Copyright © 2006 Hindawi Publishing Corporation. This is an open access article distributed under the
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Abstract
We consider the problem of autonomously locating a number of
asynchronous sensor nodes in a wireless network. A strong focus
lies on reducing the processing resources needed to solve the
relative positioning problem, an issue of great interest in
resource-constrained wireless sensor networks. In the first part
of the paper, based on a well-known derivation of the Cramér-Rao
lower bound for the asynchronous sensor positioning problem, we
are able to construct optimal preprocessing methods for sensor
clock-offset cancellation. A cancellation of unknown clock-offsets
from the asynchronous positioning problem reduces processing
requirements, and, under certain reasonable assumptions, allows
for statistically efficient distributed positioning algorithms.
Cramér-Rao lower bound theory may also be used for estimating
the performance of a positioning algorithm. In the second part of
this paper, we exploit this property in developing a distributed
algorithm, where the global positioning problem is solved
suboptimally, using a divide-and-conquer approach of low
complexity. The performance of this suboptimal algorithm is
evaluated through computer simulation, and compared to previously
published algorithms.