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A New Approach to Airborne High Resolution SAR Motion Compensation for Large Trajectory Deviations*

Chinese Journal of Electronics 2023年第4期21卷 764-769页

作者： Dadi MENG Donghui HU Chibiao DING Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China

The Two-step algorithm (TSA) is widely used for trajectory deviation compensation of airborne Synthetic aperture radar (SAR), by which most of the motion errors are compensated before Range curve migration compensation (RCMC) and the residual after the RCMC. We found that the RCMC in the presence of the residual motion errors results in additional range shift errors hard to be compensated for. Based on theoretical investigations, this shortage of TSA is reported and a new compensation scheme which greatly alleviates the RCMC induced errors is proposed. Besides, range resampling considering the residual motion errors is very convinent, which, however, is boresome in TSA. The new method is effective to compensate the high resolution SAR systems for large trajectory deviations, which is hard to be achieved by TSA because of the uncompensated errors. Results on the simulated data are provided to demonstrate the effectiveness of the new method.

关键词： Image resolution Azimuth Motion compensation Trajectory Synthetic aperture radar

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In-plane shear failure behavior and mechanical properties of SiC/SiC Composites 3

In-plane shear failure behavior and mechanical properties of...

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2024 3rd International Conference on Applied Mechanics and Advanced Materials, ICAMAM 2024

作者： Li, Tianshan Yu, Guoqiang Zhou, Shihao Zheng, Zhikang Gao, Xiguang Song, Yingdong Key Laboratory of Aero-Engine Thermal Environment and Structure Ministry of Industry and Information Technology College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Jiangsu Province Key Laboratory of Aerospace Power System College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing210016 China

Fiber-reinforced ceramic matrix composites, especially SiC/SiC composites, have the characteristics of lightweight, high strength, high-temperature resistance, etc., which are ideal structural candidates for aerospace vehicle components, in-plane shear performance is one of the important indicators to characterize the mechanical properties of materials and component assessment, this paper designs and processes the in-plane shear test pieces and test devices and methods to study the shear mechanical behavior under the mechanical properties and failure behavior of SiC/SiC ceramic-based fiber bundle composites are studied under shear mechanical behavior. The results show that matrix cracking and fiber fracture are the main failure modes, and there are two obvious phases in the specimen shear force-displacement curves, and fiber fracture is the main cause of strain in the specimen. © Published under licence by IOP Publishing Ltd.

关键词： Ceramic matrix composites

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Model-Based Reinforcement Learning for Robotic Arm control with Limited Environment Interaction 13

Model-Based Reinforcement Learning for Robotic Arm Control w...

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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Chen, Yi Sun, Xiao Zheng, Song Huang, Weibing Zeng, Sheng Chen, Dan Xu, Zhezhuang College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Shenzhen Guangdong518000 China

ISBN: (纸本)9798350315196

Reinforcement Learning (RL) has been applied to robotic arm control, which enables the agent to learn an effective policy to solve complex tasks. However, it requires constant interaction with the environment leading to low sample efficiency. In this paper, we propose a robotic arm control approach based on planning via lookahead search, which is a model-based RL algorithm to improve the sample efficiency. The approach builds an environment model in order to obtain the dynamics of the environment. Thus the model can be used to plan future actions by a tree-based search. The experiments show that our approach can solve the task of robotic arm control with less environmental samples. © 2023 IEEE.

关键词： Robotic arms

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Optimal Linear Attack in Cyber-Physical systems with Periodic Detection

Optimal Linear Attack in Cyber-Physical Systems with Periodi...

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IEEE Conference on Decision and control

作者： Jia Qi Chongrong Fang Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Security issues are of significant importance for cyber-physical systems (CPS), where the attack design is a major concern. Most related studies on attack design implicitly consider that the control period and detection period are the same. However, the two periods could be different in practical systems with remote detection such as supervisory control and data acquisition (SCADA) systems, which could lead to new vulnerabilities for attackers. In this paper, we consider the design of innovation-based linear attack strategies for CPS when the control period and detection period are inconsistent. Specifically, we propose an attack framework that consists of attack strategies for detection and non-detection instants under the period discrepancy. On this basis, we design the optimal stealthy innovation-based linear attack strategies for state estimation and LQG control to maximize the estimation error or control cost, respectively. Simulations are given to demonstrate the effectiveness of the proposed attack strategies.

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LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Point Cloud Heat Map

arXiv

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arXiv 2024年

作者： Wu, Xinrui Xu, Jianbo Hu, Puyuan Wang, Guangming Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom

— Localization using a monocular camera in the pre-built LiDAR point cloud map has drawn increasing attention in the field of autonomous driving and mobile robotics. However, there are still many challenges (e.g. difficulties of map storage, poor localization robustness in large scenes) in accurately and efficiently implementing cross-modal localization. To solve these problems, a novel pipeline termed LHMap-loc is proposed, which achieves accurate and efficient monocular localization in LiDAR maps. Firstly, feature encoding is carried out on the original LiDAR point cloud map by generating offline heat point clouds, by which the size of the original LiDAR map is compressed. Then, an end-to-end online pose regression network is designed based on optical flow estimation and spatial attention to achieve real-time monocular visual localization in a pre-built map. In addition, a series of experiments have been conducted to prove the effectiveness of the proposed method. Our code is available at: https://***/IRMVLab/LHMaploc. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical radar

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DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation

DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spa...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Huixin Zhang Guangming Wang Xinrui Wu Chenfeng Xu Mingyu Ding Masayoshi Tomizuka Wei Zhan Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Department of Engineering University of Cambridge Cambridge U.K. UC Berkeley Berkeley CA USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure with a spatial information reuse strategy, a sequential pose initialization module, a gated hierarchical pose refinement module, and a temporal feature propagation module. First, spatial features are encoded using a point feature pyramid, with features reused in successive pose estimations to reduce computational overhead. Second, a sequential pose initialization method is introduced, leveraging the high-frequency sampling characteristic of LiDAR to initialize the LiDAR pose. Then, a gated hierarchical pose refinement mechanism refines poses from coarse to fine by selectively retaining or discarding motion information from different layers based on gate estimations. Finally, temporal feature propagation is proposed to incorporate the historical motion information from point cloud sequences, and address the spatial inconsistency issue when transmitting motion information embedded in point clouds between frames. Experimental results on the KITTI odometry dataset and Argoverse dataset demonstrate that DSLO outperforms state-of-the-art methods, achieving at least a 15.67% improvement on RTE and a 12.64% improvement on RRE, while also achieving a 34.69% reduction in runtime compared to baseline methods. Our implementation will be available at https://***/IRMVLab/DSLO.

关键词： Point cloud compression Solid modeling Laser radar Accuracy Three-dimensional displays Runtime Logic gates Robot sensing systems Real-time systems Odometry

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PCB Defect Detection Method Based on Improved RetinaNet 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Xu, Yusheng Cao, Xinrong Hu, Rong Keikhosrokiani, Pantea Li, Zuoyong College of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

In the electronic industry product quality control, PCB defect detection is a crucial part, which has the characteristics of small defect size and high similarity. The existing defect detection methods are still not good enough for detecting small target defects;therefore, the algorithm in this paper proposes an improved algorithm for PCB defect detection based on the RetinaNet model. The ResNet-D residual structure and efficient channel focus module are introduced in the model backbone network to enhance its feature extraction capability and achieve the purpose of improving the detection accuracy. At the same time, the method replaces the original multi-step learning decay strategy with a cosine annealing scheduling learning strategy, which optimizes the training process of the model. Finally, the performance of the method is verified on the publicly available PCB defect dataset from the Open laboratory of Intelligent Robotics, Peking University. The experimental results show that the algorithm improves the mAP value by 3.2% compared with the original algorithm, while the fastest detection speed reaches 36.9 FPS, which can effectively improve the defect detection performance of PCB. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Defects

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Displacement detection method of QR code reference object based on feature points 4

Displacement detection method of QR code reference object ba...

引用

4th IEEE International Conference on Power, Intelligent Computing and systems, ICPICS 2022

作者： Yang, Qiuhui Zhang, Baoxiang Ji, Xiaoyu Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Wuzhou China Faculty of Computer and Electronic Information Guangxi University Nanning China Faculty of Information Technology Macau University of Science and Technology China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the continuous development of construction technology and computer technology, in order to meet the needs of concrete quality management, a real-time monitoring information system based on computer vision is established. The identification label is added to the concrete specimen to prevent the exchange of concrete specimens. According to the needs of the application scene, this paper proposes a new feature point extraction algorithm based on Harris. By improving the positioning accuracy of feature points, it can avoid the interference of background noise points or feature points in unclear focus area on feature matching and the calculation of projection matrix;and a few feature points are used to calibrate the camera, which overcomes the problem that the traditional camera calibration method needs to make a calibration board. Experiments show that the algorithm proposed in this paper has good stability to illumination, camera angle and distractors, and is flexible in application. © 2022 IEEE.

关键词： Quality management

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Electrical resistivity-temperature characteristics enhancement of insulating cross-linked polyethylene composites by incorporating positive temperature coefficient particles with different Curie temperatures

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High Voltage 2023年第1期8卷 1-11页

作者： Guimin Jiang Yuanxiang Zhou Chenyuan Teng Yunxiao Zhang Xin Huang Lei Xue Luming Zhou The Wind Solar Storage Division of State Key Laboratory of Control and Simulation of Power System and Generation Equipment Xinjiang UniversityUrumqiChina State Key Laboratory of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina College of Information Engineering Zhejiang University of TechnologyHangzhouChina School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Incorporating positive temperature coefficient(PTC)ceramic particles into polymers provides a prospective alternative solution for suppressing severe electric field distortions caused by negative temperature coefficient(NTC)of electrical resistivity within polymer insulation in high voltage direct current *** effect of the Curie temperature of PTC particles on the inhibition of the NTC effect of cross-linked polyethylene(XLPE)is investigated in this *** temperature coefficient particles with varied Curie temperatures are surface-modified and melt blending with *** modified particles are dispersed on averagely in the *** electrical resistivity,space charge behaviour,and direct current(DC)electrical breakdown strength of the samples are investigated at different temperatures,exploring the effect of the Curie temperature of PTC particles on suppressing the NTC effect of *** is demonstrated that the reduction in Curie temperature can further suppress the NTC effect of XLPE,enhance the DC strength at elevated temperatures,and inhibit the internal space charge *** reduction in the Curie temperatures means that the initiation of the PTC effect advances,exhibiting a higher potential barrier and inhibiting the NTC effect more *** work may give a reference for improving the temperature stability of DC properties for XLPE cable insulation.

关键词： coefficient resistivity insulation

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Preserving Topology of Network systems: Metric, Analysis, and Optimal Design

arXiv

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arXiv 2023年

作者： Li, Yushan Wang, Zitong He, Jianping Chen, Cailian Guan, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless, recent works have revealed that the topology cannot be preserved under i.i.d. noises in the asymptotic sense. How to effectively characterize the non-asymptotic preservation performance still remains an open issue. Inspired by the deviation quantification of concentration inequalities, this paper proposes a novel metric named trace-based variance-expectation ratio. This metric effectively captures the decaying rate of the topology inference error, where a slower rate indicates better non-asymptotic preservation performance. We prove that the inference error will always decay to zero asymptotically, as long as the added noises are non-increasing and independent (milder than the i.i.d. condition). Then, the optimal noise design that produces the slowest decaying rate for the error is obtained. More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously. Extensions to a general class of noises with multi-lag time dependence are provided. Comprehensive simulations verify the theoretical findings. Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

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