variation,which is caused by the polarization direction change system can still accurately track the 3D motion of the relatively of the spin-antenna.Overall,our solution can accurately track complex environment with the heavy multi-path effect the translation and the rotation in the 3D space VII.CONCLUSION C.Impact of Number of Tags In this paper,we propose to track the 3D motion of a The tracking error of both the translation and the rota- tag array labeled objects via a spinning linearly polarized tion decreases when the number of tags increases.Then we antenna.By modeling the relationship between the tag array compare the tracking accuracy with the three tag arrays to and the spinning antenna,our system is able to sufficiently evaluate the impact of the number of tags.Fig.12(c)shows suppress the ambient signal interference and extract the most the translation error with the number of tags.We find that distinctive features.Based on the calibrated features.we design as the number of tags increases from 3 to 5,the translation corresponding solutions to track the translation based on the error along the X-axis decreases from 10.1cm to 6.6cm,and phase values,and estimate the rotation of the tag array from the translation error along the Z-axis decreases from 6.8cm to the RSSI variation.The extensive experiment results on the 5.7cm.The translation error along the Y-axis does not largely real testbed show that our solution can achieve an average reduce,because all the tags share the similar phase change due translation error of 13.6cm and an average rotation error of to the translation along the Y-axis.For the rotation error in 8.3°in the3 D space. Fig.12(d).we find that the error of the tag plane orientation ACKNOWLEDGMENTS decreases dramatically as we increase the number of tags.It This work is supported in part by National Natural Science is because the increment of the number of tags will increase Foundation of China under Grant Nos.61872174,61832008 phase pairs exponentially based on the phase model in Section 61872173,61802169;JiangSu Natural Science Foundation IV-C,providing more phase differences for the estimation. under Grant No.BK20180325.This work is partially sup- Besides,the error of the tag array rotation maintains small ported by Collaborative Innovation Center of Novel Software when we increase the number of tags,indicating the RSSI Technology and Industrialization.Lei Xie is the corresponding variation is stable to estimate the orientation of each tag author. D.Impact of Distance between Tag Array and Antenna REFERENCES The tracking error slightly increases as the distance between [1]H.Ding,L.Shangguan,Z.Yang.J.Han,Z.Zhou,P.Yang,W.Xi,and J.Zhao.Femo:A platform for free-weight exercise monitoring with the tag array and the antenna increases.We evaluate the rfids.In Proc.of ACM SenSys,2015. impact of the distance between the tag array and the antenna by [2]D.M.Dobkin.The rf in RFID:uhf RFID in practice.Newnes.2012. conducting the experiments at the distance of 150cm,250cm [3]M.Izz.Z.Li.H.Liu,Y.Chen,and F.Li.Uber-in-light:Unobtrusive and 350cm away from the antenna,respectively.Fig.12(e) visible light communication leveraging complementary color channel. In Proc.of IEEE INFOCOM,2016. shows the translation error along with the distance between [4]M.Jin,Y.He,X.Meng,Y.Zheng,D.Fang,and X.Chen.Fliptracer: the tag array and the antenna.It is found that the translation Practical parallel decoding for backscatter communication.In Proc.of error along the Y-axis is as low as 2.2cm,when the distance ACM Mobicom,2017. [5]T.Li,C.An,Z.Tian,A.T.Campbell,and X.Zhou.Human sensing is 150cm,and then increases to 4.1cm,when the distance using visible light communication.In Proc.of ACM Mobicom,2015. increases to 350cm.Therefore,even if the distance between the [6]Q.Lin,L.Yang,Y.Sun,T.Liu,X.-Y.Li,and Y.Liu.Beyond one-dollar tag array and the antenna indeed affects the translation error, mouse:A battery-free device for 3d human-computer interaction via rfid tags.In Proc.of IEEE INFOCOM,2015. our system can always keep the high tracking accuracy as [7]J.Liu,M.Chen,S.Chen,Q.Pan,and L.Chen.Tag-Compass: the distance increases.For the rotation error in Fig.12(f),the Determining the spatial direction of an object with small dimensions In Proc.of IEEE INFOCOM.2017. rotation errors are always below 15,even if the actual error [8]J.Liu,B.Xiao.S.Chen,F.Zhu,and L.Chen.Fast RFID grouping increases along with the increment of the distance between the protocols.In Proc.of IEEE INFOCOM,2015. tag array and the antenna. [9]L.Shangguan,Z.Zhou,and K.Jamieson.Enabling gesture-based interactions with object.In Proc.of ACM MobiSys,2017. E.Impact of Multi-path Effect [10]S.Shen,H.Wang,and R.R.Choudhury.I am a smartwatch and i can Our solution can accurately track the 3D motion in the track my users arm.In Proc.of ACM MobiSys,2016. [11]J.Wang,D.Vasisht,and D.Katabi.Rf-idraw:virtual touch screen in heavy multi-path effect environment.Finally,to evaluate the the air using rf signals.In Proc.of ACM SIGCOMM,2015. robustness of the spin-antenna in the 3D motion tracking,we [12]W.Wang.A.X.Liu,and K.Sun.Device-free gesture tracking using acoustic signals.In Proc.of ACM Mobicom,2016. deploy multiple iron plates around the spin-antenna to generate [13]T.Wei and X.Zhang.Gyro in the air:tracking 3d orientation of the heavy multi-path effect.Fig.12(g)and Fig.12(h)show batteryless interet-of-things.In Proc.of ACM Mobicom,2016. the corresponding translation error and the rotation error of [14]C.Xu,P.H.Pathak,and P.Mohapatra.Finger-writing with smartwatch: the heavy and the light multi-path effect.It is found that even A case for finger and hand gesture recognition using smartwatch.In Proc.of ACM HotMobile,2015. if the heavy multi-path effect leads to about 15cm translation [15]L.Yang,Y.Chen,X.-Y.Li,C.Xiao,M.Li,and Y.Liu.Tagoram:Real- error for both the X-axis and the Y-axis,we can still achieve time tracking of mobile rfid tags to high precision using cots devices In Proc.of ACM Mobicom,2014. the high accuracy for the y-axis.Besides,we also find that the [16]Z.Yang.C.Wu,Z.Zhou,X.Zhang.X.Wang.and Y.Liu.Mobility rotation error of the tag array rotation is also as small as 3.1 increases localizability:A survey on wireless indoor localization using with the heavy multi-path effect.It indicates that the relative inertial sensors.ACM Computing Surveys (CSUR),2015. RSSI variation is stable enough to resist the interference of [17]Y.Zheng.Y.He,M.Jin,X.Zheng.and Y.Liu.Red:Rfid-based eccentricity detection for high-speed rotating machinery.In Proc.of the multi-path effect.Therefore,the results proof that our IEEE INFOCOM.2018.variation, which is caused by the polarization direction change of the spin-antenna. Overall, our solution can accurately track the translation and the rotation in the 3D space. C. Impact of Number of Tags The tracking error of both the translation and the rota￾tion decreases when the number of tags increases. Then we compare the tracking accuracy with the three tag arrays to evaluate the impact of the number of tags. Fig. 12(c) shows the translation error with the number of tags. We find that as the number of tags increases from 3 to 5, the translation error along the X-axis decreases from 10.1cm to 6.6cm, and the translation error along the Z-axis decreases from 6.8cm to 5.7cm. The translation error along the Y -axis does not largely reduce, because all the tags share the similar phase change due to the translation along the Y -axis. For the rotation error in Fig. 12(d), we find that the error of the tag plane orientation decreases dramatically as we increase the number of tags. It is because the increment of the number of tags will increase phase pairs exponentially based on the phase model in Section IV-C, providing more phase differences for the estimation. Besides, the error of the tag array rotation maintains small when we increase the number of tags, indicating the RSSI variation is stable to estimate the orientation of each tag. D. Impact of Distance between Tag Array and Antenna The tracking error slightly increases as the distance between the tag array and the antenna increases. We evaluate the impact of the distance between the tag array and the antenna by conducting the experiments at the distance of 150cm, 250cm and 350cm away from the antenna, respectively. Fig. 12(e) shows the translation error along with the distance between the tag array and the antenna. It is found that the translation error along the Y -axis is as low as 2.2cm, when the distance is 150cm, and then increases to 4.1cm, when the distance increases to 350cm. Therefore, even if the distance between the tag array and the antenna indeed affects the translation error, our system can always keep the high tracking accuracy as the distance increases. For the rotation error in Fig. 12(f), the rotation errors are always below 15◦ , even if the actual error increases along with the increment of the distance between the tag array and the antenna. E. Impact of Multi-path Effect Our solution can accurately track the 3D motion in the heavy multi-path effect environment. Finally, to evaluate the robustness of the spin-antenna in the 3D motion tracking, we deploy multiple iron plates around the spin-antenna to generate the heavy multi-path effect. Fig. 12(g) and Fig. 12(h) show the corresponding translation error and the rotation error of the heavy and the light multi-path effect. It is found that even if the heavy multi-path effect leads to about 15cm translation error for both the X-axis and the Y -axis, we can still achieve the high accuracy for the Y -axis. Besides, we also find that the rotation error of the tag array rotation is also as small as 3.1 ◦ with the heavy multi-path effect. It indicates that the relative RSSI variation is stable enough to resist the interference of the multi-path effect. Therefore, the results proof that our system can still accurately track the 3D motion of the relatively complex environment with the heavy multi-path effect. VII. CONCLUSION In this paper, we propose to track the 3D motion of a tag array labeled objects via a spinning linearly polarized antenna. By modeling the relationship between the tag array and the spinning antenna, our system is able to sufficiently suppress the ambient signal interference and extract the most distinctive features. Based on the calibrated features, we design corresponding solutions to track the translation based on the phase values, and estimate the rotation of the tag array from the RSSI variation. The extensive experiment results on the real testbed show that our solution can achieve an average translation error of 13.6cm and an average rotation error of 8.3 ◦ in the 3D space. ACKNOWLEDGMENTS This work is supported in part by National Natural Science Foundation of China under Grant Nos. 61872174, 61832008, 61872173, 61802169; JiangSu Natural Science Foundation under Grant No. BK20180325. This work is partially sup￾ported by Collaborative Innovation Center of Novel Software Technology and Industrialization. Lei Xie is the corresponding author. REFERENCES [1] H. Ding, L. Shangguan, Z. Yang, J. Han, Z. Zhou, P. Yang, W. Xi, and J. Zhao. Femo: A platform for free-weight exercise monitoring with rfids. In Proc. of ACM SenSys, 2015. [2] D. M. Dobkin. The rf in RFID: uhf RFID in practice. Newnes, 2012. [3] M. Izz, Z. Li, H. Liu, Y. Chen, and F. Li. Uber-in-light: Unobtrusive visible light communication leveraging complementary color channel. In Proc. of IEEE INFOCOM, 2016. [4] M. Jin, Y. He, X. Meng, Y. Zheng, D. Fang, and X. Chen. Fliptracer: Practical parallel decoding for backscatter communication. In Proc. of ACM Mobicom, 2017. [5] T. Li, C. An, Z. Tian, A. T. Campbell, and X. Zhou. Human sensing using visible light communication. In Proc. of ACM Mobicom, 2015. [6] Q. Lin, L. Yang, Y. Sun, T. Liu, X.-Y. Li, and Y. Liu. Beyond one-dollar mouse: A battery-free device for 3d human-computer interaction via rfid tags. In Proc. of IEEE INFOCOM, 2015. [7] J. Liu, M. Chen, S. Chen, Q. Pan, and L. Chen. Tag-Compass: Determining the spatial direction of an object with small dimensions. In Proc. of IEEE INFOCOM, 2017. [8] J. Liu, B. Xiao, S. Chen, F. Zhu, and L. Chen. Fast RFID grouping protocols. In Proc. of IEEE INFOCOM, 2015. [9] L. Shangguan, Z. Zhou, and K. Jamieson. Enabling gesture-based interactions with object. In Proc. of ACM MobiSys, 2017. [10] S. Shen, H. Wang, and R. R. Choudhury. I am a smartwatch and i can track my users arm. In Proc. of ACM MobiSys, 2016. [11] J. Wang, D. Vasisht, and D. Katabi. Rf-idraw: virtual touch screen in the air using rf signals. In Proc. of ACM SIGCOMM, 2015. [12] W. Wang, A. X. Liu, and K. Sun. Device-free gesture tracking using acoustic signals. In Proc. of ACM Mobicom, 2016. [13] T. Wei and X. Zhang. Gyro in the air: tracking 3d orientation of batteryless internet-of-things. In Proc. of ACM Mobicom, 2016. [14] C. Xu, P. H. Pathak, and P. Mohapatra. Finger-writing with smartwatch: A case for finger and hand gesture recognition using smartwatch. In Proc. of ACM HotMobile, 2015. [15] L. Yang, Y. Chen, X.-Y. Li, C. Xiao, M. Li, and Y. Liu. Tagoram: Real￾time tracking of mobile rfid tags to high precision using cots devices. In Proc. of ACM Mobicom, 2014. [16] Z. Yang, C. Wu, Z. Zhou, X. Zhang, X. Wang, and Y. Liu. Mobility increases localizability: A survey on wireless indoor localization using inertial sensors. ACM Computing Surveys (CSUR), 2015. [17] Y. Zheng, Y. He, M. Jin, X. Zheng, and Y. Liu. Red: Rfid-based eccentricity detection for high-speed rotating machinery. In Proc. of IEEE INFOCOM, 2018. 9