Passive tracking and data association algorithm for multiple targets with single sensor

The efficiency and speed of tracking and data association algorithm are the keys to passive single sensor multiple targets tracking in practice. The paper presents a practicable algorithm, in which establishing the tree of hypothesis trajectories and summing three-continuous-step estimation covariance of every possible trajectory obtain the probabilities of true trajectories. Therefore the algorithm can avoid complex calculation of likelihood function. It also can obtain better performance of data association compared with the nearest neighbor algorithm.