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Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis


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.


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Correspondence to Mats Rydström.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Rydström, M., Urruela, A., Ström, E.G. et al. Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis. EURASIP J. Adv. Signal Process. 2006, 093043 (2006).

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