The anatomy of a context-aware application
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Bayesian Filtering for Location Estimation
IEEE Pervasive Computing
Risks of using AP locations discovered through war driving
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
GUIDE-gradient: A Guiding Algorithm for Mobile Nodes in WLAN and Ad-hoc Networks
Wireless Personal Communications: An International Journal
Demo: distance tracking using WLAN time of flight
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
I am the antenna: accurate outdoor AP location using smartphones
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
CAESAR: carrier sense-based ranging in off-the-shelf 802.11 wireless LAN
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
A model for WLAN signal attenuation of the human body
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Effective RSS sampling for forensic wireless localization
WASA'13 Proceedings of the 8th international conference on Wireless Algorithms, Systems, and Applications
Intensity-based navigation with global guarantees
Autonomous Robots
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Many previous studies have examined the placement of access points (APs) to improve the community's understanding of the deployment and behavioral characteristics of wireless networks. A key implicit assumption in these studies is that one can estimate the AP location accurately from wardriving-like measurements. However, existing localization algorithms exhibit high error because they over-simplify the complex nature of signal propagation. In this work, we propose a novel approach that localizes APs using directional information derived from local signal strength variations. Our algorithm only uses signal strength information, and improves localization accuracy over existing techniques. Furthermore, the algorithm is robust to the sampling biases and non-uniform shadowing, which are common in wardriving measurements.