Nonlinear aircraft tracking filter utilizing control variable estimation

This paper describes a filter for tracking translational and angular position, velocity, and acceleration of a maneuvering aircraft, using remote sensor data. The approach taken is to develop a 16-state extended Kalman filter that estimates not only the translational and rotational degrees of freedom but also the control variables (thrust and control surface deflections). Improved force and moment models correlated to velocity, attitude angles, and control variables are utilized. Simulations of an 1-4 fighter performing various maneuvers indicate improved tracking accuracy over conventional trackers (α-β, α-β-γ), as well as previous force-model trackers with less complete force models.