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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Li, Jie Wang, Rui Nantogma, Sulemana Xu, Yang University of Electronic Science and Technology of China Chengdu China Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China

ISBN: (纸本)9789811694912

Weapon-target assignment (WTA) is essential ability for command and control (C2) systems. The requirement for real-time decision-making, heterogeneous combat platforms are required to make effective weapon-target assignment decisions to achieve interception of fast and multi-batch targets. Since it is difficult to form an accurate modeling of the incoming target ability and obtain a large amount of training data in actual combat exercises, this problem has become a representative problem of real-time decision-making under the constraints of small training samples. Inspired by the use of rules to make coordinated air defense decisions when manned, we propose a practical rule-based machine learning approach to solve this problem in this paper. Firstly, we model heterogeneous combat platforms into multi-agents system and use genetic fuzzy trees (GFT) to make weapon-target assignment decisions. Genetic algorithm (GA) is then employed to learn fuzzy rules and tune membership functions. To evaluate the performance of the proposed algorithm, we build a typical Surface Unmanned System air defense simulation scenario that employs an auto-fire strategy as baseline. The simulation results show that our approach demonstrates a superior performance over the auto-fire strategy and can greatly improve the interception efficiency with a small amount of training data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Communication Jamming of High Power Microwave Pulse to UAV 24

Communication Jamming of High Power Microwave Pulse to UAV

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Song, Ruilong Zheng, Jingzhi Zhang, Mingwen Chen, Xu Ma, Chunguang Lu, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

High power microwave pulse (HPMP) is an effective way to anti unmanned aerial vehicle (UAV), and the jamming of frequency hopping (FH) communication is the best starting point to achieve anti UAV. This paper uses DJI Phantom 4 Pro as the research object and analyzed the relationship between the power, pulse width and duty cycle of HPMP to achieve the jamming of FH communication of the UAV based on its FH communication characteristics, and the reliability of the analysis is verified through experiments. This paper can provide a good idea for the design of an anti UAV scheme based on HPM. © 2023 IEEE.

关键词： Jamming

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Novel camera self-calibration method with clustering prior and nonlinear optimization from an image sequence

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Multimedia Tools and Applications 2024年第42期83卷 90553-90572页

作者： Jiang, Xiaohui Zhu, Haijiang An, Ning Xie, Binjian Wei, Hao Tang, Fulin Wu, Yihong College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China State Key Laboratory of Multimodal Artificial Intelligence Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Intelligent Coal Mining and Strata Control Beijing100013 China Research Institute of Mine Big Data China Coal Research Institute Beijing100013 China

In many 3D reconstruction, Simultaneous Localization and Mapping (SLAM), AR, and VR systems, the camera focal length constantly changes slightly due to loose hardware, causing their performances to deteriorate. To address this problem, we propose a novel camera self-calibration method that incorporates clustering prior and nonlinear optimization. By leveraging the Kruppa equation, we roughly estimate multiple analytical solutions for the camera focal length from an image sequence. Then, robust clustering based on the Gaussian mixture model is introduced to obtain an initial camera focal length value. Finally, a nonlinear cost function is proposed to refine the initial camera focal length value. Extensive experimental results on simulation and real data demonstrate that the proposed method outperforms the state-of-the-art methods, exhibiting good robustness and high accuracy. Moreover, the proposed method can be used in real-time videos for SLAM systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cost functions

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Health Parameters Estimation of Turbofan Engine Based on Improved UKF Method 41

Health Parameters Estimation of Turbofan Engine Based on Imp...

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第41届中国控制会议

作者： Yu Zhang Si-Xin Wen Kun-Zhi Liu Chongyi Sun Xi-Ming Sun School of Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology DUT Artificial Intelligence Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In view of the shortcomings of the standard Unscented Kalman Filter(UKF),such as slow convergence speed,low precision and easy divergence,the state estimation problem is transformed into an unconstrained optimization problem,and an iterative Unscented Kalman Filter based on the optimization method is *** Levenberg-Marquart nonlinear optimization method is used to improve the measurement update equation of the filtering ***,the numerical simulation of health parameters estimation on a certain turbofan engine is carried *** results show that the established parameters estimation model can accurately estimate the changes of health parameters in different performance degradation modes,and the convergence speed and stability are obviously better than the standard UKF *** addition,the improved algorithm was successfully deployed on the NVIDIA Jetson Xavier embedded platform to complete the online estimation,which indicates that the proposed method has good real-time performance.

关键词： Turbofan engine Kalman filter Unconstrained optimization Online estimation

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Research on active disturbance rejection control scheme of auxiliary power unit 41

Research on active disturbance rejection control scheme of a...

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第41届中国控制会议

作者： Jijun Li Jianyi Zhang Si-Xin Wen Kun-Zhi Liu Xi-Ming Sun School of Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology DUT Artificial Intelligence Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

As an important secondary power source of the aircraft,the control performance of the Auxiliary Power Unit(APU)will directly affect the working efficiency of the aero-engines and the aircraft ***,APU has complex nonlinear characteristics and faces the influence of various inevitable and uncertain ***,the design of its highperformance control system is extremely challenging,and the traditional gain-scheduling PI control method cannot meet this *** resolve this problem,we design an Active Disturbance Rejection control(ADRC) scheme for APU *** the same time,the parametric design method of the proposed ADRC is given,so that the corresponding control parameters can be set according to the linearized model in engineering ***,a numerical comparison simulation is carried out on a certain auxiliary power unit model to verify the effectiveness and superiority of the proposed method.

关键词： Auxiliary power unit(APU) Aero-engine Active disturbance rejection control(ADRC) Extended state observer(ESO)

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Face anti-spoofing based on multi-modal and multi-scale features fusion

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The Journal of China Universities of Posts and Telecommunications 2022年第6期29卷 73-82页

作者： Kong Chao Ou Weihua Gong Xiaofeng Li Weian Han Jie Yao Yi Xiong Jiahao School of Big Data and Computer Science Guizhou Normal UniversityGuiyang 550025China Special Key Laboratory of Artificial Intelligence and Intelligent Control of Guizhou Province Guizhou Institute of TechnologyGuiyang 550003China Guizhou Science and Technology Information Center Department of Science and Technology of Guizhou ProvinceGuiyang 550002China

Face anti-spoofing is used to assist face recognition system to judge whether the detected face is real face or fake face. In the traditional face anti-spoofing methods, features extracted by hand are used to describe the difference between living face and fraudulent face. But these handmade features do not apply to different variations in an unconstrained environment. The convolutional neural network(CNN) for face deceptions achieves considerable results. However, most existing neural network-based methods simply use neural networks to extract single-scale features from single-modal data, while ignoring multi-scale and multi-modal information. To address this problem, a novel face anti-spoofing method based on multi-modal and multi-scale features fusion(MMFF) is proposed. Specifically, first residual network(Resnet)-34 is adopted to extract features of different scales from each modality, then these features of different scales are fused by feature pyramid network(FPN), finally squeeze-and-excitation fusion(SEF) module and self-attention network(SAN) are combined to fuse features from different modalities for classification. Experiments on the CASIA-SURF dataset show that the new method based on MMFF achieves better performance compared with most existing methods.

关键词： face anti-spoofing multi-modal fusion multi-scale fusion self-attention network(SAN) feature pyramid network(FPN)

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Follower Jamming to UAV FH Communication System Based on Simulink 24

Follower Jamming to UAV FH Communication System Based on Sim...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Li, Junhui Ma, Chunguang Zhao, Junyu Zhou, Jinghan Luo, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

With the vigorous rise of the unmanned aerial vehicle (UAV) market, the 'black flight' of UAVs has seriously threatened public safety, flight safety and even air defense safety. Therefore, the research of anti UAV technology is very urgent. The UAV is mainly equipped with the frequency-hopping (FH) communication system which has a strong anti-jamming capability. This paper establishes the structure diagram of the UAV FH communication system based on Simulink. And then the follower jamming of different power and interference dwell ratio (IDR) are set to interfere with the system respectively. We use the error rate to evaluate the interference effect of the model. The simulation results show that in the case of high jamming to signal ratio (JSR), follower jamming can effectively interfere with the UAV FH communication system. © 2023 IEEE.

关键词： Simulink

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MMW Broadband Radar Compressed Sensing Imaging Based on SAMP Optimization Algorithm 24

MMW Broadband Radar Compressed Sensing Imaging Based on SAMP...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Zhou, Jinghan Ma, Chunguang Liu, Jiaming Yuan, Zhenqian Luo, Yong School of Electronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China

ISBN: (纸本)9781665473217

With the development of gyrotron traveling wave amplifier, long-range high-resolution millimeterwave (MMW) imaging broadband radar has been developed rapidly. Nyquist theorem brings challenges to wideband radar signal sampling, and the hardware complexity and cost of the required equipment will increase significantly. Compression sensing (CS) takes advantage of the sparsity of the signal in the transformation domain. Under the condition that it is far less than Nyquist sampling rate, it uses random sampling to obtain discrete samples of the signal, and then perfectly reconstructs the signal through nonlinear reconstruction algorithm. This paper proposes a linear majorization sparsity adaptive matching pursuit (LMSAMP) algorithm based on CS theory. The LMSAMP algorithm with adaptive optimization step size selection is used to reconstructed two-dimensional image of wideband MMW radar. The imaging results show that LMSAMP algorithm has a good imaging effect. © 2023 IEEE.

关键词： Radar imaging

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者： Yuan Ge Jie Li Wenwu Jiang Lidan Wang Shukai Duan School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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Memristor-based multi-synaptic spiking neuron circuit for spiking neural network

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Chinese Physics B 2022年第4期31卷 225-233页

作者： Wenwu Jiang Jie Li Hongbo Liu Xicong Qian Yuan Ge Lidan Wang Shukai Duan College of Artificial Intelligence Southwest UniversityChongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China

Spiking neural networks(SNNs) are widely used in many fields because they work closer to biological ***,due to its computational complexity,many SNNs implementations are limited to computer ***,this paper proposes a multi-synaptic circuit(MSC) based on memristor,which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse *** synapse circuit participates in the calculation of the network while transmitting the pulse signal,and completes the complex calculations on the software with ***,a new spiking neuron circuit based on the leaky integrate-and-fire(LIF) model is designed in this *** amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as *** combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron(MSSN).The MSSN was simulated in PSPICE and the expected result was obtained,which verified the feasibility of the ***,a small SNN was designed based on the mathematical model of *** the SNN is trained and optimized,it obtains a good accuracy in the classification of the IRIS-dataset,which verifies the practicability of the design in the network.

关键词： memristor multi-synaptic circuit spiking neuron spiking neural network(SNN)

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