Abstract
Air data are critical factor for the control of a hypersonic vehicle. In order to solve the air data estimation problem under hypersonic condition, a novel tightly coupled algorithm is proposed based on Kalman filter. In the method, the measurements of the pressures on the vehicle nosecap surface are integrated with the IMU raw outputs and GPS results as the system measurements. Then, the trajectory parameters and wind velocity are estimated by Cubature Kalman Filter. Using the filter results, the air data, including the attack of angle and the slide of angle, the Mach number, the freestream static pressure, and the wind velocities are obtained. Compared with traditional approaches, the proposed method can decouple the biases of inertial sensors from the wind estimates and largely improve the estimated precision of the air data as a result. Simulation cases are presented to assess the performance of the proposed method. The results demonstrate that the proposed method can effectively estimate the air data under hypersonic flight with high precision. These achievements make outstanding contributions to the control system and the flight test analyses for a hypersonic vehicle.
Published Version
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