In-flight remote sensing and identification of gusts, turbulence, and wake vortices using a Doppler LIDAR

Abstract

In this paper, in-flight remote sensing technologies are considered for two applications: active load alleviation of gust and turbulence and wake impact alleviation. The paper outlines the strong commonalities in terms of sensors and measurement post-processing algorithms and presents also the few differences and their consequences in terms of postprocessing. The way the post-processing is being made is detailed before showing results for both applications based on a complete and coupled simulation (aircraft reaction due to disturbances and control inputs during the simulation is influencing the sensor measurements). The performances in terms of wind reconstruction quality for the gust/turbulence case and in terms of wake impact alleviation performance for the wake vortex case are shown based on simulations and are very promising.

Gust load alleviation for a long-range aircraft with and without anticipation

“…The wind reconstruction process is closely related to the process shown in [6] for the identification of wake vortices. The strong commonalities as well as the existing differences between these two applications are described in [11,12]. In the next sections, the free-form wind field model and the formulation of the maximum-likelihood wind reconstruction problem are only briefly reminded and the readers are referred to [12] for the details and for the wind reconstruction results.…”

“…The strong commonalities as well as the existing differences between these two applications are described in [11,12]. In the next sections, the free-form wind field model and the formulation of the maximum-likelihood wind reconstruction problem are only briefly reminded and the readers are referred to [12] for the details and for the wind reconstruction results. Significant performance improvements of the wind reconstruction algorithm could be obtained in terms of computation time compared to the version used in [12] by exploiting the linear least-squares structure of the problem.…”

“…Whereas for other wind reconstruction problems analytical models of the wind field might exist and be applicable for reconstruction problems (see for instance [14,38,7,6,11] and references therein), gusts and turbulence are stochastic by nature and no particular model structure and shape shall be assumed. Analytical models for gust and turbulence do exist, but are not suited for the considered wind reconstruction.…”

“…When this intersection is not also defined as a node of the mesh, the wind vector at the intersection is obtained by linearly interpolating between the surrounding two nodes. Typical values permitting to estimate a wind field for load alleviation purposes are: Further details on the way the values of these parameters should be chosen can be found in [12,10]. The lead and lag time values need to be scaled with the size of the considered gust lengths (usually the sizing gusts).…”

“…Assuming that the error on each measurement does not depend on the other measurements and that these errors follow a Gaussian distribution (whose respective standard deviations are noted σ i later on), it can easily be shown (full derivation can be found in [12]) that the maximum-likelihood problem can be written as:…”