A new multi-frame state estimation mechanism is introduced to deal with the situation of target undetected under low detection probability.A Gaussian mixed probability hypothesis density filter based on multi-frame state estimation mechanism is proposed.The mechanism builds the historical weight matrix and the state extraction identifier for each target based on the target weights of the different time steps.In the process of target tracking,when a continuous-moving target is missed at some time steps,the current state of the target is estimated based on the weight matrix of the association target and the state extraction identifier,through the multi-frame state estimation mechanism.The simulation results show that the algorithm proposed has strong robustness,and can improve the target tracking performance greatly under the situation of low detection probability and relatively high clutter rate while ensuring the tracking effectiveness.