Aiming at the problem of target tracking precision in nonlinear system in clutter environment

a fuzzy C-means（ FCM） distributed fusion algorithm is proposed based on extended Kalman-Gaussian mixture probability hypothesis density（ EK-GMPHD）. The FCM clustering fusion algorithm is used in global estimation

then the maximum target state estimation of membership degree is obtained

and according to related formula

calculate and derive the global target state estimation. The algorithm can improve target tracking precision in condition of lack of local tracks. Simulation results show that the fusion algorithm for multi-target tracking estimation of the number of multiple objective and state is better in clutter environment.