In this paper, for an Low-Earth Orbit (LEO) satellite network with inter-satellite links, a routing optimization method is developed in the case of stochastic link failure. First, a discrete-time strategy is used for the satellite network to acquire several static topological graphs during a cycle. Based on the static topological graphs regarding stochastic link failure, a constraint model is established that constructs the task revenue, switching times and routing cost as indicators. Then, an improved Genetic Algorithm based on A* is proposed to optimize the topology under the constraint model. In particular, to reduce the cost of computation, a new generation strategy for the initial solution is presented which combines the roulette wheel operator and the A* algorithm. Finally, the effectiveness of the proposed method is illustrated by a group of numerical simulations for the network with stochastic link failure.

In this paper, for multi-spacecraft systems (MSSs) with a directed complete communication topology and a time-varying virtual leader, an adaptive saturated attitude controller is proposed to achieve attitude consensus and attitude tracking under arbitrary initial attitude, mixed attitude constraints, input saturation and external disturbances. Firstly, considering the time-varying desired attitude provided by the virtual leader in a directed complete topology, an MSS attitude error function and an MSS attitude error dynamics based on SO(3) are developed. Next, an effective mixed potential function for the MSS on SO(3) is proposed for the static attitude-forbidden zones, the relative dynamic attitude-forbidden zones and the attitude-mandatory zones. In particular, different from the existing potential functions, the proposed mixed potential function is suitable for arbitrary initial attitude of the spacecraft in MSS, relaxing the restriction on the initial attitude associated with each static and dynamic attitude constraint zones. Then, an adaptive saturated attitude controller is designed to realize attitude consensus and tracking for the MSSs on SO(3) under arbitrary initial attitude, mixed attitude constraints, saturation constraints and external disturbances. Finally, simulation results of an MSS with a time-varying virtual leader are demonstrated to illustrate the efficiency of the proposed attitude controller.

In this paper, the attitude reorientation problem for over-actuated rigid spacecraft subject to multiple attitude constrained zones is studied. Considering the pointing direction deviation of sensitive equipments and constraint operating set, a robust potential function for attitude constrained zones is proposed and is further leveraged to design a high-level attitude controller, which achieves asymptotic convergence of attitude reorientation error while avoiding attitude constrained zones. Moreover, to distribute the desired control torque from high-level controller to each actuator dynamically, a finite-time adaptive control allocation is developed, resulting in an improved allocation error convergence rate when compared with existing control allocation methods. Simulation examples involving a rest-to-rest attitude maneuver are given to demonstrate the effectiveness of the proposed overall control strategy.

Spacecraft formation flying (SFF) in highly elliptical orbit (HEO) has attracted a great deal of attention in many space exploration applications, while precise guidance, navigation, and control (GNC) technology—especially precise ranging—are the basis of success for such SFF missions. In this paper, we introduce a novel K-band microwave ranging (MWR) equipment for the on-orbit verification of submillimeter-level precise ranging technology in future HEO SFF missions. The ranging technique is a synchronous dual one-way ranging (DOWR) microwave phase accumulation system, which achieved a ranging accuracy of tens of microns in the laboratory environment. The detailed design and development process of the MWR equipment are provided, ranging error sources are analyzed, and relative orbit dynamic models for HEO formation scenes are given with real perturbations considered. Moreover, an adaptive Kalman filter algorithm is introduced for SFF relative navigation design, incorporating process noise uncertainty. The performance of SFF relative navigation while using MWR is tested in a hardware-in-the-loop (HIL) simulation system within a high-precision six degrees of freedom (6-DOF) moving platform. The final range estimation errors from MWR using the adaptive filter were less than 35 $\mathsf{\mu }$m and 8.5 $\mathsf{\mu }$m/s for range rate, demonstrating the promising accuracy for future HEO formation mission applications.