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THÔNG TIN TÀI LIỆU
Cấu trúc
Abbreviations
List of Figures
List of Tables
Introduction
Motivation
Approach
Contribution
Outline
Background
Positioning Technology
Bluetooth Low Energy
Inertial sensor
RSSI-based Positioning Techniques
Fingerprinting Method
Range-based Method (Lateral)
Bayesian Filtering - From Kalman Filters to Particle Filters
General Bayes Filtering problem
Kalman Filter
Particle Filter
Proposed System
System overview and architecture
PDR subsystem
Embedded Sensor Block
Sensor–based positioning method
Step Length Estimation
LSE subsystem
RSS Uncertainty Analysis
RSSI-to-Distance Conversion
Location Estimation
Kalman Fusion
Evaluation
Experiment Setup
Device and Software
Experiment Setting
Results and Discussion
Ground Truth and Accuracy Comparisons
Performance evaluation under impact of different velocity
Performance evaluation under impact of different beacon density
Compare to Fingerprinting
Conclusion
Future Work
Nội dung
Ngày đăng: 20/07/2021, 09:30
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