Abstract
Device-free wireless localization (DFL) is a promising technique. It can localize and track a target without carrying any electronic device. Compared with traditional received signal strength (RSS)-based DFL, the recently proposed time-of-flight (TOF)-based DFL technique could achieve better performance. However, TOF-based DFL requires that each pair of nodes should perform a pairwise TOF measurement sequentially, which makes it impractical for being utilized in time and energy sensitive applications. Inspired by the fact that a target shadows only a small subset of wireless links, which travel through its spatial impact area, we incorporate link state estimation function into particle filter (PF) framework to predict shadowed links and design a parallel scanning scheme to scan multiple shadowed links simultaneously. The aforementioned methods guarantee that the effective TOF measurements can be acquired timely and energy efficiently. Meanwhile, to achieve reasonable localization performance with these reduced-under-sampled link measurements, we utilize compressive sensing (CS) algorithm to reconstruct the shadowing effect map (SEM). With the map as observation likelihood function, PF algorithm could estimate targets location accurately. Experimental results with an 802.15.4a chirp spread spectrum ranging hardware testbed show that the average running time and energy consumption reduce remarkably.
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