Transient signals are very difficult to characterize due to their short duration and their wide frequency content. Various methods such as spectrogram and wavelet decomposition have already been extensively used in the literature to detect them, but show limits when it comes to near similar transients discrimination. In this paper, we propose the multi-lag phase space analysis as a way to characterize them. This data-driven method enables the comparison between features extracted from two different signals. In an example, we compare the multi-lag phase space representations of three similar transients and show that common features can be found to discriminate them. Finally the results are compared with a wavelet decomposition.