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Multi-Stage Marine Ship Recognition Based on Stackable Residual Network 19

Multi-Stage Marine Ship Recognition Based on Stackable Resid...

引用

19th International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2023

作者： Yu, Wanwan Zhang, Junping Wang, Linlin Xi, Yunqiao Xu, Hongfeng Chen, Linxiu Hao, Mingrui Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350304398

Marine ship recognition has always been an important research field. The ships can be usually recognized by analyzing their attribute characteristics. However, in the actual process of recognition, many ship recognition methods using a single model cannot meet the requirements of this task due to the complexity of ship types, diversity of interference factors and different information obtained from distance differences. Therefore, we propose a multi-stage ship recognition scheme. First, the single radiation emitter feature recognition network model is designed for long-distance recognition. Second, the fusion feature network model for short distance recognition. The proposed network is mainly constructed with the residual units, which not only simplify the training of deep networks and facilitate the spread of information, but also can solve the vanishing gradient and exploding gradient problem. The simulation experimental results show that the proposed network model has better performance than typical methods and has great potential in applications. © 2023 IEEE.

关键词： Ships

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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...

引用

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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A Generic Anti-Windup Design under Linear Active Disturbance Rejection control Scheme

A Generic Anti-Windup Design under Linear Active Disturbance...

引用

2023 IEEE International Conference on Electrical, Automation and Computer Engineering, ICEACE 2023

作者： Hui, Li Cheng, Xu Hua, Ji Zhide, Yin Wanhai, Hu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China The 3rd Research Academy of CASIC Beijing China

ISBN: (纸本)9798350309614

A generic anti-windup compensation strategy under Linear Active Disturbance Rejection control scheme is proposed. The difference, between the controller output and the actuator output, after multiplied by a tunable parameter, together with controller output, is fed back to the extended state observer to compensate controller windup. While windup problem arises in control system, the controller output is expectedly produced, and the disadvantageous influence of nonlinearity on closed-loop dynamics is distinctly alleviated. The approach is employed to a near space vehicle with fin-deflection saturation. The numerical simulations show that the proposed approach has the better effectiveness in active disturbance rejection control designed situation than some previous anti-windup compensation strategy. © 2023 IEEE.

关键词： active disturbance rejection control anti-windup compensation two-step design method Windup problem

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Infrared small target detection algorithm with complex background based on YOLO-NWD 22

Infrared small target detection algorithm with complex backg...

引用

4th International Conference on Image Processing and Machine Vision, IPMV 2022

作者： Zhou, Xiao Jiang, Lang Guan, Xujun Mou, Xingang Wuhan University Of Technology China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781450395823

Because of small number of occupied pixels, lacking shape and texture information, the reliability of infrared remote target detection has always been a difficult research topic. To improve the accuracy and precision of detection of infrared small targets under complex background conditions, a deep learning-based infrared small target detection algorithm YOLO-NWD is proposed. According to the characteristics of small and medium targets in infrared images, multi-channel feature fusion image was used as the input of YOLO detection framework combined with image preprocessing method. Combined with SE module and ASPP module, feature weights are explored to improve feature utilization efficiency. Finally, the normalized Wasserstein distance (NWD) loss is used to replace the original IoU calculation loss to reduce the sensitivity of small target position deviation. The experimental results show that the algorithm proposed in this paper improves the accuracy by 2.5% and the recall rate by 4%. © 2022 ACM.

关键词： Deep learning

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Distributed Communication Based Cooperative Multi-aircraft Attack Guidance Law

Distributed Communication Based Cooperative Multi-aircraft A...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Lyu, Zhongshi Guo, Xiaoyun Hao, Mingrui Xu, Cheng Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Institute of Mechanical and Electrical Engineering Beijing100074 China

ISBN: (纸本)9789811966125

New requirements for coordinated aircraft attacks have been introduced with the development of the anti-missile systems. To address the problem of multi-flight collaborative strike, this paper proposes a distributed collaborative guidance strategy that allows for efficient information interaction. Based on the principle of distributed communication topology, the cooperative guidance law is designed to control each vehicle simultaneously in terms of velocity magnitude and direction, so that the state information of each vehicle converges quickly. The purpose of sequential arrival of vehicles is achieved, and a cooperative attack guidance law with good stability and high reliability is constructed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicles

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Parameter Dynamic Selection Method of Multi-UAV Cooperative Search Based on Expert system

Parameter Dynamic Selection Method of Multi-UAV Cooperative ...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Zhenchang Hao, Mingrui Wei, Donghui Liu, Yuting Zhao, Hongyin Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789811966125

The cooperative search strategy is designed with the distributed model predictive method in this paper. For the rationality of decision-making of UAV swarm in different stages of the cooperative search, a dynamic parameter selection method based on the expert system is proposed. The weight of the objective function is adjusted online through the expert system so that the result of the search decision is more in line with the task requirements. Besides, a jump grid method is proposed for grid selection in cooperative search so that the UAV can select non-adjacent grids as the search point for the next time. The UAV's search frequency and trajectory maneuverability can be changed by adjusting the number of jump grids through the expert system. The simulation shows that the UAV with the expert system can dynamically adjust the search interval and search requirements, making the UAV swarm able to quickly discover targets, explore unknown areas, ensure collision avoidance, and meet the boundary constraints. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Improved Image Matching Method Between SAR and Optical Based on Gaussian Vote by Ballot 11th

Improved Image Matching Method Between SAR and Optical Based...

引用

11th China Conference on Command and control, C2 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 Coopration Laboratory Beijing China

ISBN: (纸本)9789819990207

Aiming to obtain the high-precision matching position and reduce time and resource requirements, an image matching method between SAR and optical based on CSP-DenseNet and Gaussian vote by ballot is proposed. First, in order to detect stable interest points and extract deep feature in SAR image, we use FAST operator and CSP-DenseNet. Then, in order to save time and resource requirements, we use gaussian vote by ballot to determine the high-precision matching position between two *** simulation results reveal the validity of the algorithm. © Chinese Institute of Command and control 2024.

关键词： Synthetic aperture radar

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Multi-view and Multi-target Association Algorithm for Unmanned Aerial Vehicle Clusters Based on Siamese Network

Multi-view and Multi-target Association Algorithm for Unmann...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Hang Song, Chuang Zheng, JiangBin Hao, MingRui School of Software Northwestern Polytechnical University Shaanxi Xi’an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811966125

The multi-target association algorithm of unmanned aerial vehicles (UAV) clusters in unknown environments is used to solve the problem of multiple UAVs, which can correctly determine whether the data from different perspectives contain the same target and eliminate redundant targets. This problem is different from that of multi-target tracking under the same perspective. However, the inherent relationship and differences of data from various perspectives of UAV clusters contribute to the problem of inaccurate target positioning information caused by low-cost detectors and inertial measurement units of UAVs and the constraints of limited communication capability between UAV clusters. Thus, using multi-perspective data is the key to improving the accuracy of multi-perspective situational awareness. This paper proposes a multi-view and multi-target association algorithm for UAV clusters based on the Siamese network. This algorithm can realise the problem of multi-view and multi-target identity judgement with high accuracy, achieve the requirements of high accuracy and high generalisation performance with the depth model based on convolution neural networks, extract the depth features from the optical image and map the original data to the depth feature space. Thus, the same target is matched by comparing the distance measurement of multi-view data in the feature space. The algorithm is verified by an aircraft cluster flight test, which proves the feasibility and accuracy of the algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Target Recognition Inference Based on Knowledge Graph and Graph Neural Network

Target Recognition Inference Based on Knowledge Graph and Gr...

引用

2024 China Automation Congress, CAC 2024

作者： Li, Wei Xu, Hongfeng Li, Yuan Beijing Institute of Technology Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9798350368604

In complex environments with vast and diverse information sources, target recognition serves as a crucial precursor to situational analysis, providing the foundation for further decision-making and analysis. Traditional algorithms for target recognition often rely on human experience and rules, necessitating expert knowledge and subjective judgments, which introduces uncertainties. This paper introduces a method for target recognition inference, leveraging Situation Knowledge Graph Convolutional Neural Network (SKGCN). By employing active and passive radar sensor data in complex scenarios, the algorithm processes inputs within a self-constructed situational knowledge graph. It derives vector representations of target entities through aggregation operations among neighboring nodes and extracts perceptual data vectors using the embedding layer. The algorithm calculates the alignment between sensor data and target entities, facilitating target recognition and inference in complex scenarios. Simulation results confirm the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Knowledge graph

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A Method for Marine Ship Formation Intention Recognition based on BiConvLSTM-Attention 3

A Method for Marine Ship Formation Intention Recognition bas...

引用

3rd International Conference on Electronic Information Engineering and Computer science, EIECS 2023

作者： Xi, Yunqiao Zhang, Junping Liu, Jian Wang, Linlin Xu, Hongfeng Chen, Linxiu Jiang, Jixiang Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Institute of Electrical and Mechanical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316674

To solve the problem that current dynamic intention recognition methods fail to make full use of time domain variation information between multi-temporal group targets, which leads to low accuracy of intention recognition. This paper proposes a bidirectional convolutional long short term memory-attention network for marine formation target intention recognition. The network takes the multi-source trajectory data of the marine ship formation target as the input, extracts and uses the target change rule and time domain characteristics of the Marine formation data, and trains the model to have the ability to independently learn the weight of information in different time periods. The simulation results show that the method has good performance and can meet the needs of practical application. © 2023 IEEE.

关键词： intention recognition long short-term marinship formation temporal features

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