This paper presents an approach to radar target classification using fractal geometry techniques. The classification techniques used here exploit the geometric nature of the target and its effect on the backscattered signals. Target high range resolution radar signatures are transformed into fractals via fractal interpolation techniques, and their fractal dimensions are used to discriminate different targets. The results showed that different target have different targets. The results showed that different target have different fractal dimensions and thus can be discriminated according to their fractal dimensions. High range resolution fully-polarized radar backscattered signals of five aircrafts at different aspects are used to test the algorithm. The classification results presented in this paper are promising. The experiments indicate that the fractal dimension feature used in this paper seems to be independent of amplitude, thus is regarded as a promising new way for radar target classification. It also shows that this opens up an entirely new feature space which needs to be explored further in the field of radar target classification.