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A Multimodal Image Matching Algorithm Based on Structure Feature 1

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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Reinforcement learning-based three-dimensional cooperative guidance law

Reinforcement learning-based three-dimensional cooperative g...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Zhen Gu Zeqi Zhang Honglong Kang Jianfeng Li Keyuan Yue Shenmin Song 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: (数字)9798350373691

ISBN: (纸本)9798350373707

An innovative three-dimensional cooperative guidance law for striking stationary target, based on proximal policy optimization (PPO), is introduced. This novel guidance law directly correlates engagement state information with the navigation ratio of proportional navigation guidance (PNG). Initially, the cooperative homing guidance problem is transformed into a Markov decision process, and the reward function incorporates considerations for the zero-effort-miss (ZEM) and the consensus error of time-to-go. Subsequently, the cooperative homing guidance problem is transposed into the framework of reinforcement learning (RL). Ultimately, the effectiveness of the cooperative homing guidance solution is validated through numerical simulations, encompassing agent model training and Monte Carlo cases.

关键词： Training Monte Carlo methods Navigation Markov decision processes Reinforcement learning Numerical simulation Robustness

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Research on Depth Estimation Method of Single Aerial Image 6

Research on Depth Estimation Method of Single Aerial Image

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6th IEEE Information technology, Networking, Electronic and Automation control Conference, ITNEC 2023

作者： Gao, Wang Pu, Lin Li, Lei Deng, Fei Bie, Lingzhi Beijing Institute of Mechanical and Electrical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Wuhan University School of Geodesy and Geomatics Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

ISBN: (纸本)9781665460033

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. The results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. The image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information. © 2023 IEEE.

关键词： Antennas

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An Adversarial Defense Algorithm Based on Triplet Network and Voting Decision

An Adversarial Defense Algorithm Based on Triplet Network an...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Zheng, Haonan Zhao, Jiajia Tan, Wei School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In the field of artificial intelligence, neural network is one of the key technologies used for image classification and recognition. However, recent work has demonstrated that deep neural networks are easily attacked by adversarial examples to make misjudgments. Adversarial examples are almost indistin-guishable from normal examples and yet cannot be classified correctly by neural networks. The existence of adversarial examples is a major obstacle to the practical application and deployment of neural networks, so the research on adversarial defense algorithms is an important topic in the field of AI security. This paper proposes an adversarial example defense algorithm based on a triplet network and voting decision mechanism. Firstly, two neural networks with different structures are trained based on normal dataset. Secondly, the first network is fine-tuned using the adversarial examples generated by these two networks, resulting in a third neural network. Then, these three neural networks are used as sub-networks in parallel to construct a triplet network. Through adversarial training and differences in structures, the transferability of adversarial examples among the three sub-networks is weakened. Finally, the final classification result is obtained by majority voting, based on the parallel output results of the three sub-networks. Through the complementarity between these three sub-networks, the defense against adversarial examples is realized. The experimental results demonstrate the effectiveness of this algorithm. © 2022 IEEE.

关键词： Deep neural networks

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Collaborative Mission Planning for UAV Swarms Launched from Aerial Carriers

Collaborative Mission Planning for UAV Swarms Launched from...

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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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A Comparative Study on Adversarial Attacks for Visible and Infrared Images

A Comparative Study on Adversarial Attacks for Visible and I...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Guo, Haiwang Tan, Wei Zhao, Jiajia School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Agent Cooperation Laboratory Science and Technology on Complex System Control and Intelligent Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In recent years, the booming development of artificial intelligence has driven the development and progress of society. With its excellent performance, deep learning has been widely used in many fields, including some security-sensitive fields such as unmanned systems, auto-driving and so on. Research has found that deep neural networks are vulnerable to adversarial samples, which can lead to misclassification of neural networks and can cause serious safety incidents. Hence, the study of adversarial samples has received increasing attention, and researchers have conducted studies from different perspectives, and relevant research results have emerged. However, most of these studies have focused on visible images, and few have studied infrared images, which play an important role in military and other important fields. In this paper, a comparative study on adversarial attacks for visible and infrared images is presented. A number of adversarial attack experiments are conducted on ResNet18 and VGG16 models for visible and infrared images. By comparing the experimental results, the characteristics of infrared adversarial samples are derived relative to those with visible adversarial samples. Then, a gradient attack method from a frequency domain perspective is proposed. The adversarial perturbation noise is added to the low frequency component of images. It is verified experimentally that the proposed method improves the transferability of infrared adversarial samples compared to some baseline methods. © 2022 IEEE.

关键词： Deep neural networks

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Active Disturbance Rejection Gain Scheduling control of Hypersonic Vehicle Based on Guardian Maps

Active Disturbance Rejection Gain Scheduling Control of Hype...

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Data Driven control and Learning systems (DDCLS)

作者： Tingyu Zhang Yongshuai Wang Mingwei Sun Mingrui Hao Zengqiang Chen College of Artificial Intelligence Nankai University Tianjin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper presented an adaptive gain scheduling algorithm for hypersonic vehicles with wide envelopes. First, the linear parameter variable parameter (LPV) model of hypersonic vehicles is established in the flight envelope. Then, the active disturbance rejection controller is considered to cope with disturbances and uncertainties, and the control gain is scheduled using the guardian maps method to adapt to the wide envelope of velocity and height. Finally, numerical simulation results show good control performance and meet the required performance indexes in all operating conditions, demonstrating the effectiveness and robustness of the proposed method.

关键词： Uncertainty PI control Scheduling algorithms Atmospheric modeling Numerical simulation Scheduling Robustness

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Stabilization of linear systems with multiple unknown time-varying input delays by linear time-varying feedback

arXiv

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arXiv 2025年

作者： Zhou, Bin Zhang, Kai Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China

This paper addresses the stabilization of linear systems with multiple time-varying input delays. In scenarios where neither the exact delays information nor their bound is known, we propose a class of linear time-varying state feedback controllers by using the solution to a parametric Lyapunov equation (PLE). By leveraging the properties of the solution to the PLE and constructing a time-varying Lyapunov-Krasovskii-like functional, we prove that (the zero solution of) the closed-loop system is asymptotically stable. Furthermore, this result is extended to the observer-based output feedback case. The notable characteristic of these controllers is their utilization of linear time-varying gains. Furthermore, they are designed entirely independent of any knowledge of the time delays, resulting in controllers that are exceedingly easy to implement. Finally, a numerical example demonstrates the effectiveness of the proposed approaches. © 2025, CC BY.

关键词： State feedback

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An autonomous path planning method considering terrain aided navigation constraints

An autonomous path planning method considering terrain aided...

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2022 Chinese Automation Congress, CAC 2022

作者： Jiang, Min Xu, Cheng Ji, Hua Wang, Yuqi Engineering Institute Beijing Electro-Mechanical Bejing China Beijing Electro-Mechanical Engineering Institute System Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex Bejing China

ISBN: (纸本)9781665465335

In order to solve the autonomous path planning problem with terrain aided navigation constraints, a navigation-first path planning method was adopted, that is, the distribution of terrain matching regions and the drift of navigation errors were given priority, and the path planning problem was transformed into the shortest path problem of single source directed graph to determine the nodes on the path. Secondly, the path planning between adjacent nodes is transformed into a path planning problem with initial direction constraint and terminal direction freedom/constraint, and the lateral path is smoothed. Finally, for the local path passing through the no-fly zone, the obstacle avoidance path planning with initial and terminal direction constraints is carried out based on convex optimization method. The simulation results show that the autonomous path planning method considering terrain aided navigation constraints can plan the shortest flight path under the constraints of navigation accuracy, maneuverability and no-fly zone. © 2022 IEEE.

关键词： Motion planning

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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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