Synthesis of Algorithm of Trajectory Processing in Case of Dense Flows of Cluttered Data and Rarefied Flow of Trajectories

An algorithm of detecting and estimating trajectories in case of high density of flows of cluttered data is synthesized on the basis of the stochastic flow theory. Expressions to estimate trajectory parameters have been derived as well as the detection rule, taking into account the probability and accuracy requirements to make a decision. The Bar-Sholom PDA filter of probabilistic identification of data follows, in particular, from the expressions produced.