A refined track initiation algorithm is proposed for the objects in dense formation.The measurement clustering algorithmwhich needs significant amount of computationis not needed in the method.Firstall possible associate point sequences are built up by extending the track initiation conditions.Thenclustering is made to all the sequences by comparing the different sequences to see if they have the common measurements.At lastoptimized distribution is taken to the initial relative sequences belong to the same clusterand the optimum scheme is selected to each object in the formation for track initiation.Simulation results prove that the method has fine performance on formation track initiationlow computational burden and high accuracy rate on track initiation.