Visual navigation technology holds significant potential for applications involving unmanned aerial vehicles (UAVs). However, the inherent spectral limitations of optical-dependent navigation systems prove particularly inadequate for high-altitude long-endurance (HALE) UAV operations, as they are fundamentally constrained in maintaining reliable environment perception under conditions of fluctuating illumination and persistent cloud cover. To address this challenge, this paper introduces microwave vision to assist optical vision for environmental measurement and proposes a novel microwave vision-enhanced environmental perception method. In particular, the richness of perceived environmental information can be enhanced by SAR and optical image fusion processing in the case of sufficient light and clear weather. In order to simultaneously mitigate inherent SAR speckle noise and address existing fusion algorithms’ inadequate consideration of UAV navigation-specific environmental perception requirements, this paper designs a SAR Target-Augmented Fusion (STAF) algorithm based on the target detection of SAR images. On the basis of image preprocessing, this algorithm utilizes constant false alarm rate (CFAR) detection along with morphological operations to extract critical target information from SAR images. Subsequently, the intensity–hue–saturation (IHS) transform is employed to integrate this extracted information into the optical image. The experimental results show that the proposed microwave vision-enhanced environmental perception method effectively utilizes microwave vision to shape target information perception in the electromagnetic spectrum and enhance the information content of environmental measurement results. The unique information extracted by the STAF algorithm from SAR images can effectively enhance the optical images while retaining their main attributes. This method can effectively enhance the environmental measurement robustness and information acquisition ability of the visual navigation system.

The attitude tracking synchronization control of an orbit-predetermined leader–follower spacecraft swarm for the space moving target is discussed in this paper. The information exchange between all spacecraft is assumed to be discrete in time and on the undirected connected graph. Moreover, due to the demand for saving communication resources, wireless interference has been utilized, which allows all the neighbors of a spacecraft to access the same channel frequency spectrum simultaneously. Then the backstepping control algorithm is designed to let the spacecraft $\left(\beta ,\mathit{A}\right)$-practically stably synchronize their states and track a time-varying trajectory in the presence of unknown fading channels. Finally, simulation is provided to verify that using the proposed control scheme, the attitude tracking synchronization can be achieved with high precision.

This paper present a fault detection and isolation method for GNSS/SINS integrated navigation system based on MSS (Multiple Solution Separation) and PNN (Probability Neural Network). The method can also be well applied in the field of general aviation aircraft. Firstly the GNSS/SINS tightly integrated navigation system is designed. Based on the model, the principles and methods of MSS used for fault detection are deduced. Then the fault isolation method using PNN are analyzed too. Lastly, by establishing a simulation system, the analysis and availability for the method are verified.

Agile spacecraft with rapid rotational maneuverability still attracts considerable attentions due to the increasingly complex space missions. Input saturation and low energy consumption are taken into consideration in the design of the attitude agile maneuvering controller. This paper aims to address the above problems using a saturation backstepping based attitude controller for rapid rotational maneuver. The backstepping attitude controller is designed at first for the maneuvering only includes acceleration phase and deceleration phase. After considering input constraints of attitude angular velocity and control torque, the backstepping controller is modified into a two-layer cascade-saturation backstepping controller using saturation control method. The attitude angular velocity and the control torque constraints are satisfied respectively by designing the one-layer cascade-saturation based virtual control input and the control torque saturation function. The resulted maneuvering is divided into three phases: acceleration phase, coast phase and deceleration phase. In the coast phase, the energy cost for attitude maneuvering is reduced. Finally, simulations are carried out to verify the performance of the proposed controller. The maximum control torque and attitude angular velocity are constrained and the energy cost is greatly reduced with high control accuracy.