Abstract: Considering the traditional data association algorithm of multiple maneuvering targets tracking being of hard constraint condition, lower estimated accuracy, and higher computational complexity, a non data association tracking algorithm based on the random set theory was proposed. Since the proposed algorithm integrates the both advantages of Gaussian mixture probability hypothesis density (GMPHD) filter and current statistical mode1, avoids the difficult problem of data association, it is able to deal with multiple maneuvering targets tracking effectively. A simulation experiment was performed in the complex environment with clutter, miss detection, false alarm, dense, and cross targets. The simulation results show that the proposed algorithm has higher tracking accuracy and more steady tracking performance.