Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Antennas and Propagation for Wireless Communication Systems
Antennas and Propagation for Wireless Communication Systems
Wireless LAN location-sensing for security applications
WiSe '03 Proceedings of the 2nd ACM workshop on Wireless security
Adaptive Temporal Radio Maps for Indoor Location Estimation
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
Sensor-assisted wi-fi indoor location system for adapting to environmental dynamics
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Location-Based Services: Back to the Future
IEEE Pervasive Computing
Estimating signal strengths in the design of an indoor wireless network
IEEE Transactions on Wireless Communications
Indoor geolocation science and technology
IEEE Communications Magazine
Adaptive localization techniques in WiFi environments
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
A 3-D indoor radio propagation model for WiFi and RFID
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
The WiMap: A Dynamic Indoor WLAN Localization System
International Journal of Advanced Pervasive and Ubiquitous Computing
Locating schemes based on adaptive weighting strategy in heterogeneous wireless networks
International Journal of Ad Hoc and Ubiquitous Computing
Locating schemes based on adaptive weighting strategy in heterogeneous wireless networks
International Journal of Ad Hoc and Ubiquitous Computing
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With the remarkable advances in wireless networking and pervasive computing, there have been an increasing need to figure it into LBS (location-based services) applications. This paper proposes an adaptive positioning system for the mobile terminal (MT) localization using the radio propagation modeling (RPM) and Kalman filtering (KF) according to the measurements of signal-to-noise ratio (SNR) information between indoor IEEE 802.11b (WiFi) APs and reference points (Tags). Comparing with the conventional empirical method (such as the fingerprinting method), the adaptive RPM algorithm can perform on-line calibration in real dynamic environments and reduce the number of training points. Additionally, the KF algorithm is used to track the location of MTs, where the observation information is extracted from the empirical and RPM positioning methods. The numerical simulations and experimental results show that not only the calibrating and positioning method of the RPM algorithm can improve the accuracy of an indoor WiFi locating system and alleviate the phenomenon of aliasing in the signal space, but also the estimating and tracking method of the KF algorithm can overcome the problem of the aliasing and reduce the positioning error with smaller sampling time.