Transcript 下載/瀏覽Download

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 GPS
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
A. System Overview
• The scenario comprises two mobile devices held by pedestrians,
denoted as A and B. As localization requirements mostly exist in
scenarios that two devices can not see each other, a wall is
added as a obstruction between two mobile devices to make
the proposed method more adaptive.
• By the measured parameters, the relative location of A towards
B can be calculated. The details of the implement are given in
the coming part of this section. It is worth noting that, during
time period 𝑇1 𝑇2 and 𝑇2 𝑇3 , at least one of the two devices
should be moving.
𝑚1𝐴
𝑚2𝐵
𝑟3
𝑟2
𝑚2𝐴
𝑟1
𝑚1𝐴
6
2) THE PROPOSED APPROACH
B.
Relative Movement Calculation
a.
Step detection:
 Nonlinear model is selected to estimate the step length. The step length L of pedestrians is determined by his
accelerator readings:𝑳 = 𝒌 ∗ 𝟒 𝑨𝒎𝒂𝒙 − 𝑨𝒎𝒊𝒏
 Based on the counted number of steps, the estimated step length and the direction of each step, the movement
vector of device A and B can be calculated separately by:
b. Relative movement:
a. The relative movement of A towards B, denoted by mi, ∀i ∈ T1 T2, T2 T3,
can be calculated by:
7
2) THE PROPOSED APPROACH
C. Distance Measurement using RSSI
 Let 𝑑i denote the distance between A and B on time i, ∀i ∈ {T1, T2, T3}. According to the free space radio
propagation model, the relationship between 𝑑i and 𝑟i is denoted as:
8
2) THE PROPOSED APPROACH
D. Relative Location Calculation
• B is set to be the origin of the coordinates, the direction
of axis y is north, and the direction of axis x is east. A’s
location at 𝑇1 is set to be 𝐴1 . On 𝑇2 , A’s relevant
location according to B is set to be 𝐴2 , which can be
calculated by 𝐴2 = 𝐴1 + 𝑚1 . Accordingly, 𝐴3 is
calculated by 𝐴3 = 𝐴2 + 𝑚1 . To know the original
relative location of A towards B, is to know the distance
between 𝐴1 and B, denoted as 𝑑1 and the direction of
𝐴1 B, denoted as α.
Targeted Parmeter: 𝑑1 𝑎𝑛𝑑 α
9
2) THE PROPOSED APPROACH
D. Relative Location Calculation
1. Calculation of 𝑑1 : Accoording to Cosine theorem,
𝛼1 𝑎𝑛𝑑 𝛼2 𝑐𝑎𝑛 𝑏𝑒 𝑑𝑒𝑛𝑜𝑡𝑒𝑑 𝑏𝑦 𝑑1 .
Calculation: 𝑑1
10
2) THE PROPOSED APPROACH
2. Calculation of α: To calculate α, the angle
𝛼4 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝐴1 𝐵 and x can be calculated instead.
11
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 0.304 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
Initial locations of volunteers A and B
Impact of walking distance to localization error
13
3) EXPERIMENTS
B.
Localiztion accuracy in indoor environment and outdoor environment
Localization error of different initial distance in indoor
environment and outdoor environment
14
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
Thank you
• The ending......
17