Method for acquiring and modelling, by a LiDAR sensor, an incident wind field in a space situated upstream of said LiDAR sensor, characterized in that the method comprises: a) a step of meshing of the space situated upstream of said LiDAR sensor in which the mesh of the space is produced by a set of discretized points positioned according to a predefined three-dimensional grid which comprises a set of meshes composed of estimation points and measurement points, b) a step of measurement of the amplitude and of the direction of the wind at the different measurement points situated in the space upstream and positioned at at least two distinct distances from the LiDAR sensor, along at least three measurement axes, c) a step of estimation of the amplitude and of the direction of the wind at any instant (t) over all of the estimation points and the estimation is made by means of optimization by a recursive least squares method weighted by a cost function J ( t) which uses at least the data from the measurement points, spatial wind speed consistency data, temporal wind speed consistency data, and data qualifying the quality of the measurements performed on the measurement points, and said cost function J ( t) at any instant (t) expressed in the following form: in which ω is an ordered vector composed of all the components of the speed of the points of the space where the wind is estimated, ω̂ is the estimation of the wind speed at the time 0, P 0, Q, R s and R m are weighting matrices of appropriate dimension, and C s, C m are matrices which take into account the wind speed and the measurement noises, d) a step of reconstruction (MOD 3D), in real time and within a defined reference frame, of the incident wind field in three dimensions from the amplitudes and the directions of wind estimated and measured for each point of said mesh. a) a step of meshing of the space situated upstream of said LiDAR sensor in which the mesh of the space is produced by a set of discretized points positioned according to a predefined three-dimensional grid which comprises a set of meshes composed of estimation points and measurement points, b) a step of measurement of the amplitude and of the direction of the wind at the different measurement points situated in the space upstream and positioned at at least two distinct distances from the LiDAR sensor, along at least three measurement axes, c) a step of estimation of the amplitude and of the direction of the wind at any instant (t) over all of the estimation points and the estimation is made by means of optimization by a recursive least squares method weighted by a cost function J ( t) which uses at least the data from the measurement points, spatial wind speed consistency data, temporal wind speed consistency data, and data qualifying the quality of the measurements performed on the measurement points, and said cost function J ( t) at any instant (t) expressed in the following form: in which ω is an ordered vector composed of all the components of the speed of the points of the space where the wind is estimated, ω̂ is the estimation of the wind speed at the time 0, P 0, Q, R s and R m are weighting matrices of appropriate dimension, and C s, C m are matrices which take into account the wind speed and the measurement noises, d) a step of reconstruction (MOD 3D), in real time and within a defined reference frame, of the incident wind field in three dimensions from the amplitudes and the directions of wind estimated and measured for each point of said mesh.