Kalman filter-based tracking of a device-free passive entity in wireless environments

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Abstract
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.

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