The laser-detected micro-Doppler (MD) effect is more likely to achieve precision target identification and recognition because of its high-accuracy estimation ability. MD features overlapping in the time–frequency (TF) are encountered in targets with similar micromotion parameters, which cannot be solved with one-channel detection. In this letter, a novel separation method based on a constrained particle filter (PF) in a time-varying autoregressive (TVAR) model is developed to solve this extremely underdetermined problem. First, the TVAR model for a multicomponent MD signal is established, and the connection between the interested instantaneous frequency (IF) and model poles is analyzed. Then, the continuity characteristic of the IF law is used to design a constraint condition for a PF assuming that the laser MD effect obeys the sinusoidal frequency modulation form. By fusing the constraint into the process of particle update and weight computation, the IF curve for each component is correctly separated through the well-tracked pole trajectories. Finally, the performances of the presented method and traditional method are compared for a TF overlapping scenario. The simulation results verify the validity and necessity of the new method; meanwhile, the low-level computational complexity makes it possible for real-time processing.