Abstract: Aiming at the problems that locating nodes of wireless sensor network are easy to be interfered, a localization algorithm is proposed based on grouping particles swarm evolution and inertia weight adaptive adjustment. To suppress disadvantage of locally optimum and premature convergence, the proposed algorithm makes nonlinear adjustment for the inertia weight with the diversity of current particle and swarm optimization. The population is divided into several small swarms centralized with superior particle to search in each regions of solution space and to update best solutions in population regularly led by personal best and small swarm best, which reduces searching area and improve the convergence speed. Simulation shows that the proposed algorithm has good robustness to range error, and obviously improve localization accuracy.