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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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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Estimation of smoke echo signal using single-photon lidar 13

Estimation of smoke echo signal using single-photon lidar

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13th International Conference on Information Optics and Photonics, CIOP 2022

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhou, Shuaijun Zhang, Xin Hou, Yue Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic 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)9781510660632

The non-uniform distribution of smoke and laser spot seriously limits the imaging ability of single-photon lidar through smoke. To this end, based on the collision theory between photons and smoke particles, this paper establishes the time-domain distribution model of scattered photons (Gamma), which considers the lidar system parameters and the characteristics of smoke particles. The shape parameter and inverse scale parameter are defined as the maximum scattering number K and the average scattering number β, respectively. The indoor test effectively illustrates the estimation ability of the model for smoke. The parameter estimation results show that the average scattering number β and the maximum scattering number K increase linearly with the increase of attenuation coefficient. This study is of great significance for the suppression of smoke backscattering and is expected to improve the weather adaptability of single-photon lidar. © 2022 SPIE.

关键词： Backscattering

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Distance estimation of obstacles in monocular vision based on deep learning 8

Distance estimation of obstacles in monocular vision based o...

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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Shan, Liu Ming, Li Long Hui, Wei Dong Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China China Aerospace Science and Industry Corporation Limited Beijing100048 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

Aiming at the forward-looking distance perception requirements of obstacles such as mountains, forests and trees during the ultra-low-altitude flight of subsonic aircraft, an obstacle distance estimation method based on deep learning is proposed. Firstly, the relationship between adjacent hyper-pixels is modeled by the conditional random fields, the neural network model is trained using the data set, and then the loss function of the pose parameter regression is designed, and the representation of the neural network model is input to the constructed loss function to optimize the weight of the regression model. Simulation experiments show that the proposed method can effectively perceive obstacles within 3km ahead, and the distance estimation error is not more than 20% of the relative distance, which can meet the obstacle avoidance requirements of most sudden obstacles during ultra-low-altitude flight. © 2022 SPIE

关键词： Vision

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Fixed-Time Consensus-Based Nash Equilibrium Seeking

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 267-269页

作者： Mengwei Sun Jian Liu Lu Ren Changyin Sun the Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the School of Artificial Intelligence and the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationAnhui UniversityHefei 230601China

Dear Editor,This letter examines the fixed-time stability of the Nash equilibrium(NE)in non-cooperative *** propose a consensus-based NE seeking algorithm for situations where players do not have perfect information and communicate via a topology *** proposed algorithm can achieve NE in a fixed time that does not depend on initial conditions and can be adjusted in advance.

关键词： Fixed seeking letter

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Research on Intelligent Credibility Evaluation Method of Aircraft HWIL Simulation system Based on complex Network 17th

Research on Intelligent Credibility Evaluation Method of Air...

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17th Chinese Intelligent systems Conference, CISC 2021

作者： Huapin, Geng Ni, Li Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China Beijing University of Aeronautics and Astronautics Beijing China

ISBN: (纸本)9789811663192

Simulation credibility is an effective means to measure the effectiveness and correctness of simulation, and it is the cornerstone of simulation. According to the uncertainty of physical effect model and the complex interaction of model information in aircraft HWIL simulation system, The idea of time-varying directed weighted network and uncertainty measurement is introduced into the process of credibility evaluation of simulation system based on complex network and credibility evaluation theory;the credibility evaluation model of time-varying topological structure based on uncertainty measurement of model information interaction is established to quantitatively evaluate the credibility of simulation system. Taking a typical HWIL simulation system as an example, the effectiveness of the credibility evaluation method of simulation system based on complex network is fully tested. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hardware-in-the-loop simulation

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Multi-UAV Cooperative Path-planning Under complex Threat Environment

Multi-UAV Cooperative Path-planning Under Complex Threat Env...

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第42届中国控制会议

作者： Zhenchang Liu Yuting Liu Hongyin Zhao Hanchen Lu Mingrui Hao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory

This paper proposes a cooperative path-planning method based on multi-Dubins path segments to meet the penetration requirements of UAVs in a complex threat environment. A pruning strategy is used in path-planning to sift path segments, and the diversity of threat avoidance paths is considered under a reasonable calculation amount. A threat intrusion strategy is designed for no safety path condition, which makes the cooperative path-planning method have excellent robustness. A cooperative path optimization method based on particle swarm optimization is adopted for the path length and collision avoidance *** simulation results show that the UAV cooperative paths can avoid the threat area under any starting and ending points, and path lengths are close to the expected length.

关键词：

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A dual-mode navigation algorithm based on Infrared and SAR information fusion

A dual-mode navigation algorithm based on Infrared and SAR i...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yang, Yanjiao Qu, Guangzhou Li, Bo Ma, Meng Liu, Shuaishuai Chi, Qingxi Beijing Electro-Mechanical Engineering Institute Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Coopration Laboratory Beijing China

ISBN: (纸本)9781665498142

Focused on revising the cumulative error of the SINS, a dual-mode navigation algorithm based on the infrared and SAR information fusion is studied in this paper. The SAR system can provide the SAR image and the information including the distance and the beam direction of the SAR antenna, the infrared system can provide the infrared image and the optical axis direction of the infrared lens. Under the premise of the same direction of the SAR and infrared beam, a navigation algorithm by associating the matching results of the SAR image and infrared image with the digital map is studied, which can be applied to amend the aberration of the SINS in the middle phase. At the same time, the common aperture characteristic and GPS error isolation method are used to isolate the error sub area. The simulation results reveal the validity of the algorithm. © 2021 IEEE.

关键词： fusion infrared information navigation SAR information

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

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

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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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Modeling based on MOGA and the dynamic Ε -SVM for fermentation process

Modeling based on MOGA and the dynamic Ε -SVM for fermentat...

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6th World Congress on Intelligent control and Automation, WCICA 2006

作者： Xuejin, Gao Pu, Wang Chongzheng, Sun Yating, Zhang Huiqing, Zhang Yi, Jianqiang College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100022 China Key Laboratory of Complex System and Intelligence Science Chinese Academy of Sciences Beijing 100033 China

ISBN: (纸本)1424403324

To found the suitable models to describe the behavior of biochemistry systems, the dynamic Ε -SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting the parameters of SVM not only consume time, but also are difficult to find the optimal parameters. The optimal parameters were automatically decided by using multi-object Genetic Algorithm (MOGA). A new modeling method that combined MOGA with the dynamic Ε -SVM was presented. The model for penicillin titer preestimate was developed by it in Matlab6.5 with data collected from real plant. The model possesses the strong capability of fitting and generalization. Experiments show that the dynamic Ε -SVM is superior to the standard SVM modeling method. MOGA is very feasible and efficient too. ©2006 IEEE.

关键词： Fermentation

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