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arXiv · 1406.5223

Distributed, simple and stable network localization

Claudia Soares·Joao Xavier·Joao Gomes
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Abstract

We propose a simple, stable and distributed algorithm which directly optimizes the nonconvex maximum likelihood criterion for sensor network localization, with no need to tune any free parameter. We reformulate the problem to obtain a gradient Lipschitz cost; by shifting to this cost function we enable a Majorization-Minimization (MM) approach based on quadratic upper bounds that decouple across nodes; the resulting algorithm happens to be distributed, with all nodes working in parallel. Our method inherits the MM stability: each communication cuts down the cost function. Numerical simulations indicate that the proposed approach tops the performance of the state of the art algorithm, both in accuracy and communication cost.

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Claudia Soares, Joao Xavier, Joao Gomes. 2014-06-19. Distributed, simple and stable network localization. https://doi.org/10.1109/globalsip.2014.7032222

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