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X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

In order to succeed in landing asteroids, good accuracy autonomous navigation is absolutely necessary. Aims to describe a new autonomous navigation algorithm.

First, gray images of asteroid surface are acquired by optical navigation camera, and nature feature points are detected and tracked autonomously. Second, the directional vector from spacecraft to the center of each feature point can be computed from the image coordinates in camera focal plane. Then, LIDAR/LRF is directed to three feature points and the distances from spacecraft to feature points are obtained. Last, the relative position vector from spacecraft to the target asteroid is reconstructed base on measurement outputs of navigation cameras and laser light radar (laser range finder).

Suppose the initial conditions presented in this paper, the autonomous optical navigation position error and velocity error are less than 1 m and 0.1 m/s, respectively; this navigation accuracy can satisfy the requirement of soft landing on asteroids.

Based on feature detection and tracking, an autonomous optical navigation scheme is brought out and the validity is confirmed by computer simulation.

This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.

To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.

Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.

A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.

The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous navigation method where inter-satellite range measurements are used to estimate the orbits of all participating spacecrafts simultaneously.

To overcome the problem caused by an inaccurate initial state, a navigation algorithm is designed based on the multiple model adaptive estimation technique. The multiple models are constructed by different initial error covariance matrices. To reduce the computational cost, the likely-model set (LMS) algorithm is adopted to eliminate the unlikely models.

It is specified that the performance of the liaison navigation based on the extended Kalman filter (EKF) is sensitive to the initial error. Simulation results show that the VSMMAE outperforms the EKF in the presence of a large initial error.

The presented algorithm is applicable to spacecraft autonomous navigation.

A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.

The purpose of this paper is to present novel robust fault tolerant control design architecture to detect and isolate spacecraft attitude control actuators and reconfigure to redundant backups to improve the practicality of actuator fault detection.

The Robust Fault Tolerant Control is designed for spacecraft Autonomous Rendezvous and Docking (AR&D) using Lyapunov direct approach applied to non‐linear model. An extended Kalman observer is used to accurately estimate the state of the attitude control actuators. Actuators on all three axes (roll/pitch/yaw) sequentially fail one after another and the robust fault tolerant controller acts to reconfigure to redundant backups to stabilize the spacecrafts and complete the required maneuver.

In the simulations, the roll, pitch and yaw dynamics of the spacecraft are considered and the attitude control actuators failures are detected and isolated. Furthermore, by switching to redundant backups, the guarantee of overall stability performance is demonstrated.

A real time actuator failure detection and reconfiguration process using robust fault tolerant control is applied for spacecraft AR&D maneuvers. Finding an appropriate Lyapunov function for the non‐linear dynamics is not easy and always challenging. Failure of actuators on all three axes at the same time is not considered. It is a very useful approach to solve self‐assembly problems in space, spacecraft proximity maneuvers as well as co‐operative control of planetary vehicles in presence of actuator failures.

An approach has been proposed to detect, isolate and reconfigure spacecraft actuator failures occurred in the spacecraft attitude control system. A Robust Fault Tolerant Control scheme has been developed for the nonlinear AR&D maneuver for two spacecrafts. Failures that affect the control performance characteristics are considered and overall performance is guaranteed even in presence of control actuator failures. The architecture is demonstrated through model‐based simulation.

The paper aims to introduce a trade-off method for selecting a mission concept for an asteroid mining mission. In particular, the method is applied to the KaNaRiA mission concept selection. After introducing the KaNaRiA project, the KaNaRiA mission concept selection and reference scenario are described in detail.

The paper introduces past relevant asteroid missions in general and the previous studies on asteroid mining in particular. Based on the review of past mission concepts to minor planets, the paper discusses the operational phases of a potential industrial and commercial space mining mission. The methodology for selecting a mission reference scenario is explained and the selected KaNaRiA mission scenario is described.

The key technology driver for a space mining mission is the autonomous on-board capability related to navigation, guidance and handling of hardware/software anomalies or unexpected events. With the methodology presented here, it is possible to derive a mission concept which provides an adequate test-bed for the validation and verification of algorithms for enhanced spacecraft autonomy. This is the primary scientific and engineering goal of the KaNaRiA project.

The mission concept selection method presented here can be used as a generalized approach for mining missions targeting asteroids in the solar system.

The availability and usage of space resources is seen as a possible solution for the imminent problem of diminishing terrestrial materials in the foreseen future. This paper explains a methodology to select mission concepts for asteroid mining missions.

The purpose of this paper is to consider relative navigation – a vital technology to satellites formation flying, and to propose a new concept for relative navigation determination along with a technical approach for its practical implementation.

The determination of relative orbit is considered with the relative distance elevation and azimuth measurements about formation flying while the primary satellite is in a circle or ellipse orbit. This measurement is obtained by laser range finder and the estimations of the intersatellite relative position and velocity are obtained by utilizing the unscented Kalman filter instead of extended Kalman filter.

The simulation results show that the error of the relative position and velocity can be estimated with the order of cm and mm/s, respectively, under the effect of J2, converge faster than EKF, and then demonstrate that the approach is feasible.

The paper proposes a new concept for relative navigation determination and describes a technical approach for its practical implementation.

The purpose of this paper is to address the flaws of traditional methods and fulfil the special fault‐tolerant re‐entry navigation requirements of reusable boost vehicle (RBV).

A kind of improved estimation method based on strong tracking unscented Kalman filter (STUKF) is put forward. According to the fact that the traditional state χ²‐test‐based fault diagnosis method is incompetent to detect the signal point small jerks and slowly varying fault in the measurement, a kind of original fault diagnosis technology based on STUKF is used to check the working states of navigation sensors.

The comparisons with χ²‐test method under typical failure distributions validate the perfect state tracking and fault diagnosis performances of this improved method.

This kind of state estimation and fault diagnosis method could be used in the navigation and guidance systems for many kinds of aeronautical and astronautical vehicles.

A kind of novel strong tracking state estimation filter is used, and a kind of very effective fault diagnosis criterion is put forward for the navigation of RBV.

One of the primary problems in the field of on‐orbit service and space conflict is related to the approach to the target. The development of guidance algorithms is one of the main research areas in this field. The objective of this paper is to address the guidance problem for autonomous proximity manoeuvres of a chase‐spacecraft approaching a target spacecraft.

The process of autonomous proximity is divided into three phases: proximity manoeuvre, fly‐around manoeuvre, and final approach. The characteristics of the three phases are analyzed. Considering the time factor of autonomous proximity, different orbits for the three phases are planned. Different guidance algorithms, which are based on multi‐pulse manoeuvres, are then devised.

This paper proposes three phases of autonomous proximity and then designs a guidance method, which hinges on a multi‐pulse algorithm and different orbits for the three phases; in addition, a method of impulse selection is devised.

An easy methodology for the analysis and design of autonomous proximity manoeuvres is proposed, which could also be considered for other space applications such as formation flying deployment and reconfiguration.

Based on this guidance method, the manoeuvre‐flight period of the chase‐spacecraft can be set in accordance with the mission requirements; the constraints on fuel mass and manoeuvre time are both considered and satisfied. Consequently, this proposed guidance method can effectively deal with the problem of proximity approach to a target spacecraft.

An onboard autonomous technique can significantly reduce the costs of the mission. The purpose of this paper is to deal with the autonomous orbit determination and attitude determination of a satellite based on the sun, the earth and the moon sensors.

The models of the conical earth scanner are presented, and its measurement with information from the sun and the moon sensors is processed to simultaneously acquire the orbit and attitude of the satellite via extended Kalman filter.

The numerical simulation shows that the presented method can obtain the orbit and attitude information precisely; even in the new moon period, it can be used to get the satisfied results.

Autonomous orbit determination and attitude determination based on direction information of celestial objects, such as sun, earth and moon, are put forward. The method improves the survival ability of the satellite and decreases its reliance on the ground stations.