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共 319 条记录，以下是91-100 订阅

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Study on the Radio Frequency Simulation Method of Moving Ship for UAV-Borne Imaging Radar 18th

Study on the Radio Frequency Simulation Method of Moving Shi...

引用

18th Chinese intelligent systems Conference, CISC 2022

作者： Diao, Guijie Gong, Ningbo Ni, Hong Liu, Zhe Tong, Jiahui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100190 China Beijing Electro-Mechanical Engineering Institute Beijing100083 China

ISBN: (纸本)9789811962257

A radio-frequency (RF) simulation method for UAV-borne imaging radar for moving ships at the sea-surface is proposed, which mainly solves the RF radar echo simulation problem for moving target at sea-surface. Based on the electromagnetic (EM) scattering model of sea-surface and ship target, the time-varying sea-surface scattering echo and moving ship target scattering echo are established respectively. Then, the scattering echo of a composite scene consisting of sea-surface background and ship-target is obtained by vector summation. Finally, the RF simulation system based on microwave anechoic chamber is constructed, and the simulation tests are carried out. Simulation results are presented to demonstrate the validity and applicability of the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar imaging

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Research on Cooperative Multi-constraint Guidance Law for Leader-Follower Multi-aircraft 21st

Research on Cooperative Multi-constraint Guidance Law for Le...

引用

21st Asia Simulation Conference, AsiaSim 2022

作者： Xin, Du Guijie, Diao Zhe, Liu Ningbo, Gong Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811991974

In this paper, the design and optimization of multi-aircraft cooperative guidance law with multi-constraint is studied for high-speed and large maneuvering targets. Firstly, the motion of the aircraft and the target are analyzed in the inertial coordinate system. The relative motion model and the corresponding state equation are established in a plane. Then, based on the sliding mode control method, the multi-constrained ballistic forming guidance law of the lead aircraft is designed to make it hit the target in multiple dimensions. Finally, the aircraft-to-target range and line-of-sight angle of the aircraft are selected as the state variables to be controlled, and the multi-constrained cooperative guidance law is designed for the follow aircraft. So that the motion of follow aircraft can track the lead aircraft accurately, the controlled state variables converges quickly, and hit the target at the same time until the end. The simulation results show that the leader-follower cooperative guidance law designed in this paper is effective for intercepting high-speed and large maneuvering targets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sliding mode control

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Weak-Model Based Reinforcement Learning control Strategy of Aircraft Attitude system

Weak-Model Based Reinforcement Learning Control Strategy of ...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Huang, Dingcui Hu, Jiangping Peng, Zhinan Hao, Mingrui School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

intelligent aircraft control is an important strategic development trend. Traditional aircraft control algorithms have a strong dependence on the system models, and it is difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, an online intelligent controller design based on a weak-model reinforcement learning technology is proposed to solve stabilization problem of an aircraft. The control problem is firstly converted to an optimal control problem, then an adaptive dynamic programming (ADP) technology is applied for computing the corresponding nonlinear Hamilton-Jacobi-Bellman equation (HJB) equation. Then, actor-critic neural networks structures are established to learn the optimal controller online where only partial information of the aircraft dynamics is required. The proposed control strategy enables the aircraft to adjust and update its control strategy on-line according to the actual mission targets and environments, such that the requirements of autonomous learning and intelligent operation can be realized. Finally, simulation example is offered to validate the effectiveness of the proposed weak-model based controller design. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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An Algorithm of INS Error Correction Base on the Intermittent Label Measurement and the Analysis of Its Influencing Factors

An Algorithm of INS Error Correction Base on the Intermitten...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Peng, Siting Qian, Zhao Ma, Yichao Song, Zhichao Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

Integrated navigation technology is widely used in aviation, aerospace, sailing and other ground-based navigation equipment, the inertial navigation system (INS) is the most common tool. In practice, the key to navigation is precise position, and the position is cooperated with the image matching. According to the label results after image matching, the position of sensor can be calculated. However, the label results cannot be get in every period, what’ more, he output results of the inertial navigation system (INS) is with big error, thus the article studied an algorithm of INS error correction based on the intermittent label measurement, in which the cubature kalman filter is used. After that, it also studied the influencing factor of the labels, such as the label error by match, the count of label, the area of label, thus the INS positioning error can be reduced in line with the engineering guarantee. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Error correction

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Experimental research on GM-APD LIDAR point cloud classification algorithm based on deep learning

Experimental research on GM-APD LIDAR point cloud classifica...

引用

2022 Applied Optics and Photonics China: Advanced Laser technology and Applications, AOPC 2022

作者： Jiang, Yanze Sun, Jianfeng Ding, Yuanxue Jiang, Peng Zhang, Hailong Li, Sining Zhou, Shuaijun National Key Laboratory of Science and Technology on Tunable Laser Institute of OptoElectronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510662223

Geiger mode Avalanche Photo Diode (Gm-APD) array lidar is a lidar that can perform single-photon detection. It offers a wide range of applications due to its low power consumption, small size, and extended detecting distance. There haven't been many research on this detector's target classification because of its late development and small detector array. The classification technique based on the Gm-APD array lidar point cloud is the focus of this paper's research: Firstly, the Gm-APD array lidar is utilized to perform imaging tests on four targets from various angles in order to create a target classification *** that, several data preprocessing methods were chosen and implemented based on the characteristics of the obtained data, such as filling in missing values, performing range image and intensity image interpolation, using the principle of keyhole imaging to convert the range image to point cloud data, realizing the information fusion of distance image and intensity image, and using multiple point cloud data enhancement methods. Finally, the point cloud classification networks PointNet and PointNet++ are trained on point cloud data with varying levels of preprocessing, the results are compared and analyzed, and the impact of different preprocessing methods on the classification accuracy of the two networks is determined. Inferences were made and experiments were carried out to verify the inferences. The data set preprocessing method with the highest classification accuracy of the two networks is discovered, laying the groundwork for future Gm-APD lidar target classification and detection research. © 2023 SPIE.

关键词： Optical radar

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Design and simulation of a two-stage linear inverted pendulum control system based on fuzzy LQR control

Design and simulation of a two-stage linear inverted pendulu...

引用

International Symposium on Autonomous systems (ISAS)

作者： Siting Peng Jun Ren Lei Li Yichao Ma Zhichao Song Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory The Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

This paper introduces in detail the origin of the development of automatic control methods, applications and current research hotspots. It also introduces some control methods commonly used in industrial and agricultural production, and expounds the current application hotspots and new advanced control methods that are developing rapidly. The background, current situation and classification of the inverted pendulum platform are introduced in detail. In the first chapter, the LQR method in modern control theory is introduced in detail. The influence of parameters is analyzed through simulink space modeling and simulation control experiment. At the same time, the real-time experiment is also done in combination with the hardware platform. In the second chapter, the fuzzy control theory in intelligent control is introduced in detail. By combining fuzzy control with LQR method, suitable LQR parameters are calculated by pole assignment. After proper adjustment, reasonable fuzzy rules are adopted and adaptive fuzzy control principle is applied to adjust the control situation in real time. Using simulink space modeling, a good simulation control effect is obtained. Finally, the summary is made.

关键词： Fuzzy control Analytical models Adaptation models Quantization (signal) Production Aerospace electronics Real-time systems

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A Novel Attitude controller for Hypersonic Aircraft Based on FR-PI2

A Novel Attitude Controller for Hypersonic Aircraft Based on...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Fan, Jiajun Li, Tianyi Guo, Xian Hao, Mingrui Sun, Mingwei College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811581540

Due to the uncertainties and various noises of the Hypersonic Aircraft(HA), traditional method of designing attitude controllers based on accurate models faces immense challenges. To solve those proposed urgent problems effectively, in this paper, a innovative data-driven RL algorithm called FR-PI2 is proposed for the task of Hypersonic Aircraft attitude control, wherein several key techniques are introduced. Firstly, Hypersonic Aircraft attitude control is transformed into a stochastic optimal control problem, and the numerical solutions of the proposed stochastic optimal control problem are obtained with a path-integral-based method, called Policy Improvement with Path Integrals(PI2). Secondly, a model-free policy parameterization method with PID controller is integrated into the PI2 algorithm to ensure a low dependency of the Hypersonic Aircraft system model. Thirdly, a brand-new sample filtration method is proposed to guarantee rapid convergence, and an online optimization technology called rolling optimization is applied to guarantee optimality and real-time performance. Two series of experiments are carried out and analyzed to demonstrate the outstanding performance of the FR-PI2 algorithm. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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A Multimodal Image Matching Algorithm Based on Structure Feature 1

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Wang, Xing Zhao, Jiajia su, Ang Guan, Banglei Dong, Jing Han, Songlai Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China Research Institution of Aerospace Technology Central South University Changsha410083 China

ISBN: (数字)9789811966132

ISBN: (纸本)9789811966125

Multimodal image matching is a crucial technique for aircraft navigation in GPS denied environment. However, the nonlinear radiometric difference between multimodal images and significant image noise make this task considerably challenging. A multimodal image registration algorithm build on structural features is presented. The method can also accurately extract structural features in the case of severe noise distortion. Besides, A similarity measure method based on parallelism is presented for adapting nonlinear grayscale distortion. The evaluation show that the algorithm has significant superiority over other state-of-the-art algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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Collaborative Mission Planning for UAV Swarms Launched from Aerial Carriers

Collaborative Mission Planning for UAV Swarms Launched from...

引用

International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Yuan, Mingzhou Dong, Bo Yao, Weiran School of Astronautics Harbin Institute of Technology Harbin 150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing 100074 China Intelligent Science and Technology Academy Limited of China Aerospace Science and Industry Corporation (CASIC) Beijing 100043 China

ISBN: (纸本)9789819622115

This paper takes the aerial carriers to launch UAV swarms as the background, aims to minimize the total flight distance of the UAV swarms, and proposes a clustering-launching-planning solution framework. Aiming at the scenario where UAVs adopt Dubins curve trajectories, a Dubins-KMeans clustering algorithm based on the Dubins curve length as the similarity measure is proposed. To ensure the shortest distance for air carriers to traverse each cluster, a two-part genetic algorithm is used to solve this MTSP problem and find the optimal order for air carriers to traverse each cluster. Ultimately, the energy efficiency of the entire unmanned system is optimized. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Dubins-KMeans clustering algorithm Launching UAVs two-part genetic algorithm

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Attention-enhanced Relation Network for Few-shot Image Classification 23

Attention-enhanced Relation Network for Few-shot Image Class...

引用

6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Li, Jinyang Tong, Jiahui Gao, Guangyu Xu, Wenbin School of Computer Science and Technology Beijing Institute of Technology China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Optical Radiation Laboratory Beijing Institute of Environmental Characteristics Beijing100854 China

ISBN: (纸本)9781450398572

Traditional deep learning models firmly rely on a large amount of labeled data during pre-training. Whereas it lacks generalization in the face of unfamiliar categories. Recently, few-shot learning is a hot topic in computer vision to classify unseen classes with limited labels. A representative approach is to extract features from the support and query sets, respectively, and compare similarities via metric learning. However, convolutional neural networks often focus only on a local region and ignore the global region, which severely reduces the accuracy of the matching. Specifically, in this paper, we pile lightweight attention-based blocks in the embedding module, which combines an adaptive kernel size 2D convolutional network with a cross-channel attention mechanism to encode multi-scale features and implicitly increase the receptive field. The SE-relation module chooses to construct learnable non-linear comparators to compare the relationship utilizing channel information. Finally, we show experimental results on standard few-shot testing benchmarks such as mini-ImageNet and tiered-ImageNet to demonstrate effectiveness. © 2023 ACM.

关键词： Image classification

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