Aiming at the problem of multiple extended target tracking

a multiple extended target tracking algorithm based on spatiotemporal correlation and grid clustering is proposed. The current measurements can be divided into measurements of survival targets and newborn targets according to spatiotemporal correlation. For survival targets

the measurements are partitioned by fuzzy C-means（ FCM） algorithm

the trajectories of survival targets are received by Gaussian mixture probability hypothesis density（ GM-PHD） filter. For newborn targets

the measurement sets are partitioned by grid clustering

the trajectories of newborn targets are received by ET-GMPHD filter. Simulation results show the proposed algorithm can track multiple extended target accurately

especially at the moment of targets crossing estimated number of targets

is more accurate and realtime performance of algorithm is better.