1078 IEEE TRANSACTIONS ON SYSTEMS.MAN.AND CYBERNETICS-PART C:APPLICATIONS AND REVIEWS,VOL.37.NO.6.NOVEMBER 2007 wireless sensor networks in a wide variety of applications, 2)Internetworking of different wireless positioning systems including indoor location positioning [65].Such systems using is a research and practical topic in order to extend the wireless sensor network have been described as"cooperative," positioning range. “relative,”“multi-hop,”“GPS-free,”or“network"localization; 3)Wireless combined with other technologies such as optical ad-hoc”or“sensor'”positioning;and“self-localization”in (e.g.,IR),inertial,dc electromagnetic and ultrasonic for various papers.Communication and measurements between indoor location is another trend.How to combine these many pairs of sensors are required to achieve localization technologies into a practical system is a topic of sensor for all sensors.We refer the readers to [14]for more details fusion. about cooperative localization.Up to now,two major sensor 4)How to deploy sensors to improve the positioning accu- network standards are the IEEE 802.15.4 physical(PHY)layer racy,how to finish deploying wireless positioning system and medium access control (MAC)layer standard for low-rate in a short time,especially for emergency responder appli- wireless personal-area networks(LR-WPANs),and the ZigBee cation is also worth considering [73]. networking and application layer standard [67].These standards 5)Wireless indoor location using UWB (from 3.1 to allow for localization information to be measured between pairs 10.6 GHz)techniques19 and indoor positioning using mo- of sensors.In particular,RSS can be measured in the 802.15.4 bile cellular network are other promising research top- PHY standard via the link quality indication (LQD,which ics[31]. reports the signal strength associated with a received packet 6)How to integrate indoor and outdoor positioning system to higher layers.Most of the sensor-network-based location is another area of research.20 This integration may help estimations use RSS measurement [68],[69].Some systems in developing more efficient and robust detection systems also use TOA measurement [68],[70].Others take AOA for positioning of mobile computing nodes.In this case, measurement such as ad hoc positioning system(APS)[71]. a mobile node will be tracked indoor or outdoor using the Table I briefly compares the current systems and solutions. same detection system. The systems solutions shown in this table are mainly the ones whose specifications have been reported by their developers. REFERENCES We have excluded the cases in which little or no information on them has been made available [1]J.Hightower and G.Borriello,"Location systems for ubiquitous comput- ing"Computer,vol.34,no.8,Aug.2001. [2]K.Pahlavan,X.Li,and J.Makela,"Indoor geolocation science and tech- nology,"IEEE Commun.Mag.,vol.40,no.2,pp.112-118,Feb.2002. V.CONCLUSION AND FUTURE TRENDS [3]C.Drane,M.Macnaughtan,and C.Scott,"Positioning GSMtelephones," IEEE Commun.Mag..vol.36,no.4.pp.46-54.59.Apr.1998. This paper surveys the current indoor positioning techniques [4]B.Fang."Simple solution for hyperbolic and related position fixes."IEEE and systems.Different performance measurement criteria are Trans.Aerosp.Electron.Syst.,vol.26,no.5,pp.748-753,Sep.1990. discussed and several tradeoffs among them are observed.For [5]M.Kanaan and K.Pahlavan,"A comparison of wireless geolocation al- gorithms in the indoor environment,"in Proc.IEEE Wireless Commun. example,the one between complexity and accuracy/precision Nen.Comt,2004,vol.1,Pp.177-182. needs careful consideration when we choose positioning sys- [6]D.Torrieri,"Statistical theory of passive location systems,"IEEE Trans. tems and techniques for different applications environments Aerosp.Electron.Syst.,vol.20,no.2.pp.183-197,Mar.1984. [7]J.Zhou,K.M.-K.Chu,and J.K.-Y.Ng,"Providing location services within such as warehousing,robotics,or emergency.Usually,loca- a radio cellular network using ellipse propagation model,"in Proc.19th tion fingerprinting scheme is better for open areas while Active Int.Conf.Adv.Inf.Nerw.Appl Mar.2005.pp.559-564. RFID is suitable for dense environments.In terms of scalability [8]A.Teuber and B.Eissfeller,"Atwo-stage fuzzy logic approach for wireless LAN indoor positioning,"in Proc.IEEE/lON Position Location Navigat. and availability,these positioning techniques and systems have Smp,Apr.2006,vol.4,pp.730-738. their own important characteristics when applied in real envi- [9]M.Kossel,H.R.Benedickter,R.Peter,and W.Bachtold,"Microwave ronments.The choice of technique and technology significantly backscatter modulation systems,"IEEE MTT-S Dig.vol.3.pp.1427- 1430.Jum.2000. affects the granularity and accuracy of the location information. [10]A.Gunther and C.Hoene,"Measuring round trip times to determine the Future trends of wireless indoor positioning systems are as distance between WLAN nodes,"in Proc.Nenw.2005.,Waterloo,ON. follows. Canada,May 2005,pp.768-779 [11]B.D.Van Veen and K.M.Buckley,"Beamforming:A versatile approach 1)New or hybrid position algorithms are needed.A few of to spatial filtering."IEEE ASSP Mag..vol.5,no.2.pp.4-24,Apr.1988. the works have already been started supporting such algo- [12]P.Stoica and R.L.Moses,Introduction to Spectral Analysis.Englewood rithms.For example,a calibration-free location algorithm Cliffs.NJ:Prentice-Hall.1997. [13]B.Ottersten,M.Viberg,P.Stoica,and A.Nehorai,"Exact and large based on triangulation,triangular interpolation and extrap- sample ML techniques for parameter estimation and detection in array olation (TIX),is introduced in [75].A hybrid algorithm processing."in Radar Array Processing.S.S.Haykin,J.Litva,and is presented in [76]for indoor positioning using WLAN T.J.Shepherd,Eds.New York:Springer-Verlag,1993,pp.99-151. [14]N.Patwari,J.Ash,S.Kyperountas,A.O.Hero,R.M.Moses,and that aims to combine the benefits of the RF propagation N.S.Correal,"Locating the nodes:Cooperative localization in wireless loss model and fingerprinting method.The same work has sensor networks,"IEEE Signal Process.Mag.,vol.22,no.4,pp.54-69, been done in [77].The selective fusion location estima- Jul.2005. tion (SELFLOC)[72]algorithm infers the user location by selectively fusing location information from multiple wireless technologies and/or multiple classical location 19Sapphire DART UWB-based Real-Time Location Systems.http://www. multispectral.com/ algorithms in a theoretically optimal manner. 2Place Lab,a privacy-observant location system.htp://placelab.org Authorized licensed use limited to:University of Pittsburgh.Downloaded on January 27.2009 at 17:04 from IEEE Xplore.Restrictions apply.1078 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 37, NO. 6, NOVEMBER 2007 wireless sensor networks in a wide variety of applications, including indoor location positioning [65]. Such systems using wireless sensor network have been described as “cooperative,” “relative,” “multi-hop,” “GPS-free,” or “network” localization; “ad-hoc” or “sensor” positioning; and “self-localization” in various papers. Communication and measurements between many pairs of sensors are required to achieve localization for all sensors. We refer the readers to [14] for more details about cooperative localization. Up to now, two major sensor network standards are the IEEE 802.15.4 physical (PHY) layer and medium access control (MAC) layer standard for low-rate wireless personal-area networks (LR-WPANs), and the ZigBee networking and application layer standard [67]. These standards allow for localization information to be measured between pairs of sensors. In particular, RSS can be measured in the 802.15.4 PHY standard via the link quality indication (LQI), which reports the signal strength associated with a received packet to higher layers. Most of the sensor-network-based location estimations use RSS measurement [68], [69]. Some systems also use TOA measurement [68], [70]. Others take AOA measurement such as ad hoc positioning system (APS) [71]. Table I briefly compares the current systems and solutions. The systems solutions shown in this table are mainly the ones whose specifications have been reported by their developers. We have excluded the cases in which little or no information on them has been made available. V. CONCLUSION AND FUTURE TRENDS This paper surveys the current indoor positioning techniques and systems. Different performance measurement criteria are discussed and several tradeoffs among them are observed. For example, the one between complexity and accuracy/precision needs careful consideration when we choose positioning sys￾tems and techniques for different applications environments such as warehousing, robotics, or emergency. Usually, loca￾tion fingerprinting scheme is better for open areas while Active RFID is suitable for dense environments. In terms of scalability and availability, these positioning techniques and systems have their own important characteristics when applied in real envi￾ronments. The choice of technique and technology significantly affects the granularity and accuracy of the location information. Future trends of wireless indoor positioning systems are as follows. 1) New or hybrid position algorithms are needed. A few of the works have already been started supporting such algo￾rithms. For example, a calibration-free location algorithm based on triangulation, triangular interpolation and extrap￾olation (TIX), is introduced in [75]. A hybrid algorithm is presented in [76] for indoor positioning using WLAN that aims to combine the benefits of the RF propagation loss model and fingerprinting method. The same work has been done in [77]. The selective fusion location estima￾tion (SELFLOC) [72] algorithm infers the user location by selectively fusing location information from multiple wireless technologies and/or multiple classical location algorithms in a theoretically optimal manner. 2) Internetworking of different wireless positioning systems is a research and practical topic in order to extend the positioning range. 3) Wireless combined with other technologies such as optical (e.g., IR), inertial, dc electromagnetic and ultrasonic for indoor location is another trend. How to combine these technologies into a practical system is a topic of sensor fusion. 4) How to deploy sensors to improve the positioning accu￾racy, how to finish deploying wireless positioning system in a short time, especially for emergency responder appli￾cation is also worth considering [73]. 5) Wireless indoor location using UWB (from 3.1 to 10.6 GHz) techniques19 and indoor positioning using mo￾bile cellular network are other promising research top￾ics [31]. 6) How to integrate indoor and outdoor positioning system is another area of research.20 This integration may help in developing more efficient and robust detection systems for positioning of mobile computing nodes. In this case, a mobile node will be tracked indoor or outdoor using the same detection system. REFERENCES [1] J. Hightower and G. Borriello, “Location systems for ubiquitous comput￾ing” Computer, vol. 34, no. 8, Aug. 2001. [2] K. Pahlavan, X. Li, and J. Makela, “Indoor geolocation science and tech￾nology,” IEEE Commun. Mag., vol. 40, no. 2, pp. 112–118, Feb. 2002. [3] C. Drane, M. Macnaughtan, and C. Scott, “Positioning GSM telephones,” IEEE Commun. Mag., vol. 36, no. 4, pp. 46–54, 59, Apr. 1998. [4] B. Fang, “Simple solution for hyperbolic and related position fixes,” IEEE Trans. Aerosp. Electron. Syst., vol. 26, no. 5, pp. 748–753, Sep. 1990. [5] M. Kanaan and K. Pahlavan, “A comparison of wireless geolocation al￾gorithms in the indoor environment,” in Proc. IEEE Wireless Commun. Netw. Conf., 2004, vol. 1, pp. 177–182. [6] D. Torrieri, “Statistical theory of passive location systems,” IEEE Trans. Aerosp. Electron. Syst., vol. 20, no. 2, pp. 183–197, Mar. 1984. [7] J. Zhou, K. M.-K. Chu, and J. K.-Y. Ng, “Providing location services within a radio cellular network using ellipse propagation model,” in Proc. 19th Int. Conf. Adv. Inf. Netw. Appl., Mar. 2005, pp. 559–564. [8] A. Teuber and B. Eissfeller, “A two-stage fuzzy logic approach for wireless LAN indoor positioning,” in Proc. IEEE/ION Position Location Navigat. Symp., Apr. 2006, vol. 4, pp. 730–738. [9] M. Kossel, H. R. Benedickter, R. Peter, and W. Bachtold, “Microwave backscatter modulation systems,” IEEE MTT-S Dig., vol. 3, pp. 1427– 1430, Jun. 2000. [10] A. Gunther and C. Hoene, “Measuring round trip times to determine the distance between WLAN nodes,” in Proc. Netw. 2005., Waterloo, ON, Canada, May 2005, pp. 768–779 [11] B. D. Van Veen and K. M. Buckley, “Beamforming: A versatile approach to spatial filtering,” IEEE ASSP Mag., vol. 5, no. 2, pp. 4–24, Apr. 1988. [12] P. Stoica and R. L. Moses, Introduction to Spectral Analysis. Englewood Cliffs, NJ: Prentice-Hall, 1997. [13] B. Ottersten, M. Viberg, P. Stoica, and A. Nehorai, “Exact and large sample ML techniques for parameter estimation and detection in array processing,” in Radar Array Processing, S. S. Haykin, J. Litva, and T. J. Shepherd, Eds. New York: Springer-Verlag, 1993, pp. 99–151. [14] N. Patwari, J. Ash, S. Kyperountas, A. O. Hero, R. M. Moses, and N. S. Correal, “Locating the nodes: Cooperative localization in wireless sensor networks,” IEEE Signal Process. Mag., vol. 22, no. 4, pp. 54–69, Jul. 2005. 19Sapphire DART UWB-based Real-Time Location Systems. http://www. multispectral.com/ 20Place Lab, a privacy-observant location system. http://placelab.org Authorized licensed use limited to: University of Pittsburgh. Downloaded on January 27, 2009 at 17:04 from IEEE Xplore. Restrictions apply