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Techniques of Indoor Positioning 蔡智強 副教授 國立中興大學電機工程學系.

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Presentation on theme: "Techniques of Indoor Positioning 蔡智強 副教授 國立中興大學電機工程學系."— Presentation transcript:

1 Techniques of Indoor Positioning 蔡智強 副教授 國立中興大學電機工程學系

2 Outline Introduction Basic Techniques Advanced Techniques Commercial Products Using the Indoor Map Information Indoor Positioning Using Femtocell 4G LTE-A Localization System In-Location Alliance Conclusions

3 Introduction Location-aware real-time services ◦ Elderly nursing ◦ Child monitoring ◦ Object positioning Global Positioning System (GPS) is the most well-known positioning service The restrictions of GPS ◦ Requiring a line of sight (LOS) with satellite systems

4 Introduction (cont.) ◦ GPS signal is easily affected by buildings ◦ Errors up to 10m Need other techniques for indoor positioning

5 Basic Techniques Employ some information between beacon nodes and the unknown node

6 Trilateration

7 Trilateration (cont.) Node A’s coordinate is (x a, y a ) Node B’s coordinate is (x b, y b ) Node C’s coordinate is (x c, y c ) The unknown node D’s coordinate is (x, y) The distance between A (or B or C) and D is d 1 (or d 2 or d 3 )

8 Trilateration (cont.)

9 Triangulation (cont.)

10 The unknown node D’s coordinate is (x, y) Node A’s coordinate is (x a, y a ) and the angle to the D is ∠ADB Node B’s coordinate is (x b, y b ) and the angle to the D is ∠ADC Node C’s coordinate is (x c, y c ) and the angle to the D is ∠BDC

11 Triangulation (cont.)

12 Measuring Distance Three basic properties to measure the distance between a beacon node and a unknown node 1. Received signal strength indication (RSSI) 2. Time of flight (TOF) 3. Angle of arrival (AOA)

13 Received signal strength indication Two kinds of methods for RSSI location 1. Database 2. Radio propagation model

14 Received signal strength indication (cont.) Database ◦ Measure the relation between distances and RSSI values ◦ Set up a database According the database, we can calculate the distance between two nodes

15 Received signal strength indication (cont.) Radio propagation model ◦ In the RADAR system, the Wall Attenuation Factor (WAF) model is: where n indicates the rate at which path loss decreases with distance, P(d 0 ) signal power at some reference d 0, and d is the transmitter- receiver distance.

16 Received signal strength indication (cont.) Moreover, C is the maximum number of obstructions (walls), nW the number of obstructions between the transmitter and receiver, and WAF is the wall attenuation factor.

17 Time of flight Calculate the distance between a transmitter and a receiver by the time of flight ◦ Time of arrival (TOA) ◦ Time difference of arrival (TDOA)

18 Time of flight (cont.) TOA ◦ The transmitter and receiver must synchronize their time ◦ The transmitter sends a signal to the receiver ◦ Upon receiving the signal, based on the propagation time, the receiver can calculate the distance between the transmitter and it

19 Time of flight (cont.)

20 TDOA ◦ Based on the difference of time between different signals from the transmitter arriving at the receiver ◦ The transmitter sends two different signals with propagation speeds α 1, α 2, respectively ◦ The receiver receives two such signals at different times, say T 1 and T 2, respectively ◦ The distance is

21 Time of flight (cont.)

22 Angle of arrival By the propagation direction of radio- frequency waves incident on an antenna array

23 Comparisons RSSI ◦ Advantage: simple hardware ◦ Disadvantage: unstable, easily impacted by the environment TOA ◦ Advantage: good accuracy ◦ Disadvantage: time synchronization required, complex hardware

24 Comparisons (cont.) TDOA ◦ Advantage: no time synchronization, good accuracy ◦ Disadvantage: complex hardware AOA ◦ Advantage: nice accuracy ◦ Disadvantage: Directional antenna array required

25 Maximum likelihood estimation

26 Maximum likelihood estimation (cont.) n reference nodes with coordinates The unknown node in (x, y) The distances between reference nodes and the unknown node are, respectively, measured by RSSI values

27 Maximum likelihood estimation (cont.) Subtract the last equation from each equation

28 Maximum likelihood estimation (cont.) Use the matrix representation AX=b The coordinate of the unknown node :

29 Self-Calibrating Indoor Positioning System Based On ZigBee Devices This paper presents a positioning system based on the round-trip time-of-flight (RTT) measurement RTT can be modeled as:

30 System Architecture The developed system is composed of three types of transponders: ◦ Mobile node ◦ Calibration node ◦ Fixed node

31 System Architecture (cont.) Mobile node ◦ Chipcon CC2431 : Zigbee chip ◦ TMS320C6713(DSP) : Timing and control functions ◦ TDC-GP2 : Time interval measurement function, timing and control functions

32 System Architecture (cont.) Calibration node ◦ Chipcon CC2431 : Zigbee chip ◦ TDC-GP2 : Time interval measurement function, timing and control functions Fixed node ◦ Chipcon CC2431 : Zigbee chip

33 Measuring procedure 1.Initiated by a mobile node 2.It transmits a packet to a fixed node 3.Fixed node retransmits a packet 4.The master node receives the packet and its TDC determines the RTT Calibrating procedure 1.Initiated by a mobile node 2.It transmits a packet to a calibration node 3.The calibration node initializes its TDC

34 Measuring procedure (cont.) 4.The calibration node transmits a packet to a selected fixed node 5.The selected fixed node received and retransmits the packet 6.The calibration node receives the packet and its TDC determines the RTT 7.The calibration node repeats the foregoing procedure to a set of fixed nodes 8.The results of RTT are sent to the mobile node for calibration

35 Measuring procedure (cont.) By using the calibration data, the mobile node DSP can determine the unknown position more accurately

36 Tested Result Three fixed node, one calibration node

37 NTU Indoor Localization RSSI fingerprinting localization ◦ Training  Collect RSSI values at every specific position  Use all collected RSSI values to build a database ◦ Tracking  Upon receiving RSSI values, an end-device can compare them with those in the database  Then calculate the position by KNN (K-Nearest- Neighbor)

38 NTU Indoor Localization (cont.) Fingerprintlocation (B1,B2,B3,B4…)(x1,y1,z1) ….. …... Beacon 1 Beacon 3 Beacon 2 Look up the table

39 NTU Indoor Localization (cont.)

40 Example of KNN AP2 AP1 AP3 1 2 12 11 10 9 87 6 5 43 30m 50m

41 NTU Indoor Localization (cont.) STEP1 ◦ The end-device receives the RSSI values and normalizes them STEP2 ◦ The normalized RSSI values are compared with those in the database, and find the minimum L differences Dn ◦ ◦ S T is the received RSSI value ◦ S n is store at the database STEP3 ◦ For L nearest neighbors, the location estimate is ◦

42 NTU Indoor Localization (cont.) STEP1 ◦ PT = (-94dbm -96dbm -95dbm) ◦ PT = (0dbm -2dbm -1dbm) RL123456789101112 x, y 10, 10 20, 10 30, 10 40, 10 10, 20 20, 20 30, 20 40, 20 10, 30 20, 30 30, 30 40, 30 AP1-73-82-89-94-82-86-91-95-89-91-94-97 AP2-82-86-91-95-73-82-89-94-66-80-87-93 AP3-94-89-82-73-93-87-80-66-94-89-82-73 AP1000000000000 AP2-9-4-29421231174 AP3-21-77-21-111129-521224 Normalize 正規化

43 NTU Indoor Localization (cont.) STEP2 STEP3 ◦ RL123456789101112 D218822156133025131626

44 AeroScout

45 AeroScout Tag Tag using RFID 2.4Ghz WiFi transmission, MAX read range 200M, LF125k precise positioning 1~2M ,

46 AeroScout Location Receivers Location Receivers allow accurately positioning in outdoor or harsh environments They execute sophisticated radio signal measuring and calculating methods Then the results are sent to the AeroScout Engine for accurately positioning

47 AeroScout TDOA Use TDOA for positioning

48 AeroScout System Architecture

49 AeroScout Engine Processes information received from any vendor's wireless Access Points nearby Allow accurate and reliable positioning for assets equipped with AeroScout's Wi- Fi-based Active RFID Tags

50 AeroScout MobileView Customers use MobileView to TRACK, MANAGE and INTEGRATE their assets from a single platform

51 Ekahau

52 Ekahau System Architecture Ekahau RTLS works on top of any standard 802.11 compliant networks, even with multi-vendor networks Key components of the system include: ◦ Wi-Fi tags  Various physical formats, battery options and features ◦ Ekahau RTLS Controller (ERC)  Sends messages and remotely configure the tags ◦ Server software  Calculates the location using Wi-Fi signal strength readings

53 Ekahau System Architecture (cont.) ◦ Ekahau Site Survey (ESS)  An easy-to-use utility for network verification and creating positioning models during system set-up ◦ Ekahau Vision  A web-based rules, work-flow and alerting engine  Allows users to configure a variety of applications and alerts that take advantage of the precise location calculated by ERC  Configures various status, event and tag rules

54 Ekahau System Architecture

55 Ekahau Tags Using 2.4G WiFi (RSS)& IR transmission, MAX read range 100M, precise positioning 1M

56 RTLS (ERC) Ekahau RTLS (ERC) Ekahau's patented algorithm adopts a probabilistic approach for interpreting the RF signals ◦ Called Multi-Hypotheses tracking ◦ The algorithm is constantly calculating multiple possible locations for a tracked object and gives each possible location a score  Based on all known factors outside: environment characteristics, differences between mobile devices, signal history and the movement models  Chooses the location with the highest score

57 Ekahau Site Survey A easy-to-use professional Wi-Fi Network planning, site survey, and management software tool

58 Ekahau Site Survey (cont.) ESS enables users to quickly and easily create, improve and troubleshoot a Wi-Fi positioning system

59 Ekahau Vision Help users find important assets and people

60 Ekahau API Tag location, presence and status information Tag commissioning and management Two-way text messaging and commands Floor plan images and zones Business rules and event notifications Open architecture and XML-based web services

61 Identec

62 Identec System Architecture

63 Identec Tags Active RFID UHF & LF UHF label ( 916.5MHz ), MAX read range 500M i-SAT 300 RTLS i-MARK 2 i-PORT M350 RTLS i-CARD CF 350i-Q350 RTLS

64 Identec SensorSMART Platform

65 Identec Software (i-SHARE, Watcher, CTAS) i-SHARE

66 Identec Software (i-SHARE, Watcher, CTAS) CTAS

67 Identec Software (i-SHARE, Watcher, CTAS) Watcher

68 Comparisons 項目國內 AeoScoutEkahauIdentec 方法 Zigbee & LF RFID 2.4G WiFi & LF 2.4G WiFi(RSS) & IR RFID UHF & LF Tag 頻率 2.4GHz 920Mhz 定位距離 0.5~6M20cm~6MNA0~3.5M 電池省電性 1~5 年 4年4年 3~5 年 4年4年 年 / 發射間隔 1 年 20sec/ 發射 3.75 年 5min/ 發射 3 年 15min/ 發射 4 年 2sec/ 發射 最遠讀取距離 80M200M100M500M 定位精度 3M1~2M1M Gsensor 振動功 能 選配 OKN/A 選配 緊急按鈕功能 N/A 選配 LCD 顯示功能 N/A 選配 N/A 受金屬干擾程度易受干擾 不易 Tag 大約價格 (NTD) 1200 ~6000 3000 ~6000 N/A

69 Comparisons (cont.) 技術分類代表性廠商準確度優點缺點 Wi-Fi (RSS) ITRI, Ekahau, Skyhook, Intel Research 室內: 1 ~ 5m 室外: 20 ~ 40m 室內外皆可使用, 準確度高,純軟 體方案,支援標 準 WiFi AP ,可 判斷樓層資訊, 不需更動網路設 備  開闊空間準確 度較差  需事先對環境 做過校正  環境變動會影 響準確度 Wi-Fi (TDOA) AeroScout, Hitachi AirLocation 1 ~ 5m 準確度較高  需要專屬的網 路硬體設備

70 利用室內圖資之即時室內定位系統

71 Background Wireless sensor network’s(WSN) requirements 71 National Chung Hsing University System and Network Laboratory

72 Background (cont.) Low communication speed Low power consumption Low cost IEEE 規格 802.15.4802.15.1802.11b 技術名稱 ZigBeeBluetoothWi-Fi 使用頻率 868MHz/915MHz /2.4GHz 2.4GHz 調變方式 O-QPSK,BPSKGFSKCCK,PBCC 通信距離 30m~100m10m100m 傳輸速率 20Kbps 、 40Kbps 、 250Kbps 1Mbps11Mbps 網路容量 65536 節點 7 節點 32 節點 電池壽命 YearsDaysHours 應用監控 / 量測控制語音 / 資料傳輸影像 / 數據傳輸 72

73 Knowledge of Map Matching Using digital map and road network to enhance the positioning accuracy 73 National Chung Hsing University System and Network Laboratory

74 Knowledge of Map Matching (cont.) 1. Vertex-based Map Matching 2. Segment-based Map Matching 74 National Chung Hsing University System and Network Laboratory

75 Knowledge of Map Matching (cont.) 1. Vertex-based Map Matching 2. Segment-based Map Matching 75 National Chung Hsing University System and Network Laboratory

76 Knowledge of Map Matching (cont.) Map Matching Technique ◦ Distance of point-to-point ◦ Distance of curve-to-curve ◦ Angle of curve-to-curve 76 National Chung Hsing University System and Network Laboratory

77 Knowledge of Map Matching (cont.) Distance of point-to-point 77 National Chung Hsing University System and Network Laboratory

78 Knowledge of Map Matching (cont.) 78 National Chung Hsing University System and Network Laboratory

79 Knowledge of Map Matching (cont.) 79 National Chung Hsing University System and Network Laboratory

80 System Implementation User (End Device) Router Coordinator Server (laptop) 80 National Chung Hsing University System and Network Laboratory

81 System Implementation (cont.) Hardware: CC2530ZDK 81 National Chung Hsing University System and Network Laboratory

82 System Implementation (cont.) Software: ◦ IAR Embedded Workbench IDE  For ZigBee network ◦ Visual C#2010  For positioning algorithm 82 National Chung Hsing University System and Network Laboratory

83 System Implementation(cont.) 83

84 System Implementation (cont.) RSSI data collect 84

85 System Implementation (cont.) Positioning Algorithm ◦ Two-intersected-circles algorithm ◦ Indoor-map-matching algorithm 85 National Chung Hsing University System and Network Laboratory

86 System Implementation (cont.)  Two-intersected-circles algorithm 86 National Chung Hsing University System and Network Laboratory

87 System Implementation (cont.) 87 National Chung Hsing University System and Network Laboratory

88 System Implementation (cont.) 88 National Chung Hsing University System and Network Laboratory

89 Flow Chart 89

90 System Implementation (cont.) Indoor-map-matching algorithm ◦ Path database ◦ Matching algorithm 90 National Chung Hsing University System and Network Laboratory

91 Path Database Use vertices and segments to denote paths 91 National Chung Hsing University System and Network Laboratory

92 Path Database (cont.) Vertex 點 IDX 座標 Y 座標 Segment 區段 ID 起始點 ID 結束點 ID abc 92 National Chung Hsing University System and Network Laboratory

93 Matching Algorithm 1. If there is no reference node, use distance of point-to-point 2. If there is a reference node, use distance of curve-to-curve 93 National Chung Hsing University System and Network Laboratory

94 Matching Algorithm (cont.) 1. Planning paths and set up the database in the server 2. If no reference node, find the closest vertex to the unknown node 3. Find all the segments that are connected to the closest vertex, and determine the closest segment 4. If there is a reference node, find the closest segment like step1~3 94 National Chung Hsing University System and Network Laboratory

95 Matching Algorithm(cont.) 5. If the segment is connected with previous segment, this segment is the right segment 6. If it is not connected, calculate the distances between the two nodes and the two segments 7. Compare the sum of distances. The smaller one is the right segment 95 National Chung Hsing University System and Network Laboratory

96 Flow Chart 96

97 Experiment and Result 97

98 Experiment and Result (cont.) Database 1 98 National Chung Hsing University System and Network Laboratory

99 Experiment and Result (cont.) 99 National Chung Hsing University System and Network Laboratory

100 Experiment and Result (cont.) 100 National Chung Hsing University System and Network Laboratory

101 Experiment and Result (cont.) Database 2 101 National Chung Hsing University System and Network Laboratory

102 Experiment and Result (cont.) 102 National Chung Hsing University System and Network Laboratory

103 Experiment and Result (cont.) 103 National Chung Hsing University System and Network Laboratory

104 Experiment and Result (cont.) Database 3 104 National Chung Hsing University System and Network Laboratory

105 Experiment and Result (cont.) 105 National Chung Hsing University System and Network Laboratory

106 Experiment and Result (cont.) 106 National Chung Hsing University System and Network Laboratory

107 Indoor Positioning Using Femtocell Publication Year: 2011 IEEE CONFERENCE PUBLICATIONS

108 Femtocell Overview Femtocell coverage is smaller ◦ Mainly used to compensate for the region the other base stations can not cover ◦ Enhances the data transfer rate ◦ Typically used for residential or small business environment.

109 Femtocell Based Positioning Methods To locate a mobile device in a network of femtocells, we need to determine its position relative to at least three femtocells to achieve successful triangulation ◦ Femtocells’ locations are known

110 Femtocell Based Positioning Methods (cont.) The distance between the mobile and a femtocell is estimated by: ◦ Calculating the signal propagation loss (pathloss) between them ◦ Or the time taken by the signal to propagate from one point to the other.

111 Femtocell Based Positioning Methods (cont.) Signal Strength Triangulation based methods: Generate a database of pathloss at all locations via ray-tracing simulation of detailed building interiors Using WinProp software tool Being matched against the database to estimate the position

112 Femtocell Based Positioning Methods (cont.) Time based methods : ◦ The signal propagation delay between femtocells and mobile ◦ Though useful in calculating distance, this is ineffective for indoor positioning

113 Position Based On Downlink Signal Strength The position of a mobile can be estimated by measuring the strength of the received downlink signals at the mobile from a group of femtocells ◦ The pathloss to each visible femtocell can then be calculated using the femtocell transmit powers

114 Position Based On Downlink Signal Strength (cont.) The serving femtocell requests the mobile to send a Measurement Report Message (MRM) ◦ Containing Ecp/Io and Ecp information  Ecp is the received signal strength of the serving femtocell pilot  Io is the total received energy on the serving femtocell frequency (as measured by the mobile)

115 Position Based On Downlink Signal Strength (cont.) The fingerprint is matched against the database ◦ Containing pathloss values from all points in the network’s coverage region to all femtocells The methods used to create time orthogonalization of signals To avoid persistent interferences

116 Position Based On Downlink Signal Strength (cont.) Inter-frequency Beacon Transmission ◦ Each femtocell may transmit its beacon pilot on different frequency channels  In a time division multiplexed manner (TDMA) ◦ As measurements are made by the mobiles on the channels at multiple instances, the mobile will now be able to detect signals from different femtocells as all other interferers are removed

117 Position Based On Downlink Signal Strength (cont.) Co-ordinated Silence Techniques ◦ Techniques also help create time orthogonalization of signals to avoid the problem of strong interference from the serving femtocell  Such as HDP and OTDOA-IPDL Femtocells need to also support alternative solutions for mobiles that are not equipped with these features

118 Position Based On Uplink Signal Strength The position of a mobile can also be estimated by measuring the strength of the mobile uplink pilot ◦ Received at a group of femtocells  Since the transmit power of the mobile is unknown and dynamic, the pathloss cannot be estimated from this measurement  The difference of the measured strength at two femtocells is equal to the pathloss difference from the mobile’s location to these femtocells

119 Position Based On Uplink Signal Strength (cont.) The difference in the pathloss values can be used as a fingerprint. ◦ Those femtocells that can sense the mobile send the measured Ecp/Nt and Nt values to the positioning server ◦ The server calculates the pathloss difference to a number of pairs of femtocells and matches this against the database to predict the mobile’s position

120 Simulation Model

121 Simulation Model (cont.)

122 Beamforming basics Beamforming uses multiple antennas ◦ Control the direction of a wavefront by appropriately weighting the magnitude and phase of ndividual antenna signals (transmit beamforming). ◦ This makes it possible to provide better coverage to specific areas  Because every single antenna in the array makes a contribution to the steered signal, an array gain (also called beamforming gain) is achieved

123 Beamforming basics (cont.) Beamforming makes it possible to determine the direction that the wavefront will arrive ◦ Direction of Arrival, or DoA Adaptive beamforming refers to the technique of continually applying beamforming to a moving receiver. ◦ This requires rapid signal processing and powerful algorithms.

124 Beamforming basics (cont.) Antenna array with a distance d between the individual antennas. The additional path that a wavefront must traverse between two antennas is d * sin Ѳ.

125 Beamforming basics (cont.) The antenna diagram is affected by the distance d between the antennas.

126 OTDOA OTDOA : Observed Time Difference of Arrival

127 4G LTE-A Localization 127 Marcocell BS UE Femtocell BS2 Femtocell BS3 Femtocell BS1 UE 在 Downlink 時透過 OTDOA+DOA 方式取得位置 Femtocell BS UE 即使 UE 不在 Femtocell 範圍 內, UE 自身透過 Beam Steering 方式增強接收訊號 UE 利用陣列天線估測 DOA 並結合 OTDOA 完成自身定位 具有陣列天線的 BS 亦可使用 TX beamforming 技術將訊號 能量集中至 UE 具有陣列天線的 BS 可採 用多階層 (Layers) 傳輸提 高系統下行容量

128 結合的技術 結合 GPS 、 Marcocell 以及 Femtocell 定位 ◦ DOA estimation in UE ◦ Beamforming technique 當使用者位於戶外使用 GPS+ Marcocell 當使用者位於室內或 GPS 無 LOS 訊號時, 則自動轉為 Femtocell BS 輔助定位系統 改善 Positioning system QoS 128

129 UE 之 DOA 估測技術 Downlink Positioning Reference signals/pilots are arranged across time and frequency domain (OFDMA modulation) Collect those pilots to form a virtual array ◦ 解決實體陣列維度不足問題 ◦ 可同時估測多 BS 方向 129

130 Founded by 22 companies across industries ◦ Nokia, Samsung Electronics, Sony Mobile Communications, Qualcomm, Broadcom and CSR, etc. ◦ To drive innovation and market adoption of high accuracy indoor positioning and related ◦ The primary solutions will be based on enhanced Bluetooth® 4.0 low-energy technology and Wi-Fi (802.11.ac) standards In-Location Alliance

131 IEEE 802.11ac spec. 802.11ac802.11n Band5GHz Band2.4GHz/5GHz(opt) Channel Bandwidth20,40,80,160 MHz20,40MHz Max Data rate6933Mbps~600Mbps Spatial StreamsUp to 8 spatial streams4 spatial streams Modulation256-QAM64-QAM MIMOMulti-User MIMOSingle-User MIMO Backward compatibility 802.11n(on 5GHz) 802.11a 802.11 b/g

132 Band Operating on 5GHz band Less interference than on 2.4GHz More non-overlapping channel avaliable. (25 to 3 on 2.4GHz) 7 Mandatory support 20/40/80MHz, 160MHz optional.

133 Bandwidth Table of Data rate:

134 Higher Order Modulation Increase 33% PHY rate relied on 256-QAM QAM is Quadrature Amplitude Modulation. 6 bits coded information to 8bits coded information.

135 Improved MIMO Up to 8 spatial streams 4 spatial streams with 11n Multi-Users MIMO Single-Users MIMO Beneficial for handset or tablet Multiple antennas are not necessary

136 Dynamic Bandwidth Management Improved handshake mechanism. RTS/CTS Interference detection threshold improved -62dBm down to -72dBm

137 Beamforming focuses the APs transmit energy of spatial stream toward Clients Limitation of TxBeamforming on 5GHz band Single Closed Loop-Method Transmit Beamforming AP STAs Special Sounding Signal Report their Beamformaing matrices

138 Backward Compatibility Required to be fully compatible with 802.11n(Operating on 5GHz)and 802.11a 802.11b/g not support

139 NOKIA – Bluetooth 4.0 The High Accuracy Indoor Positioning (HAIP) technology ◦ Nokia is looking to employ it based on Bluetooth 4.0 ◦ Even in its current form it will have accuracy of one meter  That’s certainly good enough for general positioning inside  It gets much more interesting when it can get down to 20cm with modification  Industry application for stock control

140 NOKIA – Bluetooth 4.0 (cont.) Using a single antenna and fixed mobile height, mobile can resolve its 2D location

141 NOKIA – Bluetooth 4.0 (cont.) Using multiple positioning beacons, mobile can resolve its 3D location or increasing the position reliability and accuracy

142 Conclusions 預期遭遇困難 ◦ 無直射路徑問題 (NLOS propagation)  手機有 GSM900 、 WCDMA 、 HSDPA 等等的不同 規範 ◦ 多重路徑干擾 (Multipath Interference) ◦ 多使用者環境的影響 ◦ 手機電源消耗問題 (power issue) 142

143 Thanks for your attention! Any questions?


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