Wake Sensing for Aircraft Formation Flight

Abstract

It is well established that flying aircraft in formation can lead to improved aerodynamic efficiency. However, successfully doing so is predicated on having knowledge of the lead aircraft’s wake position. Here, a wake-sensing strategy for estimating the wake position and strength in a two-aircraft formation is explored in a simplified proof-of-concept setting. The wake estimator synthesizes wing-distributed pressure measurements, taken on the trailing aircraft, by making use of an augmented lifting-line model in conjunction with both Kalman-type and particle filters. Simple aerodynamic models are introduced in constructing the filter to enable fundamental wake-sensing challenges to be identified and reconciled. The various estimation algorithms are tested in a vortex lattice simulation environment, thus allowing the effects of modeling error to be analyzed. It is found that biases in the position estimates no longer arise if a particle filter is used in place of the Kalman-type filters. Filter divergence is observed when the relative aircraft separations are held fixed. This divergent behavior can be alleviated with the introduction of relative aircraft motions, for example in the form of a cross-track dither signal.