Wake Sensing and Estimation for Control of Autonomous Aircraft in Formation Flight

Abstract

The continued development of sophisticated aircraft with high-fidelity control systems will enable autonomous execution of challenging tasks such as aerial refueling and close-formation flight. To achieve such tasks autonomously, an aircraft must sense other aircraft in close proximity and position itself relative to them. For example, formation-flying aircraft must position themselves strategically to realize benefits of aerodynamic efficiency; aerial refueling requires the follower aircraft to intercept the filling nozzle attached to the leader aircraft. This paper uses lifting-line theory to represent a two-aircraft formation and presents a grid-based, recursive Bayesian filter for estimating the wake parameters of the lead aircraft using noisy pressure measurements distributed along the trailing aircraft’s wing; the estimator also uses a binary, relative-altitude measurement to break the vertical symmetry. The paper employs measures of observability to quantify spatial regions prone to degraded estimation performance. Optimal control strategies are presented to steer the follower aircraft to a desired lateral position relative to the leader while simultaneously optimizing the observability of the leader’s relative position. The control algorithms guide the follower aircraft along trajectories that maintain adequate observability, thereby guaranteeing estimator performance. Theoretical results are illustrated using numerical examples of a two-aircraft formation.