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2021 China Automation Congress, CAC 2021

作者： Wang, Zijian Hou, Mingzhe Hao, Mingrui Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665426473

In this paper, the problem of anti-disturbance, anti-saturation and fixed-time control for a class of telescopic wing morphing aircraft is studied. The telescopic wing morphing aircraft treats the variable wingspan as an extra control input to construct the dynamic model of the morphing-aided maneuver. According to the model characteristics, the controller design is divided into two loops: the speed loop and the attitude loop. Through a fixed-time continuous feedback control scheme, fixed time of the tracking reference trajectory is ensured. By combining the integral sliding mode control (ISMC) method with super-twisting control (STC), the uncertainties of aerodynamic coefficients and external disturbances are overcome. In addition, the anti-saturation problem of the aircraft actuator is solved by the initial solution correction method based on Null-space augmented solutions. The simulation result shows that the designed algorithm has great tracking performance, while the robustness and anti-saturation performance are guaranteed. © 2021 IEEE

关键词： Robust control

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Research on Simulation Method of Space-Ground Consistency for UAV Cluster Combat

Research on Simulation Method of Space-Ground Consistency fo...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Qing, Zhang Jing, Li Jiahui, Tong Jian, Han Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

The Space-ground consistency of the unmanned aerial vehicle (UAV) cluster combat distributed interactive simulation system is the fundamental guarantee to simulate and reproduce the authenticity and correctness of UAV cluster combat mission, combat environment and combat process. This paper analyzes the common inconsistency problems of UAV cluster combat distributed simulation system, gives the technical connotation of the space-ground consistency of UAV cluster combat simulation, deeply analyzes all kinds of factors that affect the consistency of UAV cluster combat simulation space and ground, and puts forward the control methods of time-space consistency of UAV cluster combat simulation system, the control strategies and suggestions of model consistency and service consistency. It provides a theoretical basis and technical support for the construction of distributed interactive simulation system for UAV cluster combat. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Cross-cycle iterative unmanned aerial vehicle reentry guidance based on reinforcement learning

Cross-cycle iterative unmanned aerial vehicle reentry guidan...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Cheng, Yang Shui, Zunshi Xu, Cheng Feng, Tianyu Jiang, Yiyang Beijing Aerospace Technology Research Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

The traditional predictive correction algorithm requires a large number of iterative calculations for the predicted trajectory, which greatly occupies a large amount of computing resources, so that the real-time solution of the guidance command can not be guaranteed, and the guidance accuracy will have a large impact. And the prediction correction guidance requires the algorithm to have the ability of selfadaptation and intelligent learning. Therefore, this paper proposes a cross-cycle iterative hypersonic UAV predictive correction guidance method based on reinforcement learning. The parametric control variable (CVP) method is used to construct the parametric model of the guidance command. The actor-critic-based reinforcement learning method is used to solve the guidance command in real time, and the guidance information is effectively transmitted in the adjacent guidance solution cycle. The guidance error converges to within the allowable accuracy range during the cross-cycle iteration. Monte Carlo simulation shows that the proposed method has good adaptability to initial conditions and flight parameter uncertainty, and can guarantee the real-time performance of the guidance command while achieving high-precision guidance. © 2019 IEEE.

关键词： Reinforcement learning

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Relative navigation method for unmanned aerial vehicles formation using consensus unscented Kalman filter 6

Relative navigation method for unmanned aerial vehicles form...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Zhuang, Zhixing Gong, Baichun Ding, Xin Hao, Mingrui Chen, Linxiu Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

A relative navigation method in which the measurement information between aircraft only has distance or angle was proposed to achieve accurate relative navigation between aircraft formations in the global navigation satellite system (GNSS) Denied Environment. In addition, four relative measurement schemes are analyzed. An augmented state is introduced in the relative navigation system model, and the observability analysis of the navigation system is carried out relying on the Lie derivative theory, which gives the limitation of motion: the relative position and velocity of the aircraft cannot be parallel or zero, and a single aircraft cannot keep flying straight. A consensus unscented Kalman filter (CUKF) algorithm is established using the geometric characteristics in flight. The observability of the system state is improved after using the additional constraint. Finally, a standard Monte Carlo simulation system is established, and the system simulation is carried out, which shows that the Observability analysis is verified to be correct, and the algorithm demonstrates high accuracy. © 2023 IEEE.

关键词： Observability

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EPM-Net: A better way for optical and infrared scene matching via edge point 12

EPM-Net: A better way for optical and infrared scene matchin...

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SPIE 12th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2023

作者： Huang, Shixiang Chi, Longyun Fu, Wenxing Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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A GPR-Aided Method for Collaborative Relative Navigation for Multiple Unmanned Aerial Vehicles During Ranging Measurement Outages 6

A GPR-Aided Method for Collaborative Relative Navigation for...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Ding, Xin Hao, Mingrui Gong, Baichun Chen, Linxiu Zhuang, Zhixing Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

To maintain reliable relative navigation accuracy of unmanned aerial vehicles (UAVs) during range measurement outages, a GPR-aided ranging method is proposed to assist the extended Kalman filter for measurement updates. Specifically, when the on-board ranging measurement is available, a Gaussian process regression (GPR) algorithm is used to train the mapping model between acceleration, angular velocity of the inertial navigation system (INS), relative position, and the ranging distance. When ranging measurement is unavailable, the trained GPR algorithm is used for distance prediction, replacing the ranging measurement and being used for consensus extended Kalman filter (CEKF) measurement update to reduce the degree of relative navigation error divergence. Numerical simulation was conducted with three UAVs performing cooperative flight, the results show that the proposed algorithm can provide reliable distance prediction during ranging outage and effectively reduce the divergence of relative state estimation error. © 2023 IEEE.

关键词： Inertial navigation systems

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Scribble-Supervised Video Object Segmentation

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 339-353页

作者： Peiliang Huang Junwei Han Nian Liu Jun Ren Dingwen Zhang Brain and Artificial Intelligence Laboratory School of AutomationNorthwestern Polytechnical UniversityXi’an 710072China IEEE Department of Engagement Services Mohamed Bin Zayed University of Artificial IntelligenceAbuDhabiUnited Arab Emirate Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory BeijingChina

Recently,video object segmentation has received great attention in the computer vision *** of the existing methods heavily rely on the pixel-wise human annotations,which are expensive and time-consuming to *** tackle this problem,we make an early attempt to achieve video object segmentation with scribble-level supervision,which can alleviate large amounts of human labor for collecting the manual ***,using conventional network architectures and learning objective functions under this scenario cannot work well as the supervision information is highly sparse and *** address this issue,this paper introduces two novel elements to learn the video object segmentation *** first one is the scribble attention module,which captures more accurate context information and learns an effective attention map to enhance the contrast between foreground and *** other one is the scribble-supervised loss,which can optimize the unlabeled pixels and dynamically correct inaccurate segmented areas during the training *** evaluate the proposed method,we implement experiments on two video object segmentation benchmark datasets,You Tube-video object segmentation(VOS),and densely annotated video segmentation(DAVIS)-*** first generate the scribble annotations from the original per-pixel ***,we train our model and compare its test performance with the baseline models and other existing *** experiments demonstrate that the proposed method can work effectively and approach to the methods requiring the dense per-pixel annotations.

关键词： Convolutional neural networks(CNNs) scribble self-attention video object segmentation weakly supervised

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A LSTM-based method for simulation execution validity evaluation 33

A LSTM-based method for simulation execution validity evalua...

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33rd European Modeling and Simulation Symposium, EMSS 2021

作者： Wang, YuLun Li, Wei Li, Jing Control and Simulation Center Harbin Institute of Technology Harbin150080 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

This paper improves the concept of simulation execution validity and a methodology to assess the complex simulation system. As the complexity of the simulation system gradually rises, the magnitude of the simulation data obtained continues to increase, which makes it extremely difficult for experts to provide expert knowledge to evaluate the execution validity of the simulation system. More precisely, the essence of execution validity is to dig out the hidden relationships in the simulation time series data and complete the classification task whether it is valid. Considering that machine learning can better complete the two tasks of mining data features and classification, this paper adopts long short-term memory, a neural network used to process time series data, to evaluate the execution validity. Finally, an experiment is conducted on a simulation system, and the results show that the evaluation method based on LSTM can accurately evaluate the validity of the simulation system, and can greatly improve the efficiency of evaluation. © 2021 The Authors.

关键词： Long short-term memory

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Phase Unwrapping Based on CFAR Detection for Multi-baseline InISAR

Phase Unwrapping Based on CFAR Detection for Multi-baseline ...

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2021 CIE International Conference on Radar, Radar 2021

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

ISBN: (纸本)9781665498142

A phase unwrapping method based on constant false alarm rate (CF AR) detection is proposed for multi-baseline interferometric inverse synthetic aperture radar (InISAR). Aiming at the problem of ambiguity number estimation error under the condition of phase noise, Chinese remainder theorem (CRT) and cluster analysis are utilized to acquire the probability distribution of phase noise. By introducing CFAR detection, the novel method reduced the error probability of ambiguity number estimation. Through simulation, it is verified that the novel method can effectively suppress phase noise and obtain accurate phase unwrapping results. © 2021 IEEE.

关键词： CFAR multi-baseline InISAR interferometric phase phase noise phase unwrapping

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Image Matching Method for SAR and Optical Image Based on Siamese Network 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

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

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

Aiming at the difficulty of the similarity extraction between the SAR and optical satellite image, an image Matching method for SAR and Optical image based on siamese network is studied. The radar system can provide SAR images while also providing SAR distance and other measurement information. Optical satellites can obtain real-time optical images and provide corresponding longitude and latitude information. Based on the satellite positioning algorithm, the cumulative error of sins can be corrected by kalman filter using SAR and optical image matching results and SAR measurements. Simulation results show the effectiveness of the algorithm. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Synthetic aperture radar

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