As a vast amount of data with respect to the moon and Mars is collected, exploration missions are shifting to the next step, the aim of which is a precise landing on a predetermined target. A promising technology for precision landing is terrain relative navigation (TRN), which collates landmarks detected from images and maps of landmarks. Crater detection is one of the essential technologies for TRN. A problem in detecting craters is the apparent change in craters due to illumination conditions. Another problem is the change in shape due to crater degradation. We propose a novel crater detection method based on combining a support vector machine (SVM) and a convolutional neural network (CNN) to make detection performance robust against apparent change. In the linear SVM, gradient images of a crater image dataset are learned. The learned classifier is then used to calculate the objectness score for region proposal. Next, the CNN identifies the image of the proposed region as to whether or not it is a crater. Our results show that the proposed method can detect craters in a wide range of illumination and shape conditions, and has better average precision than traditional crater detectors.

Hopping rovers have become a promising way of asteroid surface exploration. This paper focuses on the hopping trajectory design between two given surface points and discusses the irregular terrain's influence on the design process. By taking the hopping rover as a point mass, dynamical equations are derived based on the polyhedral method. The principle of hopping trajectory planning is summarized with the related solving algorithm. The initial velocity increments required to control the subsequent hopping trajectories are determined based on parabolic motion. The numerical simulations apply a triaxial ellipsoid to approximate comet 133P/Elst-Pizarro preliminarily. The smooth and rocky polyhedron models of the ellipsoid are constructed, respectively. With the two models, the different initial conditions' hopping trajectories are planned and compared to verify the proposed planning method and discuss the influence of terrain roughness on the trajectory design.

This paper presents an effective maximal-length sequence design for system identification of a continuous-time linear aircraft model. The maximum-length sequence is used as the exciting signal because it is a realistic signal for identifying the aircraft model. This paper proposes two design parameters for the maximum-length sequence, which are related to the dynamical modes of aircraft. According to the identification procedures using the proposed design parameters and the subspace identification method, a continuous-time linear aircraft model in longitudinal motion is well identified in a numerical simulation.

High thrust propulsion systems that can be used in small spacecraft are urgently needed to expand the use of small spacecraft. This study proposes a hybrid thruster for small spacecraft using wire-shaped magnesium as a fuel and water as an oxidizer. “Hybrid thruster” means that the in-space propulsion system generates thrust using a chemical reaction between a solid fuel and a vapor oxidizer, such as those utilized for hybrid rockets. Both magnesium and water are very safe, highly available, and very storable. To assess the feasibility of a hybrid thruster, we carried out experiments utilizing magnesium-wire combustion in water vapor at a pressure lower than the atmosphere, and estimated the input power for ignition, ignitability, and the average magnesium mass consumption rate. Then, propulsion performances were calculated using the experimental results, which show there is an input power of 2–3 W, with higher ignitability and a lower average mass consumption rate for thinner magnesium wires. The calculated specific impulse achieved its maximum at 323 s, with a mass mixture ratio of 1.25. At that mass mixture ratio, the calculated thrust using magnesium wires having diameters of 0.5 mm and 0.8 mm was 49.8 mN and 68.5 mN, respectively. Additionally, the applicability of the hybrid thruster was shown through a case study considering an existing deep-space misson.

In recent years, there has been a steady increase in the small satellite launch market. With the rapid development of novel launchers, for small satellite owners and operators, how to effectively and efficiently choose appropriate launch vehicles has become a major concern. Based on updated launch records, a reliable launch data source for multi-attribute evaluation and reclassification is established. Using a statistical classification process, active launch vehicles are classified into five representative-in-class launchers on the basis of their capabilities and performance. Unlike the previous categorisation based on payload ability, this method captures launch cost, technology maturity, reliability and availability of each category within the current launch vehicles in service. Moreover, representatives are selected as the baseline types for the high-level planning and designing of complex small satellite launch missions. The analysis indicates that this study provides a valid statistical classification and selection strategy of representative-in-class launch vehicles to support decision-making for rapid assessment on a large number of small satellite launch missions.