LAN. On the Dynamic Performance of Indoor Positioning System using Wireless LAN on Smartphone



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一 般 社 団 法 人 電 子 情 報 通 信 学 会 信 学 技 報 THE INSTITUTE OF ELECTRONICS, IEICE Technical Report INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL ITS2015-6 REPORT(2015-06) OF IEICE. THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS LAN 338 8570 255 E-mail: {masaki,manabe,takaaki}@hslab.ees.saitama-u.ac.jp LAN ( ) R R ( ) R -60dBm LAN On the Dynamic Performance of Indoor Positioning System using Wireless LAN on Smartphone Masaki IIDUKA, Tetsuya MANABE, and Takaaki HASEGAWA Saitama University 255 Shimo Okubo, Sakura ku, Saitama, 338 8570 Japan E-mail: {masaki,manabe,takaaki}@hslab.ees.saitama-u.ac.jp Abstract This paper describes the dynamic performance evaluation of an indoor positioning system using the wireless LAN on smartphones. As a result, positioning errors of the longitudinal direction are increased in a negative direction along with an increase of the moving velocity. We define the access point variance rate R and the access point invariance rate R respectively, and find the adjusted delay which multiply the delay time and the access point invariance rate. Then, the adjusted delay is roughly constant when the threshold is -60dBm. Consequently, this paper suggests the existence of the value of the adjusted time to make the effects of the variance of the access points. Key words Dynamic performance, Positioning, Wireless LAN, Smartphone 1. (Location-Based Services; LBS) ( [1]) 7 LBS LBS GPS (Global Positioning System) WLAN (Wireless LAN) GPS ( [2], [3]) ( [4]) WLAN GPS 1 29 This article is a technical report without peer review, and its polished and /or extended version may be published elsewhere. Copyright 2015 by IEICE

LBS t (x, y) (x(t),y(t)) LBS WLAN 2. GPS WLAN GPS 4 GPS [5] WLAN Proximity [6], Trilateration (Triangulation) [7], Scene analysis [8] 3 Proximity (WLAN ) ( ) WLAN ID(BSSID; Basic Service Set Identifier) (RSSI; Received Signal Strength Indicator) WLAN BSSID Trilateration Proximity BSSID 3 WLAN RSSI Scene analysis (scene; ) ( ) [9] Triangulation Scene analysis Scene analysis [10] GPS PDR (Pedestrian Dead Reckoning) MDM (Magnetic Deviation Map) [11] GPS [12] GPS [13] WLAN RSSI RSSI [14] ( ) ( ) ( ) [15] WLAN ( ) [16] [17] M-CubITS (M-sequence Multimodal Markers for ITS; M-Cubed for ITS) 2 1 1 M-CubITS 1 ( ) 1 [18] WLAN 16 ( ) ( ) 3. 3. 1 WLAN [14] - 4 1(a) [14] BUFFALO WHR-300(IEEE 802.11n/g/b 2.4GHz ) 10 1(b) WLAN 2m 144 1(c) WLAN (BSSID RSSI) Android (SHARP AQUOS PHONE Xx 203SH) (BSSID RSSI 1 ) 1.2m 3. 2 1(c) ( 2) [14] 30 2

56.1m 2.3m 2.1m 39.6m 2.5m (a). 10m 5m AP4 AP2 AP3 AP1 AP10 AP8 AP6 AP9 AP7 AP5 10m (b). 142 143 144 2.0m 0.55m 0.55m 67 68 69 64 65 66 0.65m 0.65m 2.0m 1 2 3 3. (c). 1. 2 4. 2 /. 30 15 15 3. 3 3. 2 ( 3) 1(c) 144 48 1.2km/h 0.5 1.5 2.0 0.6km/h 1.8km/h 2.4km/h 1.2km/h 4 4. 1 3. 2 3. 3 [13] (x m (t),y m (t)) (x tr (t),y tr (t)) t ( ) e lat (t) =x m (t) x tr (t) ( ) e lon (t) =y m (t) y tr (t) 4 ( ) 0.6km/h 1.8km/h 2.4km/h -0.4m 5 ( ) 0.6km/h 1.2km/h 1.8km/h 2.4km/h ( ) 6 5 e lon [m] v[m/h] 31 3

4. 7 AP R. 5. 8. t (t+10) AP R= (1) t (t+10) AP R =1 R (2) 6. 4. 2 4. 1 WLAN R R R R RSSI -50dBm -60dBm -70dBm -80dBm -90dBm -99dBm RSSI 7 8-50dBm -60dBm n RSSI 9 1 32 4

9 n RSSI. n RSSI n =1, 3, 4, 5, 10, 20 n RSSI [18] WLAN 40m 55m 16 4km/h 16km/h [18] 16km/h 5. WLAN ( ) R R ( ) -60dBm WLAN ( ) [1] A. Kupper, Location-based Services, Wiley, 2005. [2] ITS2009-64 pp.153 158 Feb. 2010 [3] GPS/Wi-Fi/ ITS2013-76 pp.69 78 March 2014 [4] A.J. Weiss, On the accuracy of a cellular location system based on RSS measurements, IEEE Trans. Vehicular Tech., vol.52, no.6, pp.1508 1518, Nov. 2003. [5] WYSIWYAS IT ITS2008-30 pp.19 24 Dec. 2008 [6] J. Krumm and K. Hinckley, The NearMe Wireless Proximity Server, Proc. 6th Int. Conf. Ubiquitous Comput., pp.283 300, Ubicomp 04, Nottingham, UK, Sept. 2004. [7] A. LaMarca, Y. Chawathe, S. Consolvo, J. Hightower, I. Smith, J. Scott, T. Sohn, J. Howard, J. Hughes, F. Potter, J. Tabert, P. Powledge, G. Borriello, and B. Schilit, Place Lab: Device Positioning Using Radio Beacons in the Wild, Proc. 3rd Int. Conf. Pervasive Comput., pp.301 306, Pervasive 05, Springer-Verlag, Munich, Germany, May 2005. [8] J. Yin, Q. Yang, and L. Ni, Adaptive Temporal Radio Maps for Indoor Location Estimation, Proc. 3rd IEEE Int. Conf. Pervasive Comput. & Commun., pp.85 94, PerCom 05, Kauai, HI, USA, March 2005. [9] B. Li, J. Salter, A.G. Dempster, and C. Rizos, Indoor Positioning Techniques Based on Wireless LAN, Proc. 1st IEEE Int. Conf. Wireless Broadband & Ultra Wideband Commun., pp.13 16, AusWireless 06, Sydney, Australia, March 2006. [10] K. Sunagawa, L.-T. Hsu, and S. Kamijo, Pedestrian Dead Reckoning for Mobile Phones with Magnetic Deviation Map and GPS Accuracy, IEICE Technical Report ITS2014-17, Sept. 2014. [11] Y. Sekimoto, K. Todori, and T. Okutani, Hybrid high accuracy positioning combining positioning devices and infrastructure information, Proc. 11th ITS World Congress, Nagoya, Japan, Oct. 2004. [12] GPS ITS2014-12 pp.23 28 Aug. 2014 [13] LAN C vol.126 no.10 pp.1212 1220 Oct. 2006 [14] LAN ITS2012-41 pp.239 244 Feb. 2013 [15] LAN ITS2012-59 pp.7 12 March 2013 [16] Wi-Fi ITS2014-7 pp.69 78 June 2014 [17] M-CubITS (A) vol.j89-a no.11 pp.993 1003 Nov. 2006 [18] LAN ITS2014-65 pp.69 78 March 2015 33 5