An improved Multiple Model Particle Filter based on Track-before-detect (MMPF-TBD) algorithm for maneuvering target detection and tracking in low signal-to-noise environment is proposed. The algorithm uses sliding window to determine whether the particles are affected by the estimation of the target. When the value exceeds threshold, it adds new particles in accordance with the state estimation of the previous moment. Then it uses the expanded particles to detect and estimate the target. Compared with the existing methods, the simulation results show that the proposed algorithm can effectively solve the particle degeneration problem and improve the probability of maneuvering target detection and tracking accuracy in real time.