The active badge location system
ACM Transactions on Information Systems (TOIS)
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Challenges: device-free passive localization for wireless environments
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Radio Tomographic Imaging with Wireless Networks
IEEE Transactions on Mobile Computing
Analysis of a device-free passive tracking system in typical wireless environments
NTMS'09 Proceedings of the 3rd international conference on New technologies, mobility and security
A deterministic large-scale device-free passive localization system for wireless environments
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
New insights into wifi-based device-free localization
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
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Device-free passive (DfP) localization has been recently proposed to allow localizing a stationary entity that neither carries a device nor participates actively in the localization process. In this paper, we present a Kalman filter-based system that enables tracking a continuously moving entity in a typical wireless environment rich in multipath. The concept behind DfP tracking is that the received signal strength at monitoring points in a wireless environment is influenced by any changes in the environment. These changes include the movement of an entity, such as a human being, within the environment. This can be utilized to track an entity in many military and civil applications. We evaluate the performance of our system by conducting experiments in a typical office environment rich in multipath. Our results show that we were able to track a passive entity in a long corridor with a 1.2m median distance error and a less than 4.6m distance error with probability one.