LANDMARC: Indoor Location Sensing Using Active RFID
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Models and solutions for radio irregularity in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
CILoS: a CDMA indoor localization system
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Combining GPS and GSM Cell-ID positioning for Proactive Location-based Services
MOBIQUITOUS '07 Proceedings of the 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking&Services (MobiQuitous)
A measurement study of zigbee-based indoor localization systems under RF interference
Proceedings of the 4th ACM international workshop on Experimental evaluation and characterization
A novel approach of RFID based indoor localization using fingerprinting techniques
APCC'09 Proceedings of the 15th Asia-Pacific conference on Communications
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
Tracking vehicular speed variations by warping mobile phone signal strengths
PERCOM '11 Proceedings of the 2011 IEEE International Conference on Pervasive Computing and Communications
Accurate GSM indoor localization
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
A survey of indoor positioning systems for wireless personal networks
IEEE Communications Surveys & Tutorials
Spatial Models for Human Motion-Induced Signal Strength Variance on Static Links
IEEE Transactions on Information Forensics and Security - Part 1
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Indoor localization based on signal strength fingerprinting has received significant attention from the community. This method is attractive because it does not require complex hardware beyond off-the-shelf radio transceivers. However, its main limitation is the inaccuracy caused by the variability of the signal strength. When applied to the localization of people, the signal variability can be attributed to three main sources: environmental dynamics (movement of people or objects), movement of transceiver (changes in the position and/or orientation of the transceivers) and body effects (distortion of the wireless signal due to body absorption). Our work focuses on the impact of the last two sources and provides two important contributions. First, we present an analysis to quantify the effects of antenna disorientation and transceiver misplacement. For the RFID system used in our work, these effects can decrease the localization accuracy by up to 50%. Motivated by these results, we identify parts of the human body where tags are less affected by unintentional movements and describe how multiple transceivers can be used to overcome the absorption effects of the human body. We validate our findings through an extensive set of measurements gathered in a home environment. Our tests indicate that by following a set of simple guidelines, we can increase the localization accuracy (the percentage of correct location estimations) by a factor of four (from 20% to 88%), and reduce the maximum localization error (from 7 to 4 m).