The classical distance vectorhop(DVHop) method has the problem of error in distance estimation among nodes and low accuracy of node localization in nonuniform distributed networks. The calculation rule of similarity factor for multihop shortest path among nodes is introduced, which is used to correct the hopsize of a node in the distance estimation step, and to select the beacon node involved in localization calculation in the position calculation step. The initial position of a node is optimized using an improved simulated annealing (SA) algorithm. The simulation results show that under the condition of randomly generated network topology, the improved strategy can reduce the positioning error by about 20% on average compared with the classical DVHop algorithm, and about 4% on average compared with the existing methods, which shows good positioning performance.