1660IEICE TRANS. COMMUN., VOL.E102–B, NO.8 AUGUST 2019

PAPERLocalization Method Using Received Signal Strength for WirelessPower Transmission of the Capsule Endoscope

Daijiro HIYOSHI†, Student Member and Masaharu TAKAHASHI†a), Fellow

SUMMARY In recent years, capsule endoscopy has attracted attentionas one of the medical devices that examine internal digestive tracts with-out burdening patients. Wireless power transmission of the capsule endo-scope has been researched now, and the power transmission efficiency canbe improved by knowing the capsule location. In this paper, we develop alocalization method wireless power transmission. Therefore, a simple algo-rithm for using received signal strength (RSS) has been developed so thatposition estimation can be performed in real time, and the performance isevaluated by performing three-dimensional localization with eight receiv-ing antennas.key words: capsule endoscope, position estimation, received signalstrength, wireless power transmission

1. Introduction

In recent years, capsule endoscopes which are able to ob-serve a wider range than conventional endoscope as oneof the medical devices examining the interiors of digestivetracts and without pain in examination have attracted at-tention. The capsule endoscope is a capsule type medicaldevice having a diameter of about 16 mm and a length of26 mm, and having an image photographing function and awireless communication function [1]. As an examinationprocess, the capsule is firstly taken from the mouth, movesthrough the GI tract by peristaltic exercise, photographs ex-amination regions, and transmits the image data to a sensorarray outside the body by wireless communication.

One of the problems of capsule endoscopy is drivingpower source. Currently, electricity is supplied by the bat-tery built in the capsule. However there are problems suchas the limit to the number of images, and the risk that theelectrolyte leaked from the battery may adversely affect thehuman body when the capsule is clogged in the body.

In order to solve these problems, techniques for wire-less power transmission from the outside of the body havebeen developed. Using a sensor array that receives imagedata from the capsule, electric power is supplied to cap-sules by transmitting radio waves [2]. With this technol-ogy, the capsule can work in the body all the time in en-doscopy. Furthermore, the battery is unnecessary to build inthe capsule, hence miniaturization can be expected. Here,since the receiving electrodes outside the body are in theform of an array, it is possible to give directionality the ra-

Manuscript received November 9, 2018.Manuscript publicized February 18, 2019.†The authors are with Chiba University, Chiba-shi, 263-8522

Japan.a) E-mail: omei@m.ieice.org

DOI: 10.1587/transcom.2018EBP3328

dio wave by controlling the phase [3], [4]. Therefore, inwireless power transmission, it is expected to improve theefficiency of power transmission by limiting the radio wavesto a specific position. For that, it’s necessary to specify theposition of the capsule endoscope. In this paper, we proposea localization method for wireless power transmission.

There are various methods of localization. The perfor-mance of Time of Arrival (TOA) technology is susceptibleto the influence of bandwidth and not suitable for positionestimation in the human body [5]. And the Angle of Arrival(AOA) technology is difficult to realize inside a complex hu-man body structure [6]. In Received Signal Strength (RSS)localization technology, the received signal strength of theradio frequency wireless signal is measurable at the receiverside during the routine data communication without requir-ing additional power or occupying extra bandwidth [7]. RSSlocalization technology is the best choice for in-body local-ization [8], [9].

In order to enable more accurate localization, variousmethods for the capsule endoscope have been so far pro-posed [10]–[13], [19]–[22]. However, there are problemsthat take a huge amount of time to localize in order to per-form complicated calculations according to the living body[14], [15]. In order to realize wireless power transmission,position information needs to be obtained during the endo-scopic examination. Therefore, shortening the calculationtime is essential. Furthermore, most of these studies havedeveloped algorithms on the assumption that radio wavesare radiated from omnidirectional antennas. On the otherhand, the wireless power transmission technology in thesestudies adopts the microwave method [16] which supplieselectric power via the antenna, consideration of the directiv-ity of the antenna is required. Among the previous studies,there are no studies that are described with the antenna whentransmitting and receiving, and antenna characteristic is notconsidered.

In the previous study, the purpose is to grasp the posi-tion of the capsule in inspection and to consider the directiv-ity of the antenna by a small amount of calculation [17]. Inthis paper as well, we aim to specify the position informa-tion of the capsule endoscope in real time, and localizationis performed by a simple algorithm in consideration of thedirectivity of the antenna in the simulation.

The structure of this paper is shown below. Section 2shows the system structure of localization and the simula-tion model created for analysis. In Sect. 3, the investigateresult is shown about the parameter for localization. Fur-

Copyright c© 2019 The Institute of Electronics, Information and Communication Engineers

HIYOSHI and TAKAHASHI: LOCALIZATION METHOD USING RECEIVED SIGNAL STRENGTH FOR WIRELESS POWER TRANSMISSION1661

thermore, we introduce angle characteristics which causethe error of the parameter and discussed processing on it. InSect. 4, we assume a capsule endoscope is moving in a three-dimensional space, deal with the tasks obtained in Sect. 3,and propose a localization method under more realistic con-ditions. Finally, we conclude this paper in Sect. 5.

2. Localization Method and Simulation Model

2.1 Localization Method

In this section, the system of localization is explained. Asshown in Fig. 1, on the numerical simulation, we assumedthat a radio wave was transmitted from a transmitting elec-trode installed in a human body model to a plurality of re-ceiving electrodes installed on the body surface. Biologicaltissue is a lossy medium, and RSS at the receiving antennasdecreases depending on the thickness of the tissue. There-fore, by measuring RSS, the distance between the transmit-ting antenna and receiving antennas is able to be calculatedbackward. Spheres whose radii from the receiving antennasare defined as the distance obtained by back calculation aredrawn. By obtaining the coordinates of the intersections ofthese spheres, the localization result can be calculated.

Next, the theoretical formula is shown. As shown inFig. 1, the surface of the human body model is set as the x-z plane in the orthogonal coordinate system. The positionsof the receiving antennas are grasped in advance, the loca-tion of the transmitting antenna is localized by the knownreceiver location. We assumed that there were N receivingantennas and the transmitting antenna, and define locationsof the n-th receiving antenna Rn (n = 1, · · · ,N) and the orig-inal transmitting antenna T as:

Rn =[xn, yn, zn

](1)

T =[xt, yt, zt

](2)

Hence the ideal distance dn from the n-th receiving antennato the transmitting antenna can be represented as:

dn =

√(xt − xn)2 + (yt − yn)2 + (zt − zn)2 (3)

When RSS of the n-th antenna is defined as pn, the distancebetween the transmitting antenna and the receiving antennarn is obtained by:

rn = Q(pn) (4)

as a function with pn. In this case, n equation of the spherecentered on the n-th receiving antenna is given.

As shown in Fig. 1, one intersection point is obtainablefrom three hemispheres centered on the antennas. There-fore, by preparing three formulas, the coordinates (x, y, z)solved as a ternary simultaneous equation are the coordi-nates of I in Fig. 1. In this study, the coordinate of I is cal-culated as the localization result.

Since there are N receiving antennas, NC3 combina-tions for selecting three antennas are obtained in total. De-fine M as:

Fig. 1 Intersection of spheres in rectangular coordinate system.

M = NC3 (5)

Where the m-th intersection location Im (m = 1, · · · ,M) isrepresented as:

Im =[xm, ym, zm

](6)

Consequently, average Im is outputted as the localization re-sult. This result is compared with the position of the trans-mitting antenna T . The distance between them is calculatedand used to evaluate the performance of the algorithm.

2.2 Simulation Model

In this section, the simulation model used for numericalcalculation is introduced. In electromagnetic field analy-sis with consideration of the human body, FDTD method isused as an analysis method. Next, the operating frequencyis considered. The industrial, scientific and medical (ISM)radio bands are permitted to use for the medical device.Among them, the use of 2.45 GHz band (2.4 to 2.5 GHz),915 MHz band (902 to 928 MHz, North and South Amer-ica), and 433.92 MHz band (433.05 to 434.79 MHz, Europeand Africa) is particularly active in the microwave band. Inthe previous study, the electric field intensity of electromag-netic waves radiated from the power transmitting antennawas calculated by using these three frequency bands and asimple human body model. As a result, the lower the fre-quency, the smaller the attenuation of radio waves and thehigher RSS [17]. Therefore, similarly to the previous re-search, 433.92 MHz, which is the lowest frequency amongthe above three bands, is used as the operating frequency.

As a channel model, a simple rectangular paral-lelepiped model simulating human abdomen is used. Sinceduodenum contains little air, we treat small intestine as aseries of masses rather than tubes, and assume that trans-mitting antenna is contained in it. The model is shown inFig. 2. The dimension is 300 × 200 × 300 mm3 to simulatethe abdomen. Skin of 2 mm in thickness was placed on the

1662IEICE TRANS. COMMUN., VOL.E102–B, NO.8 AUGUST 2019

Fig. 2 Simulation model (Human body).

Table 1 Electrical constants of each tissue.

surface of the body as living tissue, and fat with a thicknessof 10 mm was placed inside it. For the sake of simplicity,the inside of the human body was composed of all the mus-cles, and the size was adjusted so that the size of the entiremodel was 300 mm. The dielectric constant and conduc-tivity of each tissue of the human body at the frequency of433.92 MHz used for analysis are shown in Table 1. Com-pared with this model, the actual human abdomen has amore complicated structure. Therefore, examining the prac-ticality in this model is needed. In Sect. 3.2, the result ofthe investigation on the influence of human body tissues onRSS is reported.

Antennas used for analysis are introduced. Origi-nally, these antennas also serve as antennas for wirelesspower transmission besides transmitting photographed im-age data. However, the design of antennas with the perfor-mance suitable for wireless power transmission is done byothers [2], [18].

Therefore, the antennas in this study are assumed to beused for only data transmission (from the capsule to sensorarray).

Propagation loss occurs when radio waves pass throughliving tissue. And the degree of attenuation of RSS is used tocalculate the distance between the transmitting and receiv-ing antennas. Therefore, in this paper, in order to confirmthe basic operation, antennas fitting within the capsule en-doscope and fitting on the human abdomen surface are usedwithout consideration of matching.

• For the transmitting antenna, a 10 mm dipole antenna,which is small enough to install into the capsule endo-scope and has a simple structure, is used. The shape ofthe antenna is shown in the left part of Fig. 3.

• A spiral antenna is adopted as the receiving antennaso that it can be received irrespective of the orienta-tion of the capsule endoscope. The spiral antenna hasa wide frequency band and can radiate circularly polar-

Fig. 3 Antenna models.

ized waves. On the other hand, the directivity is dis-torted. The directivity of the antenna causes degrada-tion of the localization accuracy due to reasons to beexplained later. Therefore, as shown in the right part ofFig. 3, a 4-wire spiral antenna is used.

3. Calculation of Distance Between Antennas

In this section, the method of calculation of the distance be-tween antennas is explained, which is an indispensable fac-tor in the localization. In addition to the distance betweenthe receiving and transmitting antennas, there are the factorscalled angle characteristics that affect RSS. Their investiga-tion and the way to process them are considered.

3.1 Attenuation Characteristic for Distance Calculation

In order to obtain the distances rn used for localization, afunction Q (pn) with p as a variable used in the formula (2)is calculated. As shown in Fig. 4, one receiving antenna isinstalled in the central part of the human body model, and atransmitting antenna is installed on a straight line perpendic-ularly crossing the feeding point at the center of the receiv-ing antenna. Then, in the range where the inter-antenna dis-tance dn is 40 to 160 mm, the transmitting antenna is movedin intervals of 10 mm. And, as receiving radio waves trans-mitted from the transmitting antenna at each position, RSSwas calculated. The simulation results are shown in Fig. 5.For the simulation result, the approximate curve was cal-culated by the least-squares method, and this function wasdefined as Q (pn).

Even at the same distance RSS varies depending on thedirection of the transmitting antenna. In this report, we pro-pose an algorithm in one direction, in which the dipole an-tenna is fixed vertically as a basic algorithm. We plan tosolve this problem by proposing a position estimation algo-rithm using orthogonal antennas in the near future.

3.2 Influence of Human Body Tissues on RSS

This section explains the influence of human organization

HIYOSHI and TAKAHASHI: LOCALIZATION METHOD USING RECEIVED SIGNAL STRENGTH FOR WIRELESS POWER TRANSMISSION1663

Fig. 4 Calculation model on the RSS depending on antenna depth.

Fig. 5 Distance characteristic for RSS.

on RSS. There are studies reporting a detailed analysis ofRSS and distance [23]. This study is described character-istics of nonmonotonicity of human tissues. In comparisonwith the actual human body, if the value of RSS in the pro-posed simple model is significantly different, the reliabilityof the result in the simple human body model is lost. There-fore, it is necessary to investigate the change of the RSS bythe organization.

Studies on the effects of changes by tissues have alsobeen conducted in previous studies [17]. We changed thethickness of fat layer and muscle layer while keeping thedistance between antennas constant, and investigated thechange of RSS value. The results are shown in Table 2.The amount of change in RSS due to the presence of tissuewas the largest in fat and was about 3 dB. This is consideredto be a major cause of layer reflection. The change amountof RSS due to the thickness of the tissue was about 0.02 dBevery 10 mm. The influence on the RSS due to the change inthe presence or the thickness of the tissue absence of inter-nal tissue is minimal. From this result, we judged that evenif the tissue structure of the medium between the antennaschanged, there was hardly any influence on the value of RSSand it can be evaluated with a simple model.

Therefore, the human tissue with a complex structurewas replaced by a simple model, and concluded that thisproposed model is effective in the basically study.

Table 2 Influence of human tissues on RSS.

Fig. 6 Two types of angle characteristics.

3.3 Angle Characteristics

In the process of collecting RSS as changing the positionof the capsule endoscope by simulation, it was found that,when the capsule was installed in a portion other than thefront, less RSS compared to the position in the front wasobtained. This is considered to be due to the angle charac-teristics of the receiving antenna. Since the directivity existson the antenna, ease of transmission and reception is dif-ferent for each direction in transmitting and receiving radiowaves. This has an effect on RSS.

As shown in Fig. 6, there are two kinds of elements inthe angle characteristic. The first is the depth direction, andthe second is the surface direction. In this paper, the anglein the depth direction is referred to as θ, and the angle in thesurface direction as ϕ. We investigated the details of anglecharacteristic, and how it affected RSS, by simulation.

First, angle characteristic in the depth direction is ex-plained. Comparing the radio waves receiving from the frontdirection with receiving from the oblique direction, differentRSSs are obtained in spite of the same distance. This is be-cause the directivity in the oblique direction is lower thanthat in the front. Therefore, when radio waves are receivedobliquely, longer distances compared to the front are calcu-lated. This causes deterioration of accuracy.

We investigated how much the angle characteristics inthe depth direction affected RSS. As shown in Fig. 7, RSScalculation was carried out by moving the transmitting an-tenna so that the distance between the antennas is fixed at80 mm on the x-y plane with the z axis fixed, and changingθ. The calculation result is shown in Fig. 8. Compared withthe position of θ = 90◦ which is a position orthogonal to thereceiving antenna, when θ becomes smaller than 45◦, RSSbecomes smaller and RSS attenuates by about 7 dBm at themaximum.

1664IEICE TRANS. COMMUN., VOL.E102–B, NO.8 AUGUST 2019

Fig. 7 Investigation model in depth direction.

Fig. 8 Angle characteristic in depth direction.

Fig. 9 Investigation model in the surface direction.

Secondly, angle characteristic in the surface directionis explained. RSS varies depending on the angle ϕ withrespect to the direction of the surface of the human bodymodel when a radio wave comes from the diagonal direc-tion. The ease of receiving radio waves varies depending onthe corner of the spiral antenna, and RSS varies dependingon the angle.

Figure 9 shows the model of the simulation for inves-tigation. A receiving antenna is placed at the center of thehuman body surface. A transmitting antenna is installed bymoving so that the distance between the antennas is 110 mmon a plane 50 mm away in the depth direction. The resultsare shown in Fig. 10. RSS varies acceding to angle. Conse-quently, the difference of about 12 dBm between the maxi-mum value and the minimum value is confirmed.

Fig. 10 Angle characteristic in the surface direction.

In this result, note that the results in Fig. 10 are not onlydue to the angle characteristic in the surface direction. Theinfluence of the angle characteristic of the transmitting an-tenna is contained in addition to one in the depth direction.In particular, since the dipole antenna which is the trans-mitting antenna is installed in the vertical direction, RSSbecomes extremely small at the position of ϕ = −90◦, 90◦

where the receiving antenna and the transmitting antenna arejust above and below relationship. Hence, RSSs of these po-sitions were corrected by linear interpolation based on sur-rounding values, and the influence of the angle characteristicof the transmitting antenna was reduced.

3.4 Processing on Angle Characteristics

The angle characteristics in the surface direction have themost effect on RSS. As shown in Fig. 5, when RSS changesby 12 dBm, the distance to be calculated also changes bynearly 40 mm. This is too large error for the distance usedfor localization accuracy. To solve this problem, correctionfor angle characteristics is applied as one of the processes oflocalization algorithm.

A specific correction method is described. First, theprocessing for angle characteristics in the depth direction isdescribed. As can be seen from Fig. 8, there is almost nochange in RSS up to a certain angle. Therefore, we dealwith it by reducing the number of receiving antennas usedfor localization. Accuracy was improved by removing suchreceiving antennas from localization.

Next, a correction method in the angle characteristic inthe surface direction is described. Regarding the surface di-rection, correction is performed by a method of correctingthe calculated distance according to the angle ϕ. Withoutcorrection, rn has been calculated differently from dn due tothe influence of angle characteristics. Therefore, it is desir-able to calculate rn as close as possible to dn as possible. Inthis study, the method of correction using surface angle isproposed. As shown on the right side of Fig. 10, an approx-imate function corresponding to the angle is obtained andused as a correction function C (ϕ). Correction is made bymultiplying the distance rn by the value obtained from thisfunction.

Algorithms using these correction functions are ex-plained in Sect. 4.

HIYOSHI and TAKAHASHI: LOCALIZATION METHOD USING RECEIVED SIGNAL STRENGTH FOR WIRELESS POWER TRANSMISSION1665

Fig. 11 Localization environment and Localization area.

4. Three Dimensional Localization

4.1 Localization Environment

The arrangement of the antenna is described when perform-ing localization in three dimensions. Figure 11 shows theinstallation positions of receiving antennas and the movingrange of the transmitting antenna. Eight receiving anten-nas are arranged with the origin at the center of the x-zplane of this model surface. These coordinates are basedon actual placement in the capsule endoscopy. Positions Rn(n = 1, · · · , 8) of each arrangement are defined as:

Rn =

(0, 0)(0, 80)

(−60, 60)(60, 60)

(−80,−20)(80,−20)

(−40,−80)(40,−80)

(n = 1, . . . , 8) [mm] (7)

after defining the center of the model surface as the originO.

The transmitting antenna is placed within the areashown in red in the figure. This area is assumed to be therange where the small intestine exists. The dimension is200 × 70 × 160 mm3. By taking lattice points at regular in-tervals within this range, the localization of 792 points isperformed.

Additionally, in this study, the continuous movementof the capsule endoscope is considered. In the actual cap-sule endoscopy, the information of the received RSS is up-dated at regular time intervals. Therefore, it is assumed thatthe transmission antenna moves to one adjacent lattice pointfor each update. As a result, it is possible to know the dis-placement distance of positions by updating. In this paper,in order to minimize the error, this distance is utilized forlocalization.

4.2 Procedure of Localization

The flow of localization of per round is shown in Fig. 12.

Fig. 12 The flow of localization per round.

Localization consists of two steps. The first is calculatingtemporary position for calculating the angle, and the secondis to correct the distance using the obtained angle, to drawspheres again and to obtain the intersection as the localiza-tion result.

First, localization is performed using only four of theeight RSS (pn) having large values for the purpose of mini-mizing of the influence of angle characteristics in the depthdirection. Let the four selected RSSs be pn′ (n′ = 1, · · · , 4)and convert them to the distance rn′ using formula (4).Spheres with these distance as a radius is drawn aroundeach receiving antennas and the intersection points Im (m =

1, · · · , 4) of the spheres are calculated. Four intersectionpoints is obtained from the four receiving antennas. In thefirst step, the average coordinate’s Im are determined as thetemporary position.

The second step begins by calculating the angle formedby the temporary position and each receiving antenna. Anangle θn′ in the depth direction and an angle ϕn′ in the sur-face direction are calculated with the each receiving an-tenna. Angle correction is performed using them. First, inaccordance with the combination of (rn′ , θn′ ), an appropri-ate angle correction function C(ϕn′ , rn′ ) is determined fromamong a plurality of prepared functions. And r′n′ is definedas the corrected distance and given by:

r′n′ = C (ϕn′ , rn′ ) × rn′ (8)

Finally, spheres with radii r′n′ are drawn, and the coordinatesof the intersection points I′m are calculated. The averagevalue I′m of I′m is output as the final position I′.

At this time, since there is a limit of the accuracy ofthe correction function, there is a possibility that correctionhas not been appropriately applied. Therefore, if there is noway to deal with the distorted distance, the localization er-ror increases. We addressed this problem by considering theweight of intersection points. After four intersection points

1666IEICE TRANS. COMMUN., VOL.E102–B, NO.8 AUGUST 2019

are recalculated, the variance of four intersection points iscalculated. A large variance suggests that the incorrect dis-tance (outliers) is included in intersections. As a methodof detecting outliers, the localization result before updat-ing introduced in Sect. 4.1 is utilized. Specifically, it is as-sumed that localization has performed i-th update (i ≥ 3).At this time, by calculating the inclination and the displace-ment distance in the traveling direction from i-1 th and i-2 thpositions, the i-th position can be estimated. As the highlyreliable position, this position is compared with the four in-tersection obtained from the spheres.

At the four intersections, it is assumed that the clos-est point from this estimated position has the smallest er-ror. Therefore, the weight at the nearest position is doubled,and the weight at the furthest position is halved. Weightsare set so that {w1: w2: w3: w4} = {4: 2: 2: 1} in orderfrom the nearest position, and the coordinates obtained bythe weighted average are output as the localization result.Then, the value of the variance of the four coordinates isdefined as V. WhenV is extremely large or small, anotherweight is set. When V < 0.5, it can be judged that the dis-persion of the error is small, and it is assumed that {w1: w2:w3: w4} = {1: 1: 1: 1} assuming that weighting is unnec-essary. When V > 10, it can be determined that the error islarge, and {w1: w2: w3: w4} = {2: 1: 1: 0} is weighted asthe farthest coordinates lead to the cause of the error.

In the case of update count i < 3, since there is no local-ized position before updating, the weighting is determinedusing the distance from the temporary position. Althoughthe error is not necessarily small as it is closer to the tem-porary position, at least since there is a tendency to moveaway from the temporary position when correction is failed,{w1: w2: w3: w4} = {2: 2: 2: 1}, and outputs the weightedaverage coordinates as the localization result.

4.3 The Performance of Localization

First, we show to the time required for localization. At all792 points, it was judged that the time from the input ofRSS to the output of localized coordinate is extremely small(< 0.1 s), and the real time property which is the conditionfor use in the wireless power transmission is sufficient. Theerror between the localization result and the original posi-tion was obtained. Then, colors are separately displayed ineach magnitude of the error. A part of the result is shownin Fig. 13. Since it is difficult to show all the points in threedimensions, results at 50 mm from the front surface (y =

50) and at 50 mm from the right surface are displayed. Asshown in the figure, an error within 40 mm was achieved atall points. Furthermore, the number of points within 20 mmof error was more than 70%. At present, the study to impartdirectionality by phase control in wireless power transmis-sion is still in the development stage, and there is no decisionas to how much error is specifically tolerated. However, inthis paper, we confirmed that the error range could be within2 capsules (40 mm) within all area, hence we judged that theposition information was able to be tracked sufficient accu-

Fig. 13 Localization result.

racy by the proposed algorithm.

5. Conclusion

In the paper, a localization method for wireless power trans-mission to the capsule endoscope is developed. Real-timelocalization has been required, and the position has been es-timated by a simple algorithm using RSS. We have devel-oped a method including algorithms that take antenna direc-tivity into consideration by setting transmitting and receiv-ing antennas respectively in the simulation.

Considering the angle characteristic of the antenna, inthis paper, the localization was performed in two steps ofcalculating the temporary position and calculating the finalposition. By calculating the temporary position, the influ-ence of the angle characteristic of the antenna was corrected.In addition, considering the position was updated at certaintime intervals, localization was also performed using the es-timated position before updating. As a result, it was possi-ble to estimate the position within an error of 40 mm whilemaintaining real time property.

As a future task, it is important to consider the direc-tion of the transmitting antenna. As shown in Sect. 3.1, theRSS changes according to the direction of the transmittingantenna even at the same distance. Therefore, based on thisalgorithm, we aim at localization independent of orientationby combining the localization results when the transmittingantenna is horizontal and vertical.

Furthermore, we are planning to estimate the positionusing a model with a complex structure close to the hu-man body, using an antenna for wireless power transmis-sion. Specifically, the techniques in localization such as an-tenna characteristics are also required to practical models.Therefore, we plan to try to adapt processing of angle char-acteristic to a complex body model. In fact, factors such asthe curvature of the abdomen are left behind in the error oflocalization. However, as discussed in the weighting discus-

HIYOSHI and TAKAHASHI: LOCALIZATION METHOD USING RECEIVED SIGNAL STRENGTH FOR WIRELESS POWER TRANSMISSION1667

sion, discussion of RSS with neighboring external elementscan be considered locally, and we think that a plane model issufficient. This area is thought to be a degradation factor ofpositional accuracy, but we plan to discuss it in verificationwith a real model to be carried out in the future.

Acknowledgments

This work was supported by Chiba University SEEDS Fund(Chiba University Open Recruitment for International Ex-change Program).

This work was supported by JSPS KAKENHI GrantNumber 18K04123.

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Daijiro Hiyoshi was born in Chiba, Japan,in 1994. He received the B.Eng. degree fromChiba university, Japan in 2017. He is currentlypursuing the M.Eng. course at Chiba university,engaging in the research on localization in bodyarea networks.

Masaharu Takahashi was born in Chiba,Japan, in December 1965. He received theB.E. degree in electrical engineering from To-hoku University, Miyagi, Japan, in 1989, andthe M.E. and D.E. degrees in electrical engi-neering from the Tokyo Institute of Technology,Tokyo, Japan, in 1991 and 1994, respectively.From 1994 to 1996, he was a Research Asso-ciate, and from 1996 to 2000, an Assistant Pro-fessor with the Musashi Institute of Technology,Tokyo, Japan. From 2000 to 2004, he was an

Associate Professor with the Tokyo University of Agriculture and Technol-ogy, Tokyo, Japan. He is currently an Associate Professor with the Re-search Center for Frontier Medical Engineering, Chiba University, Chiba,Japan.