Signal and Information Processing, Networking and Computers

With the explosive growth of data traffic flow, mobile edge computing (MEC) has been suggested as an advancement of conventional cloud computing. However, as the spread of emerging applications and the requirement for quality of service (QoS) increases, the performance of the edge network has been an important issue. In order to provide better service, in this paper, we focus on the queuing problem in a single edge server and propose a scheduling algorithm in which tasks are placed in the different queues and the higher priority is given to the delay-sensitive task. Besides, we derive the theoretical formulation for the service curve under this algorithm with network calculus, and then derive the delay bounds. Finally, the numerical results are presented to show that the delay is significant reduced in our proposed algorithm compared with the existing algorithms.

Pathfinding algorithm play a crucial role in the field of mobile robots. Among various algorithms, RRT* stands out as a representative sample-based approach that is increasingly utilized in complex environments due to its computational efficiency and minimal reliance on obstacle map information. However, the key to RRT*’s effectiveness lies in its convergence rate, given its asymptotic optimality. To address this challenge, this paper presents a novel Variable Step Size (VSS) strategy based on RRT*. The VSS strategy dynamically adjusts the expansion step size based on both the direction of the vertex and the goal point in the random tree, aiming to reach the goal point more rapidly. Since various variants of RRT* already involve extended steps, the VSS strategy exhibits excellent applicability in practice. Furthermore, VSS significantly enhances the likelihood of connecting the random tree to the goal point, facilitating faster identification of the initial path to initiate the optimization phase. Leveraging the optimization characteristics of VSS, when combined with the optimization methods employed in different variants of RRT*, the convergence rate of the algorithm can be further accelerated. In the simulation results, VSS combines well with the RRT*, RRT*-Connect, Informed- RRT*, Improved- RRT* and RRT*-Smart, not only reducing the number of iterations of the initial path, but also speeding up the convergence.

For the task scheduling problem in edge computing scenarios, whale optimization algorithm (WOA) can be used to solve this non-deterministic polynomial situation (NP-hard). However, WOA is prone to local extreme values and slow convergence speed. To address these issues, we developed an innovative algorithm incorporating adaptive weights, Levy flight strategies, and Gaussian variation to improve the whale optimization algorithm’s global search capacity and convergence speed, ultimately helping to reduce delays and energy consumption in edge computing task scheduling. We applied the new algorithm to solve edge computing task scheduling problems using Matlab, simulating varying numbers of edge nodes and tasks. Subsequently, we compared our algorithm with four benchmark algorithms, including the original whale algorithm and other improved versions. The results demonstrate that our algorithm outperforms others in relation to optimization delay, energy consumption, and overall efficacy, demonstrating its efficacy in addressing the edge computing task scheduling problem.

Objective: Based on a variety of machine learning algorithms, screen the hyperactivity syndrome e elements of liver yang syndrome. Methods: Using the classification of hyperactivity of liver yang syndrome standards and searching for relevant standards of hyperactivity of liver yang syndrome, The study constructed a matrix data set containing the syndrome elements of hyperactivity of liver yang syndrome and screened out key syndrome elements with the help of three machine learning algorithms, including XGBoost, SVM, and RF. Based on the results of the expert questionnaire, the key syndrome elements of liver yang syndrome are derived. Results: A total of 10 key elements were screened out through 3 machine learning algorithms. Combined with the results of multi region, multi field and multi-level research, the core syndrome elements of irritability, soreness and softness of the waist and knees, stringy pulse and red tongue were obtained. Conclusion: There is still a need to expand clinical samples and continuously optimize the diagnosis model of hyperactivity of liver-Yang syndrome based on expert opinions because of this study, as it provides a data base for the digitalization and objectification of TCM syndrome differentiation.

In this paper, an autonomous positioning method for user terminals based on false TDOA reports is proposed. In the cellular network, the user terminal calculates its own position directly by falsely reporting TDOA measurements to the BS without calculating the BS position, which simplifies the positioning process in the back calculation BS position-based autonomous positioning method and reduces the computing process of the user terminal.

With the rise of ChatGPT and its applications in education, the world has entered a new era where human intelligence and artificial intelligence engage in collaborative development and coexistence in education. Therefore, it’s essential to reshape the opportunities and challenges in higher education brought by artificial intelligence technology. Firstly, this paper redefines the coupling connotation between higher education and artificial intelligence from the perspective of organizational ecology theory which forms an ecosystem diagram of the symbiotic relationship between them. Secondly, it analyzes the dilemmas which emerge from this symbiotic system, such aspects as technology, education, supervision, security, and human resources. Finally, according to the application scenario of the organizational ecology principle, the practice element strategy is summarized from the coupling framework model of college education and artificial intelligence, and the application of accounting education + Chatgpt scenario is taken as an example for practice application.

In an educational ecology of information explosion, critical thinking becomes an important quality of students to adapt to the future society that schools should educate. But in reality, there is a conflict between the requirements for college entrance education and developmental thinking. To address the difficulty in implementing the development of critical thinking in teaching practice, this paper proposes a method that analysis of process errors on student tests. The approach is to trace the causes and explore solutions through self-reflection and discussion. The specific process includes testing students, collecting error information, student self-reflection, and group discussion. Subsequently, students with incorrect and correct answers are selected for open discussion and analysis in the classroom, culminating in an evaluation of their thinking development and subject accumulation. The analysis of process errors method has a positive effect on students’ expression, thinking, and inference skills, and can be effective in developing critical thinking in teaching.

The explosive growth of Internet data traffic, driven by various resource-intensive and delay-sensitive smart applications supported by 5G communication networks, has posed higher requirements on latency and Quality of Service (QoS). Therefore, the decision-making of data offloading in the new type of core network has become an urgent problem. To address the stochastic optimization problem of data offloading and resource scheduling between terminals and MEC servers, this paper takes into account the randomness of terminal data generation process and dynamics of wireless channels, and constructs a stochastic optimization model for data offloading to meet user QoS requirements. This paper uses Lyapunov optimization theory and Convex optimization method to decompose the random optimization problem into three sub problems for solution, and proposes a MEC data offloading for UPF sinking of 5G core network algorithm (MOUS). Experimental results demonstrate that the MOUS algorithm effectively reduces data offloading and network scheduling costs, significantly improving the performance of the existing network.

Some parts of the emitted lights are scattered and reflected into the focal plane arrays (FPA) in one optical terminal by suspended particles in the outside wireless channel. The reflected lights are the interference sources for the signal detection and make its performance much lower. These interference lights also make the centrioding of light spots in the FPA inaccurate. In this paper, a recursive algorithm based on integrated control and adaptive filtering (ICAF) is proposed for the FPA signal detection. The ICAF method can reduce the noises in the received optical signal, and improve the detection performance effectively. The integrated control and adaptive filtering algorithm is simulated and validated in this paper.

Data fusion and integration is an important subject for coal enterprises to develop and utilize coalbed gas. In the current situation of the shortage of coalbed gas database resources and analysis tools in China’s coal mine areas, how to mine valuable information from massive data, and then promote the development and utilization and rational layout, has become an urgent problem to be solved. Aiming at the shortcomings of traditional data collection, analysis and management mode, based on the principle of collaborative computing and distributed storage of big data technology, and according to the business needs of coalbed gas development and utilization in coal mine areas, this paper establishes a big data analysis and management platform construction scheme for coalbed gas, and makes preliminary exploration in actual projects. The typical application direction of CBM big data platform is given, which lays a foundation for the informatization, digitization and systematic development of coalbed gas.

In China, cable TV, Internet protocol television (IPTV) and over the top TV (OTT TV) are the three main ways for users to watch TV. In recent years, with the development of Internet and TV technology, more and more users choose the convenient OTT TV. OTT TV will overtake IPTV as the most popular TV for users. In order to better improve IPTV user watching experience, the group issued 1395 questionnaires and tested 186 IPTV set-top boxes, analyzed that the main reason for poor IPTV user experience is the long start-up time. Finally, we made several suggestions, expecting to find new user growth points for IPTV and improve IPTV user experience in the future.

As a key enabling technology for implementing the concept of intelligent manufacturing, digital twin can reflect the entire life cycle process of physical entities and effectively solve the information-physical fusion problem in intelligent manufacturing. It has been widely applied in multiple fields such as product design, manufacturing, visualization monitoring, and intelligent operation and maintenance. However, currently there is a lack of research on the cross-application of digital twin and modular production systems (MPS systems), which cannot meet the needs of intelligent development of MPS systems. This article completes the mutual mapping of physical and virtual models through the collaborative operation of the electromechanical integration concept design function and control program in Siemens NX UG software. The verification of the MPS system and the construction of the digital twin system have been achieved, which aims to reduce costs and increase efficiency in the design and operation of the MPS production system. This article provides a complete design process and solution for an MPS intelligent control system based on digital twins, which can serve as a reference for future MPS intelligent control system designs.

In the current era, the expansion of subterranean parking facilities has been notable, accompanied by the consequential issue of prolonged time expenditure in locating parked vehicles. This situation pertains to what can be termed as reverse vehicle discovery. Distinguishing itself from outdoor positioning, indoor localization presents a more intricate set of impediments attributed to diminished signal reception quality of satellite-based positioning signals, compounded by the scarcity of communication base stations in such enclosed environments. In light of these challenges, this research introduces an innovative methodology for establishing a node map within the Internet of Vehicles (IoV) framework. This proposed approach involves the utilization of communication delay metrics amongst stationary subterranean vehicles, whereby the communication delays are treated as indicative of relative distances. Subsequently, a comprehensive node distribution map is formulated, drawing upon the derived distance matrix. Rigorous simulation experiments are conducted to validate the efficacy of the devised algorithms. The outcomes of these empirical assessments lend credence to the potential utility of the proposed techniques as foundational components for enhancing navigation systems within indoor vehicular environments.

With the advent of the information era, big data technology nowadays has become an important area in the technology research. It is gradually applied into various fields of people’s daily life. This article is concerned about big data technology by introducing its background, describing its development from domestic and international aspects, analyzing five basic processes (data collecting, data pre-processing, data storage, data processing, data visualization), illustrating its appliance on the artificial intelligence and data privacy security area and finally looking into the opportunities and challenges of the future development of big data technology.

This paper presents a signal processing flow based on the time-domain pulse compression algorithm, consisting of three parts: theoretical introduction, MATLAB simulation, and FPGA verification. First, after simulating the echo signal, the time-domain waveform and parameters of the matched filter coefficients are saved during MATLAB simulation. Then, VIVADO uses the ROM core to read the file and the DDS core to generate the local oscillator signal required for down-conversion. Once down-conversion is done, passes the two signals through low-pass filters separately, and finally performs time-domain pulse compression and modulus calculation. In terms of this paper, replacing most of the self-programming with instantiated IP cores has the advantages of greatly simplifying the code and improving the maintainability of the flow. Moreover, implementing pulse compression with time-domain methods has advantages over frequency-domain methods, such as reducing compilation time and saving resource consumption. Results of simulation and test represent that the signal processing flow based on the time-domain pulse compression algorithm is consistent with theoretical expectations and is suitable for processing echo signals with relatively low intermediate frequency.

This paper presents two kinds of bias circuit structures, including multisegmented reference current bias network based on current mirror control, and multisegmented reference current bias network based on hysteresis comparator and multiplexer selector control. Both of them are composed of PTAT current sources, CTAT current sources and other control circuits to accomplish proportional control, current segmentation and current superposition. This method can flexibly compensate for temperature changes of various complex types of RF amplifiers. Designed in SMIC 0.18 μm CMOS technology, simulation results show that the proposed CMOS temperature compensating bias circuit can effectively compensate cascode RF amplifier. The gain change rate of the cascode structure amplifier decreases to 1.37% over the temperature range from 20 ℃ to 85 ℃.

With the development of economy and science and technology, artificial intelligence has been widely used in various fields, which has greatly changed the existing production and life style. However, in the field of rural revitalization in China, the participation degree of artificial intelligence is significantly weaker. Through the method of artificial intelligence, this paper establishes a SWOT management model for rural revitalization. By analyzing the current advantages, disadvantages, opportunities and threats in the field of rural revitalization in China, it systematically analyzes the leverage effect and problem of the application of artificial intelligence in rural development, and finally puts forward corresponding development countermeasures according to the actual situation in China.

Wastewater treatment and its quality prediction have always been pivotal for environmental protection and public health. Accurate forecasting of wastewater quality parameters is essential for optimizing treatment processes and ensuring water safety. In light of this, our study proposes a hybrid model integrating Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Convolutional Neural Network-Long Short-Term Memory (Conv1D-LSTM) for wastewater quality prediction. DBSCAN enables anomaly detection in the influent data, reducing noise impact. The Conv1D-LSTM model automatically extracts features and captures time series dependencies. Experiments demonstrate superior performance of the proposed model over LSTM alone in both single-step and multi-step forecasting of ammonia nitrogen levels, with lower RMSE, MAE and RMSLE. The integration of DBSCAN and Conv1D-LSTM can effectively leverage their respective strengths for enhanced wastewater quality prediction. Further research will focus on multi-variable prediction and incorporating data smoothing techniques.

Under the guidance of curriculum ideology and politics, the goal of specialty construction is to cultivate outstanding talents who possess both specialty competence and political awareness among students. This process involves integrating the Party’s theories with specialty knowledge, establishing courses on ideological and political education, enhancing the quality of the teaching staff, strengthening curriculum design, guiding students to engage in social practices, and continuously assessing and improving. Through these measures, specialty development aims to nurture students with a strong sense of party ideology, social responsibility, and specialty innovation consciousness, making a positive contribution to the development of the country and society.

In this paper, the attitude control problem of a class of micro-nano satellites in low Earth orbit without solar array driving mechanism is studied. Firstly, based on the attitude dynamics, a three-axis decoupled attitude control law is proposed so that each channel can be designed independently. Then, various constraints in satellite attitude design during on-orbit standby were analyzed. Under the constraints of energy security, a satellite attitude maneuver was proposed to ensure the sun orientation of the solar array. During the design process, multiple constraints such as attitude reference guarantee and thermal control condition guarantee were introduced. For different orbital characteristics, methods were proposed to determine the orientation attitude towards the sun by combining the geocentric vector, orbital normal vector, and solar vector, as well as the on-orbit standby control strategy of sun orientation in the sun light area with earth orientation in the shadow area. Then the optimal maneuver strategy and angular velocity planning method was proposed in the aspect of large angle attitude maneuver, which makes the attitude control of satellites safe and stable during on-orbit standby. The mathematical simulation results show that the scheme proposed in this paper is applicable to low Earth orbit micro-nano satellites with various inclinations, which verifies the effectiveness of the method proposed in this paper.

The fire detection system is a new kind of space borne intelligent fire detection and alarm system. In order to ensure the safety, high efficiency, stable operation system in orbit, this paper proposes a multi-level information flow design. This paper considers five aspects, including the basic function, the in-orbit application, sensor calibration, on-orbit maintenance and in-orbit security. Respectively, it puts forward the basic function design, the system application design, the calibration design, on-orbit maintenance design and on-orbit security design. The design of this article has certain innovation and practicality, greatly improving the intelligence and autonomy level of the sensor, and has strong promotional significance.

To solve the problem of hypersonic vehicle trajectory planning in cruise stage, this paper proposes a trajectory planning algorithm based on a hybrid PSO algorithm. Based on PSO algorithm, a crossover operator from the genetic algorithm is introduced to further improve the searching ability of PSO algorithm in complex solution space. To solve the problem of swarm intelligence optimal algorithms being trapped into local optimization, the clustering behavior of the artificial fish swarm algorithm is used to prevent the PSO algorithm from falling into local optima. Moreover, to address sudden threats during cruise stage, an online trajectory planning algorithm is designed to solve the online trajectory planning problem when sudden threats occur. Simulation results demonstrate that the hybrid PSO algorithm is better than traditional PSO algorithm, and the planned route is the most smoothly compared with other algorithms. Besides the online trajectory planning algorithm is proved validity dealing with sudden threats.

X-ray pulsar navigation (XPNAV), as a new autonomous navigation method, has been widely used in deep space exploration. XPNAV requires a certain filtering time, and the length of filtering time will affect the final navigation accuracy. At the same time, orbital altitude and pulsar selection are also important factors affecting navigation accuracy. Based on the XPNAV theory and the traditional three-pulsar navigation method, this paper uses UKF algorithm and STK software to analyze the influence of different pulsar combinations, orbit heights and observation steps on navigation accuracy for nonlinear systems, and gives the optimal observation time and navigation accuracy under different conditions. The simulation results show that with the increase of orbit altitude, the observation step size increases, and the navigation accuracy increases gradually. In this paper, when the pulsar combination is B0531 + 21, B1821–24 and B1937 + 21, achieves the highest navigation accuracy on the high orbit, where the position error is 739 m and the velocity error is 0.1906m/s. The simulation results provide a theoretical basis for determining navigation accuracy, orbit selection and observation time parameters in the application of Earth-orbiting pulsar navigation.

On the basis of establishing a parameter system, this article determines an independent indicator synthesis method based on the engineering properties and characteristics of each parameter in the special system for the final results. That is, a special calculation way of combining the indicator values of each level of parameter into the indicator values of the previous level.For this moment, Analytic Hierarchy Process is a good way to solve the problem. And Fuzzy Comprehensive Evaluation Method is also used for the answer. Because of the above reasons, the special comprehensive safety evaluation model for satellite assembly operations is established. The model includes a weight calculation method for evaluation factors, providing specific technical support and tools for the comprehensive safety judgment of satellite assembly operations. Next, develop principles for protection plans, classify and rank them, and propose general requirements for risk control measures. Through application, it can be proven that the proposed satellite assembly safety evaluation method and model are reasonable and feasible, and can be promoted.

During the process of establishing airborne optical links traditionally, the scanning of field of uncertain (FOU) is very important and its performance cannot be improved easily because of the limitation of the range and bandwidth of pointing mechanisms. The technology of optical phased arrays (OPAs) can make a fast scanning, but it is not practical because of its low efficiency, narrow range and high cost. With the development of laser array technologies, the laser array with low cost and high beam quality is available, which provides an opportunity for the enhancement of scanning performance. A novel design of multiple-beam scanning for optical terminals is presented in this paper, which can improve scanning performance dramatically. With this special and innovative design, optical terminals can implement a fast scanning by taking advantage of the high bandwidth of the fine pointing assembly (FPA) and the bandwidth-limited characteristics of the vibration for the satellite platform. The improvement in scanning performance is verified by the simulation and testing of this system design.

A systematic approach to quality management has been accumulated in aerospace industry, and also a large amount of quality data has also been accumulated, making it possible to mine the potential value of aerospace quality big data. In this paper, we investigate the application of vast amounts of data in process monitoring, quality prediction, and product process optimization. About Aerospace products quality control, this paper proposes scenarios for applications ranging from the collection and storage of quality data to what can be applied in real-time decision making such as traceability analysis, and what can be used to prevent quality risks through data statistical analysis and related business experience analysis. Finally, taking a flywheel product as an example, the data envelope analysis method is successfully applied to analyze and apply the test data of the product, and it is proposed that knowledge precipitation can promote continuous quality improvement. This paper provides some ideas on how to complete big quality data collection, integration and ways to mine the value of aerospace quality data.

The ultra-high accuracy indoor and outdoor positioning is fundamental for a variety of applications such as industrial automation, Internet of Things and structure monitoring. Approaches based on optical methods, ultrasound and computer vision are often suffer from limited coverage areas, obstruction by objects and high computing load. While the GNSS and canonical radar-like radio frequency (RF) methods are suffered from insufficient accuracy and are not feasible for many scenarios. Now we achieve an inverse GPS microwave positioning system based on ultra-stable frequency synchronization in free space and carrier phase difference principle to surpass the limitation of current methods. The stability of frequency synchronization link is better than 10−13/s. The distance resolution retrieved from phase information is 25 µm and the Mean Squared Error (MSE) of three-dimensional positioning is 16 µm. An ultra-high accuracy positioning system with large coverage area, compatibility and versatility can potentially be achieved gearing to extensive needs..

To realize rapid batch development target of small satellites industrialization, the first problem that to be solved is how to realize the automatic real-time monitoring interpretation of working states for small satellites. Traditional means of data automatic monitoring interpretation lack real-time monitoring ability for time-varying parameters, while artificial intelligence algorithm doesn’t support the practical engineering application for small satellites at present. Taking load current which is a classic time-varying parameter as an example for the problems above, this paper firstly carefully studies the influence factors and correlation interpretation demand of load current. Secondly, it analyzes the difficulties of automatic interpretation for load current. Finally, this paper based on the difficulties above expounds the overall design idea and the concrete realization methods of multi-parameters real-time fusion interpretation method, and the operation flow and interpretation logic of key links in this method are explained in detail. The method described in this paper has experienced engineering application verification of mass production of many small satellites, and can effectively realize the automatic monitoring target of load current.

A proper yaw control mode is very important for an inclined-orbit satellite because of the complexity of the energy and thermal control, which is caused by the large range of the sun elevation angle variation. To get an accurate sun-pointing of solar panels, the ideal yaw attitude planning for sun-tracking is analyzed first. To avoid the excessive ideal yaw angular velocity, which is unavoidable for the ideal yaw attitude planning when the sun elevation angle nears to zero, a sinusoidal model for yaw attitude control is proposed without any singular value of the sun elevation angle. Then a seamless handoff strategy for the sinusoidal control mode is put forward to get a continuous and smooth attitude control effect. The solar panel sun-pointing accuracy of the sinusoidal yaw control mode is also analyzed. The mathematical simulation and in orbit flight results indicate that the methods are efficient and practicable in engineering application.

The return trajectory optimization of spacecraft is a typical problem on optimal control. The spacecraft is affected by quality, kinetic energy, aerodynamics, thermal flux, overload and so on, which determines it difficult to attain the analytical solutions to the return trajectory problem. Currently, most of numerical methods on trajectory optimization mainly reduce indirect and direct methods. Because the spacecraft problem is a non-linear optimization problem containing terminal and procedure constraints, it is solved by Gauss pseudo-spectral method, which could attain higher precision by using fewer scattered points, and the estimation accuracy on boundary values is also higher. Optimize the return trajectory using Gauss pseudo-spectral method to obtain the optimal value satisfies terminal and process constraint, and the inaccuracy of the opening point is smaller, the estimation accuracy is higher.

The interference signal in satellite communication may seriously affect the efficiency and stability of data transmission. In order to solve the interference problem, it is necessary to encode the satellite interference channel and estimate its parameters. Traditional coding and parameter estimation methods have weak adaptability and robustness, and cannot effectively deal with complex interference situations. As an effective tool, machine learning has been widely used in the field of signal processing, which can realize adaptive identification and parameter estimation of interference channel coding types and improve data transmission efficiency and stability. In this paper, machine learning is used to adaptively identify the coding type of satellite jamming channel, and the accuracy of identification is improved by parameter estimation method. The comparative experimental results show that the application of machine learning algorithm in satellite jamming channel coding type identification and parameter estimation has achieved remarkable results in improving data transmission efficiency and stability. Compared with the traditional fixed coding method, machine learning can improve the transmission efficiency by about 4.76%. The results highlight the importance of machine learning in coding type identification and parameter estimation of satellite jamming channels, and provide new ideas and directions for the development of satellite communication technology.

Comparing with traditional solar-synchronous orbit satellite, the angle between orbital plane and solar vector of the inclined-orbit satellite varies over a much wider range, up to ±90°. In order to constantly align with solar vector, one of important means is to replace single-axis solar array drive assembly with biaxial solar array drive assembly (BSADA). However, BSADA may result in interference between solar array and satellite body, and is vulnerable to reaction force of solar array deployment. To solve this problem, this paper introduces a novel BSADA, increasing the distance between two axes (named axis A and axis B) by an extension rod, and designs solar array deployment scheme in the satellite injection phase, in which, other than traditional spring-damping device, axis B far away from the satellite is used to deploy the solar array to reduce reaction force. Relevant analysis, simulations and experimental results show that this scheme can effectively avoid solar array’s potential interference to satellite structure, and keep the reactional impact allowable during solar array deployment, which can meet the requirements of inclined orbit satellite to track the direction of solar vector.

In order to improve the autonomous operation capability of the long-life satellite with dual satellite autonomous formation flight function requirements during its lifetime, a multi constraint autonomous orbit control scheme for formation flight is proposed. First, the thruster optimization sequence is determined according to the satellite centroid change and thruster installation. Second, real-time hydrazine amount of each thruster is calculated and thus the thruster and target attitude for this orbit control task is able to be settled. Third, both real-time thrust and post-control thrust are estimated by the pressure sensor, followed by thrust coefficient calibration via the measurement of semi-major axis. Experimental results have been verified in orbit that our method can realize autonomous orbit control tasks in various working conditions such as accompanying flight, flying around, and holding point maintenance. Hence, this control scheme can be extended to future satellite networking, which is of great significance.

The architecture design of successful envelope intelligent analysis system for spacecraft includes management of successful envelope analysis object, construction and management of successful envelope, intelligent data acquisition, successful envelope analysis, and data integration. The successful envelope intelligent analysis system compares and analyzes the envelope range of the spacecraft data to be analyzed and the data of the successful flight spacecraft, obtains the data envelope status of the spacecraft to be analyzed, and evaluates the health status of spacecraft. The system architecture has been successful applied in launch sites testing and flight control of manned spacecraft, which realizes standardized description of envelope analysis objects, digitization envelope construction and analysis processes, and intelligence of envelope data acquisition and result analysis. The successful envelope intelligent analysis method and system architecture design of spacecraft have universality and expansibility in practice, which can guide other batch production to carry out successful envelope analysis.

Aiming at the radiation processing problem caused by the fact that the black body calibration data cannot track the corresponding observation strip in time due to the transmission of the same observation circle in different orbits of the 5-meter optical 02 satellite infrared camera, an image radiation processing technology based on the orbital alignment technology is proposed. After the actual image processing verification, the radiation processing technology of the 5-meter optical 02 star infrared camera is proved. It can not only satisfy the absolute calibration accuracy of the black body of the observation band in different down-pass circles, but also solve the relative radiometric correction accuracy of the single track statistics, and achieve good results in the actual ground processing process.

Most of the scanning multispectral data from domestic land observation satellites only provide the imaging geometry of the scene center, missing the geometry of other pixels. This paper proposes a method for the reconstruction of observational geometry and verify the method using images with observational geometry. The result shows that the relative deviations of the reconstructed observation zenith and azimuth are less than 5%, combined with the Ross-Li BRDF model, it can significantly improve the accuracy of directional surface reflectance and of the calibration coefficients.

Digital twin technology has currently received widespread attention in aerospace field, and is applied in scenarios such as spacecraft design, simulation, operation and maintenance. Compared with traditional simulation, the most significant feature of digital twin is that it can make the model evolve continuously in operation through virtuality-reality interaction, so as to keep consistent with physical entity. In order to meet the high reliability requirements of engineering applications, digital twin for spacecraft control system is constructed in this paper which has high-precision and evolvable characteristics. Multiple typical modeling problems of digital twin for spacecraft control system are proposed with the consideration of model evolution, such as dynamics modeling, orbit prediction modeling, sensor modeling, active component modeling and electromechanical component modeling. In response to these problems, model evolution approaches are introduced to illustrate the functions in various scenarios, providing feasible solutions for precise modeling and model evolution of digital twin for spacecraft control system.

The effectiveness of on-orbit maintenance of onboard embedded software directly affects the correctness of satellite system operation. In order to improve the reliability and safety of on-orbit maintenance, a rollback-able on-orbit maintenance method based on running-state information was designed on the basis of existing implementation methods for onboard embedded software. The running information table of on-orbit injection block is established to describe the abnormal retrieval features of the injection block, and the association information table of on-orbit injection block is established to describe the correlation relationship between the on-orbit blocks. The content of tables is used for anomaly judgment and positioning, and the abnormal operation position and related information are quickly identified. The experimental results show that on-orbit maintenance method proposed in this paper can achieve autonomous removal of exception blocks in the event of on-orbit injection, effectively improving the effectiveness and correctness of on-orbit maintenance for onboard embedded software.

In order to solve the integration energy loss problem in GNSS receiver caused by the reversal of cross-data bit, this paper proposed one improved Costas loop which could carry out cross-data bit coherent integration. The coherent integration scheme of proposed loop was divided into two steps, firstly, a short coherent integration over one code period was performed, secondly, another long coherent integration cross-data bit was performed based on the short coherent integration result and its sign. A theoretical analysis to proposed Costas loop was made in the paper. A simulation compare between proposed loop and classic Costas loop was made. Analysis and simulation results showed that, proposed loop could improve carrier tracking precision at weak signal by increasing coherent integration time without navigation data bit limitation.

The method of pure angle observation has serious nonlinearity in celestial navigation system, the angle measurement error is converted to a large distance error, which caused navigation accuracy degradation. Aiming at the problem of celestial navigation accuracy, this paper proposes a celestial navigation method based on laser ranging auxiliary. High-precision distance measurement from satellite to ground reference beacon can be directly obtained by means of laser ranging. In the celestial navigation system which takes the starlight angular distance as the observation measurement, the introduction of laser ranging auxiliary data can not only expand the filter observation dimension, but also improve the filtering effect obviously. Meanwhile, in order to reduce the second-order truncation error due to the linearization of Taylor expansion, it is necessary to use the unscented Kalman filter (UKF) method for the data fusion of integrated navigation system. Research results show that integrated navigation system of celestial navigation and laser ranging can significantly reduce estimation error and improve the navigation accuracy.

According to the application requirements of GPS/BDS dual-mode navigation terminals and the improvement requirements of orbit determination accuracy index for low-earth-orbit remote sensing satellite, the on-board factors affecting the real-time and the post orbit determination accuracy of navigation terminals for LEO remote sensing satellite are systematically analyzed and described. A method to improve the stability of antenna phase center and the quality of received signal by optimizing the layout of navigation receiving antenna is proposed. The verification of ground and in orbit test data shows that the real-time orbit determination accuracy of the improved system in GPS and BDS mode meets the requirements of 3~5 m index, and the post precise orbit determination accuracy meets the requirements of 10 cm index, which indicates that the design of the GPS/BDS dual-mode navigation can meet the requirements of satellite mission and can provide reference for the design of subsequent remote sensing satellites.

In this paper, we adopt a low-power platform to implement the porting of LwIP protocol stack based on SpaceOS for the characteristics of high reliability of space model mission operating system, low power consumption of hardware platform, high volume of control packet transmission, high data transmission rate and high real-time requirement. First, Zynq platform is selected in this paper to effectively integrate the software programmability of ARM processor with the hardware programmability of FPGA, which can realize the functions of multi-core hardware acceleration, data processing, signal processing. Based on this, the board-level support package, kernel management, software middleware and other modules of SpaceOS are ported to realize task scheduling and management, inter-task communication management and exception management. Further, based on the LwIP protocol stack, LwIP bare-metal porting and porting for SpaceOS are carried out respectively to design and implement the Ethernet data transmission system, conduct UDP server function test, and verify the system transmission capability.

The 3D reconstruction technology is of great significance for the research of Martian topography. In this paper, an unmanned aerial vehicle (UAV) based Mars topography mapping and 3D reconstruction system is proposed. In the system, an on-board range-visual-inertial odometry (on-board range-VIO) is applied to solve UAV navigation and flight path planning problems. The pictures of simulated Mars topography are photted. Images are processed and 3D model is reconstructed by applying high-performance computing unit (HPCU). By building an experimental system on the ground and conducting flight simulation and 3D reconstruction experiments, the effectiveness of the system was verified.

Space craft engineering is a complex unmanned system with large scale, and there are couplings among the subsystems, so multi-disciplinary modeling and simulation in every development stage is necessary. In order to study how to achieve spacecraft multi-disciplinary modeling and simulation quickly, using Modelica to model the key equipment of subsystems, and accomplish the Modelica model libraries, refining a modeling method: a multi-disciplinary parallel simulation framework is proposed to solve the problem of low simulation efficiency caused by large models in multidisciplinary unified modeling and simulation of complex systems. On base of the modeling method, simulating the early partial elimination, the correctness of the model is verified. This modeling method could be used to verify the correctness of early programs of unmanned system.

Considering the requirements of traditional thruster layout, the characteristics of missions and working loads of the satellites, a thruster layout method for attitude controlling (AC) with force couple and orbit controlling (OC) with multi-thrust options is proposed. By making reasonable use of surface space and optimizing configuration quantity of thruster of the satellites, impact on orbit altitude caused by attitude control is reduced as far as possible. With different thrust options, requirements for large impulse orbit transfer and small impulse trajectory maintenance are satisfied. Mathematical simulation and in-orbit flight verification show that the proposed method is effective and feasible.

This paper proposes a distributed adaptive spectrum planning concept based on blockchain, designs a licensed spectrum planning blockchain type, implements a blockchain link method that can be used for spectrum planning, and meets the diversified needs of decentralized spectrum planning and user adaptive frequency usage. And aiming at the adaptive demand, the intelligent contract of spectrum planning is proposed, and the adaptive spectrum planning rules are designed. The cell, resource and interference are transformed into graph correlation matrix, and the real-time spectrum planning algorithm based on matrix calculation is realized.

The optical axis pointing device is an important guarantee for star camera to realize high precision measurement, The optimal focal plane position of the light source will affect the accuracy of the optical axis pointing device. This paper deals with the determination of the optimal focal plane position of the light source in the optical axis pointing device, A fast focal plane location determination method based on Gaussian fitting is proposed. The measurement of the focal point of the tiny luminous surface of the light source of the optical axis position recording device is converted to the measurement of the luminosity of the light spot emitted by the light source of the optical axis pointing device. First, a test platform for focal surface position of light source was built, and light source spots under different gaskets thicknesses were obtained by replacing gaskets; Second, the centroid of each light spot is determined, and the DN value of centroid brightness of each light spot is calculated; Thirdly, the least square method is used to fit the centroid brightness of the obtained spot to get the best focal plane position of the light source; Finally, the center of mass standard deviation is calculated to verify the test results. The test results show that the method is effective.

This paper applies Analytic Hierarchy Process to comprehensively evaluate the design of communication satellites. Firstly, comprehensive evaluation indexes are determined based on the design requirements of the satellite system, and total of 29 evaluation indexes are classified in five categories at three levels; Afterwards, each index is standardized according to its different characteristic, and the weight of each index is assigned by pairwise comparison matrix; Finally, the score of the satellite system design scheme is calculated, and through the evaluation and analysis of six design cases, the suggestion of optimization of satellite system design are identified. The application of this method helps to quickly identify weakness in satellite system design, and also provides a mean of evaluation for system optimization.

Telemetry parameters are the main reference for characterizing the state of spacecraft and are an important component of spacecraft management. With the rapid development of space technology, the number and types of spacecrafts have increased and enriched, and the volume of telemetry parameters has increased, making it more difficult to analyze. In order to avoid information loss caused by manual operations during information transmission, this paper proposes an XML based method for analyzing spacecraft telemetry translation information, considering the homogeneity of spacecraft telemetry information. This method is used to batch analyze the physical meaning of telemetry, improve processing efficiency and accuracy, and achieve efficient and accurate transmission of spacecraft telemetry information from the development direction to the measurement and control side.

The Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) “Goumang” is equipped with several payloads targeting worldwide or China’s domestic specific ground-objects, for example, the Aerosol Lidar working over lands in lighting and domestic area in shadow, the Directional Polarization Camera working in lighting area and the Fluorescence Spectral Imager aiming for lands in lighting. In order to improve the operation intelligence, a method of autonomous task planning for remote sensing satellites based on ground-object properties is proposed. The longitude and latitude of the nadir point after 90 min is extrapolated and forecasted firstly, and the lighting-shadow, land-ocean and domestic-overseas properties of the forecasted nadir point are obtained according to the on-board map and the solar elevation angle. Then the time table of every payload is generated based on the smoothed ground-object properties. Results of autonomous task planning for every payload can be created about one-revolution in advance.

In this work, we deal with the pointing control problem for the whole tracking process of a non-cooperative object via a two-axis turntable-based early warning satellite, where the initial target acquisition process and the subsequent visual tracking process are addressed respectively. First, to conquer the capture error caused by the camera assemble error and the inconsistency of the center of the viewing field for multiple channels of the camera, a high-accuracy capture protocol with bias compensation is devised by utilizing the image kinematics of the turntable and the satellite. Second, an image-based nonlinear visual servoing controller via a novel velocity estimator is developed, where the angular rate of the turntable and the satellite is involved to predict the image velocity. In addition, the planning scenario for the expected image trajectory is introduced to improve the performance of the transient period. Finally, on-board experiment is performed to testify the effectiveness of our methodology.

In the traditional scene simulation simulator storage device, FLASH is low access speed, small storage capacity, DDR power loss data loss, and the dynamic and flexible data output cannot be realized. In view of this situation, we propose an implementation scheme of key components of remote sensing satellite scene simulator based on NVMe. NVMe has the advantages of high bandwidth, speed and flexibility, and can conduct multi-thread and multi-file high-speed storage and broadcasting, to meet the reading and writing requirements of big data storage of remote sensing satellites. In this scheme, based on FPGA platform and referring to NVMe protocol, we realize NVMe high-speed read and write data stream and storage on the basis of PCIe Gen 3. The read speed of PCIe quad-channel data stream is up to 2.53 GB/s, and the write speed is up to 2.51 GB/s. At the same time, we also implemented the PCIe single-word read and write register function to facilitate small-scale data transfer.

Space network systems with inter satellite links or multi-beam cross coverage provided by LEO satellite constellations, MEO navigation satellite systems, and GEO communication satellites can offer continuous short message transmission services for LEO spacecraft. Due to the high end-to-end packet loss rate caused by the high bit error rate and data packet congestion because of the limited storage capacity of space-based devices, this paper proposes an Adaptive Forward Packet Loss Recovery algorithm for space TT&C data based on Beidou-3 short message system. The simulation results show that under the transmission condition of CCSDS AOS transmission frame carrying space TT&C data, 892-bytes VCDU requires 14 short messages (about 60-bytes payload length) to carry. Under the condition of 95% delivery success rate of short message system, the success rate of whole frame recovery without compensation and only out-of-sequence correction is about 49%. The whole frame recovery success rate of the Adaptive Forward Packet Loss Recovery algorithm is improved to at least 85%, and the system performance is improved to not less than 70%, which can ensure real-time transmission and effectively improve the reliability of space TT&C data transmission based on short message system.

Computational thinking is one of the abilities that students must have in the era of artificial intelligence. How to cultivate students’ computational thinking has become a hot spot of attention. Using programming to teach is an effective way to cultivate computational thinking, and programming is a process of communication between humans and computers. However, the current information technology teaching focuses on learning algorithms, ignoring the cultivation of computational thinking. Taking advantage of the advantages of project-based teaching, this paper designs a project-based teaching model for computational thinking training from the three links of introducing projects, project implementation, and project evaluation, and puts forward five specific tasks: introducing problems, building models, designing algorithms, optimizing algorithms, and inductive transfer. This paper uses bubble sorting as an example of project-based teaching design. The teaching design takes the project as the main line, aiming to improve the computational thinking ability of middle school students and promote students’ learning.

Angular vibration environment of sensitive components such as large optical cameras and laser devices will directly affect the imaging quality. Angular vibration is an important parameter for indirectly evaluate imaging quality. The current angular vibration measurement equipment is large and heavy, so it is difficult to be directly installed around the sensitive devices for the direct measurement of the angular vibration parameters. According to the measurement requirement of angular vibration, an indirect measurement method based on the linear acceleration is proposed in this paper. The linear vibration sensor is reasonably arranged, and the angular vibration measurement model based on linear acceleration is established. The method is verified by the ground and in orbit angle vibration measurement, and compared with the measurement value of the angular vibration sensor. The measurement results show that the deviation of the angular vibration parameters is within 10%. The method has the characteristics of convenient implementation, high measurement accuracy, and direct measurement of sensitive devices. Research achievement in this paper can provide an important reference for the measurement of angular vibration environmental parameters of various sensitive devices in orbit.

Laser pointing accuracy is one of the key performance indexes of pointing, acquisition and tracking (PAT) technology for free space optical communication (FSOC) system, which has important influence on the rapid acquisition of optical signals. At present, the error correction approach of laser pointing mainly achieved by the ground precision measurement of reference mirror installing on the optical antenna and obtain the correction parameters. The disadvantage of this method is that the error correction parameters will slowly drift with the deformation of optical antenna while the FSOC system operated on-orbit. In this paper, a star sensor-based laser pointing error correction method for FSOC system has been proposed. The laser pointing error model has been described, and the robust information fusion method based on the attitude data from star sensor has been developed. Numerical simulation results demonstrate that the novel error correction approach effectively improves the laser pointing accuracy.

Contactless Power Supply (CPS) uses electromagnetic coupling technology to supply power without mechanical contact. It is mostly used for mobile equipment, which has great advantages in safety, flexibility, maintenance costs and other aspects. In response to the 24-h uninterrupted and unmanned operation requirements of modern smart factories, this paper constructs an energy system composed of CPS, the lithium iron phosphate battery and the inverter to supply power for Automated Guided Vehicles (AGVs), and monitors and controls the working state of the battery in real time through the battery management system (BMS), so as to effectively extend battery life. After the charging efficiency test and practical application test, it has been verified that the proposed design scheme can enable the production line to realize the 24-h uninterrupted operation without manual intervention, which meets the demand of reliable and stable manufacture.

With the establishment of China's space station, real experimental verification conditions have been provided for conducting research on space radiation effects of nanoscale electronic components in orbit. Considering the urgent needs of spacecraft for in orbit maintenance, hardware replacement, functional upgrades, and other in orbit services, this paper designs a testing platform that can simultaneously support dozens of nanoscale electronics for space radiation effects in orbit, solving the current dilemma of single types of in orbit verification tests for electronic components, inability to generate economies of scale, and inability to systematically conduct scientific experimental research. The testing platform adopts standard mechanical, electrical, and thermal interfaces, adopts a modular replaceable architecture, supported in orbit software upgrades, reconfigurable system design, and supported astronauts to regularly replace test modules in orbit. We can continuously complete in orbit radiation resistance performance testing research for new materials and new process nanoscale electronics, and achieve in orbit upgrade of nano level electronics verification tasks. In this paper, the test data of space radiation effect of 16 nm FinFET process FPGA in orbit are given, and the real Single-event upset rate caused by space radiation effect in Low Earth orbit (orbit height is 400–450 km) and the countermeasures are analyzed, providing strong support for the aerospace applicability research of domestic nanoscale electronics.

With the increasing scale of spacecraft, the demand for simulation computing continues to increase, and the requirements for high-performance computing (HPC) resources for simulation jobs are gradually increasing. For the spacecraft designers, the estimation of computing resources and running time required by simulation computing jobs is not accurate enough. Accurate prediction of the running time of spacecraft simulation job is helpful to the effective operation of Backfilling scheduling strategy and further improves the utilization rate of resources. In this paper, according to the characteristics of spacecraft simulation computing jobs, the historical logs and simulation application parameters are analyzed, and key operation characteristics are extracted. At the same time, considering the time sequence correlation of computing jobs, we propose a running time prediction algorithm based on hierarchical clustering and LSTM. Through the comparative analysis of experiments, it is verified that the algorithm has high accuracy in predicting the running time of spacecraft simulation operation, and the prediction effect is better than other related machine learning algorithms.

The thermal requirements for star trackers of SSO satellite are very stringent to guarantee the lower frequency error on the attitude due to thermal drift. An independent radiator is fixed on the satellite and thermally coupled to star sensor through heat pipes to provide cooling in the common scheme, which is complex and a unique thermal design is required for the same star sensor on different satellites. A generalized thermal control system for star trackers is designed and verified by thermal balance test and flight. Firstly, an integrated thermal approach is proposed in the paper. The radiator always exposed to cold space is mounted on the baffle of star trackers with thermal insulation pads and thermally coupled to star sensor through heat pipes to thermal dissipation. The direction of the radiator is consistent with the optical axis. Less solar heat flux is received by the radiator due to 30° sun rejection angle of star tracker. Then, enhanced thermal insulation design is used to reduce the influence of external thermal environment and heater loops with proportional control algorithm are adopted to decrease temperature fluctuations. Finally, taking APS star sensors mounting on remote sensing satellite as an example, the scheme is verified by thermal balance test and flight. The results show that, the temperature range of optical component and flange are from 18 ℃ to 22 ℃. The temperature gradient is less than 1.5 ℃ in the whole lifetime and the temperature fluctuation is less than 0.5 ℃/orbit. The validity of thermal control design is proved．

The satellite momentum wheel which has high torque accuracy can exchange angular momentum with the spacecraft by changing the size of angular momentum to achieve attitude control. It is widely used in communication, remote sensing and other satellite platforms, and is an important control component of the spacecraft. When the momentum wheel is in orbit, there is a need for long-term high-speed operation, so it is very prone to malfunctions. The traditional fault detection method is limited to relying on the knowledge and experience of experts and relevant technical personnel, as well as the interpretation of the threshold value of the single machine working state. If the key telemetry values of the momentum wheel do not exceed the interpretation range, it is difficult to detect the fault in a timely manner and miss the optimal disposal time, which may lead to abnormal satellite attitude. The friction torque of the momentum wheel is the main characteristic that affects the performance of the momentum wheel bearing. In this context, this article mainly analyzes the momentum wheel motor current telemetry that is strongly related to the friction torque. The Variation-al Mode Decomposition is used to extract the signal amplitude characteristics of motor current telemetry, and then the signal amplitude characteristics of motor current telemetry are learned by using auto-encoder and variational-auto-encoder respectively to get cross entropy. Finally, it is concluded that due to the inherent constraints of the variational-auto-encoder, it is more suitable for extracting fault features of momentum wheel bearing.

The wide application of various communication methods has become the most prominent symbol of this new era. In this paper, we suppose that dynamically changing the coding scheme according to the signal to noise ratio could keep the error rate for a communication channel at a lower lever comparing to continuously using one coding scheme. Firstly, we generate a data sequence with 0 and 1 uniformly distributed. Then we add noise to the sequence and code the sequence with multiple coding schemes, then decode the sequence. Finally, we compare the error rate for different coding schemes. The experimental result shows that dynamically changing the coding scheme could be helpful.

As terahertz range used to be a gap, it has been researched more and more nowadays. This paper aims to design a half wave plate and a quarter wave plate operating at the terahertz frequency. This paper introduces the background of the terahertz technology, wave plate. Based on the background, the equations which are related to the optical parameters used in the wave plate design and data processing are also given. Further details on the structure and simulation process of the wave plate are given in the paper. Through the calculation, simulation and design modifying, the half wave plate finally reaches the phase difference of 179.86 degrees while the quarter wave plate reaches the phase difference of 90.15 degrees which are approaching to the theoretical values.