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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Luo, Yihang Zhao, Zhenyu Hu, Yinji Jie, Feiran Science and Technology on Electro-Optical Control Laboratory Luoyang471000 China Luoyang Institute of Electro-Optic Equipment AVIC Luoyang471000 China

ISBN: (纸本)9789811966125

Most of the existing trackers usually rely on a multi-scale searching schemes or predefined anchor boxes to accurately estimate the scale and aspect ratio of objects. However, this operation requires tedious and heuristic configurations to obtain ideal results, which is inefficiency. To solve this problem, we introduce an anchor-free and pixel-wise convolution algorithm (named SiamAPF). SiamAPF transforms the tracking problem into a classification problem and a regression problem, and directly performs classification and bounding box regression on the target in fully convolutional network. The proposed network architecture is simple, and does not need to set responsible hyper-parameters. Meanwhile, it can improve the network's ability to express spatial information through pixel-wise convolution. It achieves state-of-the-art performance on the test datasets OTB100, UAV123 and runs at 50 FPS. In order to achieve better engineering applications, we successfully deployed SiamAPF under the NVIDIA Jetson Xavier hardware platform and recorded video for verification. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

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UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

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Journal of Systems Engineering and electronics 2024年第3期35卷 644-665页

作者： ZHAN Guang ZHANG Kun LI Ke PIAO Haiyin School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Electro-Optic Control Laboratory Luoyang 471009China

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control ***, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

关键词： unmanned aerial vehicle(UAV) maneuvering decision-making autonomous air-delivery deep reinforcement learning reward shaping expert experience

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A polarization sensitive interferometer:Delta interferometer

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Chinese Physics B 2024年第3期33卷 369-377页

作者：卫超奇刘建彬董翼飞孙雨农周宇郑淮斌刘严严闫秀生李福利徐卓 Key Laboratory of Multifunctional Materials and Structures Ministry of Education & International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'an 710049China MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Department of Applied PhysicsXi'an Jiaotong UniversityXi'an 710049China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300308China

A new type of polarization sensitive interferometer is proposed,named the Delta interferometer,inspired by its geometry resembling the Greek letter *** main difference between the Delta interferometer and other existing interferometers,such as Michelson,Mach-Zehnder and Young's double-slit interferometers,is that the two interfering paths are asymmetrical in the Delta *** visibility of the first-order interference pattern observed in the Delta interferometer is dependent on the polarization of the incidental *** coherence theory is employed to interpret this phenomenon and single-mode continuous-wave laser light is employed to verify the theoretical *** theoretical and experimental results are *** Delta interferometer is a perfect tool to study the reflection of electromagnetic fields in different polarizations and may find applications in polarization-sensitive scenarios.

关键词： phase sensitive interferometer Fresnel formula first-order interference

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Terahertz quasi-perfect vortex beam with integer-order and fractional-order generated by spiral spherical harmonic axicon

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Chinese Physics B 2024年第1期33卷 458-467页

作者：涂思语刘德峰刘劲松杨振刚王可嘉 Wuhan National Laboratory for Optoelectronics School of Optical and Electronic InformationHuazhong University of Science and TechnologyWuhan 430074China AVIC Beijing Changcheng Aeronautical Measurement and Control Technology Research Institute Beijing 101111China

We propose a new method to generate terahertz perfect vortex beam with integer-order and fractional-order. A new optical diffractive element composed of the phase combination of a spherical harmonic axicon and a spiral phase plate is designed and called spiral spherical harmonic axicon. A terahertz Gaussian beam passes through the spiral spherical harmonic axicon to generate a terahertz vortex beam. When only the topological charge number carried by spiral spherical harmonic axicon increases, the ring radius of terahertz vortex beam increases slightly, so the beam is shaped into a terahertz quasi-perfect vortex beam. Importantly, the terahertz quasi-perfect vortex beam can carry not only integer-order topological charge number but also fractional-order topological charge number. This is the first time that vortex beam and quasi-perfect vortex beam with fractional-order have been successfully realized in terahertz domain and experiment.

关键词： terahertz spiral spherical harmonic axicon quasi-perfect vortex beam topological charge number

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Cooperative attack–defense decision-making of multi-UAV using satisficing decision-enhanced wolf pack search algorithm

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Soft Computing 2024年第17-18期28卷 9575-9586页

作者： Zhou, Tongle Chen, Mou Wang, Yuhui Zhu, Ronggang Yang, Chenguang College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Avionics System Integrated Technology Shanghai200241 China Science and Technology on Electro-optic Control Laboratory Luoyang Institute of Electro-Optical Equipment of Avic Luoyang471000 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

Unmanned aerial vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack–defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack–defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. To improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Decision making

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6G Network Traffic Intrusion Detection Using Multiresolution Auto-encoder and Feature Matching Discriminator 5th

6G Network Traffic Intrusion Detection Using Multiresolution...

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Li, Yuhai Sun, Yuxin He, Dong Xi, Liang Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300300 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9783031360107

With the development of 6G technology, security and privacy have become extremely important in the face of larger network traffic bandwidth. An effective intrusion detection system can deal with the network attacks. Deep learning has been developed in the field of intrusion detection, which can identify normal and abnormal traffic. However, existing methods cannot guarantee good performance in accuracy and efficiency. In this paper, based on the autoencoder and generative adversarial network, the multiresolution autoencoder is adopted in the network traffic feature extraction, which can obtain different encoding lengths and guarantee better data reconstruction. In addition, we add an extra feature matching loss to encourage the discriminator to get more discriminative information from the reconstructed samples. Our experimental results on the CIC-IDS2018 dataset indicates that compared with autoencoder and generative adversarial network, our model can effectively improve the detection accuracy and can be applied to 6G network traffic security detection. © 2023, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Intrusion detection

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Classification of Deforestation Factors in 6G Satellite Forest Images 5th

Classification of Deforestation Factors in 6G Satellite Fore...

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Li, Yuhai Sun, Yuxin Meng, Xianglong Xi, Liang Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300300 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9783031360107

The terrestrial satellite network will play an essential role in 6G. Through the satellite system, people can obtain a lot of ground image information to process tasks and feedback. Forest resource is an essential resource. Determining the causes of deforestation is crucial for the development and implementation of forest protection plans. In this article, we propose a novel deep neural network model for distinguishing drivers of deforestation events from satellite forest images. To solve the problems of image rotation caused by satellite angle rotation and image blurring caused by extreme weather occlusion during satellite image acquisition, we add data enhancement and a self-supervised rotation loss to the model to improve the robustness and adaptability. We use deforestation maps generated from Landsat 8 satellite imagery as a dataset and demonstrate that our approach achieves better results than the baselines. © 2023, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Deforestation

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Research on Ballistic Planning Method Based on Improved DDPG Algorithm

Research on Ballistic Planning Method Based on Improved DDPG...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Xue, Shuai Han, Yun Bai, Hongyang Nanjing University of Science and Technology School of Energy and Power Engineering Nanjing China Science and Technology on Electro-Optic Control Laboratory Luoyang Institute of Electro-Optical Equipment Cavic Luoyang China

ISBN: (纸本)9798350312492

Aiming at the ballistic planning problem given the target position indication under the condition of satisfying the missile capability boundary and process constraints, an improved deep deterministic policy gradient (DDPG) algorithm is proposed. This method solves the problems of the traditional trajectory planning method, such as strong dependence on model, low adaptability to environment and lack of real-time performance. The agent is firstly trained by this algorithm at the initial stage in a simple environment through a guided training based on the slow training speed of deep neural network, and then the generated strategy is adopted as an initial strategy for retraining. In the process, the sampling strategy of experience-first playback is applied to the gradient algorithm of deep deterministic strategy, and the Ornstein-Uhlenbeck (OU) noise model is employed for increasing the exploration ability of the agent. Then, this work develops a comprehensive simulation model according to an actual environment, where an improved DDPG method is thus introduced into the ballistic planning field by combining with performance indicators for planning and the trajectory can also meet the constraints. In order to verify the effectiveness of this method, the Gaussian pseudo-spectrum method is also used to compare with the proposed method in this paper. The simulation results show that the ballistic planning time of this improved algorithm is only within 10ms, which is about 8 times shorter than that of Gaussian pseudo-spectrum method. The corresponding ballistics that satisfy the constraints can be quickly generated, which has a good convergence and robustness, and is also suitable for solving online ballistic planning problems. © 2023 IEEE.

关键词： Ballistics

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Scale Normalization and Lightweight FPN for Small Object Detection in Aerial Images 3

Scale Normalization and Lightweight FPN for Small Object Det...

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3rd International Conference on Computer Graphics, Image, and Virtualization, ICCGIV 2023

作者： Wei, Haokun Liu, Jingyi Chen, Jinyong Sun, Yuxin Chu, Boce Zhu, Jin Key Laboratory of Aerospace Information Applications of CETC Shijiazhaung China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China

ISBN: (纸本)9781510671720

The detection of small objects by oriented bounding box in aerial images is a recent hot topic. However, since the aerial images are not collected at the same height, the Ground Sample Distance (GSD) is different for each image, so that small objects are easily overlooked. Existing algorithms are designed for multi-scale object detection, and feature fusion is time-consuming, resulting in a large amount of model parameters that is not easy to deploy on embedded devices. We propose three methods to address the above problems. First, we scale the collected aerial images to the same scale according to the GSD value. Second, we change the structure of Feature Pyramid Network (FPN) and only keep the necessary low-level feature maps. Finally, we rescale the anchor for the specific scene. We validate our proposed method on the DOTA dataset. The results show that the modified model using our method can identify more small-scale objects, and the maximum number of model parameters can be reduced by 2.7%, the inference speed can be increased by 13.24%, and the model size was reduced by up to 28% when the detection accuracy is the same as the original algorithm. © 2023 SPIE.

关键词： Object detection

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B+-Tree-Quantization-Based Shared Secret Key Extraction Scheme From Atmospheric optical Wireless Channel

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IEEE Transactions on Communications 2025年第5期73卷 3394-3408页

作者： Pan, Gang Chen, Chunyi Changchun University of Science and Technology School of Computer Science and Technology Changchun130022 China Changchun University of Science and Technology School of Computer Science and Technology Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology Changchun130022 China Chongqing Research Institute Changchun University of Science and Technology Chongqing401135 China

To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes. © 1972-2012 IEEE.

关键词： optical communication

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