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Sensor Network Localization by Eigenvector Synchronization Over the Euclidean Group.

ACM Trans Sens Netw 2012 Jul;8(3)

Program in Applied and Computational Mathematics (PACM), Princeton University, Fine Hall, Washington Road, Princeton VJ 08544-1000;

We present a new approach to localization of sensors from noisy measurements of a subset of their Euclidean distances. Our algorithm starts by finding, embedding, and aligning uniquely realizable subsets of neighboring sensors called patches. In the noise-free case, each patch agrees with its global positioning up to an unknown rigid motion of translation, rotation, and possibly reflection. Read More

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http://dx.doi.org/10.1145/2240092.2240093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741000PMC
July 2012
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