Maneuvering target state estimation based on separate modeling with B-splines

The state estimation of a maneuvering target based on separate modeling of target trajectory shape and dynamic characteristics is studied in the absence of prior information about the target trajectory. Traditionally, target dynamics are described by motion models in Cartesian coordinates, in which the target trajectory is determined by target dynamic characteristics. However, due to target motions subjected to external environmental limitations such as roads, terrains, buildings, trees, flight routes, and sea-routes, the trajectory shape of a target is independent of target dynamic characteristics. In addition, although one-dimensional representation can be used to decouple the target trajectory from dynamic characteristics, it is unsuitable for direct tracking without knowing prior information about the target trajectory. For these reasons, this paper proposes a new estimation algorithm that models the target trajectory and dynamic characteristics separately as well as handles the issue of no prior information. The target trajectory over a sliding window is described by B-spline curves, which are functions of the arc length. The unknown control points defining the B-spline curves are put in the modified multiple model estimator framework and are estimated together with the base state. After the first estimation cycle, the control points entering into interaction stage of the proposed estimation algorithm are reset by the least squares (LS). Simulation results show that the proposed estimation algorithm is capable of achieving better performance than conventional tracking algorithms. (c) 2021 Elsevier Masson SAS. All rights reserved.

Automated summary

This paper presents a new estimation algorithm that models the target trajectory and dynamic characteristics separately, and accurately estimates unknown control points defining the B-spline curves to achieve better tracking performance for maneuvering targets in complex environments.