This paper presents calibration of flush air data sensing systems during ascent period of a satellite launch vehicle. Aerodynamic results are numerically computed by solving three-dimensional time dependent compressible Euler equations over a payload shroud of a satellite launch vehicle. The flush air data system consists of four pressure ports flushed on a blunt-cone section of the payload shroud and connected to on board differential pressure transducers. The inverse algorithm uses calibration charts which are based on computed and measured data. A controlled random search method coupled with neural network technique is employed to estimate pitch and yaw angles from measured transient differential pressure history. The algorithm predicts the flow direction stepwise with the function of flight Mach numbers and can be termed as an online method. Flow direction of the launch vehicle is compared with the reconstructed trajectory data. The estimated values of the flow direction are in good agreement with them.
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