Tracking a time-varying number of targets with radio-frequency tomography

Abstract

Abstract:Radio-frequency (RF) tomography is an emerging technology which derives targets location information by analyzing the changes of received signal strength (RSS) in wireless links. This paper presents and evaluates a novel RF tomography system which is capable of detecting and tracking a time-varying number of targets in a cluttered indoor environment. The system incorporates an observation model based on RSS attenuation histogram and a multi-target tracking-by-detection filtering approach based on probability hypothesis density (PHD) filter. In addition, the sequential Monte Carlo method is applied to implement the multi-target filtering. To evaluate the tracking system, the experiments involving up to 3 targets were performed within an obstructed indoor area of 70 m². The experimental results indicate that the proposed tracking system is capable of tracking a time-varying number of targets.

Keywords

radio-frequency tomography / multi-target tracking / wireless sensor networks / particle filtering / tracking by detection / random finite sets

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