Improving Unmanned Aerial Vehicle–Based Acoustic Atmospheric Tomography by Varying the Engine Firing Rate of the Aircraft

Abstract

f the acoustic signature of an unmanned aerial vehicle (UAV) is observed as it overflies an array of ground microphones, then the projected and observed Doppler shifts in frequency of the narrowband tones generated by its engine may be compared and converted into effective sound speed values. This allows 2D and 3D spatially varying atmospheric temperature and wind velocity fields to be estimated using tomography. Errors in estimating sound speed values are inversely proportional to the rate of change in the narrowband tones received on the ground. As this rate of change typically approaches zero at least twice per microphone during the UAV?s overflight, errors in the time of flight estimates are typically too large to deliver useful precision to the tomographically derived temperature and wind fields. However, these errors may be reduced by one or two orders of magnitude by continuously varying the engine throttle rate, thereby making the tomographic technique potentially feasible. This is demonstrated through reconstruction of realistic simulated conditions for a weakly sheared daytime convective atmospheric boundary layer.