodiments, the system  10 ,  100  analyzes the phase of a signal received from the RFID tag  52  (see  FIG. 2 ) carried by or housed in the items  46 ,  146  over multiple successive readings of the RFID tag  52  to identify and track the items  46 ,  146  as the items  46 ,  146  reach a bagging area  39 . The system  10 ,  100  may also sort multiple items  46 ,  146  present at the same time in a read region  13 ,  113  during a checkout process to ensure that each item  46 ,  146  is tracked and captured. 
     For the purposes of the following description, the progress and reading/tracking may be described with reference to a single item  46 , but it should be understood that the system may handle multiple items  46  concurrently transported by the conveyors  30 ,  32 . With particular reference to  FIG. 1 , in an example operation, a user, which could be either a customer  36  or check-out clerk  38 , (collectively/alternately referred to as a “user”) places the item  46  onto a leading conveyor section  30  that transports the item  46  in a substantially linear direction of motion  26  toward one or more RFID readers  50 . As each item  46  approaches a read region  13  of the RFID reader  50 , the RFID reader  50  interrogates one or more RFID tags  52  on the item  46  to read, track, and sort the items  46  during the checkout process. In some embodiments, the scanner unit  12  may also capture various images of the item  46  (including images of a bottom surface of the item  46  captured by a bottom scanner unit  18 ) and processed to capture other data from the item  46  (such as barcodes for items that may not have RFID tags  52 . The images of the item  46  may be presented to the customer  36  (or clerk  38 ) via a display  150  for review and verification. Once the appropriate data is captured, the item  46  transitions onto a trailing conveyor section  32 , which may deposit the item  46  into a bagging area  39  where the item  46  may be placed in a bag for the customer  36 . The following sections describe further details of this and other embodiments of the data reading system  10 , including additional details relating to locating, tracking, and sorting methods used by the data reading system  10 ,  100 . 
     With reference to  FIG. 1 , the data reading system  10 ,  100  includes a scanner unit  12  installed on a checkout counter  20  in one embodiment. The checkout counter unit  20  includes an inlet end  22  and outlet end  24 , and the conveyor sections  30 ,  32  as described previously. Preferably, the conveyors  30 ,  32  operate at a constant speed, (e.g., 0.5-3.0 meters/second (m/s)), to optimize the performance of the RFID readers  50 , but it should be understood that in many instances, the conveyors  30 ,  32  operate at a variable speed. Additional details are described below with particular reference to  FIGS. 6-9  for handling the variable speed of the conveyors  30 ,  32  in relation to obtaining accurate readings from the RFID tags  52 . 
     The scanner unit  12  may include data capture devices  14 ,  16  in the form of inverted U-shaped arches extending over the conveyors  30 ,  32 . Data capture devices  14 ,  16  may house the RFID readers  50  and other components (such as data readers or imagers) for capturing RFID tags  52  from items  46 , and for capturing images (such as top views, side views, etc.) or other information corresponding to the items  46 . Further details and example embodiments of a scanner unit  12  are described in U.S. Pat. No. 8,746,564, the disclosure of which is incorporated herein by reference. As mentioned previously, the automated checkout system  10  may include a bottom reader section  18  that reads the bottom side of items  46  as they are passed over the gap  31  between the conveyor sections  30 ,  32 . Additional details and example embodiments of such an automated checkout system are further described in U.S. Patent Application Pub. No. 2012/0187195, the disclosure of which is incorporated herein by reference. 
     It should be understood that the data reading system  10 ,  100  includes various modules or subsystems that perform various tasks. These subsystems are described in greater detail below. One or more of these systems may include a processor, associated software or hardware constructs, and/or memory to carry out certain functions performed by the systems. The processors of the systems may be embodied in a single central processing unit, or may be distributed such that a system has its own dedicated processor. Moreover, some embodiments may be provided as a computer program product including a machine-readable storage medium having stored thereon instructions (in compressed or uncompressed form) that may be used to program a computer (or other electronic device) to perform processes or methods described herein. The machine-readable storage medium may include, but is not limited to, hard drives, floppy diskettes, optical disks, CD-ROMs, DVDs, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, flash memory, magnetic or optical cards, solid-state memory devices, or other types of media/machine-readable medium suitable for storing electronic instructions. Further, embodiments may also be provided as a computer program product including a machine-readable signal (in compressed or uncompressed form). Examples of machine-readable signals, whether modulated using a carrier or not, include, but are not limited to, signals that a computer system or machine hosting or running a computer program can be configured to access, including signals downloaded through the Internet or other networks. For example, distribution of software may be via CD-ROM or via Internet download. 
     The following sections describe example data-reading methods that the data reading system  10 ,  100  may employ to obtain data from the RFID tags  52  on the items  46  for tracking and sorting the items during the checkout process. 
     One-Dimensional Data-Reading Scenario 
       FIG. 2  is a simplified schematic of the data reading system  10  illustrating a one-dimensional (1-D) data-reading scenario, according to one embodiment. The following section discusses calculations and analysis methods performed by the RFID reader  50  (such as by an internal processor thereof or by a computer system  170  in communication with the RFID reader  50  as described in  FIG. 7 ) to track and sort an item  46 .  FIG. 2  illustrates a one-dimensional (1-D) data-reading scenario where an RFID reader  50  interrogates an RFID tag  52  on the item  46  moving on the conveyor  30 . With reference to  FIG. 2 , in the 1-D data-reading scenario, d is a minimum distance between an antenna of the RFID reader  50  and the RFID tag  52 , the point “0” indicates the origin of the axes (i.e., an intersection point between the expected trajectory of the RFID tag  52  and a central axis of the RFID reader  50 ), and x(t) is the tag distance from the origin of the axes, point “0”. 
     Briefly, the following section discusses phase-distance relation in UHF tag backscattering. For a given RFID reader-tag distance, the phase variation due to the signal propagation can be determined by the following equation: 
                   Δφ   =     4   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢           d   2     +       x   ⁡     (   t   )       2         c               (   1   )               
where f 0  is the carrier frequency (866 MHz) and c indicates the speed of light. By this equation, the variation of the reader-tag distance can be appreciated by measuring the received signal phase. The set of all phase variations assumed by the RFID tag signal when the RFID tag  52  moves along the x-axis  54  is called phase history (Δφ varies between 0 and 2π). The equation underlines two distinct behaviors as depicted in  FIG. 3 . When the RFID tag  52  is far away from the RFID reader, that is, when x(t) much greater than d, Δφ is almost linear with respect to x(t). On the other hand, when the RFID tag  52  approaches the minimum distance d, Δφ is non-linear. The boxed region in  FIG. 3  illustrates an example region where the phase history is non-linear.
 
     With reference to  FIGS. 2-5 , the following section describes an example algorithm for identifying the position of the RFID tag  52  relative to the RFID reader  50  assuming a one-dimensional reading scenario. After the phase history is collected, a first step is to create a set of hypotheses for the tag position at the first reading x hp =[x (0)   (1) , x (0)   (2) , . . . x (0)   (m) ] and create different phase sets of size N k  (where N k  is the number of tag reader per each tag k) indexed by m. The calculation results in: x hp =[x hp   (1) , x hp   (2) , . . . , x hp   (m) ], where each set x hp   (i) =[x hp   (i) (t 1   k ), x hp   (i) (t 2   k ), . . . x hp   (i) (t N1   k )] is related to a hypothesis of the tag position at the first reading x (0)   (i) . These sets define curves called nominal histories that were considered sampled at the same time instants of measurements. It should be noted that the algorithm assumes a possible starting position for the RFID tag  52  when testing the hypothesis (i.e., a tag location at the first reading) comprised in the range x min , x max , which may also be referred to as a searching area. The spatial resolution of the algorithm d s  determines both the accuracy and the computation complexity. A smaller value d s  indicates a higher accuracy of the tag position estimate, but also a higher number of hypotheses to be tested. Example phase histories and nominal histories obtained for three different tag position at the first reading are depicted in  FIGS. 4A, 4B, and 4C . 
     A second step of the algorithm is to correlate the measured phase history data with all the nominal histories. Specifically, the m-th correlation value C (m)  is computed according to the following equation in the complex domain:
 
 C   (m) =∥[ e   jφ     hp       (m)   ]*[ e   jφ     measured   ]∥  (2)
 
where φ hp   (m) , is the m-th nominal history and φ measured  is the phase history.  FIG. 5  illustrates an example of the normalized correlation obtained for a single RFID tag  52 .
 
     A third step of the algorithm is to select the position x 0   (i,k)  corresponding to the correlation peak as the most probable position of tag k at the first reading, obtaining the vector x 0 =x 0   (i,1) , x 0   (i,2) , . . . x 0   (i, Nt) , where Nt indicates the number of RFID tags  52 . 
     Once the most probable position is selected, a fourth step of the algorithm is to estimate initial positions of all the RFID tags  52  present in the reading zone  13  of the RFID reader  50 . Since the RFID reader  50  obtains readings from the RFID tags  52  at different time points, it may be necessary to normalize the estimated initial positions with respect to a universal time instant. In fact, the sorting of items  146  may be incorrect if it was performed using correlation curves that are functions of different time instants for each of the tagged items. Once all the estimated initial positions are normalized, the algorithm may be used to identify and sort the RFID tags  52 . Additional details regarding example methods for determining a universal time instant are described in further detail below with regard to  FIGS. 8 and 9 . 
     Three-Dimensional Data-Reading Scenario 
     The previous description focuses on sorting and tracking RFID tags  52  in a data reading system  10  where the tagged items  46  are all the same size and shape, and are in relative motion on a conveyor or other transport system moving at a known trajectory and speed, with the foregoing equations and algorithm simplified based on these assumptions. These assumptions, however, may limit applicability of the methods to the scenario described in  FIG. 2 , where the RFID tags  52  move along the x-axis  54  in a straight line along the conveyor  30  with a constant and known value for d (minimum reader-tag distance). In many applications, however, these parameters (e.g., trajectory, conveyor speed, item location) are not constant. Accordingly, a more complex formula may be needed to account for the variability in these parameters. With particular reference to  FIGS. 6 and 7 , the following sections describe a process for sorting and tracking RFID tags in an environment where the tagged items may be located at any position on a conveyor that may move at variable speeds. 
       FIG. 6  is a simplified schematic of a data reading system  100  illustrating a three-dimensional (3-D) data-reading scenario, according to one embodiment. In this scenario, the placement of the RFID tag  152  on the item  146  and/or the speed of the conveyor  130  may vary for each of the items  146 . Accordingly, the equations for tracking and sorting the items  146  introduce additional variables to account for these changes. When considering tagged objects  146  of varying size, there is no longer a constant value for the minimum tag-to-antenna distance d, but instead, it is necessary to adopt a matrix d yz  to account for a number of possible values for the tag-to-antenna minimum distance. For example, with reference to  FIG. 6 , the equation for calculating the phase variation due to the signal propagation in a three-dimensional axis can be determined by the following equation: 
                     Δφ   xyz     =       4   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢           d   yz   2     +     d   z   2     +       x   ⁡     (   t   )       2         c     ⁢   or   ⁢           ⁢     Δφ   xyz       =     4   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢           d   yz   2     +       x   ⁡     (   t   )       2       c                   (   3   )               
where the vectors d y =[d y1 , d y2 , . . . d yn ] of size n and d z =[d z1 , d z2 , . . . d zp ] of size p represent the minimum antenna-tag distance along the y-axis and z-axis, respectively. In scenarios where the width of the conveyor  130  is small, then equation (3) may be simplified by approximating d y  to equal 0. Similarly, if all the tags  152  are located at the same height for all items  146  (e.g., the items  146  are the same or substantially similar dimensions and the tags  152  are positioned at the same relative location), then equation (3) may be simplified by approximating d z  to equal 0.
 
     The algorithm for identifying the position of the RFID tag  152  is generally the same as described previously with reference to  FIGS. 2-4 . However, because of the additional variables and increased complexity, the extension from a simple 1-D scenario to a 3-D scenario requires the creation of M different phase sets of size N k  for each element of the vectors d y  and d z , resulting in a set of n*p*M phase histories that need to be correlated with the phase history for each RFID tag  152 . Because of this complexity, the spatial resolution of the algorithm may be chosen to maximize the accuracy of the calculation while minimizing its computational complexity. The spatial sampling spaces for correlation can be different depending on the considered direction, and can be based on the following equation:
 
Δ x =( x   max   −x   min ) M≠Δy =( y   max   −y   min )/ n≠Δz =( z   max   −z   min )/ p   (4)
 
     Table 1 below illustrates the effect on computational complexity score based on the selection of the spatial sample spaces. 
     
       
         
           
               
               
               
               
               
               
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
               
                   
                 Range x 
                 Step Δx 
                 Range y 
                 Step Δy 
                 Range z 
                 Step Δz 
                 Complexity 
               
               
                   
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Case 1 
                 −4 m, 0 m 
                 1 cm 
                 0 m, 1 m 
                 2 cm 
                 0 m, 1 m 
                  5 cm 
                 429.471 
               
               
                 Case 2 
                 −2 m, 0 m 
                 2 cm 
                 0 m, 1 m 
                 5 cm 
                 0 m, 1 m 
                 10 cm 
                 23.331 
               
               
                 Case 3 
                 −2 m, −0.5 m 
                 4 cm 
                 0 m, 0.5 m 
                 12 cm  
                 0 m, 0.9 m 
                 30 cm 
                 780 
               
               
                   
               
            
           
         
       
     
     As mentioned previously, another factor that may need to be considered is the variable speed of the conveyor  130 . The variable speed of the conveyor  130  may be monitored by a position encoder  168  (discussed in more detail with respect with FIG.  7 ) and iterative computing of the nominal histories. In other words, the series of nominal histories are not obtained by uniformly sampling the theoretical correlation curves (such as those shown in  FIG. 5 ). Rather, each point forming the correlation curve is calculated after a new tag reading is performed, which may mean that the nominal histories consist of non-equally spaced points as a consequence. The current tag position x_hp i =x(t i ) associated to the last tag reading is derived starting from the previous position x_hp i-1 =x(t i-1 ) based on following the equation:
 
 x _ hp   i   (m)   =x _ hp   i-1   (m) +( t   i   −t   i-1 )* v   i , for the  mth  hypothesis  (5)
 
where t i  is the timestamp jointed with the read phase value, and v i  is the speed of the conveyor  130 , which can be defined by the following equation:
 
                       v   i     =     v   ⁡     (     t   i     )         ;       or   ⁢           ⁢     v   i       =     v   ⁡     (     t   i     )         ;       or   ⁢           ⁢     v   i       =         v   ⁡     (     t   i     )       +     v   ⁡     (     t     i   -   1       )         2               (   6   )               
When the RFID reader  150  (see  FIG. 7 ) and the position encoder  168  are synchronized, formula (5) can be rewritten as follows:
 
 x _ hp   i   (m)   =x _ hp   i-1   (m) +( s   i   −s   i-1 ), for the  mth  hypothesis  (7)
 
where s i =s(t i ) defining the spatial movement measured through the position encoder  168 .
 
     As noted previously, the simplified equations described with reference to  FIGS. 3-5  may be used by the data reading system  10  (see  FIG. 2 ) to track and sort items  46 , with the equations assuming various conditions (e.g., constant conveyor speed and fixed tag-to-antenna distance d).  FIG. 7  illustrates another embodiment of a data reading system  100  illustrating a three-dimensional (3-D) data-reading scenario, where the system  100  accounts for variations in conveyor speed and tag-to-antenna distance d. 
     With reference to  FIG. 7 , the data reading system  100  includes a conveyor  130  that may operate at a constant or variable speed for transporting the RFID-tagged item  146  toward a read region  113  of an RFID reader  150 . The RFID reader  150  includes at least one circularly polarized panel RFID antenna  160  for receiving signals  161  from the RFID tag  152 , and for transmitting signals  162  preferably in the frequency band ranging from 865-870 MHz. The RFID tag  152  preferably comprises one tag antenna and memory including an identifier code for the item  146 . It should be understood that in other embodiments, the frequency band of the RFID antenna  160  may encompass a broader range, such as 860-960 MHz (in compliance with both the European and U.S. standards). Preferably, the RFID antenna  160  is positioned over the conveyor  130  at a suitable height H ant  depending on the expected size of the items  146  being processed. For example, for use in a retail environment, the height H ant  may be approximately 2 meters (6.5 feet) above the conveyor  130 . In other embodiments, the height H ant  may range from 1-3 meters (approximately 3-10 feet) above the conveyor  130 . Preferably, the antenna  160  is centered with respect the width of the conveyor  130  to help ensure adequate coverage of the read region  113 . Preferably, the RFID reader  150  (and/or the RFID antenna  160 ) is connected to, or is in communication with, a computer or other terminal system  170 . The computer  170  may store data received from the RFID tags  152 , such as via signals  161 , and/or may be used to program features of the RFID reader  150 . 
     In some embodiments, the data reading system  100  may also include one or more presence sensors  164  configured to sense the presence of items  146  on the conveyor  130  as the items  146  pass through a detection field of the presence sensors  164 . In one embodiment, the presence sensors  164  may transmit a light beam or light curtain  166  across the conveyor  130  to detect the presence of items  146  on the conveyor  130  and tally a total number of items  146  present on the conveyor  130 . The number of items  146  detected by the presence sensors  164  may be used as a comparison tool to ensure that the RFID reader  150  has captured RFID information from each of the items  146  on the conveyor  130  (i.e., the number of items detected by the presence sensor  164  should match the number of RFID tags  152  detected by the RFID reader  150 ). Preferably, the presence sensors  164  are positioned ahead or before the read region  113  of the RFID reader  150  to monitor the total number of items  146  that should be present in the read region  113 . 
     The data reading system  100  may include a second set of presence sensors  165  adjacent the baggage area  139  (or positioned after the read region  113 ) to verify that the total number of items  146  entering the read zone  113  match the total number of items  146  exiting the read region  113  and present at the bagging area  139 . At any given point in time, the one or more presence sensors  164  track the number of items  146  being processed. 
     In some embodiments, the system  100  includes a position encoder  168  mounted above or below an actuator system (not shown), such as a belt roller, of the conveyor  130  and operable to monitor the real-time speed of the conveyor  130 . In operation, the position encoder  168  may convert movement of the actuator system, e.g., rotation of a conveyor shaft of the belt roller, into square wave output pulses to provide an accurate and reliable means of digitizing position or length of travel of the conveyor  130 . The position encoder  168  may be in communication with the RFID reader  150  to provide speed information of the conveyor  130  so that the RFID reader  150  (or other processor unit) may account for the variable speed of the conveyor  130  via equations (5)-(7) to track a position of the items  146 . 
     The following section describes an example operation of the data reading system  100  to track and sort tagged items  146  using the previously described phase-based location algorithm (see  FIG. 6 ). With reference to  FIG. 7 , a user places the items  146  on the conveyor  130 , which transports the items  146  in a substantially linear direction of motion  126  toward a read region  113  of one or more RFID readers  150 . As the item is transported on the conveyor  130 , the presence sensor  164  detects the item  146  (e.g., the item  146  may interrupt one or more beams of light  166 ), which may power on or activate a mode of the RFID reader  150  to prepare the data reading system  100  for processing the item  146 . Upon activation, the RFID reader  150  continuously interrogates the surrounding environment to identify any RFID tags  152  that may be present. Once tags  152  are identified, the RFID reader  150  obtains the electronic product code (EPC) information or other data encoded on the RFID tags  152  and stores the data in memory and/or communicates the EPC information to the computer terminal  170 . 
     Using the phase-based algorithm described previously, each EPC is assigned a coordinate value formed by both the initial estimated position of the RFID tag  152 , and the EPC first reading timestamp. Additional information relating to the EPC first reading timestamp is described below with particular reference to  FIG. 8 . 
     From the presence sensor  164 , the data reading system  100  receives a tally of the number of items  146  detected by the presence sensors  164  which corresponds to the number of items  146  that are being processed. In addition, via the RFID reader  150 , the automated checkout system  100  has a tally of how many EPCs have been identified and localized. Based on this information, the data reading system  100  computes all the estimated positions of the EPCs with respect to a defined universal time instant to find an absolute position of the RFID tagged items  146 . Based on the calculated absolute positions, the data reading system  100  may select and associate EPC information and/or other information obtained from the RFID tags  152  with the items  146 . As mentioned previously, it may be difficult to reliably track and sort items  146  from the correlation curves unless all the estimated positions of the items  146  are normalized to a universal time instant. The following sections describe two example methods that the data reading system  100  may use to calculate the universal time instant and the absolute position of the items  146 . 
       FIG. 8  is a schematic illustrating one embodiment of a timestamp-based object-sorting method for the data reading system  100  of  FIG. 7 . In general, the timestamp-based method estimates a time at which each of the items (e.g., items  146   a ,  146   b , and  146   c ) will cross a threshold line  172  (referred to as a “dead-line” in  FIG. 8 ) on the conveyor  130  based on RFID tag information obtained when the items  146   a ,  146   b , and  146   c  were located within the reading zone  113 . The time to reach the threshold line  172  is calculated based on estimated initial positions of the items  146   a ,  146   b ,  146   c  at a defined timestamp (Ts 0 ). The estimated initial positions of the RFID tags  152  may be obtained using correlation curves (see  FIG. 5 ) and are defined with reference to a position of the antenna  160  (marked as a zero position “0m” in  FIG. 8 ). Based on the estimated initial positions and timestamp (Ts 0 ), the data reading system  100  determines a projected order at which the items  146   a ,  146   b ,  146   c  will cross the threshold line  172  before entering the bagging area  139 . Based on the projected order, the data reading system  100  associates the appropriate item  146  with the EPC information obtained from the RFID tags  152 . The following section describes further details and illustrates an example of the timestamp-based method with reference to  FIG. 8 . 
     With reference to  FIG. 8 , the timestamp-based method uses the relationship of the tag positions described previously in equation (5). Using the notation in  FIG. 8  for convenience, the equation may be rewritten as follows:
 
 x _ ref   2   =x _ est +( T   k(xref2)   −Ts   0 )* v   i   (8)
 
where x_ref 2  is the distance from the antenna  160  to the threshold line  172 ; x_est is the estimated initial position of the RFID tag  152  and the tagged item  146  with reference to the antenna  160 ; Ts 0  is the timestamp associated to the first reading; v i  is the speed of the conveyor  130 , which is assumed to be a known and constant value; and T k(xref2)  is the time for which each of the RFID tags  152  and the tagged items  146  will pass the threshold line  172 . Rewriting equation (8) to calculate T k(xref2) , the equation becomes:
 
 T   k(xref2)   =Ts   0 +( x _ ref   2   −x _ est )/ v   i   (9)
 
     Using equation (9), the following describes an example implementation of the sorting method with reference to  FIG. 8 . First, the algorithm uses a defined reference position. In the example, the defined reference position, x_ref 2 , is the threshold line  172 . According to  FIG. 8 , the threshold line  172  is positioned 3 meters from the antenna  160  in this example scenario. Using the timestamp and estimated initial positions (which may be obtained from correlation curves as described previously) noted in  FIG. 8  and assuming a constant conveyor speed v i  of 2 m/s, the data reading system  100  may determine at which time T k(xref2)  each of the items  146  will cross the threshold line  172 . Substituting the values in equation (9), the time T k(xref2)  for each item is:
 
For item 146 a: T   a(xref2) =18.0 s+(3 m−(−1.5 m)/2 m/s=20.25 s  (10)
 
For item 146 b: T   b(xref2) =17.8 s+(3 m−(−1.6 m)/2 m/s=20.10 s  (11)
 
For item 146 c: T   c(xref2) =18.1 s+(3 m−(−1.7 m)/2 m/s=20.45 s  (12)
 
Based on the above calculation, item  146   b  will be the first to reach the threshold line  172 , followed by items  146   a  and  146   c  in that order.
 
     As mentioned previously with reference to  FIG. 7 , when the items  146  are in the read region  113 , the RFID reader  150  and antenna  160  interrogate the RFID tag  152  and obtain information relating to the item  146  (such as EPC information). The EPC and other information obtained from the item  146  may be stored in a memory of the RFID reader  152  and/or in a memory of the computer terminal  170  as noted previously. Turning back to the timestamp-based object-sorting illustrated in  FIG. 8 , the RFID reader  150  may obtain the information, denoted as EPC 1 , EPC  2 , and EPC 3  in  FIG. 8 , from the items  146   a ,  146   b , and  146   c , respectively, when the items are in the read region  113 . Using the algorithm described above, the RFID reader  150  is able to associate the EPC 1 , EPC 2 , and EPC 3  information with specific items. For example, since the item  146   b , with identifier EPC 2 , will be the first one to reach the threshold line  172 , the data reading system  100  assigns EPC 2  to object B and retains EPC 1  and EPC 3  in memory until those items cross the threshold line  172 . Similarly, since the second item to cross the finish line has been determined to be item  146   a , the data reading system  100  assigns EPC 1  to item  146   a  when the item  146   a  crosses the threshold line  172 , and so forth for item  146   c  and any other items. In this fashion, the data reading system  100  is able to track the items  146  through the checkout process and ensure that the items  146  are processed correctly and tracked through to the bagging area  139 . 
       FIG. 9  is a schematic illustrating one embodiment of an encoder-based object-sorting method for the data reading system  100  of  FIG. 7 . In general, the encoder-based method uses the information collected by both the presence sensor  164  and the position encoder  168  and is capable of tracking both the number of items  146  on the conveyor  130 , and the time at which the items  146  will reach the bagging area  139 . In general, the encoder-based method tracks items  146  as they approach the threshold line  172  and uses that information, along with the actual speed of the conveyor  130  (obtained via the position encoder  168 ) to identify and associate captured tag information with each of the items  146 . The encoder-based method utilizes some of the same principles as the previously described timestamp-based method. Accordingly, some features and/or components of the encoder-based method may not be described in full detail to avoid repetition. The following section describes further details and illustrates an example of the encoder-based method with reference to  FIG. 9 . 
     With reference to  FIG. 9 , when an item  146  is detected by the presence sensor  168 , the current encoder value (enc ref1 ) is stored in a memory of the data reading system  100 , such as via the computer terminal  170 , and the encoder units (denoted “enc”) counter begins counting. As noted previously with reference to the embodiments of  FIGS. 6 and 7 , the position encoder  164  converts the speed of the conveyor  130  into square wave output pulses, which are referred to here as “encoder units.” As the item  146  (and RFID tag  152 ) travels across the conveyor  130  from the presence sensor  164  to the threshold line  172 , the end-value of the encoder units can be characterized by the following equation:
 
 enc   ev   =enc   ref1   +Δn   enc   (13)
 
where enc ev  is the end value of the position encoder  168  when the item  146  reaches the threshold line  172 ; enc ref1  is the encoder value when the item  146  is sensed by the presence sensor  164 ; Δn enc  depends only on the speed of the conveyor  130  and the distance between the presence sensor  164  and the threshold line  172 .
 
     As is explained in further detail below with reference to equation (14), the estimated position of the RFID tags  152  is determined with respect to the encoder value enc ref1  to obtain an absolute position of the RFID tags  152 . The absolute position helps maintain a synchronization between the RFID reader  150  and the position encoder  168 . The absolute position may be obtained by the following equation:
 
 P   abs   =P   est +( enc   ref1   −enc   tsi)   (14)
 
where P abs  is the absolute position of the item  146 ; P est  is the estimated position; and enc tsi  is the encoder value associate to the time instant of the first reading of the i-th tag. In some embodiments, equation (14) may include an additional conversion factor in cases where P abs  and P est  are measured using different units as the encoder values enc ref1  and enc tsi , as illustrated in the examples (15)-(17) below.
 
     Using equations (13) and (14), the following describes an example implementation of the sorting method with reference to  FIG. 9 . In one example, it is assumed that enc ref1 =10 enc, where 1 enc=1 cm (this value may be programmed as desired); the presence sensor  164  is positioned 2 meters in front of the antenna  160 ; and the threshold line is positioned 3 meters after the antenna  160 . In this example, the distance from the presence sensor  164  to threshold line  172 , or Δn enc , is 5 meters, or 500 enc. Substituting the values into equation (13) provides enc ev =510 enc. Using the values illustrated in  FIG. 9  (which may be obtained using correlation curves), equation (14) yields the following absolute positions for the three items  146 :
 
For item 146 a: P   abs =−1.5 m+(10  enc− 100  enc )/100  enc /m=−2.40 m  (15)
 
For item 146 b: P   abs =−1.6 m+(10  enc− 55  enc )/100  enc /m=−2.05 m  (16)
 
For item 146 c: P   abs =−1.5 m+(10  enc− 110  enc )/100  enc /m=−2.70 m  (17)
 
In this example, when the item “B” approaches the threshold line  172  at the encoder value enc ev , the data reading system  100  determines that the RFID tag  152  nearest to the presence sensor  164  at the encoder value enc ref1  was the RFID tag  152  for item  146   b , which is identified by the EPC 2  code (since −2.05 m is approximately equal to −2.0 m, which is the position of the presence sensor  164 ). Accordingly, the data reading system  100  associates the EPC 2  code with the item B. The data reading system  100  may continuously perform this analysis until it has identified and associated RFID tags  152  with each of the respective items  146 .
 
       FIG. 10  is a flowchart  200  illustrating an example method of data reading performed by the automated data reading system, comprising the following steps. 
     Step  202 , transporting, via a conveyor system, one or more items through a read region of a data reader. 
     Step  204 , obtaining, via a data reader, a first reading of data at a first time from each tag carried by one or more items as the items pass through the read region. The tag may comprise an electronic tag, such as an RFID tag. 
     Step  206 , obtaining, via the data reader, a second reading of data at a second time from each of one or more tags carried by the one or more items as the items pass through the read region. It should be understood that the data reading steps (e.g., steps  204  and  206 ) may be repeated numerous times to obtain multiple readings of data at subsequent times to accurately sort the items  146 . The number of necessary tag readings (N k ) per each tag is unknown a priori since it may depend on several factors, such as: the tag orientation, the conveyor speed (which dictates the tag permanence in the read region), tag transmitting power and reader receiving power (which may be affected by clutter and interferences). Accordingly, the method of data reading may include the additional steps of: obtaining, via the data reader, a third reading of data at a third time from each of one or more tags, and obtaining, via the data reader, a fourth reading of data at a fourth time from each of one or more tags, and so forth to obtain N k  readings. 
     Step  208 , receiving, via a processor, the first reading, the second reading, . . . the N k  readings of data obtained by the data reader. Step  210 , estimating, via a processor, an initial position of each of the one or more items based at least on the first and second readings at the first and second times. In some embodiments, the initial position of each of the one or more items may be estimated based on the N k  readings. 
     Step  212 , determining, via the processor, an order at which each of the one or more items reaches a reference position on the conveyor system. 
     It is intended that subject matter disclosed in any one portion herein can be combined with the subject matter of one or more other portions herein as long as such combinations are not mutually exclusive or inoperable. In addition, many variations, enhancements and modifications of the imager-based optical code reader concepts described herein are possible. 
     The terms and descriptions used above are set forth by way of illustration only and are not meant as limitations. Those skilled in the art will recognize that many variations can be made to the details of the above-described embodiments without departing from the underlying principles of the invention.