Title :
Mars Entry Navigation With Uncertain Parameters Based on Desensitized Extended Kalman Filter
Author :
Liansheng Wang ; Yuanqing Xia
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Abstract :
Mars entry phase is the most challenging part among Mars entry, descent, and landing (EDL). One of the main reasons is that the lander suffers tough tests from the uncertainties, which include atmospheric density, lift over drag ratio, ballistic coefficient, and initial conditions. In this paper, the desensitized extended Kalman filter (DEKF) is introduced. State estimations from DEKF are obtained by minimizing a cost function that is composed of the trace of posterior covariance matrix and the weighted norm of the posterior state estimation error sensitivities (PSEES). By applying inertial measurement unit (IMU), Mars orbiters and Mars surface beacons (MSBs) integrated navigation simulations demonstrate that the introduced DEKF is far less sensitive to uncertain parameters than standard EKF during Mars entry. With the increase of uncertainties one by one, the root-mean-square errors (RMSE) of the states are still convergent in case of DEKF as compared to standard EKF where they become larger. At last, the consistency test is carried on to further validate the proposed DEKF.
Keywords :
Kalman filters; Mars; aerospace instrumentation; entry, descent and landing (spacecraft); nonlinear filters; state estimation; DEKF; IMU; MSB; Mars entry navigation; Mars entry, descent, and landing; Mars orbiters; Mars surface beacons; RMSE; desensitized extended Kalman filter; inertial measurement unit; posterior state estimation error sensitivities; root-mean-square errors; uncertain parameters; Atmospheric modeling; Covariance matrices; Extraterrestrial measurements; Mars; Mathematical model; Navigation; Uncertainty; Atmosphere Density Uncertainty; Atmosphere density uncertainty; Ballistic Coefficient Uncertainty; Desensitised Extended Kalman Filter; ballistic coefficient uncertainty; consistency test; desensitized extended Kalman filter (DEKF); lift over drag ratio uncertainty;
Journal_Title :
Industrial Informatics, IEEE Transactions on
DOI :
10.1109/TII.2015.2463763