Abstract: Node localization is a key technology of wireless sensor networks. Although radio-ranging is accuracy, using least squares algorithm for node localization may lead to big error. To increase the node localization accuracy of range-based wireless sensor network, in this paper, the node localization problem was transformed into a constrained optimization problem, and then the problem was solved by using particle swarm optimization algorithm. In the solution process,by setting the constraint fitness function and the distance fitness function, the search computation was reduced, the convcrgenee rate was speeded up,and a better solution was achieved faster. The result from simulation experiments show that compared with least squares algorithm, under the circumstances of different ranging error, different distance radius,different number of anchors and different number of nodes,applying this algorithm can achieve a solution with more accuracy. hhis shows that the algorithm has stronger anti error, better astringency and less investment in hardware, etc. In addition,it performs better in the sparse network node localization.

Key words: Wireless sensor networks, Node localization, Particle swarm optimization, Constraint optimization