Localization in mobile sensor networks is more challenging than in static sensor networks because mobility increases the uncertainty of nodes' positions. Most existing localization algorithms in mobile sensor networks use Sequential Monte Carlo (SMC) methods due to their simplicity in implementation. In this paper, we propose a localization algorithm which outperforms the existing state of the art in terms of communication overhead and location accuracy. Our proposal is a range-free positioning system based on heading data provided by a variety of orientation-tracking sensors of different precisions, applied to the Monte Carlo sampling technique. Simulation results indicate that our approach is also much more reliable against radio irregularities.
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