The Tianwen-1 probe, used in China’s first Mars exploration mission, features multiple flight phases, numerous spatial pointing constraints, and complex working modes. During the braking and capture process, it faces challenges such as uplink or downlink command delay, unique capture window, post-control “occultation”, short-time significant change in speed increment, and interference caused by low-frequency and low-damping solid–liquid flexible coupling oscillations. Therefore, high reliability, high autonomy, and high precision are required for the braking and capture process. As the executor of braking and capture control, the GNC (guidance, navigation, and control) subsystem of the orbiter employs an online orbit control strategy reconstruction method based on arc loss compensation to realize high reliability, the main engine anomaly recognition and a seamless switching scheme to realize high autonomy, and the attitude–orbit coupling control algorithm with thrust direction compensation to realize high-precision speed increment control. According to the on-orbit flight validation of the Tianwen-1 probe, the GNC subsystem of the orbiter has completed the braking and capture control task reliably and autonomously with millimeter-per-second-level accuracy, effectively ensuring the successful execution of subsequent landing and patrol tasks. This paper analyzes the online orbit control strategy reconstruction method, anomaly recognition and seamless switching method, and thrust vector control method of the braking and capture process and offers valuable insights for future interplanetary exploration flight control.

The distribution and change of sea surface salinity (SSS) have an important influence on the sea dynamic environment, marine ecological environment, global water cycle, and global climate change. Satellite remote sensing is the only practical way to continuously observe SSS over a wide area and for a long period of time. The salinity retrieval model of flat sea surface, which primarily includes empirical model and iterative model, is the key to retrieving satellite SSS products. The empirical models have high computational efficiency but low inversion accuracy, while the iterative models have high inversion accuracy but low computational efficiency. In order to reconcile the contradiction between the computational efficiency and inversion accuracy of existing models, this paper proposes a universal deep neural network (DNN) model architecture and corresponding training scheme, and provides 3 DNN models with extremely high computational efficiency and high inversion accuracy. The inversion error range, the root mean square error (RMSE), and the mean absolute error (MAE) of the DNN models on 311,121 sets of data have decreased by more than 40 times, 150 times, and 150 times, respectively, compared to the empirical model. The computational efficiency of the DNN models on 420,903 sets of data has improved by more than 100,000 times compared to the iterative model. Therefore, the algorithm developed in this paper can effectively solve the contradiction between the computational efficiency and inversion accuracy of existing models, and provide a theoretical support for high-precision and high-efficiency salinity inversion research.

To efficiently plan the point-to-point path for a 7-degrees-of-freedom (7-DOF) free-floating space manipulator system, a path planning method based on Legendre pseudospectral convex programming (LPCP) is proposed. First, the non-convex dynamics are approximated by utilizing the first-order Taylor expansion in the vicinity of the initial guess path, which results in a convex system. Next, the linearized dynamics are discretized at Legendre–Gauss–Lobatto collocation points to transcribe the differential equations to a set of equality constraints. To obtain a reliable initial guess trajectory, the auxiliary path planning problem of the 7-DOF space manipulator with a fixed base is initially resolved. Additionally, the penalty function method is introduced to enhance the convergence performance of the LPCP. Finally, simulation results show that the proposed algorithm in this paper can generate the point-to-point path and has higher computational efficiency than the general sequential convex programming method while ensuring optimality.

Jupiter exploration is one of the focuses of deep space exploration in the near future. Design and optimization of trajectories in the Jovian system are crucial technologies for Jupiter exploration missions due to the unique and challenging multi-body dynamical environment. Various methodologies have been proposed and developed. However, there is a lack of comprehensive review of these methodologies, which is unfavorable for further developing new design techniques and proposing new mission schemes. This review provides a systematic summarization of the past and state-of-art methodologies for 4 main exploration phases, including Jupiter capture, the tour of the Galilean moons, Jupiter global mapping, and orbiting around and landing on a target moon. For each exploration phase, the related methods are categorized according to the fundamental features. The advantages and capabilities of the methods are described or analyzed, revealing the research progress. Finally, a prospect of future development of the methods is presented, aiming at providing references for further studies on trajectory design and optimization in the Jovian system.

Relative navigation is a key enabling technology for space missions such as on-orbit servicing and space situational awareness. Given that there are several special advantages of space relative navigation using angles-only measurements from passive optical sensors, angles-only relative navigation is considered as one of the best potential approaches in the field of space relative navigation. However, angles-only relative navigation is well-known for its range observability problem. To overcome this observability problem, many studies have been conducted over the past decades. In this study, we present a comprehensive review of state-of-the-art space relative navigation based on angles-only measurements. The emphasis is on the observability problem and solutions to angles-only relative navigation, where the review of the solutions is categorized into four classes based on the intrinsic principle: complicated dynamics approach, multi-line of sight (multi-LOS) approach, sensor offset center-of-mass approach, and orbit maneuver approach. Then, the flight demonstration results of angles-only relative navigation in the two projects are briefly reviewed. Finally, conclusions of this study and recommendations for further research are presented.

From March 20, 2019 to April 30, 2019, the 10th China Trajectory Optimization Competition (CTOC10) was jointly held by the Chinese Society of Theoretical and Applied Mechanics and Nanjing University of Aeronautics and Astronautics. The CTOC10 focused on trajectory optimization for Jovian exploration. The team from Harbin Institute of Technology won the first prize. In this paper, first, the history of the CTOC is presented. Subsequently, the mission of the CTOC10 is introduced, and an account of the final rankings of the competition is given. Finally, trajectory optimization methods are discussed, and suggestions for practical missions are provided.

This research furthers the development of a closed-form solution to the angles-only initial relative orbit determination problem for non-cooperative target close-in proximity operations when the camera offset from the vehicle center-of-mass allows for range observability. In previous work, the solution to this problem had been shown to be non-global optimal in the sense of least square and had only been discussed in the context of Clohessy-Wiltshire. In this paper, the emphasis is placed on developing a more compact and improved solution to the problem by using state augmentation least square method in the context of the Clohessy-Wiltshire and Tschauner-Hempel dynamics, derivation of corresponding error covariance, and performance analysis for typical rendezvous missions. A two-body Monte Carlo simulation system is used to evaluate the performance of the solution. The sensitivity of the solution accuracy to camera offset, observation period, and the number of observations are presented and discussed.

Scheduled for an Earth-to-Mars launch opportunity in 2020, the China’s Mars probe will arrive on Mars in 2021 with the primary objective of injecting an orbiter and placing a lander and a rover on the surface of the Red Planet. For China’s 2020 Mars exploration mission to achieve success, many key technologies must be realized. In this paper, China’s 2020 Mars mission and the spacecraft architecture are first introduced. Then, the preliminary launch opportunity, Earth-Mars transfer, Mars capture, and mission orbits are described. Finally, the main navigation schemes are summarized.