计算机科学与技术（参考文献）Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings

IEEE INFOCOM 2018-IEEE Conference on Computer Communications Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings Chunhui Duan*,Lei Yangt,Huanyu Jia*,Qiongzheng Lint,Yunhao Liu*and Lei Xiet *School of Software and TNLIST,Tsinghua University.China fDepartment of Computing.The Hong Kong Polytechnic University,Hong Kong FDepartment of Computer Science and Technology,Nanjing University,China Email:[hui,young,jia,lin@tagsys.org,yunhao@greenorbs.com,Ixie@nju.edu.cn Abstract-Conventional spinning inspection systems,equipped with separated sensors (e.g.,accelerometer,laser,etc.)and com- munication modules,are either very expensive and/or suffering from occlusion and narrow field of view.The recently proposed RFID-based sensing solution draws much attention due to its intriguing features,such as being cost-effective,applicable to occluded objects and auto-identification,etc.However,this solution only works in quiet settings where the reader and MA spinning object remain absolutely stationary,as their shaking would ruin the periodicity and sparsity of the spinning signal (a)Quiet setting (b)Noisy setting making it impossible to be recovered.This work introduces Tagtwins,a robust spinning sensing system that can work in Fig.1:Frequency distributions of the spinning signal noisy settings.It addresses the challenge by attaching dual RFID collected in quiet or noisy settings.(a)The spectrum is com- tags on the spinning surface and developing a new formulation of spinning signal that is shaking-resilient,even if the shaking posed of several primary harmonic frequencies and thereby the involves unknown trajectories.Our main contribution lies in signal is very sparse in frequency domain as described in [2]. two newly developed techniques,relative spinning signal and (b)The spectrum is out of order and not sparse any more due dual compressive reading.We analytically demonstrate that our to the noise from surroundings. solution can work in various settings.We have implemented Tagtwins with COTS RFID devices and evaluated it extensively. To address the above issues,[2]proposes a novel measure- Experimental results show that Tagtwins can inspect the rotation frequency with high accuracy and robustness. ment approach(i.e.Tagbeat),which supplements the RFID Index Terms-RFID,spinning sensing,robust,dual-tag. communication functionality with fine-grained spinning (or vibration)sensing ability.Specifically,a slight and battery-free I.INTRODUCTION RFID tag is attached on the spinning object(i.e.turntable).The Spinning is a mechanical phenomenon which dominates spinning displaces the tag within a small range,resulting in our industrial lives everyday,such as conveyors,motors, a regular change pattern of backscatter signal.Then we can robotics,and so on.In many cases,spinning is undesirable and reveal the spinning information by discerning such communi- must be observed accurately,especially in smart factory.For cation pattern without specialized sensors.Compared against example,rotating machineries nowadays are widely employed traditional means,Tagbeat offers an appealing alternative,with in industrial equipment.The unexpected downtime due to the advantage of being cost-effective,applicable to occluded their undesirable vibrations has become more costly than objects,and auto-associative with the spinning object(by the ever before [1].In particular,utilizing spinning frequency for tag's ID).Moreover,since battery-free tags are powered and equipment diagnosis is a common method. driven by wireless signals,no additional energy suppliers or There are numerous traditional methods to inspect rotation.RF transceivers are required,making them small and light However,all of these methods are based on conventional enough to be attached on tiny objects. motion sensors,such as acceleration,infrared sensors or cam- In spite of high availability and promising foreground, eras.Unfortunately,most of them are bulky,heavy,intrusive, Tagbeat requires a quite rigorous assumption that the de- and energy-consuming.For example,accelerometers require vices and the deployment surroundings must remain quiet, wiredly connecting to a control panel for power supply and i.e.motionless and stationary.This assumption must hold signal transmission.Even integrated with WSN,they still need in practice because any irregular and unexpected jitters of extra and cumbersome batteries and transceivers,making it the tag's backscatter signal incurred by the shaking of the impossible to sense the rotation of small objects with high reader,the turntable,or the changes of surroundings,would spinning speed.Infrared sensors are common choices for disturb the periodicity of spinning signal and further violate its high-resolution and high-speed measurements,but fail in the sparsity in frequency domain.Fig.I compares the spectrums absence of a line-of-sight to the objects.High-speed cameras of two spinning signals collected in quiet and noisy settings may be another option,but are seldom adopted in industry due respectively.Clearly,Tagbeat,which is driven by the technique to their high cost. of compressive sensing,fails to recover the non-sparse signal 978-1-5386-4128-6/18/$31.00©20181EEE

Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings Chunhui Duan⇤, Lei Yang†, Huanyu Jia⇤, Qiongzheng Lin†, Yunhao Liu⇤ and Lei Xie‡ ⇤School of Software and TNLIST, Tsinghua University, China †Department of Computing, The Hong Kong Polytechnic University, Hong Kong ‡Department of Computer Science and Technology, Nanjing University, China Email: {hui, young, jia, lin}@tagsys.org, yunhao@greenorbs.com, lxie@nju.edu.cn Abstract—Conventional spinning inspection systems, equipped with separated sensors (e.g., accelerometer, laser, etc.) and com￾munication modules, are either very expensive and/or suffering from occlusion and narrow field of view. The recently proposed RFID-based sensing solution draws much attention due to its intriguing features, such as being cost-effective, applicable to occluded objects and auto-identification, etc. However, this solution only works in quiet settings where the reader and spinning object remain absolutely stationary, as their shaking would ruin the periodicity and sparsity of the spinning signal, making it impossible to be recovered. This work introduces Tagtwins, a robust spinning sensing system that can work in noisy settings. It addresses the challenge by attaching dual RFID tags on the spinning surface and developing a new formulation of spinning signal that is shaking-resilient, even if the shaking involves unknown trajectories. Our main contribution lies in two newly developed techniques, relative spinning signal and dual compressive reading. We analytically demonstrate that our solution can work in various settings. We have implemented Tagtwins with COTS RFID devices and evaluated it extensively. Experimental results show that Tagtwins can inspect the rotation frequency with high accuracy and robustness. Index Terms—RFID, spinning sensing, robust, dual-tag. I. INTRODUCTION Spinning is a mechanical phenomenon which dominates our industrial lives everyday, such as conveyors, motors, robotics, and so on. In many cases, spinning is undesirable and must be observed accurately, especially in smart factory. For example, rotating machineries nowadays are widely employed in industrial equipment. The unexpected downtime due to their undesirable vibrations has become more costly than ever before [1]. In particular, utilizing spinning frequency for equipment diagnosis is a common method. There are numerous traditional methods to inspect rotation. However, all of these methods are based on conventional motion sensors, such as acceleration, infrared sensors or cam￾eras. Unfortunately, most of them are bulky, heavy, intrusive, and energy-consuming. For example, accelerometers require wiredly connecting to a control panel for power supply and signal transmission. Even integrated with WSN, they still need extra and cumbersome batteries and transceivers, making it impossible to sense the rotation of small objects with high spinning speed. Infrared sensors are common choices for high-resolution and high-speed measurements, but fail in the absence of a line-of-sight to the objects. High-speed cameras may be another option, but are seldom adopted in industry due to their high cost. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 Frequency (Hz) Energy Harmonic frequency (a) Quiet setting 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 Frequency (Hz) Energy (b) Noisy setting Fig. 1: Frequency distributions of the spinning signal collected in quiet or noisy settings. (a) The spectrum is com￾posed of several primary harmonic frequencies and thereby the signal is very sparse in frequency domain as described in [2]. (b) The spectrum is out of order and not sparse any more due to the noise from surroundings. To address the above issues, [2] proposes a novel measure￾ment approach (i.e. Tagbeat), which supplements the RFID communication functionality with fine-grained spinning (or vibration) sensing ability. Specifically, a slight and battery-free RFID tag is attached on the spinning object (i.e. turntable). The spinning displaces the tag within a small range, resulting in a regular change pattern of backscatter signal. Then we can reveal the spinning information by discerning such communi￾cation pattern without specialized sensors. Compared against traditional means, Tagbeat offers an appealing alternative, with the advantage of being cost-effective, applicable to occluded objects, and auto-associative with the spinning object (by the tag’s ID). Moreover, since battery-free tags are powered and driven by wireless signals, no additional energy suppliers or RF transceivers are required, making them small and light enough to be attached on tiny objects. In spite of high availability and promising foreground, Tagbeat requires a quite rigorous assumption that the de￾vices and the deployment surroundings must remain quiet, i.e. motionless and stationary. This assumption must hold in practice because any irregular and unexpected jitters of the tag’s backscatter signal incurred by the shaking of the reader, the turntable, or the changes of surroundings, would disturb the periodicity of spinning signal and further violate its sparsity in frequency domain. Fig. 1 compares the spectrums of two spinning signals collected in quiet and noisy settings respectively. Clearly, Tagbeat, which is driven by the technique of compressive sensing, fails to recover the non-sparse signal IEEE INFOCOM 2018 - IEEE Conference on Computer Communications 978-1-5386-4128-6/18/$31.00 ©2018 IEEE

IEEE INFOCOM 2018-IEEE Conference on Computer Communications counters numerous challenges.First,the measured phase val- ues are discontinuous due to the operation of mod.Worsely, the phase may randomly jump radians because of the half- wave loss phenomenon [3].Second,1=2 =0 happens Turntable only when two tags are attached on a straight line which passes through the turntable center.Apparently,we do not Fig.2:Spinning sensing with dual-tags expect to attach tags under some scheduled rules,thus,the two because there are too many linear combinations.Many real formulas cannot be simply merged together like this.Third, scenarios are against such assumption.For instance,industrial all COTS tags are randomly and exclusively read in a time- sharing fashion to avoid signal collisions.It is impossible to operations can happen in unstable platforms (e.g.vehicles and ships),whose shaking would lead to dramatic translations of simultaneously acquire the two tags'phase values at a same readers and tags.It is also hard to let a worker stably hold a time point for the calculation of relative phase.To address these challenges,we firstly develop Relative Spinning Signal handheld reader for a long time measurement.Our empirical study suggests that even a 5cm noisy translation of the device (RSS).We analytically demonstrate that RSS is resilient to would make the spinning signal unrecoverable. surrounding noise even in the presence of multipath effect. Motivated by the above limitation,we present Tagtwins,a Importantly,the underlying sparsity assumption that compres- robust spinning sensing system that can work in noisy settings. sive reading [2]is built on still holds true.We then design Here noise means unpredictable shaking or translation of and implement Dual Compressive Reading (DCR)to recover RSS using COTS RFID devices,with no extra infrastructure devices (readers and/or spinning objects).Tagtwins addresses the challenge by attaching dual RFID tags on the spinning or pre-calibration efforts. surface,as shown in Fig.2,and develops a new formulation Contributions:Tagtwins enhances the RFID-enabled sys- tem that makes sense of mechanical rotation within sub-hertz of spinning signal that is shaking-resilient.We allow both the turntable and reader to be randomly and simultaneously shaken accuracy using dual tags'backscatter signals.It addresses when monitoring the spinning.Even if the shaking involves a practical problem of how to robustly sense spinning in unknown trajectories,we can accurately recover its spinning noisy settings.Second,we develop RSS to depict the shake- resilient sensing,and DCR to inspect high-frequency spinning. signal.To this end,we exploit the observation that the distance between two tags is fixed independent of how the turntable or Third,we implement and evaluate our prototype with extensive the reader shakes.Leveraging this,we develop the relative experiments,demonstrating the practicality and effectiveness spinning signal which is derived from the relative wireless of our design. channels of two tags,to depict the spinning that occurs in noisy II.OVERVIEW settings,without knowing any information on the absolute position or translation of the devices. Tagtwins is an RFID-based solution for inspecting me- To quickly grasp our basic idea,we give a simplified chanical spinning frequency of any objects.Although we explanation why our relative spinning signal can work.As present the system in the context of spinning in most of shown in Fig.2,the phase values of signals backscattered the time,Tagtwins'technique could be applied to any other from tag Ti and T2 are respectively given by modalities of periodic mechanical motion (like vibration or pendulum).Specifically,it decomposes the sensing problem 01()≈红(d-n1cos(2mft+1》mod2m into the following two cases: (1) Sensing with a single tag.We firstly consider a simplified 4π 02(t)≈ (d-ra cos(2f+))mod 2 case where a single tag is used to sense the spinning in quiet settings in Sec.III.Correspondingly,we develop the where A is the wavelength,d is the distance between the reader refined spinning signal with the RF phase values to address and turntable center,fs is the spinning frequency,ri,r2 are the discontinuity caused by either the modulus operation or distances of two tags to the turntable center,and 1.2 are the half-wave loss. the initial angles of two tags.The detailed geometric model is Sensing with dual tags.We then consider a general presented in Sec.III.Assuming1=2=0,we can obtain case where dual tags are used to defend against signal noises the relative phase by subtracting the above two equations: introduced by the devices or the surroundings in Sec.IV. △0)=4r (r2-r1)cos(2nfst)mod 2m (2) Correspondingly,we develop the relative spinning signal to enhance the system robustness. Clearly,the distance d is perfectly eliminated from the for- The next few sections elaborate on the above steps,provid- mula.This means that no mater how the reader or the turntable ing the technical details. moves,the relative phase is only dependent on fs.Meanwhile, A(t)also maintains the same frequency as the original. III.SENSING WITH A SINGLE TAG One might consider using the above relative phase as the In this section,we introduce RFID-based spinning sensing spinning signal.Unfortunately,performing it in practice en- with a single tag as well as its limitations

O T1 T2 Turntable Shaking Reader Fig. 2: Spinning sensing with dual-tags because there are too many linear combinations. Many real scenarios are against such assumption. For instance, industrial operations can happen in unstable platforms (e.g. vehicles and ships), whose shaking would lead to dramatic translations of readers and tags. It is also hard to let a worker stably hold a handheld reader for a long time measurement. Our empirical study suggests that even a 5cm noisy translation of the device would make the spinning signal unrecoverable. Motivated by the above limitation, we present Tagtwins, a robust spinning sensing system that can work in noisy settings. Here noise means unpredictable shaking or translation of devices (readers and/or spinning objects). Tagtwins addresses the challenge by attaching dual RFID tags on the spinning surface, as shown in Fig. 2, and develops a new formulation of spinning signal that is shaking-resilient. We allow both the turntable and reader to be randomly and simultaneously shaken when monitoring the spinning. Even if the shaking involves unknown trajectories, we can accurately recover its spinning signal. To this end, we exploit the observation that the distance between two tags is fixed independent of how the turntable or the reader shakes. Leveraging this, we develop the relative spinning signal which is derived from the relative wireless channels of two tags, to depict the spinning that occurs in noisy settings, without knowing any information on the absolute position or translation of the devices. To quickly grasp our basic idea, we give a simplified explanation why our relative spinning signal can work. As shown in Fig. 2, the phase values of signals backscattered from tag T1 and T2 are respectively given by ✓1(t) ⇡ 4⇡ λ (d − r1 cos(2⇡fst + φ1)) mod 2⇡ ✓2(t) ⇡ 4⇡ λ (d − r2 cos(2⇡fst + φ2)) mod 2⇡ (1) where λ is the wavelength, d is the distance between the reader and turntable center, fs is the spinning frequency, r1, r2 are distances of two tags to the turntable center, and φ1, φ2 are the initial angles of two tags. The detailed geometric model is presented in Sec. III. Assuming φ1 = φ2 = 0, we can obtain the relative phase by subtracting the above two equations: ∆✓(t) = 4⇡ λ (r2 − r1) cos(2⇡fst) mod 2⇡ (2) Clearly, the distance d is perfectly eliminated from the for￾mula. This means that no mater how the reader or the turntable moves, the relative phase is only dependent on fs. Meanwhile, ∆✓(t) also maintains the same frequency as the original. One might consider using the above relative phase as the spinning signal. Unfortunately, performing it in practice en￾counters numerous challenges. First, the measured phase val￾ues are discontinuous due to the operation of mod. Worsely, the phase may randomly jump ⇡ radians because of the half￾wave loss phenomenon [3]. Second, φ1 = φ2 = 0 happens only when two tags are attached on a straight line which passes through the turntable center. Apparently, we do not expect to attach tags under some scheduled rules, thus, the two formulas cannot be simply merged together like this. Third, all COTS tags are randomly and exclusively read in a time￾sharing fashion to avoid signal collisions. It is impossible to simultaneously acquire the two tags’ phase values at a same time point for the calculation of relative phase. To address these challenges, we firstly develop Relative Spinning Signal (RSS). We analytically demonstrate that RSS is resilient to surrounding noise even in the presence of multipath effect. Importantly, the underlying sparsity assumption that compres￾sive reading [2] is built on still holds true. We then design and implement Dual Compressive Reading (DCR) to recover RSS using COTS RFID devices, with no extra infrastructure or pre-calibration efforts. Contributions: Tagtwins enhances the RFID-enabled sys￾tem that makes sense of mechanical rotation within sub-hertz accuracy using dual tags’ backscatter signals. It addresses a practical problem of how to robustly sense spinning in noisy settings. Second, we develop RSS to depict the shake￾resilient sensing, and DCR to inspect high-frequency spinning. Third, we implement and evaluate our prototype with extensive experiments, demonstrating the practicality and effectiveness of our design. II. OVERVIEW Tagtwins is an RFID-based solution for inspecting me￾chanical spinning frequency of any objects. Although we present the system in the context of spinning in most of the time, Tagtwins’ technique could be applied to any other modalities of periodic mechanical motion (like vibration or pendulum). Specifically, it decomposes the sensing problem into the following two cases: • Sensing with a single tag. We firstly consider a simplified case where a single tag is used to sense the spinning in quiet settings in Sec. III. Correspondingly, we develop the refined spinning signal with the RF phase values to address the discontinuity caused by either the modulus operation or the half-wave loss. • Sensing with dual tags. We then consider a general case where dual tags are used to defend against signal noises introduced by the devices or the surroundings in Sec. IV. Correspondingly, we develop the relative spinning signal to enhance the system robustness. The next few sections elaborate on the above steps, provid￾ing the technical details. III. SENSING WITH A SINGLE TAG In this section, we introduce RFID-based spinning sensing with a single tag as well as its limitations. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

IEEE INFOCOM 2018-IEEE Conference on Computer Communications Y牡 2nd perio (a)Original phase sequence (b)Refined spinning signal (c)Distorted spinning signal Fig.3:Spinning signals induced by a spinning tag.(a)Original phase sequence 0(t),which is split into many short discontinuous fragments due to the operation of mod and half-wave loss.(b)The refined spinning signal s(t),which is continuous,smooth and periodic as the original one.(c)The Distorted spinning signal caused by the shaking of reader. 8(t)=rcos(2xfst+) RT is approximately equal to RA(RO L AT)when the reader is far away from the tag (e.g.>2A)[6].Substituting Eqn.4 into Eqn.3,we have the revised phase function: 9e0≈Fd-ros(2rft+o》mod2m (5) From the equation,we see that the RF phase is a cosine signal Turntable which has a fundamental frequency as same as the spinning. Fig.4:Geometric model for spinning.The clockwise ro- Thus,RF phase can be considered as a raw spinning signal. tating turntable displaces the attached tag T along a circle, B.Refining Spinning Signal leading to a varying phase shift. With respect to the continuity,using RF phase as spinning signal raises two issues in practice.First,the measured phase A.Modeling Spinning Signal value jumps when it approaches to 0 or 2m due to the mod The concept underlying spinning sensing is to develop a operation [2].Second,COTS reader may introduce m radians spinning signal which has a fundamental period or frequency of ambiguity such that the reported phase can be the true phase as same as the spinning itself,such that we can inspect (or the true phase plus radians (+due to the half- the states of the spinning through this signal.Using RFID wave loss [3].These two issues cause the measured phase tag (which is attached on a turntable)for spinning sensing out of order.Fig.3(a)presents an example of phase sequence considers all discrete,random and low-frequency readings of which is collected in our lab.From the figure,we can see that the tag as samplings of the spinning states.The goal is to the sequence is split up into many short discontinuous series, develop a continuous spinning signal through these readings. which goes against our analysis of their frequency or period. The RF phase is a common parameter supported by com- To address them,we transform the original phase 0(t)to the mercial RFID readers [4].Suppose a tag T is attached on the space of sin(20).Then,the spinning signal,denoted as s(t), turntable.Let d=|RO and r ITO]as sketched in Fig.4. is refined as: Then the phase shift during the spinning is defined as [3]: s()=sin(20()≈sin (6 ()d()+bax mod 2 (a-ros2ft+） (3) Suppose the original period equals T(T=1/fs).It is easy to where the term Odiv(called as diversity term)denotes the figure out that s(t+Ts)=sin(20(t+Ts))=sin(20(t))=s(t), constant phase shift introduced by the device's hardware that is,the refined spinning signal maintains the period as the characteristics [5].As 0div is a constant term which remains original phase sequence.Meanwhile,the refined signal is also unchanged during the measurement,we can omit this term for resistant to haft-wave loss (see Theorem.1). simplicity.Note the total distance is 2(d-6(t))because the signal traverses a double distance back and forth in backscatter Theorem 1.The refined spinning signal does eliminate the communication.o(t)is the function of time-varying displace- T-ambiguity caused by half-wave loss. ment due to the spinning,which can be expressed as: Proof.Because sin(2(θ(t)±π)=sin(29(t)±2r）= 6(t)≈rcos(2πfst+φ) (4) sin(20(t)),s(t)has the same value no matter the reported value equals 6 or 6+m.Thus,the refined spinning signal where f,is the spinning frequency that we expect to inspect,resists to half-wave loss. 口 and o is the initial angle TOR when t =0.Note the distance Fig.3(b)illustrates an example of the refined spinning IIt is easy to show that its omission does not affect our subsequent signal,which is much more smooth and continuous compared derivation and the periodicity of the spinning signal. against the original phase sequence shown in Fig.3(a)

0 1 2 3 4 5 6 x 104 −2 0 2 4 6 8 Time (ms) Phase (rad) mod π half−wave loss 1st period 2nd period 2π 3rd period (a) Original phase sequence 0 1 2 3 4 5 6 x 104 −1.5 −1 −0.5 0 0.5 1 1.5 Time (ms) s(t) 1st period 2nd period 3rd period (b) Refined spinning signal 0 1 2 3 4 5 6 x 104 −1.5 −1 −0.5 0 0.5 1 1.5 Time (ms) s(t) 1st period 2nd period 3rd period (c) Distorted spinning signal Fig. 3: Spinning signals induced by a spinning tag. (a) Original phase sequence ✓(t), which is split into many short discontinuous fragments due to the operation of mod and half-wave loss. (b) The refined spinning signal s(t), which is continuous, smooth and periodic as the original one. (c) The Distorted spinning signal caused by the shaking of reader. T Turntable Clockwise R O A d δ(t) = r cos(2⇡fst + φ) r 2⇡fst + φ Fig. 4: Geometric model for spinning. The clockwise ro￾tating turntable displaces the attached tag T along a circle, leading to a varying phase shift. A. Modeling Spinning Signal The concept underlying spinning sensing is to develop a spinning signal which has a fundamental period or frequency as same as the spinning itself, such that we can inspect the states of the spinning through this signal. Using RFID tag (which is attached on a turntable) for spinning sensing considers all discrete, random and low-frequency readings of the tag as samplings of the spinning states. The goal is to develop a continuous spinning signal through these readings. The RF phase is a common parameter supported by com￾mercial RFID readers [4]. Suppose a tag T is attached on the turntable. Let d = |RO| and r = |T O| as sketched in Fig. 4. Then the phase shift during the spinning is defined as [3]: ✓(t) = 4⇡ λ (d − δ(t)) + ✓div mod 2⇡ (3) where the term ✓div (called as diversity term) denotes the constant phase shift introduced by the device’s hardware characteristics [5]. As ✓div is a constant term which remains unchanged during the measurement, we can omit this term for simplicity1. Note the total distance is 2(d − δ(t)) because the signal traverses a double distance back and forth in backscatter communication. δ(t) is the function of time-varying displace￾ment due to the spinning, which can be expressed as: δ(t) ⇡ r cos(2⇡fst + φ) (4) where fs is the spinning frequency that we expect to inspect, and φ is the initial angle \TOR when t = 0. Note the distance 1It is easy to show that its omission does not affect our subsequent derivation and the periodicity of the spinning signal. |RT| is approximately equal to |RA| (RO ? AT) when the reader is far away from the tag (e.g. > 2λ) [6]. Substituting Eqn. 4 into Eqn. 3, we have the revised phase function: ✓(t) ⇡ 4⇡ λ (d − r cos(2⇡fst + φ)) mod 2⇡ (5) From the equation, we see that the RF phase is a cosine signal which has a fundamental frequency as same as the spinning. Thus, RF phase can be considered as a raw spinning signal. B. Refining Spinning Signal With respect to the continuity, using RF phase as spinning signal raises two issues in practice. First, the measured phase value jumps when it approaches to 0 or 2⇡ due to the mod operation [2]. Second, COTS reader may introduce ⇡ radians of ambiguity such that the reported phase can be the true phase (✓) or the true phase plus ⇡ radians (✓ + ⇡) due to the half￾wave loss [3]. These two issues cause the measured phase out of order. Fig. 3(a) presents an example of phase sequence which is collected in our lab. From the figure, we can see that the sequence is split up into many short discontinuous series, which goes against our analysis of their frequency or period. To address them, we transform the original phase ✓(t) to the space of sin(2✓). Then, the spinning signal, denoted as s(t), is refined as: s(t) = sin(2✓(t)) ⇡ sin ✓8⇡ λ (d − r cos(2⇡fst + φ))◆ (6) Suppose the original period equals Ts (Ts = 1/fs). It is easy to figure out that s(t+Ts) = sin(2✓(t+Ts)) = sin(2✓(t)) = s(t), that is, the refined spinning signal maintains the period as the original phase sequence. Meanwhile, the refined signal is also resistant to haft-wave loss (see Theorem. 1). Theorem 1. The refined spinning signal does eliminate the ⇡-ambiguity caused by half-wave loss. Proof. Because sin(2(✓(t) ± ⇡)) = sin(2✓(t) ± 2⇡) = sin(2✓(t)), s(t) has the same value no matter the reported value equals ✓ or ✓ ± ⇡. Thus, the refined spinning signal resists to half-wave loss. Fig. 3(b) illustrates an example of the refined spinning signal, which is much more smooth and continuous compared against the original phase sequence shown in Fig. 3(a). IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

IEEE INFOCOM 2018-IEEE Conference on Computer Communications dtd Fig.5:Illustration of device translation in 2D.The reader translates from position R to R'. (a)Spinning with shaking (b)Relative spinning model Fig.6:Illustration of relative spinning.(a)Although the C.Limitations of Single-Tag Based Approach turntable translates a lot when it is spinning,the relative distance between two tags remain unchanged.(b)From the The refined spinning signal is a good indicator to describe perspective of T1,T2 appears to move around Ti in a circle. the spinning in quiet settings.However,such signal heavily Thus,the relative phase only depends on the spinning itself depends on d,i.e.the distance between the reader and turntable instead of the shaking induced translation. center,as suggested in Eqn.6.As aforementioned,it is hard to hold the distance in noisy industrial settings.Even tiny shaking of the reader or the turntable would introduce not change.We can get the two tags'phase values when the unpredictable distances.This is the reason why the prior reader is translated to position R'as follows: work [2]requires a mandatory assumption that both the RFID 4π reader and spinning source have no additional displacements 0h(④≈元(d+△d-ncos(2rf.t+血+a》mod2m except those induced by the spinning during the measurement. 4T 02(t)≈ Further,the final received phase is derived from a combination (d+△d0-r2cos(2xf.t+2+a》mod2x of multiple copies of RF signals due to multipath effect.The Then,we define the relative phase of the two tags (denoted as measured phase value usually far deviates from the expected A(t))by subtracting their phase values.Since (a-b)mod one.Fig.3(c)shows the spinning signal acquired from a same c=(a mod c-b mod c)mod c,A0(t)can be given by: spinning process as shown in Fig.3(b)but under a noisy △0(t)=(0(t)-02(t)mod2m environment.Clearly,it totally cannot represent the original spinning any more.Therefore,we need to develop a more (ra cos(2+a)-r1 cos(2+a))mod 2 robust spinning signal. (r2 cos(+a)-ri cos(+))cos(2) (r2 sin(2 +a)-ri sin(1+a))sin(2fst)]mod 2 IV.SENSING WITH DUAL TAGS rcos(2f+arctan 2)mod 2 a (7) We call the instability caused by either motion of devices where or changes of environment as system shaking.The approach which can tolerate the system shaking is called as anti-shaking a1 =T2 coS(62+a)-r1 cos(1+a) sensing.We attach dual tags on the same spinning object to a2 r2 sin(2 +a)-ri sin(o1 +a) achieve more robust sensing r=Vai+a It is easy to find that r is actually the separated distance of A.Rationale Behind Anti-Shaking Sensing two tags.Both the variables d and Ad(t)are removed by the subtraction,which means the relative phase at an arbitrary time Why could dual tags resist shaking?We begin to answer this is independent of either the initial position or device translation question from line-of-sight scenario(i.e.free-space scenario), as long as the reader's direction does not change.Eqn.7 fully where the signal from the reader arrives along one dominate considers the initial angles of both tags when t=0,which path,and then discuss it in a more complex scenario with allows to attach tags at arbitrary positions on the turntable as multipath effect later. long as they are driven by the same spinning.Interestingly,the Relative phase:For simplicity,we assume that both tags relative phase can be finally converted into a cosine function and the reader lie on a two dimensional plane (extension to with the same frequency as the spinning,like what we discuss 3D will be addressed later).We consider the dual tags Ti and with a single tag. T2 are attached on a turntable,as shown in Fig.5.The reader We can also understand the relative phase from another situates at direction a (i.e.the angle of arrival).When the intuitive perspective.Relative to the position of T,the second tags rotate an angle of 2mft at time t,we observe Ad(t)tag T2 simply appears to move around a circle,as illustrated in translation between RO and R'O due to the shaking of the Fig.6(a).Although the turntable translates due to the shaking, reader or the target.Notice that here we have a reasonable the relative distance between two tags remains unchanged.In assumption that the reader is at a far distance compared to other words,two tags perform relative motion driven by the the movement of devices,thus,the angle of arrival a does spinning instead of the shaking.In this way,we can simplify

O d + ∆d d 2⇡fst T1 T2 R Shaking 0 R ↵ 2⇡fst Fig. 5: Illustration of device translation in 2D. The reader translates from position R to R0 . C. Limitations of Single-Tag Based Approach The refined spinning signal is a good indicator to describe the spinning in quiet settings. However, such signal heavily depends on d, i.e. the distance between the reader and turntable center, as suggested in Eqn. 6. As aforementioned, it is hard to hold the distance in noisy industrial settings. Even tiny shaking of the reader or the turntable would introduce unpredictable distances. This is the reason why the prior work [2] requires a mandatory assumption that both the RFID reader and spinning source have no additional displacements except those induced by the spinning during the measurement. Further, the final received phase is derived from a combination of multiple copies of RF signals due to multipath effect. The measured phase value usually far deviates from the expected one. Fig. 3(c) shows the spinning signal acquired from a same spinning process as shown in Fig. 3(b) but under a noisy environment. Clearly, it totally cannot represent the original spinning any more. Therefore, we need to develop a more robust spinning signal. IV. SENSING WITH DUAL TAGS We call the instability caused by either motion of devices or changes of environment as system shaking. The approach which can tolerate the system shaking is called as anti-shaking sensing. We attach dual tags on the same spinning object to achieve more robust sensing. A. Rationale Behind Anti-Shaking Sensing Why could dual tags resist shaking? We begin to answer this question from line-of-sight scenario (i.e. free-space scenario), where the signal from the reader arrives along one dominate path, and then discuss it in a more complex scenario with multipath effect later. Relative phase: For simplicity, we assume that both tags and the reader lie on a two dimensional plane (extension to 3D will be addressed later). We consider the dual tags T1 and T2 are attached on a turntable, as shown in Fig. 5. The reader situates at direction ↵ (i.e. the angle of arrival). When the tags rotate an angle of 2⇡fst at time t, we observe ∆d(t) translation between RO and R0 O due to the shaking of the reader or the target. Notice that here we have a reasonable assumption that the reader is at a far distance compared to the movement of devices, thus, the angle of arrival ↵ does t1 t2 t3 Translations of turntable (a) Spinning with shaking t1 t2 t3 T1 T2 r ↵ r cos(2⇡fst + φ + ↵) (b) Relative spinning model Fig. 6: Illustration of relative spinning. (a) Although the turntable translates a lot when it is spinning, the relative distance between two tags remain unchanged. (b) From the perspective of T1, T2 appears to move around T1 in a circle. Thus, the relative phase only depends on the spinning itself instead of the shaking induced translation. not change. We can get the two tags’ phase values when the reader is translated to position R0 as follows: ✓1(t) ⇡ 4⇡ λ (d + ∆d(t) − r1 cos(2⇡fst + φ1 + ↵)) mod 2⇡ ✓2(t) ⇡ 4⇡ λ (d + ∆d(t) − r2 cos(2⇡fst + φ2 + ↵)) mod 2⇡ Then, we define the relative phase of the two tags (denoted as ∆✓(t)) by subtracting their phase values. Since (a − b) mod c = (a mod c − b mod c) mod c, ∆✓(t) can be given by: ∆✓(t)=(✓1(t) − ✓2(t)) mod 2⇡ ⇡ 4⇡ λ (r2 cos(2⇡fst + φ2 + ↵) − r1 cos(2⇡fst + φ1 + ↵)) mod 2⇡ = 4⇡ λ [(r2 cos(φ2 + ↵) − r1 cos(φ1 + ↵)) cos(2⇡fst) − (r2 sin(φ2 + ↵) − r1 sin(φ1 + ↵)) sin(2⇡fst)] mod 2⇡ = 4⇡ λ r cos(2⇡fst + arctan a2 a1 ) mod 2⇡ (7) where 8 < : a1 = r2 cos(φ2 + ↵) − r1 cos(φ1 + ↵) a2 = r2 sin(φ2 + ↵) − r1 sin(φ1 + ↵) r = pa2 1 + a2 2 It is easy to find that r is actually the separated distance of two tags. Both the variables d and ∆d(t) are removed by the subtraction, which means the relative phase at an arbitrary time is independent of either the initial position or device translation as long as the reader’s direction does not change. Eqn. 7 fully considers the initial angles of both tags when t = 0, which allows to attach tags at arbitrary positions on the turntable as long as they are driven by the same spinning. Interestingly, the relative phase can be finally converted into a cosine function with the same frequency as the spinning, like what we discuss with a single tag. We can also understand the relative phase from another intuitive perspective. Relative to the position of T1, the second tag T2 simply appears to move around a circle, as illustrated in Fig. 6(a). Although the turntable translates due to the shaking, the relative distance between two tags remains unchanged. In other words, two tags perform relative motion driven by the spinning instead of the shaking. In this way, we can simplify IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

IEEE INFOCOM 2018-IEEE Conference on Computer Communications follows [6]: 1的≈5c奖 (11) (,a2 h2(t)≈∑ 9 where d is the distance from the reader to T through the Fig.7:Multipath scenario.Because of two reflectors,the signal coming from reader propagates through two different kth propagation path,and r cos(2f+)is the saved distance to T2 compared with T.Then we compute the paths with different directions and distances. relative wireless channel h(t)=h1(t)h(t): the relative phase using another equivalent model as shown K 1eJd 1 -J经(dk-rcos(2xfat+中+ak) in Fig.6(b).Suppose the angle of arrival and the distance h(t)= between two tags are equal to a and r respectively,then the (12) K relative phase is also given by: 马9reos(2mt++a) +e (dx-dp) ≠k △9④=rcos(2mft++amod2x (8) Notice that the phase of the first term,i.e.r cos(2ft where o is the initial angle between TT2 and x-axis at time )in the above equation is nearly identical to the relative t =0,and rcos(2mft++a)is the saved distance of phase in Eqn.8 derived in the line-of-sight scenario,and is signal propagating to T2 compared with that to T1.It is easy independent of any translation.Unfortunately,the second term to prove that Eqn.7 and Eqn.8 are completely equivalent and indeed depends on the distances.However,two observations convertible.We will use Egn.8 by default in the subsequent inspire us:First,if the environment remains constant (i.e.,mul- sections for simplicity. tiple propagations hold),the second term reduces to a constant Relative spinning signal:Similarly,to deal with the dis-multiplier,which merely scales the final phase value.Second. continuity of phase,we formally define the relative spinning even if the environment changes or the shaking changes the signal (RSS)as below: propagations,any variance caused by the second term drops significantly when summing over all multipath propagations. s(t)=sin(2△9t)=sin(291(t)-202(t) (9) These two observations show that RSS is resistant to shaking 1 and 02 are measured phase values of two tags in prac- even in multipath scenarios.This property holds no mater tice.One might wonder if the periodicity generated by the how the turntable or the reader is shaken.Even so,we must above equation is indeed maintained as that of the actual stress that shaking-induced translation cannot be unbounded spinning.In fact,it is easy to observe from Eqn.9 that and must be relatively small compared to the distance between s(t+T)=sin(20(t+T.))=sin(2A0(t))=s(t).We the turntable and the reader,even if the reader/turntable shakes can also intuitively understand such conclusion from Fig.6. moderately.This is not a harsh assumption and can be easily The only movement that drives T2 to rotate around Ti is the met in practice as validated in our evaluation. spinning of the turntable. C.Extending to Three Dimensional Scenario B.Dealing with Multipath Effect Let us now consider the RSS in 3D space.The spinning Our discussion so far has involved line-of-sight scenarios. surface is considered as the x-y plane (i.e.horizontal plane). Here,we extend to multipath environment,showing RSS while the reader may not lie on this plane.In this way, continues to be resistant to shaking.As aforementioned,no apart from the azimuthal angle o in the horizontal plane,we matter how the reader or turntable shakes,the final effect also need another parameter,i.e.the polar angle B along the is equivalent to the relative spinning that 72 rotates around vertical direction to fully describe the reader's incident signal. T1.Here,we also employ such model to show how the Correspondingly,the relative phase in 3D is given by: multipath propagation affects the relative spinning signal. As shown in Fig.7,suppose the wireless signal propagates △0)=4红7 cos(2ft++a)sin B mod 2 (13) along K different paths to arrive at Ti with initial lengths di,d2,...,dk,along directions 1,a2,...,aK.Finally,these Apparently,even generalizing to three dimensions,RSS de- copies of signals are overlapped at each tag.From basic pends only on the reader's spatial orientation instead of its channel models,the wireless channel h;arrived at tag Ti movement.Notice,such a generalization is crucial because (i=1,2)can be expressed as the complex number [7]: we can not require the reader and object to perfectly stay on a two dimensional plane during the whole spinning in practice. h() (10) D.Putting Things Together where d(t)and 0(t)are the distance and phase shift at time In summary,after all the above discussions,RSS holds well t.We can then get the overlapped RF signals at T and T2 as either in complex indoor environment(i.e.,multipath exists)or

T1 T2 R Obstacle (d1, ↵1) (d2, ↵2) Reflector Reflector ↵1 ↵2 Fig. 7: Multipath scenario. Because of two reflectors, the signal coming from reader propagates through two different paths with different directions and distances. the relative phase using another equivalent model as shown in Fig. 6(b). Suppose the angle of arrival and the distance between two tags are equal to ↵ and r respectively, then the relative phase is also given by: ∆✓(t) = 4⇡ λ r cos(2⇡fst + φ + ↵) mod 2⇡ (8) where φ is the initial angle between T1T2 and x-axis at time t = 0, and r cos(2⇡fst + φ + ↵) is the saved distance of signal propagating to T2 compared with that to T1. It is easy to prove that Eqn. 7 and Eqn. 8 are completely equivalent and convertible. We will use Eqn. 8 by default in the subsequent sections for simplicity. Relative spinning signal: Similarly, to deal with the dis￾continuity of phase, we formally define the relative spinning signal (RSS) as below: s(t) = sin(2∆✓(t)) = sin(2✓1(t) − 2✓2(t)) (9) ✓1 and ✓2 are measured phase values of two tags in prac￾tice. One might wonder if the periodicity generated by the above equation is indeed maintained as that of the actual spinning. In fact, it is easy to observe from Eqn. 9 that s(t + Ts) = sin(2∆✓(t + Ts)) = sin(2∆✓(t)) = s(t). We can also intuitively understand such conclusion from Fig. 6. The only movement that drives T2 to rotate around T1 is the spinning of the turntable. B. Dealing with Multipath Effect Our discussion so far has involved line-of-sight scenarios. Here, we extend to multipath environment, showing RSS continues to be resistant to shaking. As aforementioned, no matter how the reader or turntable shakes, the final effect is equivalent to the relative spinning that T2 rotates around T1. Here, we also employ such model to show how the multipath propagation affects the relative spinning signal. As shown in Fig. 7, suppose the wireless signal propagates along K different paths to arrive at T1 with initial lengths d1, d2,...,dK, along directions ↵1, ↵2,..., ↵K. Finally, these copies of signals are overlapped at each tag. From basic channel models, the wireless channel hi arrived at tag Ti (i = 1, 2) can be expressed as the complex number [7]: hi(t) = 1 d2(t) e J✓(t) (10) where d(t) and ✓(t) are the distance and phase shift at time t. We can then get the overlapped RF signals at T1 and T2 as follows [6]: h1(t) ⇡ XK k=1 1 d2 k eJ 4⇡ λ dk h2(t) ⇡ XK k=1 1 d2 k eJ 4⇡ λ (dk−r cos(2⇡fst+φ+↵k)) (11) where dk is the distance from the reader to T1 through the kth propagation path, and r cos(2⇡fst + φ + ↵k) is the saved distance to T2 compared with T1. Then we compute the relative wireless channel h(t) = h1(t)h⇤ 2(t): h(t) = XK k=1 1 d2 k eJ 4⇡ λ dk XK k=1 1 d2 k e−J 4⇡ λ (dk−r cos(2⇡fst+φ+↵k)) = XK k=1 1 d2 k eJ 4⇡ λ r cos(2⇡fst+φ+↵k) 2 4 1 d2 k +X l6=k eJ 4⇡ λ (dk−dl) 3 5 (12) Notice that the phase of the first term, i.e. 4⇡ λ r cos(2⇡fst+φ+ ↵k), in the above equation is nearly identical to the relative phase in Eqn. 8 derived in the line-of-sight scenario, and is independent of any translation. Unfortunately, the second term indeed depends on the distances. However, two observations inspire us: First, if the environment remains constant (i.e., mul￾tiple propagations hold), the second term reduces to a constant multiplier, which merely scales the final phase value. Second, even if the environment changes or the shaking changes the propagations, any variance caused by the second term drops significantly when summing over all multipath propagations. These two observations show that RSS is resistant to shaking even in multipath scenarios. This property holds no mater how the turntable or the reader is shaken. Even so, we must stress that shaking-induced translation cannot be unbounded and must be relatively small compared to the distance between the turntable and the reader, even if the reader/turntable shakes moderately. This is not a harsh assumption and can be easily met in practice as validated in our evaluation. C. Extending to Three Dimensional Scenario Let us now consider the RSS in 3D space. The spinning surface is considered as the x-y plane (i.e. horizontal plane), while the reader may not lie on this plane. In this way, apart from the azimuthal angle ↵ in the horizontal plane, we also need another parameter, i.e. the polar angle β along the vertical direction to fully describe the reader’s incident signal. Correspondingly, the relative phase in 3D is given by: ∆✓(t) = 4⇡ λ r cos(2⇡fst + φ + ↵) sin β mod 2⇡ (13) Apparently, even generalizing to three dimensions, RSS de￾pends only on the reader’s spatial orientation instead of its movement. Notice, such a generalization is crucial because we can not require the reader and object to perfectly stay on a two dimensional plane during the whole spinning in practice. D. Putting Things Together In summary, after all the above discussions, RSS holds well either in complex indoor environment (i.e., multipath exists) or IEEE INFOCOM 2018 - IEEE Conference on Computer Communications