Abstract: In this paper, a double closed loop multiple hypothesis tracking method based on clutter perception is proposed to solve the engineering application problem of multiple hypothesis tracking method, since the calculated amount of the multiple hypothesis tracking method in a clutter environment increases exponentially. In this method, a clutter perception and processing module is added into the original algorithm framework, which greatly reduced the number of false tracks, by reducing the number of clutter points. Based on that, a double closed loop structure is used for processing the unsteady track and the steady track respectively, which further reduced the calculated amount of this algorithm, by solving the cluster expansion and merge problem caused by false tracks. It has been verified that the proposed method can reduce 50% of calculated amount, and the number of false tracks is reduced at the same time, which verified the effectiveness of the proposed method.