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13th European Space Power Conference, ESPC 2023

作者： Li, Dawei Wang, Shaoning Cai, Junliang Shi, Gengxin Li, Jianping Hou, Xuelong He, Fengping Zhang, Xuan Li, Kang Institute of Telecommunication and Navigation Satellites China Academy of Space Technology Beijing China Lanzhou Institute of Space Technology Physics China Academy of Space Technology Lanzhou China Beijing Institute of Control Engineeringing China Academy of Space Technology Beijing China Tianjin Institute of Power Sources China Electronics Technology Group Corporation Tianjin China Shenzhen Aerospace New Power Technology Ltd. S.Z. Academy of Aerospace Technology Yantai China

ISBN: (纸本)9798350328998

The application of electric propulsion systems in spacecraft is becoming increasingly widespread, and the demand for high-voltage power supplies is also increasing rapidly. Especially for ion propulsion systems, there is a stronger demand for space high-voltage power supplies with an output voltage of 1kV. This article is based on the user requirements of the ion electric propulsion subsystem, a highvoltage constant voltage power supply for the ion electric propulsion system is designed, and its output voltage can be reconstructed through 2 modules selection from 3 modules to ensure that the average working time of devices or circuits in each module is equivalent, and this high-voltage power supply has the function of neutralizer current interlocking. In the measurements and performance evaluation of the high-voltage power supply, its output voltage stability, output voltage ripple, efficiency and interlocking time characteristics meet the user index requirements. The reconfigurable high-voltage power supply has excellent output characteristics, consistency, and excellent performance in orbit. © 2023 IEEE.

关键词： Ions

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A Global-local Feature Interaction Network for Anti-cloud Interference Change Detection based on Contrastive Learning

A Global-local Feature Interaction Network for Anti-cloud In...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Jiyuan Yang Kun Gao Qiong Wu Zefeng Zhang Baiyang Hu Yuqing He Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education Beijing Institute of Technology Beijing China China Ordinance Industry Navigation and Control Technology Research Institute Beijing China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Bi-temporal change detection (CD) constitutes a vital task within the domain of remote sensing (RS). due to pseudochange caused by factors such as seasonal climate variations, temporary objects, and cloud interference. To address the pseudochange issue stemming from cloud interference, we propose a global-local feature interaction anti-cloud interference change detection network (ACCDNet) based on contrastive learning. To mitigate the scarcity of remote sensing datasets with cloud interference, we leverage contrastive learning principles, using remote sensing images of the same scene at the same time with and without cloud interference as positive sample pairs to pre-train anti-cloud interference capability of the feature extractor. The proposed CD network which bases on a CNN-transformer network, utilizes Resnet to extract multi-scale features from the original input images. We introduce transformer modules and attention mechanisms to effectively extract the contextual information within the input images. To address the pseudochange issue caused by cloud interference, we simulate the effect of thin cloud interference using Perlin noise and add it to classical datasets. Experimental results on LEVIR-CD and LEVIR-CD-cloud datasets augmented with cloud interference demonstrate the priority and efficiency of the proposed method.

关键词： Measurement Attention mechanisms Clouds Noise Interference Contrastive learning Feature extraction Transformers Robustness Remote sensing

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Distributed Guidance for Flexible Spacecraft Landing on Asteroid 73

Distributed Guidance for Flexible Spacecraft Landing on Aste...

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73rd International Astronautical Congress, IAC 2022

作者： Zhang, Chengyu Liang, Zixuan Cui, Pingyuan Ge, Dantong School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Key Laboratory of Autonomous Navigation Control for Deep Space Exploration Ministry of Industry and Information Technology Beijing100081 China

For the microgravity asteroid, even small residual impact energy may cause the spacecraft to bounce and overturn, triggering unexpected events. To suppress the rebound and overturn, a flexible spacecraft concept has been proposed. Nevertheless, a strong coupling exists between the rotational and translational dynamics of the flexible spacecraft. In this paper, a distributed guidance law is developed to control the overall flexible spacecraft's orbit and attitude motion simultaneously through the coordination of the motion of mass blocks. The composite motion of mass blocks can approximate the overall motion of the flexible spacecraft, and the relative height difference of mass blocks can also reflect the attitude of the flexible spacecraft. Therefore, the working principle of the integrated translation and rotation distributed guidance scheme is that each localized controller cooperates to adjust the relative height difference and composite motion of mass blocks. To qualitatively characterize the effort required to adjust the relative altitude difference, a pseudo-attitude control effort index is derived, which is a function of the relative altitude difference. By weighting the attitude control effort index into the minimum orbit control efficiency index, an analytical distributed guidance law is obtained, which guarantees the near-fuel optimality. Monte Carlo simulations show that the attitude requirement of the flexible spacecraft can be realized during landing. Copyright © 2022 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Orbits

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Research on disruptive design pre-identification in the preliminary design phase of aero engine flow pass multidisciplinary optimization

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Chinese Journal of Aeronautics 2022年第11期35卷 264-276页

作者： Shaojing DONG Yufan FANG Wentong HU Xiuli SHEN Gaoxiang CHEN School of Energyand Power Engineering Beihang UniversityBeijing 10083China Beijing Key Laboratory of Aero-Engine Structure and Strength Beihang UniversityBejing 100083China Jiangxi Research Institute Beihang UniversityNanchang 330096China Navigation and Control Technology Research Institute of China Ordnance Industries Beijing 100089China Research Institute of Aero-engine Beihang UniversityBeijing 100083China

In aero engine design, determining whether the preliminary design will have disruptive effects on the detailed design is the key to multidisciplinary design optimization in the preliminary design stage. In order to adapt to the non-orthogonal parameter value range caused by the selfconstrained parametric modeling method, a non-orthogonal space mapping method that maps the optimal Latin hypercube sampling points of the traditional orthogonal design space to the non-orthogonal design space is proposed. Based on the logical regression method in machine learning field, a kind of feasible domain boundary identification method is employed to identify whether the sample spatial response meets the relevant criteria. The method proposed in this paper is used to identify and analyze the key technologies of the high-pressure turbine mortise joint structure. It is found that the preliminary design of the aero engine may lead to the failure to obtain a mortise joint structure meeting the design requirements in the detailed design stage. The mortise joint structure needs to be pre-optimized in the preliminary design stage.

关键词： Aero engine Disruptive design Flow pass multidisciplinary optimization Pre-identification Preliminary design phase

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Multi-View Joint Target Selection for Relativistic-Perturbed Starlight navigation

Multi-View Joint Target Selection for Relativistic-Perturbed...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yaru Zhao Dantong Ge Kai Xiong School of Aerospace Engineering Beijing Institute of Technology Beijing China Key Laboratory of Autonomous Navigation Control for Deep Space Exploration Beijing Institute of Technology Beijing China National Key Laboratory of Space Intelligent Control Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Autonomous navigation is one of the key technologies for spacecraft to realize long-term space operation and carry out science missions. In order to meet the requirement of high precision autonomous navigation, the effects of the gravitational deflection of light, stellar aberration and measurement bias of sensor are considered to establish a relativistic-perturbed starlight navigation scheme. To obtain high quality measurements, a multi-probe star sensor composed of multiple field of view probes is adopted for observation. A polygonal star pair selection method is proposed to conduct multi-view joint target selection. By constructing irregular polygons to select high quality star pair observations, the accuracy of navigation estimation is expected to be improved. The performance of relativistic-perturbed starlight navigation using the multi-view joint target selection method is then verified through a numerical simulation.

关键词： Space vehicles Accuracy navigation Space missions Simulation Stars Estimation Numerical simulation Probes Autonomous robots

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Rapid Conjunction Screening Based Collision Avoidance for Mega-constellations with Coverage and Thrust Constraints 73

Rapid Conjunction Screening Based Collision Avoidance for Me...

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73rd International Astronautical Congress, IAC 2022

作者： Guo, Hao Long, Jiateng Cui, Pingyuan Zhu, Shengying Nie, Tao School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information Technology Beijing100081 China

In recent years, low Earth orbit (LEO) mega-constellations, composed of hundreds to thousands of satellites to provide global broadband even including the most rural areas, have been designed and launched by commercial aerospace companies, such as OneWeb and SpaceX. For these mega-constellations, however, one of the most significant threats to the safe operation is the collision of constellation to the active/inactive satellites, rocket bodies, debris, etc. Such collisions may result in catastrophic damage to the spacecraft operating environment. Therefore, the collision avoidance maneuver (CAM) strategy must be considered for the safe operation of the constellation. In order to properly conduct the CAM, conjunction screening is the first and essential step, which is to distinguish the satellite that need to be maneuvered. However, compared with the conventional CAM strategy of a single satellite, that of the mega-constellations is much more complicated, mainly because of the enormous quantity of satellites. This leads to conjunction screening incredibly slow even infeasible for online purpose application. What is worse is that mega-constellations have limited maneuverability, and the coverage of the satellite is sensitive to its position, compared with traditional navigation satellite constellations. To this end, a rapid conjunction screening based collision avoidance method considering coverage and thrust constraints is proposed. In view of global coverage, constellations are generally distributed in several orbital planes with dozens of satellites. To expedite the conjunction screening step, the threatened orbital planes are screened out firstly by evaluating the minimum miss distance between the danger space object and the orbital planes. Then, the satellites in the plane that need to perform CAM can be determined by the orbital period and the time of closest approach. Consequently, the computational complexity is related to the number of orbital planes rather t

关键词： Satellites

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Data Processing Method of Dynamic Gravity Gradiometer Based on Time-frequency Combination 29

Data Processing Method of Dynamic Gravity Gradiometer Based ...

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29th Saint Petersburg International Conference on Integrated navigation Systems, ICINS 2022

作者： Li, Da Zhao, Lin Gao, Hongwei Ma, Guoqing Weng, Haina Li, Zhong Harbin Engineer University Harbin China Tianjin Navigation Instrument Research Institute Tianjin China Lab. of Sci. and Technology on Marine Navigation and Control of China State Shipbuilding Corporation Tianjin China Jilin University Changchun China

ISBN: (纸本)9785919950844

Gravity gradiometer is an instrument for continuous measurement of small gravity gradient changes on the earth's surface. The gravity gradiometer based on the principle of rotating accelerometer is the only gravity gradiometer to realize near surface dynamic measurement. Due to the weakness of gravity gradient signal and the limitation of accelerometer performance, the direct output signal of gravity gradiometer contains a lot of motion noise under dynamic conditions, and the signal-to-noise ratio is very low. In conventional gravity gradient data processing, the noise outside the measurement frequency band is removed by low-pass filter after motion compensation, but the dynamic noise distribution is full frequency band, and the low-pass filter cannot eliminate the noise in the passband. In addition, the real gravity gradient signal also has the characteristics of multi-scale and non-stationary in space. Therefore, the time-domain filtering link of wavelet threshold filtering is added in data processing, and the limitation of Fourier transform to non-stationary signal is solved to a certain extent by using the multi-resolution analysis characteristics of wavelet transform in time domain. According to the characteristics of surface gravity gradient signal, the appropriate wavelet base is selected, and the influence of threshold control method, threshold estimation method and decomposition layers on the filtering effect is discussed in detail by using the measured data of gravity gradient vehicle test. On this basis, the optimal filtering parameters are determined. Finally, the above time-frequency combined data processing method is used to process the measured data of gravity gradient aerial test. The processing results show that compared with conventional low-pass filtering, the data processing method proposed in this paper can improve the internal coincidence accuracy of airborne gravity gradient measurement by 30% without losing spatial resolution, and has obvious

关键词： Accelerometers

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Research on full-range autonomous navigation decision making of ships based on finite state machines

Research on full-range autonomous navigation decision making...

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International Conference on Transportation Information and Safety (ICTIS)

作者： Yingjun Hu Yangwen Dan Guangming Shao Shuangning Yu Junqing Han Bin Li Tianjin Navigation Instruments Research Institute Tianjin China Laboratory of Science and Technology on Marine Navigation and Control China State Shipbuilding Corporation Tianjin China

Intelligent ship is a major trend of future ship development, and ship intelligent navigation decision is one of the key technologies of intelligent ship. In order to further improve the level of ship intelligence and informatization and strive to realize the full autonomous navigation of the ship from berth to berth, this paper proposes a full-range autonomous navigation decision-making method of the ship based on finite state machine. Firstly, the full-range autonomous navigation is divided into different navigation scenarios according to the navigation task. Secondly, based on the finite state machine theory, the ship autonomous navigation decision model is constructed. Finally, the experimental verification is carried out in the simulation system based on the constructed autonomous navigation decision model. The experimental results show that the ship can realize the full-range autonomous navigation based on the model proposed in this paper, which verifies the feasibility of the construction method and can effectively support the ship autonomous navigation.

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Cmifdf: A Lightweight Cross-Modal Image Fusion and Weight-Sharing Object Detection Network Framework

SSRN

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SSRN 2024年

作者： Zhao, Chunbo Mo, Bo Zhao, Jie Tao, Yimeng Zhao, Donghui School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China North Navigation Control Technology Co. Ltd. Beijing100176 China

In today's research, unimodal target detection can no longer meet the needs of target detection in complex backgrounds as well as harsh environments. To solve the problems of the existing cross-modal image fusion and cross-modal image target detection algorithms with network-heavy parameters and redundant network design, a selectable cross-modal image fusion and target detection algorithm framework (CMIFDF) is proposed. The framework consists of a lightweight dual-branch cross-modal image fusion network (LDFet) and a cross-modal object detection algorithm with shareable weights (CM-YOLO) to rationally utilize the cross-modal image information and improve the performance of target detection under complex backgrounds. LDFet is a two-branch fusion module based on depth-separable convolutional and attentional mechanisms, and it can adequately extract the feature information of visible and infrared images. In CM-YOLO, fused images or original images (visible and infrared) are input into a target detection network with shared weights for training and detection, and a simplified asymptotic feature pyramid network (SFPN-AFPN) is proposed to achieve an efficient fusion of features with fewer model parameters and low dissipation computational power to improve the network detection performance. Experiments on publicly available datasets show that the algorithmic framework can make full use of the feature information of cross-modal images as inputs and can effectively improve detection performance in complex environments. © 2024, The Authors. All rights reserved.

关键词： Image fusion

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DVL Modeling Using a RVM based on Artificial Bee Colony Algorithm in SINS/DVL

DVL Modeling Using a RVM based on Artificial Bee Colony Algo...

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IEEE International Conference on Mechatronics and Automation

作者： Bo Zhao Wei Gao Xiuwei Xia Xiaofeng Wei Navigation Guidance and Control from School of automation Harbin Institute of Technology Harbin China HIT (ANSHAN) Institute of Industrial Technology Anshan China

For underwater Strapdown Inertial navigation System/Doppler Velocity Log(SINS/DVL) integrated navigation system, it is a crucial factor for the performance of integrated navigation system to estimate the scale factor of DVL and its installation relationship with SINS accurately. Firstly, the theoretical model of DVL influenced by scale factor error, installation error between SINS and DVL and dynamic attitude are established. Due to the effect of dynamic attitude angle, the velocity measurement model of DVL presents great complexity and strong nonlinearity. Hence, this paper proposes a novel DVL model training approach using relevance vector machine (RVM), in which all error sources are considered in this model without separated DVL velocity measurement models. The Artificial Bee Colony (ABC) algorithm is used to optimize the key parameters of RVM. Secondly, the constraint information from GNSS and depth sensor is applied to strengthen the accuracy and generalization of the model. Finally, the performance of this method is verified with experiment in the Yellow Sea. Compared with the traditional least square estimation method based on SVD (SVD-LS), the DVL measurement model shows higher accuracy, and the positioning error of SINS/DVL integrated navigation system has been reduced from 3.1‰ of the voyage to 1.5‰ of the voyage.

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