Refined statistic-based localisation for ad-hoc sensor networks

Localisation is required for many ad-hoc sensor network applications. In this paper, we look at the limitations of many of the existing proposed localisation techniques with regards to coping with non-uniform anchor distributions and errors in ranging information. We present a refined approach that uses a combination of mobile anchor scenarios for anchor information distribution, along with statistical techniques for performing localisation with inaccurate range data. Simulations with our refined approach have shown significant reductions (in the order of magnitude range) to the required processing for performing statistical localisation over previous attempts, as well as improving the generated location information in situations with non-total anchor information coverage, making possible a wider range of applications.