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检索条件"机构=Science and Technology on Complex System Control and Intelligent"

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An Adaptive Power Allocation Scheme for Mini-UAV Tracking with Distributed Radar in Dense Urban Environment 10

An Adaptive Power Allocation Scheme for Mini-UAV Tracking wi...

引用

10th International Conference on control, Automation and Information sciences, ICCAIS 2021

作者： Cao, Ziyi Yuan, Ye Yi, Wei Chen, Linxiu University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665440295

In this paper, a new power allocation scheme of the distributed radar system is proposed for mini-UAV tracking tasks in urban environments, considering the influence of the building occlusion on the probability of detection. Firstly, the probability of detection of each radar node is derived according to the estimated position of the target and the visibility of each radar node. Then, according to the probability of detection, the adaptive cost function concerning the transmit power and tracking accuracy is designed and used to the formulation of the optimization problem. Simulation results show that the proposed power allocation scheme can improve the target tracking accuracy in urban environments compared to the conventional method. © 2021 IEEE.

关键词： Cost functions

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complex-Valued Signal Capsule Network for Automatic Modulation Classification

Complex-Valued Signal Capsule Network for Automatic Modulati...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yang, Shuyuan Feng, Zhixi Wang, Nengguo Bu, Yunong Hu, Hao Luoyang471003 China Xidian University Shannxi China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Most current deep learning (DL) based AMC methods often require a large number of labeled samples to drive itself optimization study, so as to achieve a more superior performance. However, for many AMC tasks with a small amount of data, the AMC method based on deep learning still has many challenges, which makes the deep neural network model trained on a small dataset lack effective migration effect, leading to the failure to achieve better performance effect in the testing process. In this paper, we propose a novel AMC method based on complex-valued Signal Capsule Network (CSCN). Compared with other DL based methods, the proposed CSCN can achieve a better performance under the condition of small dataset and low SNR on the well-known deepsig dataset RML2016.10a and RML2016.10b. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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Event Trigger Mechanism-Based Robust control for Cyber-Physical systems under DoS Attack

Event Trigger Mechanism-Based Robust Control for Cyber-Physi...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Tian, Peng Xu, Huiling Zhao, Jiajia Dong, Lewei Nanjing University of Science and Technology School of Mathematics and Statistics Nanjing210094 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100000 China

ISBN: (纸本)9781665465335

In this paper, the event trigger mechanism-based robust control problem is investigated for cyber-physical systems under denial of service attacks and disturbances. The effects of DoS attacks are regarded as a type of data packet loss. An event trigger mechanism is introduced into the control scheme design to effectively compensate the packet loss data. The robust attenuation technology is composited into control scheme to reduce the impact of disterbances. Then, by modeling the cyber-physical systems under denial of service(DoS) attack as a class of bounded sequential switching system, and constructing the corresponding Lyapunov function, the stability of the system is verified and analyzed. Finally, simulation experiments are given to verify the correctness of the above theoretical results. © 2022 IEEE.

关键词： Sequential switching

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Distributed Multi-Sensor Multi-View Fusion of PHD Filter for Maneuvering Targets

Distributed Multi-Sensor Multi-View Fusion of PHD Filter for...

引用

2021 CIE International Conference on Radar, Radar 2021

作者： Peng, Cong Chai, Lei Yi, Wei Chen, Linxiu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665498142

This paper addresses the problem of maneuvering multi-target tracking by a network of sensors having different and limited fields of view (FoV s). Each local sensor runs the Gaussian Mixture Probability Hypothetical Density (GMPHD) filter. Due to the target maneuver, based on a single motion model, severe tracking performance degradation can be observed. We propose to use multi-model (MM) method to realize the adaptation to motion characteristic so as to overcome maneuverability of targets. Then considering FoV s of sensors in the network are different and limited, the standard weighted arithmetic average (WAA) fusion is no longer applicable and leads to an underestimation of the target number. Therefore, we use state-dependent WAA (SD-WAA) fusion rule, which performs the WAA in a more robust way by calculating a set of state-related fusion weights. Numerical experiment is designed to demonstrate the efficacy of the proposed method. © 2021 IEEE.

关键词： fields of view gaussian mixture maneuvering multi-target tracking multi-model method probability hypothesis density filter state-dependent weighted arithmetic average

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Research on Location Algorithm Based on SAR and Infrared Fusion 1

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

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

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

Aiming at the problem of sins cumulative error correction, a dual-mode navigation algorithm based on infrared and SAR information fusion is studied. Radar system can provide SAR image and range information, and can measure height under certain conditions, but it cannot work in front. Infrared system can provide infrared image and optical axis direction of infrared lens. Based on the satellite positioning algorithm, this paper studies a fusion algorithm of radar SAR image and infrared. The image matching and measurement results are used to navigate to correct the accumulated errors of sins. Simulation results show the effectiveness of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar imaging

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Design of Reinforcement Learning Environment for Multiple UAV Area Coverage Search

Design of Reinforcement Learning Environment for Multiple UA...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Sun, Yinjiang Zhang, Rui Liu, Xiaoheng Liang, Wenbao Xu, Cheng Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Unmanned aerial vehicle (UAV) plays an increasingly important role both in civil and military fields. As a typical mission, area coverage search is a primary measure for reconnaissance and surveillance of unknown areas. Due to the limited information about the mission area, UAV needs adaptiveness to the dynamic changes of the area and makes decisions based on local observation. It puts higher demands on the response speed of UAV, and traditional planning methods are tough to be directly applied. The problem becomes more noticeable for multiple UAV because of the heterogeneous function and large scale, and new solutions are urgently required. In this paper, the feasibility of reinforcement learning (RL) for performing area coverage search is explored, and an environment is designed for RL training and evaluation. Simulation results show that multiple UAV can cooperate and perform the mission with pretty high coverage. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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

引用

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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Phase Unwrapping Based on CFAR Detection for Multi-baseline InISAR

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

引用

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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Scalable Distributed Organizational Structure and Self-Organization Mechanisms for Unmanned system Cluster 9

Scalable Distributed Organizational Structure and Self-Organ...

引用

9th IEEE International Conference on Computer science and Network technology, ICCSNT 2021

作者： Liu, Haibo Lin, Yang Shen, Jing Wang, Xing Shi, Changting Zhang, Jiayu College of Computer Science And Technology Harbin Engineering University Harbin150001 China Science And Technology On Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9781665443647

Reasonable control organizational structure can help an unmanned system cluster cooperate more effectively to complete tasks. Previous research of existing organizational structures has problems implementing the task in a natural environment, such as the cluster's lack of scalability. This paper proposes a three-layer scalable distributed organizational structure and dynamic self-organization mechanisms, which overcomes the lack of scalability and ensures that the cluster can still perform stably after the cluster size changes. The simulation results show that the organizational structure realizes information sharing and cross-layer control, which enhance the flexibility and stability of unmanned system clusters. Comparison results show that our achievements can make a good performance, contributing to this area of future research. © 2021 IEEE.

关键词： Scalability

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Adversarial Example Attack and Defence of Object Recognition: A Survey

Adversarial Example Attack and Defence of Object Recognition...

引用

2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Tan, Wei Zhao, Jiajia Liang, Xinkai Lu, Hanchen Song, Baogang Guan, Hao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Mechano-Electronic Engineering Institute Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Deep learning-based intelligent object recognition algorithm has been widely applied in object detection, auto driving, ect. However, deep neural network is very vulnerable because of its high-dimensional linearization. The object recognition results can be easily mis-leaded through a tiny disturbance in the original image. This kind of sample that adds tiny disturbance to the original image is called adversarial example. The adversarial example attack is a factor that must be considered in the design of robust object recognition algorithm, that is, the need for adversarial defence. An in-depth understanding of adversarial attack can help the model defend successfully. In this survey, an introduction of adversarial attack and defense aiming to object recognition algorithm at the present stage is summarized, and the challenges to be faced and the development trend in the future are pointed out. © 2022 IEEE.

关键词： Object recognition

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