WIFI-BASED IMAGING FOR GPR APPLICATIONS: FUNDAMENTAL STUDY AND EXPERIMENTAL RESULTS

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1 WIFI-BASED IMAGING FOR GPR APPICATIONS: FUNDAMENTA STUDY AND EXPERIMENTA RESUTS Weike Feng *, Jean-Miche Friedt, Zhipeng Hu 3, Grigory Cherniak, and Motoyuki Sato 4 Graduate Schoo of Environmenta Studies, Tohoku University, Sendai, Japan FEMTO-ST, Time & Frequency department, Besancon, France 3 Coege of Geoexporation Science and Technoogy, Jiin University, Changchun, China 4 Center for Northeast Asian Studies, Tohoku University, Sendai, Japan * E-mai of corresponding author: feng.weike.q4@dc.tohoku.ac.jp Keywords: PASSIVE BISTATIC RADAR, WIFI IMAGING, GROUND PENETRATING RADAR, ACOUSTIC DEAY INES. Abstract As a fundamenta research step for subface target imaging by passive ground penetrating radar (GPR), we present some simuation and experimenta resuts of passive bistatic radar imaging for short-range targets by using IEEE 80. Wireess Fideity (WiFi) wave as the source of iumination. Because the WiFi signa ony penetrates shaow ayers and acks bandwidth for high resoution subface structure mapping, we demonstrate the interrogation of cooperative targets with the passive bistatic radar approach. This strategy is achieved by inserting Surface Acoustic Wave (SAW) deay ines acting as dedicated ectors aowing for subface tagging (identification) or sensing (temperature meaement) through the fine meaement of echo deays. Experimenta resuts show that short-range targets, such as cars and metaic pates ocated within 0 meters, can effectivey be detected and imaged. The response of the SAW deay ines can aso be we probed. Introduction Ground penetrating radar (GPR) is a safe and cost effective too for subface exporation. It works by transmitting eectromagnetic waves into subface and receiving the ected waves to acquire various information of the subface feature. The depth, size, shape and other parameters of the subface ectors can be derived. Theore, GPR has been used for many appications, such as cutura-heritage management, humanitarian demining, civi engineering, etc. [-]. A GPR system is composed of three main components, which incudes transmitter, receiver, and contro unit. Due to the reguation imitation, the transmitters of most GPR systems shoud be paced cose to the ground face to avoid generating additiona eectro-magnetic poution to the environment. To overcome this imitation, in our research, non-cooperative transmitters, such as digita terrestria teevision broadcasting signa, goba system for mobie communications (GSM) signa, and IEEE 80. Wireess Fideity (WiFi) signa, are considered to be the source of iumination to repace the dedicated transmitter of GPR [3-4]. Using existing non-cooperative sources is advantageous since there is no requirement of specific frequency aocation. In this paper, we present some simuation and experimenta resuts of WiFi based passive bistatic radar imaging for GPR appications. Athough WiFi signa based range-dopper mapping, through-the-wa imaging, and object ocaization have been we addressed in the ast decade [5-9], we show some different considerations specific to sub-face target mapping. Wifi waves with IEEE 80. n standard,.4 GHz frequency, and 40 MHz bandwidth and Wifi waves with IEEE 80. ac standard, 5 GHz frequency, and 80 MHz bandwidth are empoyed for short-range target imaging by using bistatic synthetic aperture radar (SAR) technique. It is noticed that, in [9], high-resoution SAR imaging with IEEE 80. ac signa with 60 MHz bandwidth has been studied by numerica simuations. However, we show the practica impementations of WiFi radar imaging in this paper. Being aware of the fact that the range soution is insufficient for GPR subface shaow target imaging (such as concrete monitoring), a passive and wireess cooperative sensor designed by face acoustic wave (SAW) deay ines [0-] is aso tested. Our experiments show that cars and metaic pates ocated within 0 meters can be effectivey detected and imaged. The response of the SAW deay ines is probed at a bistatic range of up to.5 m and aows recovering the identity as we as temperature of the sensor.. WIFI based bistatic SAR imaging. Signa mode In this sub-section, the signa mode for WiFi based bistatic SAR imaging is estabished. Since the WiFi transmitter is aways stationary, in order to achieve high azimuth resoution, a meaement antenna is assumed to be moved ineary to form a synthetic aperture. Normay, the non-cooperative transmitted signa cannot directy be obtained. Theore, a erence antenna is required to sampe the erence signa for cross correation based range compression. When the

2 meaement antenna is at the -th position (x, 0), without considering the mutipath echoes in the erence channe, the received erence signa and the meaement signa can be expressed as and where t s ( t) A s ( t t ) n ( t) () 0 s ( t I ) s ( t dirc ) s i 0 ( t t i ) n ( t ) () i is the time deay between the erence antenna and the WiFi transmitter, which is constant for =,,N, and sdirc ( t) A s0 ( t t ) is the direct-path signa received by the meaement antenna, is the ection coefficient of the i i-th target, i=,,...,i, I is the number of targets, and t i is the time deay of i-th target from the WiFi transmitter to the meaement antenna at -th position. In practice, the direct-path signa is much stronger than the echoes of the targets. In this paper, we use the extensive canceation agorithm (ECA) [] to suppress its infuences. For the -th position of meaement antenna, the ined meaement signa is given by ( ) ( ) ( ) s t I PP s t (3) where I denotes an identity matrix, denotes the pseudo-inversion, and P is matrix formed by the deayed copies of the erence signa s. () Then, the -th range-compressed profie can be obtained by the cross-correation process as Tint s t s 0 t dt (4) ( ) ( ) ( ) where T int denotes the integration time that determines the system signa to noise ratio and the Dopper resoution. At ast, by using back projection (BP) agorithm, the ection coefficients of targets can be estimated by In summary, the signa processing chain for passive bistatic WiFi SAR imaging is presented in Fig.. In order to test the estabished signa mode and the proposed WiFi based bistatic SAR imaging method, severa semi-experiment simuations are conducted. In the simuation, the erence signa is obtained by directy samping the IEEE 80.n signa with 40 MHz bandwidth from a WiFi access point (AP), whose spectrum shown is in Fig.. The meaement signa at each position is generated by deaying the erence signa with corresponding distance. The synthetic aperture ength is simuated to 3 m and three targets ocated at (0, 0), (-5, 5) and (5, 5) are simuated. The imaging resuts obtained by the BP agorithm and the cross-correation based BP agorithm are shown in Fig. 3 and Fig. 4, respectivey. It can be observed that these three targets can be we focused by both agorithms. However, the sideobes are much reduced by the cross-correation based BP agorithm. Theore, in the practica impementation, the cross-correation based BP agorithm is used. s Ref. Sur. Ref. Sur. s s s Bandpass fiter, Hibert transform, down-conversion to baseband s s s s s Decimation and DSI suppression s t () Fourier transform and cross-correation () Cross-correation based back projection ( xy, ) s t s SAR image Fig. Signa processing chain for WiFi based passive SAR imaging. ( x x) ( y y) RAP( x, y) ( xy, ) t (5) c where R ( x, y) ( x x) ( y y) is the distance AP AP AP between the target and the WiFi transmitter, and ( xy, ) is the estimated ampitude of the target at (x, y). To suppress the sideobes caused by the coherent summation of the range-compressed signa from a the antenna positions, the cross-correation based BP agorithm [] is further appied, which can be expressed as ( x, y) ( x, y) ( x, y) (6) o where ( xy, )= ( x, y), and o=,. o Fig. Spectrum of rea IEEE 80.n signa with 40 MHz bandwidth used in the simuations.

3 In the first experiment, an IEEE 80.n signa with 40 MHz bandwidth is used to image a car at a distance of about 9 m. The AP is ocated at (0, -), the erence antenna is ocated at (0, 0), and the meaement antenna is sed on the rai from (, 0) to (4, 0) steps with 5 cm. The data samping frequency of the oscioscope is set to 0 GSampes/s and the integration time is about.6 us. The experiment set up is shown in Fig. 6, where the metaic pate is not added in this experiment. With cross-correation based BP agorithm, the imaging resut is shown in Fig. 7. It can be seen that the car can be we focused with correct distance and azimuth, yet with a range resoution 3.75 m imited by the avaiabe bandwidth. Fig. 3 Imaging resut of three targets obtained by BP agorithm. In the second experiment, an IEEE 80.ac signa with 80 MHz bandwidth is appied to increase the range soution of the designed passive bistatic radar system. In such a case, due to the higher signa frequency (5 GHz), the data samping frequency of the oscioscope and the integration time are changed to 0 GSampes/s and 0.8 us, respectivey. Besides, the moving step of the meaement antenna is reduced to cm to avoid aiasing. Apart from the car, a metaic pate is added as an additiona target. The imaging resut is shown in Fig. 8, where the car and pate can be effectivey imaged and separated. Compared to the resut in Fig. 7, more detais of the car can be observed, the range soution is aso increased. Furthermore, some parts of a wa can aso be imaged in this experiment. Fig. 4 Imaging resut of three targets obtained by cross-correation based BP agorithm.. Experimenta resut Two experiments are further conducted to vaidate the WiFi based bistatic SAR imaging technique. The diagram of the designed system used in the experiments is shown in Fig. 5. The system mainy incudes an oscioscope, a positioner, a WiFi AP used to transmit the signa, two horn antennas, and two PCs that communicate with each other by sending a big fie. One PC is used to remotey contro the positioner and oscioscope and process the received data. A horn antenna is facing to the AP and provides the erence signa, and the second horn antenna is sed on the positioner and faced to the target to provide the meaement signa. Fig. 6 Experiment setup for passive bistatic SAR imaging. m m Oscioscope Positioner AP Ethernet cabe PC Big data stream PC Fig. 5 Configuration of the designed WiFi based bistatic SAR system. Fig. 7 Imaging resut of the car using IEEE 80.n signa with 40 MHz bandwidth. 3

4 8-bits aowing for identifying which structure is being observed. Fig. 8 Imaging resut of the car and metaic pate using IEEE 80.ac signa with 80 MHz bandwidth. 3 Detection of passive SAW sensors It can be earned from the previous resuts shown in Section that, athough the short-range targets (car and pate) can be effectivey detected and imaged, the imited range resoution caused by the imited bandwidth of the WiFi signa is the main obstace met for using WiFi based GPR in the practica mapping of shaow targets such as the underground gas pipes and the rebars inside the concrete. Athough severa bands of IEEE 80.ac waves with 60 MHz bandwidth can be combined to much increase the range resoution as suggested by [9], acquisition of such wide bands may be impossibe in practice due to the precious frequency resources and the penetration depth of 5 GHz WiFi signa may cause another probem. Theore, in order to appy WiFi signa into practica GPR appications, we propose to attach a passive sensor designed by SAW deay ines on the underground or inside-wa targets. In the sensor, a piezoeectric substrate converts an incoming eectromagnetic signa into an acoustic signa whose veocity depends on the rounding physica properties of the transducer [0-]. The acoustic wave is ected by mirrors patterned on the piezoeectric substrate back to the eectrodes that convert the acoustic wave back to the eectromagnetic wave, yieding an echo signa which has enough deay to be distinguished from the cutters. In this case, athough the range resoution is not changed, the passive sensor can be effectivey detected. Then, by simpe cacuations, the position of the target can be derived. In order to verify the proposed method, severa fundamenta experiments are carried out. The configuration and the experiment setup incuding four meaement antennas are shown in Fig. 9 and Fig. 0, respectivey. Since the roundings of the experiment induce much stronger echoes than the response of the passive sensor, we aso use ECA agorithm to reduce their infuences. The range compression resut obtained by the cross correation process is shown in Fig., where the responses of the passive sensor can be we probed. Eight responses with deays us to. us are detected, which are separated from the cutters that aways have time deays in ns scae. The 8-echoes are designed as In addition to tagging, fine acoustic veocity meaement aows for recovering the subface physica environmenta property of the cooperative target. In this exampe, the strong temperature sensitivity S=60 ppm/k of the ithium niobate piezoeectric substrate aows for detecting temperature variations. Indeed, a temperature variation d T induces a phase variation d f0sd with τ the deay difference between T two echoes and f 0=.4 GHz the centra operating frequency. Echo time deay differences must be considered to get rid of the source to cooperative target deay dependence and meae a time deay ony reated to the acoustic veocity v since τ=d/v with D the geometric distance of the acoustic path, typicay in the 3 mm range for a us deay. A one to one reation exists between phase and temperature as ong as the temperature variation remains sma enough to prevent π phase rotations, i.e. τ</(sd Tf 0). In our case, considering a temperature range of 50 K, then two echoes separated by ess than 38 ns must be seected. Such a condition is met by seecting any two adjacent pair of the echoes seen in the returned response of Fig.. Since the correation is a inear process, the phase introduced by the acoustic deay ine is aso found on the cross-correation output, aowing for the recovery of a temperature variation information as shown in Fig.. USB PC WiFi transmitter -0 db SAW deay ine Switch.48 GHz Fig. 9 Configuration of WiFi based passive sensor detection. Fig. 0 Experiment setup for WiFi based passive sensor detection. Fig. WiFi based meaement of a passive sensor using IEEE 80.n signa with 0 MHz bandwidth. Oscioscope 4

5 Fig. Temperature variation observed on the 4 antennas facing a SAW deay ine cooed twice by a freezing spray at dates 0 and 300 s. 4 Concusion We proposed and vaidated severa WiFi based passive bistatic radar imaging methods as the fundamenta researches for GPR appications. The experimenta resuts show that, combined with the passive cooperative sensor, it is possibe to use WiFi as the transmitting source of GPR. Theore, there is no need of frequency aocation, and it can save the system cost, increase the meaement fexibiity, and reduce the eectro-magnetic poution to the environment. 5 Acknowedgements This work was supported by JSPS Grant-in-Aid for Scientific Research (A) , OsciatorIMP and FIRST-TP grants from the French Projet d Investissement d Avenir (PIA), as we as Tohoku University through the funding of an invited scientist position for J.-M Friedt and a ROIS schoarship for Zhipeng Hu. WiFi radar at standoff distances', IEEE Trans. Geosci. Remote Sens., vo.50, no.4, pp. 8-6, 0 [6] Coone, F., Woodbridge, K., Guo, H., et a.: 'Ambiguity function anaysis of wireess AN transmissions for passive radar', IEEE Transactions on Aerospace and Eectronic Systems, vo. 47, no., pp , 0 [7] Coone, F., Facone, P., Bongioanni, C., et a.: 'WiFi-based passive bistatic radar: Data processing schemes and experimenta resuts', IEEE Transactions on Aerospace and Eectronic Systems, vo. 48, no., pp [8] Huang, D., Nandakumar, R., Goakota, S.: 'Feasibiity and imits of Wi-Fi imaging', Proc. ACM Conf. Embedded Netw. Sensor Syst., pp , 04 [9] Shi, J., iu Y., iu, W., et a.: 'High-resoution synthetic aperture radar based on the IEEE 80. protoco', Eectronics etters, vo. 5, no., pp.85 87, 05 [0] amothe, M., Pessky, V., Friedt, J-M, et a.: 'Utra-wideband SAW sensors and tags', Eectronics etters, vo. 49, no. 4, pp , 03 [] Friedt, J-M., Martin, G., Goavec-Mérou, G., et a.: 'Acoustic transducers as passive cooperative targets for wireess sensing of the sub-face word: chaenges of probing with ground penetrating RADAR', Sensors, vo. 8, no., pp. 46, 08 [] Coone, F., Cardinai, R., ombardo, P.: 'Canceation of cutter and mutipath in passive radar using a sequentia approach', in Proceedings of IEEE Internationa Conference on Radar, 006 [3] Feng, W., Yi,., Sato, M.: 'Near range radar imaging based on bock sparsity and cross-correation fusion agorithm ', IEEE J. Se. Topics App. Earth Observ. Remote Sens., in press, 08 6 References [] Sato, M.: 'Introduction of the advanced AIS: Advanced andmine Imaging System', Detection and Sensing of Mines, Exposive Objects, and Obscured Targets XXIII. Vo Internationa Society for Optics and Photonics, 08 [] Economou, N., Benedetto, F., Bano, M., et a.: 'Advanced ground penetrating radar signa processing techniques', Signa Processing, vo.3, pp , 07 [3] Feng, W., Friedt, J-M., Cherniak, G., et a.: 'Nove agorithm for high resoution passive radar imaging with ISDB-T digita TV signa', in Proc. IEEE Int. Geosci. Remote Sens. Symp., Vaencia, Spain, Juy 08 [4] Feng, W., Friedt, J-M., Goavec-Merou, G., et a.: 'Passive RADAR meaement of acoustic deay ines used as passive sensors', Eectronics etters, 08, under review [5] Chetty, K., Smith, G.E. and Woodbridge, K., 'Through-the-wa sensing of personne using passive bistatic 5