Phone-Radar ： Infrastructure-free Device-to-deveice Localization 班級：碩研資工一甲 姓名：高逸軒 學號： MA4G0110 Author:Zheng Song, STATE KEY LAB. OF NETWORKING & SWITCHING TECHNOL., BEIJING UNIV. OF POSTS & TELECOMMUN., BEIJING, CHINA Source:VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2014 IEEE 79TH 1

Outline 1)INTRODUCTION 2)THE PROPOSED APPROACH A.System Overview B.Relative Movement Calculation C.Distance Measurement using RSSI D.Delative Location Calculation 3)EXPERIMENTS A.Impact of moving distance to localization accuracy B.Localization accuracy in indoor environment and outdoor environment C.Comparison between PhoneRadar;Wifi localization,cell-id localization and GP S 4)CONCLUSION 2

1)INTRODUCTION Supporting applications such as the ones above requires providing accurate distance and direction to both smartphone users. An easy-to-find solution is share locations obtained from existing localization method, e.g.,GPS or WiFi based localization methods. However, existing commonly-used pedestrian localization approaches are constrained either by limited coverage or by low accuracy and is not suitable for these scenarios. GPS always fails to function in indoor environments due where the GPS signals are too weak. 3

1)INTRODUCTION Cell-id based localization method is considered to be an important aid to GPS, the basic idea of which is to use the received signal strength of GSM cell towers combined with the localizations of cell towers to calculate localization. It functions well in any area that is covered by GSM network, including indoor environments, but the hundred meter accuracy of cell-id localization method constrains its usage in device-to-device localization scenario. Another widely used localization technique is the fingerprinting localizationbas-ed on the received-signalstrength(RSS) observations of mobile devices to fixed WiFi access points. It match all measured RSS values to pre-trained RSSI finger-prints and determine the position that gives the best match. 4

1)INTRODUCTION Dead-reckoning method is another recent approach, which use the low-cost inertial sensors equipped in most smartphones to provide continuous position, velocity, and also orientation estimations. Phone-Radar is a hybrid approach taking advantages of both WiFi RSSI-based positioning and dead-reckoning techniques which improves its accuracy. Phone-Radar estimates the relative location between two smartphones by taking two measurement on the movement of the two smartphones separately and the change of the RSSI strength during the moving procedure. 5

2)THE PROPOSED APPROACH 6

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10 2)THE PROPOSED APPROACH

11 2)THE PROPOSED APPROACH

3)EXPERIMENTS Through simple setup procedures, one device serves as Wi-Fi access point(AP) and the other device is connected to the AP. They communicate by socket connection and the AP gathers both movement information and the received signal strength from the other device. When the relative location is calculated, the client’s location is shown in the screen of the AP. Before the experiments, two parameters, K and n are trained in advance. According to the test data, K is set to and n is set to 2.3. First, we verify the impact of the distance of relative movement to localization accuracy and we compare localization accuracy while the initial distance between the two devices is different. Second, we verify localization accuracy in both indoor and outdoor environments. 12

3)EXPERIMENTS A. Impact of moving distance to localization accuracy 13 Initial locations of volunteers A and B Impact of walking distance to localization error

3)EXPERIMENTS B. Localiztion accuracy in indoor environment and outdoor environment 14 Localization error of different initial distance in indoor environment and outdoor environment

3)EXPERIMENTS C.Comparison between PhoneRadar,Wifi localization,cell-id localization and GPS 15

4)CONCLUSION we present Phone-Radar, which is an infrastructure-free device-to-device localization system. We further study the relationship among the initial relative locations between the two devices, their relative movements and the change of received signal strength measurements. we implement the proposed method and measure its performance under real world conditions. As far as we know, the proposed method is the first to solve device-to-device localization on mobile devices without any fixed infrastructure or add-on module. 16

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