IEEE TRANSACTIONS ON MOBILE COMPUTING,VOL.XX,NO.XX,2020 Tagged Daily absolute touch position,we observe that the RSSI deviation during the swipe is position-independent and orientation- insensitive.We explore the signal variation when touching different positions on the tag,and build an RSSI-based MeTg Touch Ges model to verify the robustness of the RSSI deviation,which Track Rigid Touch Tag: Modon is mainly related to impedance change due to touch.Hence, Deteer Toueh based on the RSSI deviation,we can identify the absolute Gesture candidate touch positions.Note that,as the used linear Fig.1.An example application scenario of RF-Dial tag has the dipole antenna,the RSSI variation during the swipe across the tag forms a symmetric -wave pattern.To rotation of the tagged object for each snapshot based on the eliminate such ambiguity of touch positions,we use half of rigid transformation model.Note that,the phase contours the tag as buttons and the other half as the slider.Referring of RF-signals vary at different positions in the scanning to the RSSI variation,it is easy to determine which gesture area,the relationship between the tag movement and the is performed,thereby we can identify which part of the tag phase variation is different,regarding to which we split is touched and further derive the unique touch position.By the effective scanning area into linear region and non-linear tracking the consecutive touch positions of the swipe,we region.Meanwhile,based on RF-signals from the touch tag, are able to estimate the swipe direction and distance. we build an RSSI-based model to depict the relationship be- Overall,we make the following three main contribu- tween the touch position on the tag and the corresponding tions.First,we propose a novel interaction scheme via RFID RSSI variation of received RF-signals.According to the RSSI- technology,supporting the rigid motion tracking and the based model,the RSSI deviation is mainly related to the touch gesture detection.An ordinary object can be turned impedance change when touching the tag,so it is position- into an intelligent HCI device via attaching a tag array independent and orientation-insensitive.Consequently,we on the side face together with one linear tag on the top can rely on only one general RSSI deviation template to ac- face,denoted as movement tags and the touch tag,respec- curately and robustly determine the touch position,without tively.Second,we build a phase-based model to reflect the the known start touch position or the fixed tag deployment, relationship between the motion of tagged object and the among the whole monitoring area. corresponding phase variations of movement tags in the There are three key challenges to realize RF-Dial.1) array.We also build an RSSI-based model to depict the rela- How to estimate the rigid motion of the tagged object based tionship between the touch position and the corresponding on RE-signals of tags,including the translation and rotation RSSI deviation of the touch tag.Third,we implemented a simultaneously,is a key problem.To tackle this challenge,we prototype system of RF-Dial and evaluated its performance build a rigid transformation model to reflect the relationship in the real environment.Extensive experiments show that between the motion of the tagged object and the correspond- RF-Dial achieves an accurate rigid motion tracking,with a ing phase variations of each movement tag in the tag array. small error of 0.6cm for translation tracking,and a small As the topology of the movement tag array is fixed,we are error of 1.9 degrees for rotation estimation.Besides,RF-Dial able to decompose the rigid motion of the tagged object can also detect the touch gesture accurately,as the 90 percent referring to the phase variations of at least two movement of touch position errors are less than 2.09mm. tags,and then derive the translation and the rotation of the tagged object for each snapshot during the motion.2)How 2 RELATED WORK to address the variation of phase contours at different positions RFID-based Localization:A straightforward solution for in the effective scanning area is a key problem.Our empirical RFID-based human-computer interaction is to utilize RFID study shows that the phase contours are close to concentric localization schemes to directly locate tagged objects [2- circles with the antenna at the center.Hence,even for the 6,20-26].State-of-the-art systems mainly use phase values same rigid motion of the tagged object,the antenna could for the accurate localization [2-4,6,22,23].PinIt [2]uses collect different phase variations at different positions.To multi-path profiles of tags to accurately locate tags with the tackle this challenge,regarding to the relationship between synthetic aperture radar created via the antenna motion the tag movement and the phase variation,we split the Rather than the absolute localization,STPP [6]is the first whole scanning area into linear region and non-linear region. work to tackle 2D relative localization,which uses the Specifically,the tag movement in the linear region is linear spatial-temporal dynamics in the phase profiles to identify to the phase variation,thus we can extract the tag movement the relative positions of tags.More than only using the based on the phase variations detected from the two orthog- phase information,RFind [20]leverages the complete phys- onal antennas.While in the non-linear region,we locate the ical properties of RF-signals to realize the ultra-wideband tag first,then extract the tag movement based on the phase localization.RFind is capable of emulating over 220MHz of contours at the tag's position.3)How to obtain the absolute bandwidth without changing the tag and remains compliant touch position of the tag when the tag moves to any position with current regulations.However,most approaches figure with different orientations within the monitoring area is a key out the absolute positions of tags in a separate manner, problem.Existing work like [19]leverages the phase variation whereas RF-Dial aims to track the movement of the tag to detect the touch gesture,however,the phase is sensitive array in a comprehensive manner.By referring to the fixed to the position and orientation of the tag,so it can only topology of tag array,RF-Dial can accurately track the rigid track the touch position with the known start touch point transformation of tagged object,including the translation of a fixed tag.To tackle the challenge of determining the and rotation simultaneously.IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. XX, NO. XX, 2020 2 RFID Antenna Pair Track Rigid Motion · Rotation · Translation Rigid Motion Touch Tag: Detect Touch Gesture Movement Tags: Tagged Daily Objects Touch Gesture · Click · Press & Hold · Swipe Fig. 1. An example application scenario of RF-Dial rotation of the tagged object for each snapshot based on the rigid transformation model. Note that, the phase contours of RF-signals vary at different positions in the scanning area, the relationship between the tag movement and the phase variation is different, regarding to which we split the effective scanning area into linear region and non-linear region. Meanwhile, based on RF-signals from the touch tag, we build an RSSI-based model to depict the relationship be￾tween the touch position on the tag and the corresponding RSSI variation of received RF-signals. According to the RSSI￾based model, the RSSI deviation is mainly related to the impedance change when touching the tag, so it is position￾independent and orientation-insensitive. Consequently, we can rely on only one general RSSI deviation template to ac￾curately and robustly determine the touch position, without the known start touch position or the fixed tag deployment, among the whole monitoring area. There are three key challenges to realize RF-Dial. 1) How to estimate the rigid motion of the tagged object based on RF-signals of tags, including the translation and rotation simultaneously, is a key problem. To tackle this challenge, we build a rigid transformation model to reflect the relationship between the motion of the tagged object and the correspond￾ing phase variations of each movement tag in the tag array. As the topology of the movement tag array is fixed, we are able to decompose the rigid motion of the tagged object referring to the phase variations of at least two movement tags, and then derive the translation and the rotation of the tagged object for each snapshot during the motion. 2) How to address the variation of phase contours at different positions in the effective scanning area is a key problem. Our empirical study shows that the phase contours are close to concentric circles with the antenna at the center. Hence, even for the same rigid motion of the tagged object, the antenna could collect different phase variations at different positions. To tackle this challenge, regarding to the relationship between the tag movement and the phase variation, we split the whole scanning area into linear region and non-linear region. Specifically, the tag movement in the linear region is linear to the phase variation, thus we can extract the tag movement based on the phase variations detected from the two orthog￾onal antennas. While in the non-linear region, we locate the tag first, then extract the tag movement based on the phase contours at the tag’s position. 3) How to obtain the absolute touch position of the tag when the tag moves to any position with different orientations within the monitoring area is a key problem. Existing work like [19] leverages the phase variation to detect the touch gesture, however, the phase is sensitive to the position and orientation of the tag, so it can only track the touch position with the known start touch point of a fixed tag. To tackle the challenge of determining the absolute touch position, we observe that the RSSI deviation during the swipe is position-independent and orientation￾insensitive. We explore the signal variation when touching different positions on the tag, and build an RSSI-based model to verify the robustness of the RSSI deviation, which is mainly related to impedance change due to touch. Hence, based on the RSSI deviation, we can identify the absolute candidate touch positions. Note that, as the used linear tag has the dipole antenna, the RSSI variation during the swipe across the tag forms a symmetric Ω-wave pattern. To eliminate such ambiguity of touch positions, we use half of the tag as buttons and the other half as the slider. Referring to the RSSI variation, it is easy to determine which gesture is performed, thereby we can identify which part of the tag is touched and further derive the unique touch position. By tracking the consecutive touch positions of the swipe, we are able to estimate the swipe direction and distance. Overall, we make the following three main contribu￾tions. First, we propose a novel interaction scheme via RFID technology, supporting the rigid motion tracking and the touch gesture detection. An ordinary object can be turned into an intelligent HCI device via attaching a tag array on the side face together with one linear tag on the top face, denoted as movement tags and the touch tag, respec￾tively. Second, we build a phase-based model to reflect the relationship between the motion of tagged object and the corresponding phase variations of movement tags in the array. We also build an RSSI-based model to depict the rela￾tionship between the touch position and the corresponding RSSI deviation of the touch tag. Third, we implemented a prototype system of RF-Dial and evaluated its performance in the real environment. Extensive experiments show that RF-Dial achieves an accurate rigid motion tracking, with a small error of 0.6cm for translation tracking, and a small error of 1.9 degrees for rotation estimation. Besides, RF-Dial can also detect the touch gesture accurately, as the 90 percent of touch position errors are less than 2.09mm. 2 RELATED WORK RFID-based Localization: A straightforward solution for RFID-based human-computer interaction is to utilize RFID localization schemes to directly locate tagged objects [2– 6, 20–26]. State-of-the-art systems mainly use phase values for the accurate localization [2–4, 6, 22, 23]. PinIt [2] uses multi-path profiles of tags to accurately locate tags with the synthetic aperture radar created via the antenna motion. Rather than the absolute localization, STPP [6] is the first work to tackle 2D relative localization, which uses the spatial-temporal dynamics in the phase profiles to identify the relative positions of tags. More than only using the phase information, RFind [20] leverages the complete phys￾ical properties of RF-signals to realize the ultra-wideband localization. RFind is capable of emulating over 220MHz of bandwidth without changing the tag and remains compliant with current regulations. However, most approaches figure out the absolute positions of tags in a separate manner, whereas RF-Dial aims to track the movement of the tag array in a comprehensive manner. By referring to the fixed topology of tag array, RF-Dial can accurately track the rigid transformation of tagged object, including the translation and rotation simultaneously