Abstract For near-Earth spacecraft, many environmental forces are utilized to unload reaction wheels. However, effects like magnetic force or atmospheric friction hardly exist in deep-space environments where solar sails operate. Thus, this paper proposes an unloading method that uses reflectivity control devices to generate Solar Radiation Pressure (SRP) torque to conduct the unloading process of solar sails operating in deep space. Firstly, the basic principles of the Reflectivity Control Device (RCD), satellite kinetic model, and Pulse Width Pulse Frequency (PWPF) modulator are given. Secondly, based on the torque envelope obtained by traversing all switch combinations of RCD, a novel strategy using a PWPF modulator is specially designed to achieve efficient unloading. In the end, we carry out numerical simulations and analyze the influence of different parameters, through which the validity of the proposed torque resolution scheme is demonstrated.
Compared with the traditional anomaly detection methods, machine learning algorithms do not rely on manual and have the ability to extract advanced features of data. However, anomaly detection of spacecraft telemetry data by supervised machine learning is a challenging problem due to the lack of priori knowledge. This paper presents a signal anomaly detection algorithm based on attention mechanism. First, the long-distance characteristics of spacecraft telemetry data are captured by attention mechanism. Then, the stacked autoencoder compresses the data dimension and reconstructs the input signal to obtain the error reconstruction sequences. Furthermore, the anomaly indexes of the error reconstruction sequences are marked by the window threshold method to realize the anomaly detection of the spacecraft telemetry signal. Finally, the effectiveness of the algorithm is verified by a group of examples based on multi-channel spacecraft telemetry signals.
In view of the need to keep secret the transmitted control commands and the coordinates of unmanned aerial vehicles（UAVs） when they are used for reconnaissance or fire attack, a new physical layer encryption method is proposed in this paper. By considering that UAVs and ground stations have a pair of finite dimensional predictive bidirectional channel vectors（ERCVs）, the continuous encryption function（CEF） is used firstly in this method. The two ERCVs of UAVS and ground stations are converted into two quasi-continuous pseudo-random number sequences（QCPRNs） of arbitrary dimensions, and then the QCPRNs are further converted into two uniformly distributed（UD） QCPRNs sequences, and the UD-QCPRNs are superimposed on the information transmitted by UAVS in a modular manner. UD-QCPRNs is generated at the ground station to complete the decryption on the ground, and the information and coordinates are hidden for the safe ground communication of the UAV. The results of simulations show that the proposed method can counter any possible detection methods of the attacker and is suitable for the safe flight of UAV or the completion of war tasks.
The limitations of common unloading methods is analyzed such as water flotation, suspension and air floating, and a magnetic unloading mechanism is designed. A radial parallel dual structure is applied to the new mechanism which overcomes the difficulty of requiring external cooling equipment when the large bearing mechanism is suspended. The use of double-sided and seamless splicing permanent magnets realizes the consistency of magnetic field strength in space work and reduces the introduction of interference force; At the same time, the non-magnetic and non-conductive non-metallic coil winding is selected, and there is no additional hysteresis resistance and damping torque, and the requirement of zero gravity unloading is realized. The result of application test shows that the unloading mechanism meets the requirements of ground research and verification of space magnetic levitation rotary platform.
The research of air-breathing high speed aircraft is focused. Aiming at the high speed aircraft in the flight process of the great uncertainty and stamping engine dynamic pressure control method based on backstepping sliding mode is proposed to solve the problem of strict constraint on dynamic pressure during operation.Firstly,the precise linearization of the dynamics model of high speed aircraft is implemented,then based on the exact linearization model,the backstepping sliding mode controller is designed and the stability of the closed-loop system is proved by Lyapunov stability theory.Finally,the simulation verified that the proposed control method can accurately track the flight pressure in the case of large disturbance and large uncertainty and the stable operation of the ramjet is ensured.
