Maneuvering target state estimation based on separate modeling of target trajectory shape and dynamic characteristics

The state estimation of a maneuvering target, of which the trajectory shape is independent on dynamic characteristics, is studied. The conventional motion models in Cartesian coordinates imply that the trajectory of a target is completely determined by its dynamic characteristics. However, this is not true in the applications of road-target, sea-route-target or flight route-target tracking, where target trajectory shape is uncoupled with target velocity properties. In this paper, a new estimation algorithm based on separate modeling of target trajectory shape and dynamic characteristics is proposed. The trajectory of a target over a sliding window is described by a linear function of the arc length. To determine the unknown target trajectory, an augmented system is derived by denoting the unknown coefficients of the function as states in mileage coordinates. At every estimation cycle except the first one, the interaction (mixing) stage of the proposed algorithm starts from the latest estimated base state and a recalculated parameter vector, which is determined by the least squares (LS). Numerical experiments are conducted to assess the performance of the proposed algorithm. Simulation results show that the proposed algorithm can achieve better performance than the conventional coupled model-based algorithms in the presence of target maneuvers.

Automated summary

This paper studies a state estimation algorithm for maneuvering targets with trajectory shapes independent of dynamic characteristics. The algorithm separates the modeling of target trajectory and dynamic characteristics and calculates the parameter vector using least squares. Numerical experiments show that the proposed algorithm outperforms traditional coupled model-based algorithms in the presence of target maneuvers.