Aiming at problem that in the traditional distance vector-hop（ DV-Hop） localization algorithm

the error while calculating the coordinates of unknown nodes by the least squares method is too large

and the particle swarm optimization（ PSO） algorithm is easy to fall into local optimal

a fusion algorithm which fuses adaptive immune PSO and DV-Hop algorithm is presented. Firstly

the concentration mechanism is improved. Secondly

the number of sub-populations is changed by the maximum particle concentration

which makes the maximum use of population resources. Finally

after the dynamic adjustment of the vaccine scope

the inferior population began vaccination. The fusion algorithm overcomes the premature particle maturity

avoids the population degradation

and improves the convergence speed and precision of the algorithm evolution process. The experimental results show that under the same hardware cost and communication overhead

the fusion algorithm has higher positioning precision.