Aiming at the problem that the calculation of the average hop distance in the prototype DV-Hop localization algorithm produces large localization errors, this paper proposes a CADV-Hop algorithm for classifying the average hop distance. First, the inconsistent distribution of single-hop distance for different hop-count paths in wireless sensing networks is revealed, and the reasons and laws for the appearance of such differences are analyzed. Secondly,the classification average hop distance is calculated by classifying the inter-beacon paths according to the hop count and then calculating the classification average hop distance for each type of paths. Finally, on the basis of the more accurate distance estimation between the unknown node and the nearest beacon node provided by the classification average hop distance, the node coordinates are finally solved by combining the weighted least squares method. Simulation experiments show that the CADV-Hop algorithm effectively reduces the localization error without increasing the complexity of the algorithm as well as additional hardware, and with the increase of the number of beacon nodes, the CADV-Hop algorithm has higher localization accuracy than the prototype DV-Hop algorithm and the two improved DV-Hop algorithms.