Yun-Hua Wu

A time suboptimal method for real-time spacecraft attitude agile maneuvering with angular velocity constraint

A time suboptimal method for on-orbit rapid attitude maneuver control of agile spacecraft with attitude angular velocity constraint is proposed, which can generate suboptimal control torque command for real-time application. Spacecraft time-optimal slew maneuver has been studied by many researchers, and most of the interest is focused on formulating and resolving the optimization problem of spacecraft attitude maneuver in proper ways. Pseudospectral method, among most of the existing methods, is feasible to figure out the preferred solution satisfying the control precision, which possesses the values of practical application. However, pseudospectral method consumes much time for planning attitude trajectory making it impossible for on-orbit spacecraft real-time control, especially for observation mission with frequent maneuver. After thorough analysis of the time optimal attitude maneuvering results, several patterns with respect to the generation of attitude control command are summarized that result in an interpolation control method, which is time suboptimal and is capable of on-orbit real-time application for spacecraft with small products of inertia. Closed-loop control is implemented to cancel the final pointing error. Several simulations have been performed to validate the performance of the proposed strategy, and have demonstrated the potential application for small agile spacecraft with limited attitude control ability.

Adaptive estimation of attitude and angular velocity of malfunctioned satellites for on-orbit servicing

Estimating the attitude and angular velocity of a malfunctioned satellite is one of the key technologies to achieve robotic on-orbit servicing, which is a challenging space activity. In this paper, a new method of estimating attitude parameters for target satellite by using stereo-vision system is proposed. First, two sets of vectors are constructed according to the feature point coordinates in target frame and stereo-vision system frame respectively, and then the relative attitude between the target and the servicer is determined through QUEST algorithm. Secondly, a new nonlinear estimator is proposed to estimate the attitude and inertial angular momentum of the target and the angular velocity is computed according to the estimated angular momentum and attitude. The stability of the estimator is proved by using the LaSalle’s invariance principle. Thirdly, a switch rule and an adaptive regulating rule are proposed to improve the estimation performance. The former decides when to switch from the rough estimator to the precise one. The latter regulates the gain dynamically in order to reduce the influence of the varying stereo-vision noise in the precise estimating procedure. Finally, numerical simulations and an experiment are carried out to verify the validity of the proposed method.

Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.

Robust monocular vision navigation for spacecraft on-orbit service

Spacecraft on-orbit serving is vital important for future space missions and is of interest of many countries. Relative motion determination is the major problem for spacecraft on-orbit servicing. Due to the advantages of monocular vision navigation system, it has been widely proposed for spacecraft approaching for the final stage. However, due to the model uncertainty and state mobility of the target spacecraft, a strong tracking filter is proposed to overcome the above issues in estimating relative position and attitude. This article first introduces how to set up, select and match feature markers. Followed by establishing a 6DOF spacecraft dynamics model and an imaging observation model based on quaternion. Then, the recursive process of Suboptimal Fading Extended Kalman Filter is implemented. Finally, numerical simulations are carried out to verify the effectiveness of the proposed algorithm.