Frequency estimation for 3D atmospheric tomography using unmanned aerial vehicles

Abstract

Spatially varying three-dimensional atmospheric temperature profiles and wind velocity fields may be derived by observing the acoustic signature of an Unmanned Aerial Vehicle (UAV) as it flies over ground-based microphones. The Doppler shift between the UAV and the ground microphones is used to estimate the acoustic propagation times and the atmospheric parameters are then estimated from the derived acoustic propagation times. The estimates may be supplemented by local meteorological measurements made at the UAV and/or the ground receivers. The technique models the atmospheric temperature and wind speed profiles as a 3-dimensional continuous array of Radial Basis Functions. This technique has potential for atmospheric research and practical applications such as boundary layer meteorology, theories of atmospheric turbulence and wave propagation through a turbulent atmosphere. This paper describes how the propagation time and speed of sound is derived from the Doppler frequency. It then describes the method for performing tomographic inversion and then provides simulation results.