On Extended State Based Kalman Filter Design for Airspeed Estimation of Flight Vehicle via Unbiased Measurement Transformation

This paper is concerned with the problem of esti-mating the airspeed of the flight vehicle. We propose a consistent estimation algorithm based on the extended state Kalman filter (ESKF). Firstly, the unbiased transformation from the original measurement signals to the equivalent airspeed is analyzed. Secondly, the extended state Kalman filter algorithm is designed to estimate the airspeed vector by introducing a compensation parameter matrix to the disturbance in the dynamic model. Finally, the numerical simulation is carried out which shows that the proposed method can achieve better accuracy of estimation than the traditional method.