A new Monte Carlo mobile node localization algorithm based on Newton interpolation

摘要

There are some deficiencies in the Monte Carlo localization algorithm based on rangefinder, which like location probability distribution of the k moment in the prediction phase only related to the localization of the k - 1 moment and the maximum and minimum velocity. And the influences of the motion condition on the movement of the mobile node at k moment are also not considered before the k - 1 moment. What is more is the process of selecting the effective particles is slow in the algorithm. Considering the situations above, this paper presented a Monte Carlo mobile node localization algorithm based on Newton interpolation, which uses the inheritedness of Newton interpolation, inheriting the historical trajectory prediction mechanism of the moving node to estimate the current moment's movement speed and movement direction of the moving node, and optimized the moving node motion model, and used particle filter that is optimized by weight of importance to prevent particle collection depletion. The inference and simulation results show that the algorithm has improved the accuracy of the forecast using Newton interpolation. And this algorithm has effectively avoided the degradation of particles and improved the localization accuracy.