Abstract
Device-free localization (DFL) technology exploits target-induced fading over machine-type wireless links for passive object localization and tracking. In most cases, single frequency measurements are employed for DFL systems. However, machine-type communication protocols often employ slotted or time-division hopping policies over multiple channels, i.e. frequencies. In this paper, we propose a DFL system designed to extract and track the locations of the targets that are hidden into multi-frequency received signal strength (RSS) measurements. Due to strong multipath phenomena and in-band interferences, the use of some noisy channels might worsen the localization accuracy. A statistical model is thus proposed to relate RSS values obtained at various frequencies to the target location. Two different approaches based on optimal frequency selection and subspace decomposition are then proposed to identify the frequency measurements that maximize the localization accuracy. Experimental validation in an indoor multipath-limited environment reveals that the approach can improve the accuracy of both single and double target detection and localization with respect to the conventional single channel DFL approach.
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