Abstract
Networks of ultra-wideband (UWB) radar nodes have been shown to represent a practical and effective approach for precise localization and tracking of moving non-collaborative persons and objects. In UWB radar sensor networks (RSNs), the presence of strong clutter, weak target echoes, maneuvering targets, closely spaced targets, and extended targets are obstacles to achieve a satisfactory tracking performance. In this work, a track-before-detect (TBD) approach for UWB RSNs is proposed. Both spatial information and temporal relationship between measurements are exploited in generating several possible candidate trajectories, from which only the more suitable are selected. Experimental results carried out with actual UWB signals in the presence of a human target confirm the effectiveness of TBD paradigm in UWB RSNs. Remarkably, the localization error obtained by the proposed RSN can be within 0.4 m with no false trajectories, and no misdetection despite the presence of heavy clutter and the low signal-to-noise ratio (SNR) regime.
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