Extended low-altitude aircraft tracking via navigation-assisted radar measurement augmentations

In the flight test of cooperative aircraft floating at low altitudes, a single-station high-resolution radar can get sparse (even missing) and spatially incomplete measurements, while the radar observes a partial surface of the aircraft. This will lead to poor tracking accuracy for the tested aircraft. To solve this problem, this paper proposes a tracking method using augmented radar measurements by fusing aircraft navigation information. First, a symmetric positive definite random matrix is used to approximate the aircraft’s three-dimensional extension shape, which is roughly ellipsoidal, based on the structurally extended characteristic of the aircraft identified by the high-resolution radar. Subsequently, the partially observed aircraft model and the radar measurement model are both established. Further, multiple strategies are designed to augment sparse radar measurements using assisted aircraft navigation information, such that the radar measurement data is improved in both amount and spatial completeness. Finally, an implementation of aircraft state estimation under partial observation is given within the Bayesian filtering framework. The outcomes of the simulation experiment show that the proposed method improves the tested aircraft’s tracking accuracy and, consequently, awareness accuracy for its flight condition. Moreover, the proposed method has the advantages of high fusion usage of multi-source measurement information and a low computational cost.