Abstract: Wireless sensor network(WSN) is a self-organizing network that is composed of nodes within the monitoring range and can communicate with each other.In view of the long location time and low location accuracy of the traditional particle swarm Monte Carlo algorithm,an improved particle swarm Monte Carlo positioning algorithm is proposed.(IPSOMCL).The Monte Carlo algorithm is used to obtain the estimated coordinates of the node to be located,and the particle swarm algorithm is used to correct the error between the estimated distance and the measured distance.Toimprove the filtering stage,extracting the number of hops of anchor node information to obtain a more accurate sampling area instead of the traditional algorithm to determine the sampling area through the communication radius to filter.The introduction of cross mutation enables the algorithm to jump out of the local optimal solution and find a more accurate position coordinate node,which improves the efficiency and accuracy of positioning.

Key words: Wireless sensor network, Monte Carlo algorithm, Particle swarm algorithm, Circular sampling, Cross mutation