Abstract: In view of the obvious difference of Green's function in different distances, the targets at different distances can be distinguished by classification according to their characteristics. In this paper, the iterative selforganizing data analysis techniques algorithm (ISODATA) clustering algorithm is applied to the traditional multi-objective successive interference cancellation (SIC) process in multi-target positioning, and the Green's functions extracted from the SIC process are classified after repeated iteration. Therefore, the problem that the similarities and differences of Green's functions need to be judged manually in the traditional multi-target positioning process is solved, and the distance information of different targets is further calculated by using the classified Green's functions.