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Q-Learning-Based Target Selection for Bearings-Only Autonomous Navigation

Journal of Systems science & Complexity 2021年第4期34卷 1401-1425页

作者： XIONG Kai WEI Chunling Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control EngineeringBeijing 100094China

This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible *** the considered navigation system,the position and velocity of the spacecraft are estimated using an extended Kalman filter(EKF)with the measurements of inter-satellite line-of-sight(LOS)vectors obtained via an onboard star *** paper focuses on the selection of the appropriate target at each observation period for the star camera adaptively,such that the performance of the EKF is *** derive an effective algorithm,a Q-function is designed to select a proper observation region,while a U-function is introduced to rank the targets in the selected *** the Q-function and the U-function are constructed based on the sequence of innovations obtained from the *** efficiency of the Q-learning-based target selection algorithm is illustrated via numerical simulations,which show that the presented algorithm outperforms the traditional target selection strategy based on a Cramer-Rao bound(CRB)in the case that the prior knowledge about the target location is inaccurate.

关键词： Bearings-only autonomous navigation convergence analysis extended Kalman filtering Q-Learning target selection

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Analysis of Transceiver RF Impairments on Artificial Noise Suppression in Frequency-Hopping Systems

IEEE Transactions on Sustainable Computing

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IEEE Transactions on Sustainable Computing 2024年第3期10卷 475-490页

作者： Song, Changqing Zhao, Hongzhi Yu, Yong Li, Zhuo Shao, Shihai University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China Yangzhou Marine Electronic Instrument Institute Yangzhou225101 China

The artificial noise shielded frequency-hopping (ANFH) architecture can secure wireless communications against interference and eavesdropping. However, the AN suppression performance is highly sensitive to the radio frequency (RF) impairments, and the transceiver in-phase and quadrature (IQ) imbalances and phase noise in FH systems are more severe for the wide FH bandwidth. In this study, the AN-FH transceivers under RF impairments are mathematically modeled. Subsequently, distortions for transceiver phase noise are represented by the common phase error, distortions for transceiver IQ imbalances are represented by the mirror image component, and closed-form expressions for their respective power are derived and compared with the thermal noise power. Finally, the AN suppression capability is evaluated via the AN suppression ratio (ANSR), defined as the ratio of the AN-plus-noise power before and after suppression. It is found that when only phase noise exists, shortening the channel compensation cycle can enhance ANSR and reduce ANSR degradation;when the distortions' power is smaller than the thermal noise power, it is also recommended to enhance the transmitting power and the power ratio of AN to information signals. When only IQ imbalances exist, increasing the power ratio of AN to information signals is suggested;when the distortions' power is smaller than the thermal noise power, enhancing the transmitting power is also suggested © 2016 IEEE.

关键词： Phase noise

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Network Generating Network for Multi-scale Image Classification 2

Network Generating Network for Multi-scale Image Classificat...

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2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2022

作者： Dong, Hang Xiao, Liping Cong, Longjian Zhou, Bin National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9781510663107

Features extracted by the neural network do not have scale invariance, which makes multi-scale image recognition and classification a difficult problem. Recent studies have proposed many new ways to solve this problem, such as feature fusion, sensor field transformation, etc. However, none of them essentially solve the problem that the neural network does not have scale invariance. In this paper, we propose a network generating network (NGN) architecture and design the NGNResNet network, which is an improved version of the ResNet network. The network can identify images at three scales simultaneously and has scale invariance. The experimental results show that the NGN structure helps us to improve the classification accuracy of small-scale images by about 10 percentage points, and helps to improve the performance of the network in the face of small targets. © 2023 SPIE.

关键词： Image recognition

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Personalized Federated Learning for Heterogeneous Residential Load Forecasting

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Big Data Mining and Analytics 2023年第4期6卷 421-432页

作者： Xiaodong Qu Chengcheng Guan Gang Xie Zhiyi Tian Keshav Sood Chaoli Sun Lei Cui the Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and TechnologyTaiyuan 030024China the Faculty of Engineering and Information Technology University of Technology SydneyUltimo 2007Australia the Centre for Cyber Security Research and Innovation Deakin UniversityMelbourne 3125Australia the School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China

Accurate load forecasting is critical for electricity production,transmission,and *** learning(DL)model has replaced other classical models as the most popular prediction ***,the deep prediction model requires users to provide a large amount of private electricity consumption data,which has potential privacy *** nodes can federally train a global model through aggregation using federated learning(FL).As a novel distributed machine learning(ML)technique,it only exchanges model parameters without sharing raw ***,existing forecasting methods based on FL still face challenges from data heterogeneity and privacy ***,we propose a user-level load forecasting system based on personalized federated learning(PFL)to address these *** obtained personalized model outperforms the global model on local ***,we introduce a novel differential privacy(DP)algorithm in the proposed system to provide an additional privacy *** on the principle of generative adversarial network(GAN),the algorithm achieves the balance between privacy and prediction accuracy throughout the *** perform simulation experiments on the real-world dataset and the experimental results show that the proposed system can comply with the requirement for accuracy and privacy in real load forecasting scenarios.

关键词： load forecasting personalized federated learning differential privacy

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Simulation of Nanosecond Microwave Pulse Amplification Based on a Gyrotron Traveling Wave Tube

Simulation of Nanosecond Microwave Pulse Amplification Based...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Pan, Ruoyang Zhang, Zhiyuan Liu, Guo Wang, Weijie Yao, Yelei Jiang, Wei Wu, Zewei Pu, Youlei Wang, Jianxun Luo, Yong University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (纸本)9798350375909

The paper presents the simulation results for nanosecond pulse amplification utilizing a TE11 mode Ku-band gyrotron traveling wave tube (gyro-TWT). This study evaluates the output performance across various input pulse widths within the 15-17 GHz frequency range. Simulations show that the minimum output pulse width is 0.8 ns, with an output power of 183.9 kW. Moreover, when input pulse widths exceed 2 ns, it is observed that the tube can attain a saturated output power of 293.1 kW, with negligible disparity between input and output pulse widths. The gyro-TWT can serve as a nanosecond pulse source, with potential applications in fields such as military radar, biomedicine, and microwave chemistry. © 2024 IEEE.

关键词： Military radar

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Dynamic Color Transform Networks for Wheat Head Detection

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Plant Phenomics 2022年第1期4卷 395-408页

作者： Chengxin Liu Kewei Wang Hao Lu Zhiguo Cao Key Laboratory of Image Processing and Intelligent Control Ministry of EducationSchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina

Wheat head detection can measure wheat traits such as head density and head *** wheat breeding largely relies on manual observation to detect wheat heads,yielding a tedious and inefficient *** emergence of affordable camera platforms provides opportunities for deploying computer vision(CV)algorithms in wheat head detection,enabling automated measurements of wheat *** wheat head detection,however,is challenging due to the variability of observation circumstances and the uncertainty of wheat head *** this work,we propose a simple but effective idea—dynamic color transform(DCT)—for accurate wheat head detection.

关键词： Wheat breeding wheat

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Mars Terrain Segmentation Algorithm Based on Improved PSPNet

Mars Terrain Segmentation Algorithm Based on Improved PSPNet

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2023 International Conference on Optics and Machine Vision, ICOMV 2023

作者： Zhou, Peng Xiong, Kai Beijing Institute of Control Engineering Beijing100090 China Science and Technology on Space Intelligent Control Laboratory Beijing100094 China

ISBN: (纸本)9781510664777

Planet rovers are becoming more and more crucial as deep space exploration missions develop. Accurate terrain segmentation can increase the rovers' capacity for independent detection. At present, the task of Mars terrain segmentation is difficult and the computational resources on rover are limited. This paper proposes an improved PSPNet algorithm for Mars terrain segmentation. MobileNetV2 is a lightweight network that replaces ResNet as the feature extraction backbone network. The channel attention mechanism SEnet is integrated into the network structure to improve the network's feature extraction capability. The experimental results show that the number of parameters and calculation amount of M-PSPNet are greatly reduced when compared to traditional PSPNet, but the recall rate of M-PSPNet on soil, bedrock, sand, and big rock can reach 92%, 91%, 86%, and 72%, respectively. Engineering-wise, the M-PSPNet is competitive. © 2023 SPIE. All rights reserved.

关键词： Rovers

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Two performance indicators of reaction wheel underactuated configuration 1

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19th Chinese Intelligent Systems Conference, CISC 2023

作者： Xie, Jun Feng, Jia-Jia Zhang, Yu-Jie Chen, Qiang Beijing Institute of Control Engineering Beijing100190 China Science and Technology on Space Intelligent Control Laboratory Beijing100190 China

ISBN: (数字)9789819968824

ISBN: (纸本)9789819968817

It is of great engineering significance to study the underactuated configuration of reaction wheels. Aiming at the problem of how to effectively improve the control performance of the control system, this paper proposes two performance optimization indicators in the reaction wheel underactuated configuration from the control mechanism of the underactuated control, which provides a reference for the optimization design of the reaction wheel underactuated configuration. The two performance indicators are the area of the actuated Euler axis and the error angle of the underactuated axis. The simulation analysis of the performance indicators is carried out for an engineering example. The results show that the optimization of the two performance indicators proposed in this paper can effectively improve the control performance of the system under underactuated control. It is proved that the two performance optimization indicators proposed in this paper are feasible and effective, and have certain engineering application value. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

关键词： Benchmarking

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Multi-Satellite Mission Planning Method for Dynamic Targets Based on Reinforcement Learning

Multi-Satellite Mission Planning Method for Dynamic Targets ...

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2023 China Automation Congress, CAC 2023

作者： Liu, Yilong Zhang, Cong Zhang, Sihang Li, Jiaxing Beijing Institute of Control Engineering Beijing China Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory Beijing China

ISBN: (纸本)9798350303759

The autonomous mission planning problem of space targets tracking with multi-satellite is studied in this paper. For effective evaluation of different candidate tracking resource combinations, a tracking performance evaluation model based on GDOP is proposed firstly, then a tracking priorities evaluation model for maneuverable dynamic targets is designed to autonomous evaluate and update the planning priorities during the tracking. To solve the problem of conflict resolution of tracking resources scheduling, the reinforcement learning algorithm is applied, considering of restricted computation resources onboard. A pointer network is utilized as the strategy model, with the tracking targets and corresponding priorities, the tracking performance evaluation of each potential candidate tracking resources combinations as input tensors, and the tracking tasks allocation of multi-satellites will be inferenced by the network accordingly. The actor-critic reinforcement learning algorithm is selected for training. It is shown that the algorithm proposed can formulate better planning strategies than the heuristic method, which reduces the mean tracking error by 21% during the whole tracking process. © 2023 IEEE.

关键词： Reinforcement learning

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The Design and Implementation of Magnetic control of Ultra Quiet control System in Gravity Satellite 10th

The Design and Implementation of Magnetic Control of Ultra Q...

引用

10th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2022

作者： Guan, Bin Liu, Yiwu Liu, Qirui Li, Yan Fan, Jiakun Beijing Institute of Control Engineering Beijing100190 China Science and Technology on Space Intelligent Control Laboratory Beijing100190 China

ISBN: (纸本)9789811999673

In order to obtain gravity field data with high-precision, ultra quiet control should be applied in the attitude control system to reduce the influence of micro vibration caused by attitude control, since the measurement accuracy of the high-precision acceleration of the key load of the gravity measurement satellite has reached the level of 10 - 10m / s 2. A set of ultra quiet control system of magnetic control with high-precision is proposed in the paper, which makes the magnetic control accuracy reach the high-precision level of 0.01mNm and establishes an "extremely quiet" working environment for high-precision acceleration load by improving the geomagnetic field acquisition accuracy and high-precision magnetic torquer control. According to the data analysis of orbit, the result shows that the micro vibration environment of the magnetic control system has reached the ug level. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： control systems

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