以目前定位系統來看，最常見的定位方法是藉由全球定位系統global positioning system (GPS) 來幫助定位，但如果目標物進入到有遮蔽的建築物內，GPS的衛星訊號會被建築物屏蔽，造成測量上的誤差。因此在室內環境實作定位系統必須依靠其他方法，目前最廣為使用的是偵測訊號接收強度來判斷位置，此類系統必須先在建築物內，大量的布建訊號發射節點，並蒐集建築物內每個位置所收到來自不同節點的訊號強度，先建立起訊號分布圖，就可以藉由此分布圖來比對目前目標物所接收到所有訊號的強度，進而判斷出目前可能的所在位置。由於此類型方法必須先對建築物做大量布建與事先訓練出訊號分布圖的工作，於使用性上非常不方便。因此有人提出了另一種室內定位的方法：行人定位推算系統，它主要是在行人身上配置少數的慣性感測器，如：加速度計、陀螺儀、電子羅盤，利用這些感測器所量測到的數據來推算出目前行人所移動的距離和方向，相較於利用訊號強度來定位的方法，行人定位推算系統不需要事先準備的工作，於成本上相對的較低，也較易於行人在新環境的使用。依照慣性感測器配戴的位置不同，行人定位推算系統可以大約分為兩大類：足配式與腰配式。對於現有的研究結果，一般來說足配式的方法有較高的準確率，但是在方向性的偵測上，因為腳在行走時容易晃動，對於方向性的偵測上會造成許多雜訊，因為在方向的偵測上誤差較大；而腰配式的方法對於距離的偵測上較為不準，但對於方向的偵測來說，由於腰間行走時就為平穩，所以雜訊較少。若考慮到使用上的方便程度，一般來說掛於腰間比掛在腳上對於一般人使用上較為方便，因此在本篇論文內，我們提出了一個新的方法改善腰間在估計行走距離的準確度，利用簡諧運動的物理特性找到在垂直方向的零速特性，讓感測器能在垂直方向上對垂直加速度做二次積分時可以做校準，藉以算出行走時準確的腰間高度位移，再藉由畢氏定理推算出水平位移。 除了在距離的估測上有所改善，我們也針對方向性的校準提出新的方法，一般室內定位的研究，都是利用附有詳細比例尺資訊的地圖來做地圖校準，而此類地圖對於一般使用大眾並不易取得。我們的目標是利用一般簡易的大樓平面圖設計出一套新的地圖校準方法，此類地圖雖沒有比例尺等詳細資訊，卻是一般使用者最易取得的資訊，相較於現有的地圖校準方法中，雖然可參考的資訊較少但卻更為實用。

The global positioning system (GPS) is widely used for localization. However, GPS does not perform well in an indoor environment due to that it is hard to receive satellite signal inside a building. A huge body of work utilized signal strength of short range signal (such as WiFi, Bluetooth, ultra sound or Infrared) to build a radio map for indoor localization, by deploying a great number of beacon nodes in the building. The drawback of such an infrastructure-based approach is that the deployment and calibration of the system is costly and labor-intensive. To overcome that, some prior studies proposed the use of Pedestrian Dead Reckoning (PDR) for indoor localization. The PDR system does not require to build a beacon-based infrastructure, in which a small number of sensors are put on the pedestrian. These sensors (such as G-sensor and Gyro) are used to estimate the distance and direction that the user traveled. The PDR approach can be generally categorized into two types: foot-mounted and waist-mounted. In general, the foot-mounted system can get accurate step length, but perform poorly in estimated heading direction. On the other hand, the waist-mounted system can estimate direction with high accuracy, but is hard to measure the step length. It will have stable platform for heading, but it hard gets accurate distance. In this work, we separate to two parts to implement indoor localization. First, in distance estimation, we proposed a waist-mounted based PDR using one 3-axis accelerometer and one gyroscope sensor. We utilize vertical acceleration to implement double integral for measuring the user’s instant height change and use some physical features of vertical acceleration during the walking to calibrate the measurement. Then based on the Pythagorean Theorem, we can estimate each step length based on the user’s height change during his/her walking. The other part is about the orientation calibration. We design a map matching algorithm to correct the sensor drift problem which is used the map without scale information. Our experiment results show that the accuracy is about 98.26% in estimating the user’s walking distance and the location error range is about 0.48 meter.

[1] E. D.Kaplan, and C.J. Hegarty, “Understanding GPS Principles and Applications,” Artech House, November 30, 2005.
[2] F. Carl, and G. Hans, “Location and Navigation Support for Emergency Responders: A Survey,” IEEE Pervasive Computing, vol. 9, pp. 38-47.
[3] P. Bahl, and V.N. Padmanabhan, “RADAR: an in-building RF-based user location and tracking system,” in Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies 2000 (INFOCOM 2000), 2000, pp 775-784 vol.2.
[4] B.P. Nissanka, C. Anit, and B. Hari, “The Cricket location-support system,” presented at Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, Massachusetts, United States, 2000.
[5] V. Seshadri, G.V. Zaruba, and M. Huber, “A Bayesian sampling approach to in-door localization of wireless devices using received signal strength indication,” in Third IEEE International Conference on Pervasive Computing and Communications (PerCom 2005), 2005, pp 75-84
[6] A. Cesare, and V. Giovanni, “A RSSI-based and calibrated centralized localization technique for Wireless Sensor Networks,” presented at Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops, 2006.
[7] M. Sugano, T. Kawazoe, Y. Ohta, and M. Murata, “Indoor localization system using RSSI measurement of wireless sensor network based on zigbee standard,” presented at The IASTED International Conference on Wireless Sensor Networks (WSN 2006) Banff, Canada, July 2006.
[8] B.F. Rolfe, S.W. Ekanayake, P.N. Pathirana, and M. Palaniswami, “Localization with orientation using RSSI measurements: RF map based approach,” in 3rd International Conference on Intelligent Sensors, Sensor Networks and Information 2007 (ISSNIP 2007), 2007, pp 311-316.
[9] W. Roy, H. Andy, F. Veronica, and G. Jonathan, “The active badge location system,” ACM Trans. Inf. Syst., vol. 10, 1992, pp. 91-102.
[10] C. Ho-lin, T. Jr-ben, L. Tsung-Te, C. Hao-Hua, and H. Polly, “Spinning beacons for precise indoor localization,” presented at Proceedings of the 6th ACM conference on Embedded network sensor systems, Raleigh, NC, USA, 2008.
[11] L. Tsung-Han, I.-H. Ng, L. Seng-Yong, K.-M. Chen, and H. Polly, “A microscopic examination of an RSSI-signature-Based indoor localization system,” presented at Fifth Workshop on Embedded Networked Sensors 2008, 2-6.
[12] T.S. Cinotti, L.D. Stefano, G. Raffa, L. Roffia, M. Pettinari, and M. Mola, “Dead reckoning supports stereo vision in pedestrians tracking,” presented at Fourth IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06), 2006.
[13] F. Carl, M. Kavitha, H. Mike, and G. Hans, “Ultrasound-aided pedestrian dead reckoning for indoor navigation,” presented at Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments, San Francisco, California, USA, 2008.
[14] S. Chumkamon, P. Tuvaphanthaphiphat, and P. Keeratiwintakorn, “A blind navigation system using RFID for indoor environments,” in 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008 (ECTI-CON 2008), 2008, pp 765-768.
[15] C. Burcu, “HeadSLAM - simultaneous localization and mapping with head-mounted inertial and laser range sensors,” in 12th IEEE International Symposium on Wearable Computers, 2008, pp 3-10.
[16] T.-h. Wu, and W.-Y. Shih, “Measuring the location of bio-sensing sensors,” presented at 6th Wireless Ad-hoc and Sensor Networks 2010 conference, National Taiwan University, Taipei, Taiwan, 2-3 September 2010.
[17] L. Tsung-Han, I.H. Ng, L. Seng-Yong, and P. Huang, “Impact of Beacon Packet Losses to RSSI-Signature-Based Indoor Localization Sensor Networks,” in Tenth International Conference on Mobile Data Management: Systems, Services and Middleware 2009 (MDM '09), 2009, pp 389-390.
[18] C.-C. Shih. “The Implementation of a G-Sensdor-based Pedometer,” M.S. paper, Dept. C.S.I.E., National Central Univ., Taoyuan County, Taiwan 2010.
[19] F. Jorgensen, “Accurate step counter,” U.S. Patent 0 172 203 A1, Jul. 17, 2008.
[20] M. Martin, and M. Michael, “A step counter service for Java-enabled devices using a built-in accelerometer,” presented at Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009), Dublin, Ireland, 2009.
[21] P.L. Schneider, S.E. Crouter, O. Lukajic, and D.R. Bassett, “Accuracy and reliability of ten pedometers for measuring steps over a 400-m walk.,” Medicine & Science in Sports & Exercise, vol. 35, 2003, pp. 1779-1784.
[22] H.J. Ailisto, M. Lindholm, J. Mantyjarvi, E. Vildjiounaite, and S.-M. Makela, “Identifying people from gait pattern with accelerometers,” presented at Biometric Technology for Human Identification II, Orlando, FL, USA, Monday 28 March 2005.
[23] B.C. Carter, M. Vershinin, and S.P. Gross, “A Comparison of Step-Detection Methods: How Well Can You Do?,” Biophysical Journal, vol. 94, 2008, pp. 306-319.
[24] G. Davrondzhon, “Gait Recognition Using Acceleration from MEMS,” in First International Conference on Availability, Reliability and Security (ARES'06), Vienna, Austria, 2006, pp 432-439.
[25] D. Gafurov, E. Snekkenes, and P. Bours, “Spoof Attacks on Gait Authentication System,” IEEE Transactions on Information Forensics and Security, vol. 2, 2007, pp. 491-502.
[26] D. Gafurov, E. Snekkenes, and P. Bours, “Gait Authentication and Identification Using Wearable Accelerometer Sensor,” in 2007 IEEE Workshop on Automatic Identification Advanced Technologies, 2007, pp 220-225.
[27] S. Guangyi, Z. Yuexian, J. Yufeng, C. Xiaole, and W.J. Li, “Towards HMM based human motion recognition using MEMS inertial sensors,” in 2008 IEEE International Conference on Robotics and Biomimetics (ROBIO 2008), 2009, pp 1762-1766.
[28] S. Leonhardt, T. Falck, P. Mähönen, H. Ying, C. Silex, A. Schnitzer, S. Leonhardt, and M. Schiek, “Automatic Step Detection in the Accelerometer Signal” in 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007). vol. 13, R. Magjarevic, and J.H. Nagel, Eds.: Springer Berlin Heidelberg, 2007, pp. 80-85.
[29] J. Mantyjarvi, M. Lindholm, E. Vildjiounaite, S.M. Makela, and H.A. Ailisto, “Identifying users of portable devices from gait pattern with accelerometers,” in 2005 Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '05), 2005, pp ii/973-ii/976 Vol. 2.
[30] F. Nagashima, and Y. Hada, “Step Counter and method of counting steps,” U.S. Patent 7 725 289 B2, May 25, 2010.
[31] S. Godha, G. Lachapelle, and M.E. Cannon., “Integrated GPS/INS system for pedestrian navigation in a signal degraded environment,” presented at ION GNSS 2006, 26-29 September 2006.
[32] Q. Ladetto and B. Merminod, “In step with INS—navigation for the blind, tracking emergency crews,” GPS World, pp. 30–38, Oct. 2002.
[33] L. Ojeda, and J. Borenstein, “Personal Dead-reckoning System for GPS-denied Environments,” in 2007 IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR 2007), 2007, pp 1-6.
[34] J.C. Alvarez, R.C. Gonzalez, D. Alvarez, A.M. Lopez, and J. Rodriguez-Uria, “Multisensor Approach to Walking Distance Estimation with Foot Inertial Sensing,” in 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), 2007, pp 5719-5722.
[35] M. Dippold, “Personal Dead Reckoning with Accelerometers,” presented at The 3rd International Forum on Applied Wearable Computing 2006 (IFAWC2006), Bremen, Germany, March 15-16 2006.
[36] F. Eric, “Pedestrian Tracking with Shoe-Mounted Inertial Sensors,” in IEEE Computer Graphics and Applications. vol. 25, 2005, pp. 38-46.
[37] A.R. Jimenez, F. Seco, C. Prieto, and J. Guevara, “A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU,” in 2009 IEEE International Symposium on Intelligent Signal Processing (WISP 2009), 2009, pp 37-42.
[38] L. Ojeda and J. Borenstein, “Non-GPS navigation for emergency responders,” in International Joint Topical Meeting: Sharing Solutions for Emergencies and Hazardous Environments, Salt Lake City, UT, February 12-15 2006.
[39] L. Ojeda, and J. Borenstein, “Non-GPS Navigation for Security Personnel and First Responders,” Journal of Navigation, vol. 60, September 2007 2007, pp. 391-407.
[40] W. Oliver, and H. Robert, “Pedestrian localisation for indoor environments,” presented at Proceedings of the 10th international conference on Ubiquitous computing, Seoul, Korea, 2008.
[41] RaúlFeliz, E. Zalama, and J.G. García-Bermejo, “Pedestrian tracking using inertial sensors,” Journal of Physical Agents, vol. 3, 2009, pp. 35-42.
[42] K. Sagawa, H. Inooka, and Y. Satoh, “Non-restricted measurement of walking distance,” in 2000 IEEE International Conference on Systems, Man, and Cybernetics, 2000, pp 1847-1852 vol.3.
[43] Y. Xiaoping, E.R. Bachmann, H. Moore, and J. Calusdian, “Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules,” in 2007 IEEE International Conference on Robotics and Automation, 2007, pp 2526-2533.
[44] D.H. Titterton, and J.L. Weston, “Strapdown Inertial Navigation Technology,” Peter Peregrinus Ltd, 1997.
[45] P.-Y. Gillieron, and B. Merminod, “Personal Navigation System for Indoor Applications,” in Proceedings of the 11th IAIN World Congress on Smart Navigation, Systems and Services, Berlin, 2003.
[46] D. Alvarez, R.C. Gonzalez, A. Lopez, and J.C. Alvarez, “Comparison of Step Length Estimators from Weareable Accelerometer Devices,” in 28th Annual International Conference of the IEEE in Engineering Medicine and Biology Society (EMBS '06), 2006, pp 5964-5967.
[47] F. Lei, P.J. Antsaklis, L.A. Montestruque, M.B. McMickell, M. Lemmon, S. Yashan, F. Hui, I. Koutroulis, M. Haenggi, X. Min, and X. Xiaojuan, “Design of a wireless assisted pedestrian dead reckoning system - the NavMote experience,” IEEE Transactions on Instrumentation and Measurement, vol. 54, 2005, pp. 2342-2358.
[48] S.H. Shin, C.G. Park, H.S. Hong, and J.M. Lee, “MEMS-Based Personal Navigator Equipped on the User's Body,” presented at ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, 13-16 september 2005.
[49] H. Weinberg, “Using the ADXL202 in Pedometer and Personal Navigation Applications,” in Application Notes American Devices, 2002.
[50] R. Stirling, J. Collin, K. Fyfe, and F. Lachapelle, “An innovative shoe-mounted pedestrian navigation system,” presented at Proceedings of European Navigation Conference GNSS 2003, Graz, Austria, 22-25 April 2003.
[51] TelosB, Available: http://www.willow.co.uk/html/telosb_mote_platform.html
[52] MSP430 F1611, Available: http://focus.ti.com/docs/prod/folders/print/msp430f1611.html
[53] CC2420, Available: http://focus.ti.com/docs/prod/folders/print/cc2420.html
[54] 802.15.4, Available: http://www.ieee802.org/15/pub/TG4.html
[55] FTDI, Available: http://www.ftdichip.com/Documents/DataSheets/ds232b18.pdf
[56] ADXL 330, Available: http://www.analog.com/en/mems-sensors/inertial-sensors/adxl330/products/product.html
[57] IDG 500, Available: http://invensense.com/mems/gyro/idg500.html
[58] Simple Harmonic Motion, Available: http://en.wikipedia.org/wiki/Simple_harmonic_motion
[59] E. Ayyappa, “Normal Human Locomotion, Part 1: Basic Concepts and Terminology,” JPO: Journal of Prosthetics and Orthotics, vol. 9, 1997, pp. 10-17.
[60] L. Cheng, and S. Haile, “Managed exercise monitoring: a novel application of wireless on-body inertial sensing,” in 2008 5th International Summer School and Symposium on Medical Devices and Biosensors (ISSS-MDBS 2008) , 2008, pp 194-197.
[61] V. Renaudin, O. Yalak, P. Tom´e, and B. Merminod, “Indoor Navigation of Emergency Agents”, European Journal of Navigation, vol. 5, no. 3, 2007.
[62] A.R.J. Ruiz, F.S. Granja, J.C.P. Honorato, and J.I.G. Rosas, “Pedestrian indoor navigation by aiding a foot-mounted IMU with RFID Signal Strength measurements,” in 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 15-17 Sept, 2010, pp 1-7.
[63] J. Hightower, R. Want, and G. Borriello, “SpotON: An indoor 3D location sensing technology based on RF signal strength” Univ. Washington, Seattle, Tech. Rep. UW CSE 2000-02-02, Feb.2000
[64] L. M. Ni, Y. Liu, Y. C. Lau, and A. P. Patil, “LANDMARC: Indoor Location sensing using active RFID,” Wireless Netw., vol. 10, no. 6, pp. 701-710, Nov. 2004.
[65] J. J. Caffery and G. L. Stuber, “Overview of radiolocation in CDMA cellular system,” IEEE Commun. Mag., vol. 36, no. 4, pp. 38–45, Apr. 1998.
[66] M. Beigl, S. Intille, J. Rekimoto, H. Tokuda, V. Otsason, A. Varshavsky, A. LaMarca, and E. de Lara, “Accurate GSM Indoor Localization,” in UbiComp 2005: Ubiquitous Computing. vol. 3660: Springer Berlin / Heidelberg, 2005, pp. 903-903.
[67] A. Kotanen, M. Hannikainen, H. Leppakoski, and T. D. Hamalainen, “Experiments on local positioning with Bluetooth,” in Proc. IEEE Int. Conf. Inf. Technol.: Comput. Commun., Apr. 2003, pp. 297–303.
[68] J. Hallberg, M. Nilsson, and K. Synnes, “Positioning with Bluetooth,” in Proc. IEEE 10th Int. Conf. Telecommun., Mar. 2003, vol. 2, pp. 954–958.
[69] P. Prasithsangaree, P. Krishnamurthi, and P. K. Chrysanthis, “On indoor position with wireless LANs,” in Proc. IEEE Int. Symp. Pers. Indoor, Mobile Radio Commun., Sep. 2002, vol. 2, pp. 720–724.
[70] C. Krishna, I. Anand Padmanabha, and N.P. Venkata, “Indoor localization without the pain,” presented at Proceedings of the sixteenth annual international conference on Mobile computing and networking, Chicago, Illinois, USA, 2010.
[71] Y. Ji, S. Biaz, S. Pandey, and P. Agrawal, “ARIADNE: A Dynamic Indoor Signal Map Construction and Localization System,” In MobiSys, 2006.
[72] H. Lim, C. L. Kung, J. C. Hou, and H. Luo, “Zero Configuration Robust Indoor Localization: Theory and Experimentation,” In Infocom, 2006.
[73] S. Gezici, Z. Tian, G. V. Giannakis, H. Kobaysahi, A. F. Molisch, H. V. Poor, and Z. Sahinoglu, “Localization via ultra-wideband radios: A look at positioning aspects for future sensor networks,” IEEE Signal Process. Mag., vol. 22, no. 4, pp. 70–84, Jul. 2005.
[74] R. J. Fontana, E. Richley, and J. Barney, “Commercialization of an ultra wideband precision asset location system,” in Proc. IEEE Ultra Wideband Syst. Technol. Conf., Reston, VA, Nov. 2003, pp. 369–373.
[75] R. Ballagas, M. Rohs, J. G. Sheridan, and J. Borchers, “Sweep and point & shoot: Phonecam-based interactions for large public displays,” In CHI ’05: Extended abstracts on Human factors and computing systems, 2005.
[76] M. Rohs, “Real-world interaction with camera-phones,” In Proceedings of the 2nd International Symposium on Ubiquitous Computing Systems, 2004.
[77] R. Nishkam, S. Pravin, F. Andrew, E. Ahmed, and I. Liviu, “Indoor Localization Using Camera Phones,” in IEEE Workshop on Mobile Computing Systems and Applications, 2006, pp 19-19
[78] S. Thrun, D. Fox, W. Burgard, and F. Dellaert, “Robust Monte Carlo localization for mobile robots,” Artificial Intelligence, vol. 128, 2001, pp. 99-141.
[79] T. Rofer, and M. Jungel, “Vision-based fast and reactive Monte-Carlo localization,” in IEEE International Conference on Robotics and Automation, 2003. Proceedings. ICRA '03., 2003, pp 856-861 vol.1.
[80] J.S. Gutmann, and D. Fox, “An experimental comparison of localization methods continued,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002, pp 454-459 vol.1.
[81] B. Gerald and T. Andreas,“ DiaTrace - Neuartiges Assistenz- System für die Gesundheitsprävention zur Nahrungsaufnahme und Bewegungserfassung,” in Deutscher Kongress mit Ausstellung / Technologien - Anwendungen – Management, Berlin, Germany, 2008.
[82] Chen, K.Y and Bassett, D.R., “The technology of accelerometry – based activity: monitors: current & future”, American College of Sports Medicine, 2005.
[83] Shin, S.H.; Park, C.G.; Kim, J.W.; Hong, H.S.; Lee, J.M.; , "Adaptive Step Length Estimation Algorithm Using Low-Cost MEMS Inertial Sensors," Sensors Applications Symposium, 2007. SAS '07. IEEE , vol., no., pp.1-5, 6-8 Feb. 2007
[84] C.-M. Su, J.-W. Chou, C.-W. Yi, Y.-C. Tseng, and C.-H. Tsai, “Sensor-aided personal navigation systems for handheld devices,” in Proceedings of the 2010 39th International Conference on Parallel Processing Workshops, ser. ICPPW ’10. Washington, DC, USA: IEEE Computer Society, 2010, pp. 533–541.
[85] Tomoya Ishikawa, Masakatsu Kourogi, Takashi Okuma, Takeshi Kurata, “Economic and Synergistic Pedestrian Tracking System for Indoor Environments,” 2009 International Conference of Soft Computing and Pattern Recognition, pp.522-527, 2009.
[86] C. Ascher, C. Kessler, M. Wankerl, and G.F. Trommer, “Dual IMU Indoor Navigation with particle filter based map-matching on a smartphone,” in Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on, pp 1-5.
[87] Z. Hao, and J. Malik, “Learning a discriminative classifier using shape context distances,” in Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on, 2003, pp I-242-I-247 vol.1.
[88] S. Belongie, J. Malik, and J. Puzicha, “Shape matching and object recognition using shape contexts,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 24, 2002, pp. 509-522.
[89] J.A. Saghri, and H. Freeman, “Analysis of the Precision of Generalized Chain Codes for the Representation of Planar Curves,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. PAMI-3, 1981, pp. 533-539.
[90] N. Dunford and J. T. Schwartz, “Linear operators,” volumn I, Interscience Publishers, New York, 1958.
[91] Johnson, R. A. “Modern Geometry: An Elementary Treatise on the Geometry of the Triangle and the Circle.” Boston, MA: Houghton Mifflin, pp. 173-176, 249-250, and 268-269, 1929.
[92] Centroid , Available: http://en.wikipedia.org/wiki/Centroid#cite_ref-0
[93] J. A. Bitsch Link, P. Smith, and K. Wehrle, “Footpath: Accurate mapbased indoor navigation using smartphones,” in Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on, 2011.
[94] I. Constandache, R.R. Choudhury, and I. Rhee, “Towards Mobile Phone Localization without War-Driving,” in INFOCOM, 2010 Proceedings IEEE, pp 1-9.
[95] M. Quddus, W. Ochieng, L. Zhao, and R. Noland, “A general map matching algorithm for transport telematics applications,” GPS Solutions, vol. 7, 2003, pp. 157-167.
[96] C.E. White, D. Bernstein, and A.L. Kornhauser, “Some map matching algorithms for personal navigation assistants,” Transportation Research Part C: Emerging Technologies, vol. 8, 2000, pp. 91-108.
[97] G. Taylor, G. Blewitt, D. Steup, S. Corbett, and A. Car, “Road Reduction Filtering for GPS-GIS Navigation,” Transactions in GIS, vol. 5, 2001, pp. 193-207.
[98] Phuyal, Bishnu P., “Method and Use of Aggregated Dead Reckoning Sensor and GPS Data For Map Matching, ”Proceedings of the 15th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2002), Portland, OR, September 2002, pp. 430-437.
[99] Google Latitude Available: http://www.google.com/intl/en/mobile/latitude/
[100] P. Mohan, V. N. Padmanabhan, and R. Ramjee, “Nericell: rich monitoring of road and traffic conditions using mobile smartphones,” in Proceedings of the 6th ACM conference on Embedded network sensor systems, ser. SenSys ’08. New York, NY, USA: ACM, 2008, pp. 323–336.
[101] K. Chintalapudi, A. P. Iyer, and V. N. Padmanabhan, “Indoor Localization Without the Pain,” in 16th ACM International Conference on Mobile Computing and Networking (MobiCom 2010), Chicago, IL, September 2010, pp. 173–184.