The classification of radar emitters in a naval electronic-warfare (EW) context is a challenging problem. Furthermore, over the last few years, new technologies and the reduction of the fabrication costs have led to an increase in the number of radars. Thus, EW systems need to improve their capabilities of radar identification. The common operational methods, which consist of clustering pulses with similar parameters, are no longer able to solve the classification task efficiently. The main challenges of this data clustering of unknown radar emitters from passive measurements are the high dimension of the received radar pulse samples, the small sample group size, and closely located radar pulse clusters. In this paper, we propose modeling the instantaneous frequency law of the recorded pulses using Bézier curves. The spatial distribution of the control points of the Bézier curves is used as a new feature for the classification process based on the common density-based spatial clustering of applications with noise algorithms. Real data recorded near Brest, France, are used to highlight the interest in using the proposed approach. We also show the potential of the approach for specific emitter identification.