Radio-frequency positioning for airborne wind energy systems

Abstract

Conventional GPS and encoder-based solutions for the real-time position and velocity tracking of tethered aircraft in airborne wind energy (AWE) systems are known to have some practical limitations. As an alternative, the main contribution of this paper is to present a setup based on 2.4 GHz radio-frequency (RF) devices, for which there are still no reported experimental results in the literature. To this end, four estimation algorithms are formulated to a lateration problem: linear and nonlinear least squares (kinematic approaches), as well as the extended and the unscented Kalman filters (dynamic approaches). The Cramér–Rao lower bound is computed to serve as a benchmark for the filtering performance in terms of the position estimate covariance. Drawbacks of the two kinematic algorithms are discussed, followed by the advantages of using the two Kalman filters in a sensor fusion scheme that uses not only the RF rangings but also line angles and length measurements obtained from rotary encoders at the ground station. Estimates computed from field experimental data acquired with a small-scale AWE prototype are validated against the encoder measurements. The results show that setups based on RF ranging devices have many advantages over more conventional positioning techniques such as those based on line-following mechanisms with encoders, GPS and IMU, and computer vision, representing a promising solution for AWE applications.