Aiming at the problem that multiple performance indicators need to be considered comprehensively for the trajectory planning of the future lunar surface landing power descent，this paper proposes a multi objective trajectory planning method that optimizes first and decides later. First, the multiple metrics of trajectory planning are decomposed under the framework of MOEA/D-AWA (multi objective evolutionary algorithm based on decomposition with adaptive weight adjustment) to obtain several single indicator sub-problems. After that, the convex optimization algorithm is designed as the underlying algorithm for solving the single objective sub-problems. After iterative optimization, a set of powered descent segment flight trajectories can be obtained, which constitutes the Pareto optimal solution set. Finally, according to the fuzzy decision theory, the multiple trajectory indicators corresponding to each Pareto optimal solution are gradually downgraded and evaluated comprehensively, and the flight trajectory under multi-indicator constraint is obtained after the decision. The simulation results show that the trajectory planning method can optimize a set of power descent trajectories under the integrated multi objective situation, and can decide the optimal power descent trajectories from them according to different mission requirements, which can effectively solve the multi objective trajectory planning problem of the lunar vehicle.

In order to solve the problem of space avoidance of GEO service satellites, a space avoidance strategy for GEO satellites based on collision probability optimization is proposed. The stationkeeping model under pulse thrust control is established, and then the assumptions and calculation principles of the collision probability are explained, and then the original collision probability calculation method is improved for GEO satellites, and a collision probability calculation method considering the velocity error is proposed. With the pulse velocity as variable, the minimum impulse and collision probability as optimization objectives, NSGAⅡ based multi-objective optimization is carried out to obtain the Pareto optimal solution for the problem with high collision probability. Considering the service requirements of GEO satellites, the space avoidance strategies that meet the accuracy of the GEO satellites are obtained, and the effectiveness of the space avoidance strategies is verified by simulation, and the research results can provide a reference for the space avoidance methods under the condition that the on-orbit service satellites meet the requirements of the stationkeeping.

A hybrid coding differential evolution algorithm (HCDE) is proposed to satisfy the revisit period requirements of agile imaging constellation observation targets. Firstly, the working characteristics of the agile imaging satellite are analyzed, the objective function for evaluating the satisfaction of the revisit period requirements is constructed, and the imaging task constraint satisfaction model is established. Then, based on the optimization requirements for the execution, sequence, and imaging time of observation tasks, a binary real hybrid encoding differential evolution algorithm is proposed to optimize the distribution of imaging tasks on the time axis. Finally, the simulation results show that compared with the genetic algorithm based on binary coding, this algorithm has significant advantages in convergence speed and optimization effect.

When using depth data for translation registration, the iTOF (inderct time of flight) cameras have a problem of spatially nonuniform illumination, which can lead to a relatively large measurement depth error in the peripheral area of the plane, thereby affecting the accuracy of subsequent depth registration. In order to solve the mismatch caused by this problem, a masked frequency domain NCC (normalized cross correlation) depth registration method is proposed. Firstly, the gray image of the same frame as the depth map to be registered is masked in the nonuniform areas. Then, the frequency domain NCC method is used for the gray image registration. Finally, the translation vector obtained from registration is overlaid on the corresponding depth images to complete depth registration. This method can effectively solve the mismatch problem caused by spatially nonuniform illumination within a scaling range of 4%. The relative error of pixels in the horizontal direction can reach 1.97%, and the relative error of pixels in the vertical direction can reach 1.74%. The error follows a normal distribution, proving that this registration method has stability and reliability.

The operating environment of space robotic arms is time-varying and uncertain, and there exists the risk of damage caused by excessive contact force, which poses a challenge to the compliance of robotic arm operation. Firstly, in order to solve the problem that constant admittance control relies on accurate estimation to realize force tracking in the time-varying uncertain contact environment, an adaptive variable admittance control is researched for 6DOF robotic arm in this paper. Secondly, in order to solve the problem of excessive overshoot of adaptive variable admittance control, a fuzzy system for compensating the parameters of the adaptive strategy is designed and an adaptive fuzzy variable admittance control method is proposed. Based on three types of time-varying environments, the simulations are carried out to verify the effectiveness of the adaptive fuzzy variable admittance control algorithm via Matlab/Simulink. The simulation results show that the proposed adaptive fuzzy variable admittance coutrol has better comprehensive effects of force tracking and over shoot suppression in time-varying contact environments.

This paper introduces a method for updating the pointing error model of the laser inter-satellite link dynamics in low-orbit satellites, addressing the challenges posed by uncertainty factors. In engineering applications, the construction of laser links is inherently influenced by a range of uncertainties, leading to inaccuracies in estimating the pointing area during the scanning process. This, in turn, compromises the precision of inter-satellite laser link establishment. Therefore, it is imperative to consider multiple uncertainties in rectifying the dynamic pointing error model of low-orbit laser interstellar links, laying the groundwork for subsequent scanning and capture procedures. The paper begins by delineating the laser interstellar link system and its associated uncertain parameters, subsequently establishing a system dynamics model. Following this, a sensitivity analysis is conducted on these uncertain parameters, leveraging sensitivity indicators to establish a surrogate model of the original system dynamics using the Kriging method. The prediction accuracy of this model is then thoroughly verified. Subsequently, uncertainty quantification indicators are determined, and Bayesian stochastic model updating techniques are employed to refine the uncertain parameters of the system dynamics model. Finally, the effectiveness and feasibility of this dynamic model correction method for addressing pointing errors in inter-satellite links under uncertainty are demonstrated through numerical simulations.

Tracking position correction of exterior trajectory measurement data plays a key role in high accurate trajectory acquisition for aircraft fight experiment. A new method for tracking position correction using telemetry attitude data and rough trajectory parameters of aircraft is proposed in this paper. The transformation relationship of trajectory parameters between the platform center of inertial navigation and the tracking position is obtained by utilizing telemetry attitude data, and the difference numerical value of distance measurement, radial velocity, azimuth and elevation between the platform center of inertial navigation and the tracking position are calculated via rough trajectory parameters. Then the precise calculation for correction quantity of tracking position is achieved. The precision of tracking position correction under the influence of the rough trajectory errors is theoretically analyzed by using the method of errors propagation. Then the validity of this correction method in practical applications is verified. Both simulation experiment and field test are further given to demonstrate the precision of correction. Experimental results show that the calculation errors of tracking position correction are much less than the precision target of exterior trajectory measurement system. It is indicated that the proposed method has significant application value in practice.

Precise segmentation of satellite components is key to RPO (rendezvous and proximity operations) and OOS (on orbit servicing), while harsh space environment and compact layout of components hinder fine grained pixel wise recognition. An edge auxiliary supervised components segmentation network (EASCSN) is proposed to tackle these problems. First, a two branch encoder is designed where pyramidal spatial features and global semantic features are fused with gated semantic injection module in a cascade manner. Second, a slim but strong decoder with convolution free feature aggregation module is elaborately designed so that high quality parts of multi-scale features are distilled and aggregated. Meanwhile, an auxiliary edge supervised strategy is adopted during training for sharper prediction in the edge regions. Massive experiments demonstrate the superiority of the proposed EASCSN. With compact model size and low computation cost, EASCSN can achieve a new state of the art speed accuracy tradeoff. Specifically, on a single Tesla T4 GPU, EASCSN yields 74.74% mIoU and 80.99% mAcc at 43.29 FPS on UESD test set. Efficient satellite components recognization helps perceive structure of target satellites and achieve space intelligent control. There is potential value of being further deployed to spaceborne platforms.

In response to the high computational complexity and model intricacy of deep neural network object detection algorithms, as well as the substantial demand for computational power on hardware platforms, a hardware specific accelerator based on Field Programmable Gate Array (FPGA) chips is designed. Employing a collaborative approach between software and hardware, an on chip architecture with high parallelism and deep pipelining is devised. Additionally, the techniques such as model quantization and structural optimization are utilized to optimize the neural network model. Deploying the object detection algorithm of neural networks within the designed accelerator system achieves high data throughput and low power consumption for FPGA based neural network computation, with model precision loss below 1.2%. This provides an effective solution for deploying deep neural network object detection algorithms on low power embedded platforms and can be widely applied in airborne and spaceborne intelligent computing devices

With the development of space technology, the transformation of spaceborne operating system from a closed system with a single task type to an open system with mixed sets of tasks increases the difficulty of predictability and uncertainty of system. The existing table-based scheduling strategy is no longer applicable and can’t solve the schedulability analysis problem of mixed sets of tasks in this scenario. At the same time, this method can’t support the dynamic loading of new tasks during system operation, hindering the intelligent and diversified development of onboard operating systems. In response to this issue, this paper, aiming to ensure the real-time requirements and scalability of spacecraft functions, proposes a two-level admission control strategy based on task’s critical level. The real-time characteristics of tasks are described through model establishment, and the maximum interference generated by tasks with higher priority is comprehensively analyzed. Then, schedulability determination methods based on Interference Bound Function and Response Time Analysis are proposed. Experimental results show that compared to the existing algorithm, our method greatly reduces the cost of computing interference from tasks with higher priority; By tracking the runtime information of tasks, both schedulability determination methods improve real-time performance of algorithms and increase processor utilization, hence providing a theoretical basis for solving the admission control problem of aperiodic tasks in spacecraft systems.

In ultrasonic aided electrospray thrusters, liquid films are destabilized and broken up under the effect of acoustic vibration and electrostatic field, then droplets emitted and thrust produced. In order to reveal the physical mechanism of initial instability of liquid films in ultrasonic aided electrospray thrusters, the linear instability of liquid films under the coupling effect of ultrasonic and electric field force is studied theoretically. Based on the Floquet theory, the linear instability of the planar liquid film under the coupling effect of acoustic vibration and electrostatic field is analyzed, and the dispersion relationship among the rate of disturbance growth, frequency and wavenumber is solved. According to the dispersion curves, the influence of electrical, oscillation and physical parameters on the linear instability is obtained. The results show that the effect of the liquid conductivity and dielectric constant on the instability can change with the ratio of the plate spacing to the liquid film thickness. When the growth rate of the parameter unstable region is large, the increase of the electric field force will promote the instability, and when the growth rate of the parameter unstable region is small, the increase of the electric field force will restrain the instability.

In view of the current situation that the design of the magnetic circuit of Hall thrusters mainly relies on manual adjustment by designers′ experience, this paper establishes an efficient and high quality magnetic circuit optimization design method to solve the problem of low efficiency in adjusting individual magnetic circuit sizes in a step by step manner, which cannot meet the increasingly refined magnetic field requirements. Through extensive research on flight verified thrusters, the description method and range of magnetic field parameters are clarified, and the magnetic field criteria for Hall thruster design are refined. Based on this, size optimization based on finite element method is adopted, embedding the magnetic field requirements into the constraints of magnetic circuit optimization. Finally, the magnetic circuit design is completed under the automatic search and optimization of multiobjective optimization algorithm. A typical magnetic circuit structure form with double magnetic shields is selected as the initial magnetic circuit, and a 1.35kW level thruster is used for verification. The results show that the optimized magnetic circuit quality is reduced by 34.9%, and the excitation power is reduced by 5.6%. The magnetic field symmetry is significantly improved. Meanwhile, the maximum magnetic field intensity is increased by 8.3%, and the magnetic field gradient is increased by 6.4%. The size based optimization magnetic circuit design method proposed in this paper is suitable for Hall thrusters of various power levels, allowing the magnetic field requirement parameters to vary over a wide range and supporting the simultaneous adjustment of tens of key dimensions, optimizing the magnetic circuit to better meet the magnetic field design requirements.