Resonant Magnetic Coupling Indoor Localization Systemubicomp.org/ubicomp2013/adjunct/adjunct/p59.pdfpreviously been used for example for wireless power transmission [1] and user interaction

Resonant Magnetic CouplingIndoor Localization System

Gerald PirklDFKI GmbHTrippstadter Str. 12267663 Kaiserslauter, [email protected]

Paul LukowiczDFKI GmbH/TUKaiserslauternTrippstadter Str. 12267663 Kaiserslauter, [email protected]

Permission to make digital or hard copies of part or all of this work forpersonal or classroom use is granted without fee provided that copies are notmade or distributed for profit or commercial advantage and that copies bearthis notice and the full citation on the first page. Copyrights for third-partycomponents of this work must be honored. For all other uses, contact theowner/author(s). Copyright is held by the author/owner(s).UbiComp’13 Adjunct, September 8–12, 2013, Zurich, Switzerland.ACM 978-1-4503-2215-7/13/09.

http://dx.doi.org/10.1145/2494091.2494108

AbstractBuilding on previous work [4] that introduced a novelindoor positioning concept based on magnetic resonantcoupling we describe an improved system to be shownduring the UBICOMP 2013 demo session. We improvedthe magnetic field model, implemented a particle filter forposition estimation and a software suite for configurationand calibration of the system.

IntroductionDespite much research indoor localization, especially indynamic environments, has still not fully been solved (seee.g. for a recent review of existing techniques [6],[2]).The problem is particularly difficult when it comes to acombination of low cost, simple installation, high degreeof robustness with respect to changes in the environmentand accuracy in the sub meter range. In [4] we haveproposed a novel indoor location system that leverage thespecific physical properties of oscillating magnetic fields tofulfill the above requirements. Thus we use beacons thatgenerate a magnetic field that periodically expands andcontracts. Unlike in RF or ultrasonic systems, which bothgenerate propagating waves, the magnetic field in oursystem does not separate from the transmitter andpropagate. Instead the vast majority of energy is ”pulledback” into the transmitter oscillating circuit as the fieldcontracts. Energy is only transmitted if, within the area of

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field expansion, there is an oscillator tuned the preciselythe right resonant frequency (resonant coupling to thereceiver Figure 1). As described in [4] the key advantageof the system is that since there are no propagating wavesdisturbances like multi path propagation and diffractiondo not occur. Magnetic fields are also difficult to blockand even massive ferromagnetic objects only cause localdisruptions and have no influence on the positioningaccuracy in other areas.

Related WorkThe basic physical principle is well known and haspreviously been used for example for wireless powertransmission [1] and user interaction [3]. However, ourwork has been the first one to adapt it to robust, low costindoor positioning.

Compared to the system we had described in [4] the demosystem features an improved magnetic field model, onboard inertial sensors supporting particle filter basedlocation estimate stabilization, more robustsynchronisation, mature wireless data transmission, and asoftware suite for system setup, evaluation andvisualisation.

Note that our system fundamentally differs from themagnetic positioning system presented in [5],which doesnot use the resonant coupling principle.

System DescriptionAs described in our previous work [4] the system consistsof two components: stationary magnetic field transmittersand wearable receiver units which measure the magneticfield strengths at their positions. These measurements areused to determine the position and orientation of thereceiver in relation to the set of transmitters

Magnetic Field Transmitters The field emitters use 3perpendicular transmitter coils (200 turns) to sequentiallygenerate oscillating magnetic fields. This coil setup allowsto limit the position of the receiver at a low number ofrelative positions at the intersections of the magnetic fieldlines of the perpendicular and sequentially generatedmagnetic fields of a transmitter. On the hardware sideoscillating circuits tuned to 20kHz maximize the poweroutput of the 16V peak to peak 0.176A input signal of thecoils.

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Transmitter generates a magnetic field at a certain resonant frequency f

Receiver is calibrated to resonant frequency f

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Figure 1: Oscillating circuits included in the transmitter andreceiver coils filter out influences of other electro magneticsources and maximize the power output of the transmittercoils. The lower signal plot depicts the sensitivity of thereceiver coil linked to the frequency of the magnetic field.

Wearable Receiver Unit The receiver unit estimatesthe magnetic field strength at its current position using a3 axis receiver coil. To filter out electromagnetic noise,the board is also equipped with an oscillating circuit tunedto the same resonant frequency as the transmitter.Integrated adjustable amplifiers accurately allow to samplethe dynamic input signal (1.5 V at 10 cm and 0.004 V at

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4 m) even at large distances. Onboard acceleration andgyroscope sensors provide magnetic field independentinformation for gesture recognition tasks and stabilize theposition and orientation estimation of the receiver. Thegathered movement information can be either stored onthe onboard SD card or can be transmitted using a Zigbeebased RF Connection or a serial connection to the PC.The LiPo battery supplies enough power to run thereceiver for 8 hours.

Figure 2: The transmitter coils (in the background) and thereceiver circuit (in the foreground).

After collecting all measurements at the receiver’spositions, the processing program converts the rawmagnetic field measurements to distance and positioninformation, the underlying field model uses the law ofBiot Savart 1

d3 dependency to linearise the magnetic fieldinformation. Also the inhomogeneity of the magnetic fieldis taken into account. The distances, acceleration andgyroscope information are then used in a particle filter to

estimate the position, heading and orientation of thereceiver.

Figure 3: A screenshot of the MagSys software suite.

Interface SoftwareWe implemented a Java based application MagSys whichcan be used to retrieve the information transmitted in thelower level position estimation program presented in theprevious subsection. The main functions are (1)calibration and setup of the localization system, (2)definition of region of interests, (3) on- / off lineillustration of the sensor data (current position, metainformation like receiver is in a region of interest, on-lineannotation of activites and positions, sensor data), (4)integration of network cameras for ground truthinformation (online dewarping of fisheye webcampictures), (5) off-line annotation and replay functionalityof recorded data sets for post process- ing and (6) simpleintegration of new sensor modalities (especially spatialsensor). A screenshot of the system is shown in Figure 4

System PerformanceIn our previous work, we have shown that this system isrobust enough to distinguish between more than 20

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different locations in apartments, houses, bureaus orcellars. The current prototype system with handmadeprototype coils currently provides Cartesian coordinateswith an accuracy of 62.3cm with a standard deviation of34.6. This is more than enough to provide metainformation about user position required by mostapplications (e.g. The person is near the fridge.). Notethat when attaching a sensor to the body, the bodyalready covers an area of approximately 0.5m2 so thataccuracies below 50 cm are often pointless. In terms ofusefulness for typical applications it is important to notethat our system can also provide the approximateorientation of the receiver (in the coordinate system of themagnetic transmitter).

Figure 4: Example of the localization output of our system.The blue squares are the transmitter coils. The green circlesthe location estimates from the individual coils, the red cloudthe particle filter based combined location estimate.

References[1] A. Kurs, A. Karalis, R. Moffatt, J. D. Joannopoulos,

P. Fisher, and M. Soljai. Wireless power transfer viastrongly coupled magnetic resonances. Science,317(5834):83–86, 2007.

[2] H. Liu, H. Darabi, P. Banerjee, and J. Liu. Survey ofwireless indoor positioning techniques and systems.IEEE Transactions on Systems, Man and Cybernetics,Part C: Applications and Reviews, 37(6):1067–1080,2007.

[3] J. A. Paradiso, K.-y. Hsiao, and A. Benbasat. Tangiblemusic interfaces using passive magnetic tags. InProceedings of the 2001 conference on New interfacesfor musical expression, NIME ’01, pages 1–4,Singapore, Singapore, 2001. National University ofSingapore.

[4] G. Pirkl and P. Lukowicz. Robust, low cost indoorpositioning using magnetic resonant coupling. InProceedings of the 2012 ACM Conference onUbiquitous Computing. International Conference onUbiquitous Computing (Ubicomp-2012), 14th,September 5-8, Pittsburgh,, PA, USA (United States),pages 431–440. ACM, 2012.

[5] E. A. Prigge and J. P. How. Signal architecture for adistributed magnetic local positioning system. IEEESensors Journal, 4(6):864–873, December 2004.

[6] J. Torres-solis, T. H. Falk, and T. Chau. A review ofindoor localization technologies : towards navigationalassistance for topographical disorientation. English,pages 51–84, 2010.

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