Abstract:

In view of the deficiencies of Monte Carlo localization algorithm in mobile wireless sensor networks,a new localization algorithm featuring sampling optimization Monte Carlo is introduced. Accordingto the continuity of movement to carry out curve fitting, a region where the value of posterior density distribution is large is calculated, and the sample weights are optimized. Simulation results indicate that the improvedalgorithm needs fewer samples, the accuracy and robustness of target locating in wireless sensor networks can be improved effectively.