A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Particle filters for positioning, navigation, and tracking
IEEE Transactions on Signal Processing
Location sensing and privacy in a context-aware computing environment
IEEE Wireless Communications
Empirical-based analysis of a cooperative location-sensing system
Proceedings of the 1st international conference on Autonomic computing and communication systems
A novel backtracking particle filter for pattern matching indoor localization
Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Large multimedia artifacts prebuffering in mobile information systems as location context awareness
ISWPC'09 Proceedings of the 4th international conference on Wireless pervasive computing
Localization by Wireless Technologies for Managing of Large Scale Data Artifacts on Mobile Devices
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Enhancing the map usage for indoor location-aware systems
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: interaction platforms and techniques
Adaptive motion model for a smart phone based opportunistic localization system
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Did you see Bob?: human localization using mobile phones
Proceedings of the sixteenth annual international conference on Mobile computing and networking
A fine-grained context-dependent model for indoor spaces
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
Problem solving of low data throughput on mobile devices by artefacts prebuffering
EURASIP Journal on Wireless Communications and Networking - Special issue on enabling Wireless Technologies for Green Pervasive Computing
User perspective adaptation enhancement using autonomous mobile devices
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Indoor pedestrian displacement estimation using Smart phone inertial sensors
International Journal of Innovative Computing and Applications
Virtual lifeline: Multimodal sensor data fusion for robust navigation in unknown environments
Pervasive and Mobile Computing
No need to war-drive: unsupervised indoor localization
Proceedings of the 10th international conference on Mobile systems, applications, and services
Collecting location-based voice messages on a TalkingBadge
Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design
Smartphone-based pedestrian tracking in indoor corridor environments
Personal and Ubiquitous Computing
Walkie-Markie: indoor pathway mapping made easy
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
LocateMe: Magnetic-fields-based indoor localization using smartphones
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
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This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.