Aiming at wireless sensor networks（ WSNs） node localization problem

a new localization algorithm is proposed by building quantum neural network model for particle swarm mechanism to optimize localization algorithm of DV-HOP

particle swarm optimization-quantum neutral network（ PSO-QNN）. The algorithm constructs quantum neural network model according to average distance obtained by traditional DV-HOP and distance of measured actual node

and through the particle swarm algorithm to train the average distance

so as to get better average

value to achieve the optimization of DV-HOP algorithm. The combination algorithm shortens the training time of the traditional artificial neural network

and speeds up the convergence rate. Simulation results show that compared with the traditional DV-HOP algorithm

the proposed PSO-QNN algorithm can reduce the positioning error of about 20 %

and the positioning precision is significantly improved.