Abstract
Two algorithms are described for assessing systematic errors in acoustic travel-time tomography of the atmosphere, the goal of which is to reconstruct the temperature and wind velocity fields given the transducers' locations and the measured travel times of sound propagating between each speaker-microphone pair. The first algorithm aims at assessing the errors simultaneously with the mean field reconstruction. The second algorithm uses the results of the first algorithm to identify the ray paths corrupted by the systematic errors and then estimates these errors more accurately. Numerical simulations show that the first algorithm can improve the reconstruction when relatively small systematic errors are present in all paths. The second algorithm significantly improves the reconstruction when systematic errors are present in a few, but not all, ray paths. The developed algorithms were applied to experimental data obtained at the Boulder Atmospheric Observatory.
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