Calibration of static pressure sensors using Extended Kalman Filter at high angles of attack and transonic Mach numbers

Abstract

Airdata measurements play a key role in stabilization, control and improving performance of modern fighter aircraft. Airdata sensors installed on aircraft normally measure pressures and flow angles in the local flow field and do not measure the parameters of free stream conditions that the entire aircraft flies in. As a result all the measurements by airdata sensors need to be corrected. This paper proposes an Extended Kalman Filter (EKF) based technique for the calibration of various parameters measured by Air Data System (ADS). The paper specifically addresses calibration of static pressure sensors at high angles of attack and transonic Mach number as the main theme. The algorithm estimates wind states to improve the accuracy of calibration. The algorithm is extensively tested using the flight test data of a high performance aircraft.