Abstract
We introduce a novel sequence-based localization technique for wireless sensor networks. We show that the localization space can be divided into distinct regions that can each be uniquely identified by sequences that represent the ranking of distances from the reference nodes to that region. For <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> reference nodes in the localization space, combinatorially, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ") sequences are possible, but we show that, due to geometric constraints, the actual number of feasible location sequences is much lower: only <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> ). Using these location sequences, we develop a localization technique that is robust to random errors due to the multipath and shadowing effects of wireless channels. Through extensive systematic simulations and a representative set of real mote experiments, we show that our lightweight localization technique provides comparable or better accuracy than other state-of-the-art radio signal strength-based localization techniques over a range of wireless channel and node deployment conditions.
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