Abstract

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attemps to reconstruct temperature and wind velocity fields in the atmospheric surface layer (ASL) using the dependence of sound speed on temperature and wind velocity fields along the propagation path. A new statistical-based algorithm is introduced in this paper based on fixed-point unscented Kalman filter (UKF) which is capable of reconstructing and tracking temperature and wind velocity fields within a specified investigation area.

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