Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis

Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis

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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 cubs foam finger 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 eeboo coupons evaluated through computer simulation, and compared to previously published algorithms.