Abstract: In view of low real-time sampling efficiency of Monte-Carlo localization boxed, a new localization method named enhanced Monte-Carlo localization boxed was proposed. Based on the MCI3, EMCI3 introduces the crossover and mutation operations in genetic algorithm to make samples to move towards regions with large value of posterior density distribution. So the distribution of samples is optimized, and the problem of low sampling efficiency is solved. Simulation results show that compared with the MCI3, the new algorithm reduces the number of samples. Therefore, the sampling efficiency and localization accuracy arc improved by about 17 0 0 , while the cost is reduced by about 30 0 0.

Key words: Wireless sensor network, Mobile localization, Monte carlo, GA