Abstract
As a growing number of exploration missions have successfully landed on the Moon in recent decades, ground infrastructures, such as radio beacons, have attracted a great deal of attention in the design of navigation systems. None of the available studies regarding integrating beacon measurements for pinpoint landing have considered uncertain initial beacon locations, which are quite common in practice. In this paper, we propose a radio beacon/inertial measurement unit (IMU)/altimeter localization scheme that is sufficiently robust regarding uncertain initial beacon locations. This scheme was designed based on the sparse extended information filter (SEIF) to locate the lander and update the beacon configuration at the same time. Then, an adaptive iterated sparse extended hybrid filter (AISEHF) was devised by modifying the prediction and update stage of SEIF with a hybrid-form propagation and a damping iteration algorithm, respectively. The simulation results indicated that the proposed method effectively reduced the error in the position estimations caused by uncertain beacon locations and made an effective trade-off between the estimation accuracy and the computational efficiency. Thus, this method is a potential candidate for future lunar exploration activities.
Highlights
Safe and soft pinpoint landing on an extraterrestrial body has been a central objective since the beginning of human space exploration missions
Almost all existing radio beacons/inertial measurement unit (IMU)-integrated navigation algorithms in pinpoint landing are formulated using the state by the covariance matrix Σ and the mean vector μ of the multivariate Gaussian distribution and tracked via the extended Kalman filter (EKF) [4,11,13,14,15] or unscented Kalman filter (UKF) [16,17]
It can be seen from the results that the residuals converged into the 1σ uncertainty bound rapidly both in the triaxial position and velocity estimations with steady values less than 50 m and 5 m/s, which meet the demands of pinpoint landing
Summary
Safe and soft pinpoint landing (within 100 m at 3σ from the target site [1]) on an extraterrestrial body has been a central objective since the beginning of human space exploration missions. Almost all existing radio beacons/inertial measurement unit (IMU)-integrated navigation algorithms in pinpoint landing are formulated using the state by the covariance matrix Σ and the mean vector μ of the multivariate Gaussian distribution and tracked via the extended Kalman filter (EKF) [4,11,13,14,15] or unscented Kalman filter (UKF) [16,17]. Based on all the existing studies listed above, a novel distributed radio beacon/IMU-integrated localization scheme based on an adaptive iterated sparse extended hybrid filter (AISEHF) is presented in this paper. To the best of our knowledge, this is the first time that beacon location errors have been taken into consideration in the integrated navigation architecture for lunar pinpoint landing This scheme is inspired by the SEIF-based distributed framework sketched in [37] and the ISEIF proposed in [34], while several aspects have been modified according to the characteristics of lunar pinpoint landing:.
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