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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.

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

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.

Autonomous orbit determination using geomagnetic measurements is an important backup technique for safe spacecraft navigation with a mere magnetometer. The geomagnetic model is used for the state estimation of orbit elements, but this model is highly nonlinear. Therefore, many efforts have been paid to developing nonlinear filters based on extended Kalman filter (EKF) and unscented Kalman filter (UKF). This paper aims to analyze whether to use UKF or EKF in solving the geomagnetic orbit determination problem and try to give a general conclusion.

This paper revisits the problem and from both the theoretical and engineering results, the authors show that the EKF and UKF show identical estimation performances in the presence of nonlinearity in the geomagnetic model.

While EKF consumes less computational time, the UKF is computationally inefficient but owns better accuracy for most nonlinear models. It is also noted that some other navigation techniques are also very similar with the geomagnetic orbit determination.

The intrinsic reason of such equivalence is because of the orthogonality of the spherical harmonics which has not been discovered in previous studies. Thus, the applicability of the presented findings are not limited only to the major problem in this paper but can be extended to all those schemes with spherical harmonic models.

The results of this paper provide a fact that there is no need to choose UKF as a preferred candidate in orbit determination. As UKF achieves almost the same accuracy as that of EKF, its loss in computational efficiency will be a significant obstacle in real-time implementation.

The main reason for the low accuracy of magnetometer-based autonomous orbit determination is the coarse accuracy of the geomagnetic field model. Furthermore, the geomagnetic field model error increases obviously during geomagnetic storms, which can still further reduce the navigation accuracy. The purpose of this paper is to improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms.

In this paper, magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter (MDEKF) is studied. The MDEKF algorithm can effectively remove the time-correlated portion of the measurement error and thus can evidently improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms. Real flight data from Swarm A are used to evaluate the performance of the MDEKF algorithm presented in this study. A performance comparison between the MDEKF algorithm and an extended Kalman filter (EKF) algorithm is investigated for different geomagnetic storms and sampling intervals.

The simulation results show that the MDEKF algorithm is superior to the EKF algorithm in terms of estimation accuracy and stability with a short sampling interval during geomagnetic storms. In addition, as the size of the geomagnetic storm increases, the advantages of the MDEKF algorithm over the EKF algorithm become more obvious.

The algorithm in this paper can improve the real-time accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms with a low computational burden and is very suitable for low-orbit micro- and nano-satellites.

The measurement of geomagnetic field can provide a reliable and economical basis for attitude and orbit information of low earth orbiting satellite. Because the earth's magnetic field is a function of position, and its measurement on the orbit are fully observable, orbit estimation can be obtained using extend Kalman filter (EKF) algorithm. With the assistant of angle velocity information from gyro measurement, attitude estimation can also be obtained. At the same time, gyro drift rate estimation is a part of the filter output. Although orbit and attitude determination are independent of each other, the filter can give the orbit and attitude estimation at the same time. The results of the numerical test show that a signal EKF can estimate both orbit and attitude by using magnetometer and gyro measurement only. The accuracy, usually is sufficient for low earth orbiting satellites.

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 present a two-stage approach for estimation of spacecraft’s position and velocity by indirect linear measurements from a single antenna.

In the first stage, direct nonlinear antenna measurements are transformed to linear x-y-z coordinate measurements of spacecraft’s position, and statistical characteristics of orbit determination errors are analyzed. Variances of orbit parameters’ errors are chosen as the accuracy criteria. In the second stage, the outputs of the first stage are improved by the designed Extended Kalman Filter for estimation of the spacecraft’s position and velocity on indirect linear x-y-z measurements.

The complex content of the measurement matrix in the conventional method causes periodic singularities in simulation results. In addition, the convergence of the filter using direct measurements is highly dependent on the initialization parameters’ values due to the nonlinear partial derivatives in the Jacobian measurement matrix. The comparison of the accuracy of both methods shows that the estimation by using indirect measurements reduces the absolute estimation errors. The simulation results show that the proposed two-stage procedure performs both with better estimation accuracy and better convergence characteristics. The method based on indirect measurements provides an unnoticeably short transient duration.

The proposed method can be recommended for satellite orbit estimation regarding its presented superiorities.

Inputting the single antenna measurements to the filter indirectly results in a quite simpler measurement matrix. As a result, the convergence of the filter is faster and estimation errors are lower.

This article presents the optimized design, analysis and calculation concerning the trajectory of a lunar polar probe. Firstly, the trajectory design principles and constraints are determined. The preliminary design and analysis of the circumlunar orbit, transfer orbit to the moon and earth parking orbit are carried out separately and some computations for the flight trajectory concept have been made too. To reduce the fuel needed for error in orbital maneuver efficiently and satisfy the requirements on the launch window, some detailed design and analysis for the rather advanced phasing earth‐moon transfer orbit are given here and also the strategy for optimum orbit correction.

Interstellar gas passing through the solar system may effect the interplanetary gas, planetary atmospheres and satellite orbits. Interaction of the interstellar and interplanetary gases is considered; a solar system corona may be formed.