Reentry guidance algorithm based on Kalman filter for aerospace vehicles

A new predictor-corrector reentry guidance algorithm based on Kalman filter is proposed to improve the real-time performance of predictor-corrector reentry guidance for aerospace vehicles. The new algorithm fits the velocity-altitude flight profile with the fourth-order polynomial. To compute the fitting coefficients satisfying the requirements of the reentry corridor and the range to be flown, the altitude corresponding to the selected speed point is estimated by Kalman filter. The reentry flight time is adjusted by reducing a terminal constraint and adding a profile parameter to be estimated in the algorithm. It is found that the adaptability of guidance instructions can be improved by correcting uncertain parameters through online identification during the reentry. At the end of the flight, the divergence of the fitting coefficients when the flight speed is close to the terminal speed can be avoided by tracking the reference profile. The simulation results of different reentry conditions demonstrate that the reentry guidance algorithm based on Kalman filter has better real-time performance, higher guidance accuracy, controllable flight time, stronger robustness and engineering application potential. © 2021, Beihang University Aerospace Knowledge Press. All right reserved.