In this study, we propose a novel dynamic mode decomposition (DMD) energy sorting criterion that works in conjunction with the conventional DMD amplitude-frequency sorting criterion on the high-dimensional schlieren dataset of the unsteady flow of a spiked-blunt body at Ma = 2.2. The study commences by conducting a comparative analysis of the eigenvalues, temporal coefficients, and spatial structures derived from the three sorting criteria. Then, the proper orthogonal decomposition (POD) and dynamic pressure signals are utilised as supplementary resources to explore their effectiveness in capturing spectral characteristics and spatial structures. The study concludes by summarising the characteristics and potential applications of DMD associated with each sorting criterion, as well as revealing the predominant flow features of the unsteady flow field around the spiked-blunt body at supersonic speeds. Results indicate that DMD using the energy sorting criterion outperforms the amplitude and frequency sorting criteria in identifying the primary structures of unsteady pulsations in the flow field, which proves its superiority in handling an experimental dataset of unsteady flow fields. Moreover, the unsteady pulsations in the flow field around the spiked-blunt body under supersonic inflow conditions are observed to exhibit multi-frequency coupling, with the primary frequency of 3.3 kHz originating from the periodic motion of the aftershock.