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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Electronic compass calibration based on Adaptive Differential Evolution Algorithm-Fourier Neural Network

Electronic compass calibration based on Adaptive Differentia...

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Chinese control Conference (CCC)

作者： Kun Gong Fang Deng Jie Chen School of Automation Beijing Institute of Technology Beijing Beijing CN Ministry of Education Key Laboratory of Complex System Intelligent Control and Decision Beijing Beijing CN Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Beijing CN

Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from -3.4° ~ 25.2° before compensation to -0.20° ~ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency.

关键词： Compass Error compensation Adaptive systems Electronic mail Neural networks Training Measurement uncertainty

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Regional Geomagnetic Map Construction based on Support Vector Machine Residual Kriging

Regional Geomagnetic Map Construction based on Support Vecto...

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第三十九届中国控制会议

作者： Tong Liu Xingyu Li Mengyin Fu Zhaoxiang Liang Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Nanjing University of Science and Technology

Regional geomagnetic maps are widely used in geomagnetic navigation and magnetic anomaly detection. However,the complexity of geomagnetic spatial trend changes and the spatial sparseness of the geomagnetic data affect the accuracy of regional geomagnetic map construction. In order to improve the accuracy of regional geomagnetic maps, this paper proposes the Support Vector Machine Residual Kriging method（SVMRKriging）. First, Support Vector Machine（SVM） is used to fit the geomagnetic trend changes, then the residual component is interpolated by ordinary Kriging, and finally these two parts are added to construct a regional geomagnetic map. Experiments were performed using geomagnetic grid data and aeromagnetic data. The experiment results show that SVMRKriging method can improve the accuracy of regional geomagnetic maps with geomagnetic trend changes.

关键词： Regional Geomagnetic Map Kriging Support Vector Machine

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Analysis of security in cyber-physical systems

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Science China. Technological Sciences 2017年第12期60卷 1975-1977页

作者： Chen Jie Zhang Fan Sun Jian School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In recent years, cyber-physical systems (CPSs) have received much attention from both the academic world and the industrial world, which refer to a deep integration and coordination of physical and computational resources [1,2]. Typical examples of CPSs can be found in smart grids, smart transportation systems, industrial control systems, water supply systems, and so on. Furthermore, many military systems are also CPSs. The key characteristic of CPSs is the integration of computing, control and communication. The increased interconnection between the cyber and physical spaces make CPSs vulnerable to various malicious attacks. A well-known example of an attack of CPSs is the Stuxnet which infected the control system of nuclear-fuel centrifuges of Bushehr nuclear power plant in Iran. Stuxnet makes people beware of the grave consequences of a cyber-attack on a CPS. Since many national critical infrastructures are applications of CPS, ensuring security and safety of such systems is of great importance.

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An Optimized Method for Line Extraction Using Laser Scan Data

An Optimized Method for Line Extraction Using Laser Scan Dat...

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中国人工智能学会第十三届学术年会

作者： Cheng-hao Hua Lihua Dou Jie Chen Yutian Mao Beijing Institute of Technology and the Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081

In this paper an optimized line features extraction method is developed for real-time line features identification from 2D laser range finder A polished line prototype is subtly combined with Incremental algorithm which can detect line features *** ensuring the correctness,the selected line features are examined with split-and-merge fuzzy *** greatly enhances the robustness of line features extraction,especially in the clutter *** method provides a novel framework which is very efficient and robust of line features *** advantages are very helpful for the further application of mobile robots such as simultaneously localization and mapping,real-time navigation in the clutter environment *** performance of this approach is verified by simulation and experiments.

关键词： Festure extraction Mobile robot Line prototype Laserrange finder

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Coarray Tensor Train Decomposition for Bistatic MIMO Radar with Uniform Planar Array

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IEEE Transactions on Antennas and Propagation 2025年

作者： Xie, Qianpeng Wang, Zhanling Wen, Fangqing He, Jin Truong, Trieu-Kien National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Changsha410073 China Hubei University of Automotive Technology Institute of Vehicle Information Control and Network Technology Shiyan442002 China China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yichang443002 China Shanghai Jiao Tong University Shanghai Key Laboratory of Navigation and Location Based Services School of Electronic Information and Electrical Engineering Shanghai200240 China

Recently, tensor network decomposition has attracted increasing attention due to its high efficacy in modeling multi-dimensional correlations in high-order tensors. Considering this advantage, this study employs tensor train decomposition (TTD) to achieve joint two-dimensional direction-of-departure (2D-DOD) and direction-of-arrival (2D-DOA) estimation in bistatic multiple-input multiple-output (MIMO) radar systems with uniform planar array (UPA) configurations. First, a five-dimensional (5D) tensor is defined to incorporate the two-dimensional (2D) spatial information from transmit and receive UPAs, which is then combined with temporal information. Next, a low-rank four-dimensional (4D) tensor is generated by performing an autocorrelation operation along the temporal dimension of the 5D tensor, forming a structure that encapsulates the difference coarrays of the transmit and receive UPAs. Then, a TTD framework is designed to decompose the 4D tensor into interconnected lower-order TT-cores. Furthermore, a precise bidirectional mapping is performed between the TT-cores and the original Vandermonde factor matrices. Finally, leveraging distinct combinations of TT-cores, two innovative methods are developed to recover the Vandermonde factor matrices. The proposed methods conduct automatic pairing of 2D-DOD and obtain 2D-DOA estimates by enforcing consistent permutation orders across all factor matrices. The proposed methods are verified by simulation experiments. The results confirm that the proposed methods can surpass the existing tensor-based methods in terms of estimation accuracy. © 1963-2012 IEEE.

关键词： Matrix algebra

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Aeromagnetic Compensation Based on Tikhonov Regularization with Limited L-curve Parameter-choice Algorithm

Aeromagnetic Compensation Based on Tikhonov Regularization w...

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第37届中国控制会议

作者： FU Mengyin LI Jie WU Tailin LIU Tong WANG Meiling WANG Kai KANG Jiapeng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Nanjing University of Science and Technology

Magnetic anomaly detection has great application value to national economic development and national defense construction, while the presence of various interference magnetic fields on the aircraft will affect the detection of magnetic anomaly. Therefore, it is very important to compensate the aircraft interference magnetic field. In order to solve the problem that the accuracy of the parameters is poor by using ridge estimation in the process of solving the parameters of aircraft interference magnetic field model, we propose a method based on Tikhonov Regularization（TR）. Firstly, the optimal regularization parameter is obtained by the limited L-curve method in our work. Secondly, the aircraft interference magnetic field model parameters are obtained by using the TR method. Finally, we use the model parameters to calculate the aircraft interference magnetic field in the real flight, and complete the compensation. The effectiveness of this method is validated by simulation experiments. The results show that the method proposed in this paper has the advantages of high precision and convenient application, so it can be used to compensate the aircraft interference magnetic field effectively.

关键词： Aircraft Interference Magnetic Field Model Tikhonov Regularization L-curve Method Ridge Estimation

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Research on Synthetic Data Generation and Multi-modal Target Detection

Research on Synthetic Data Generation and Multi-modal Target...

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Chinese control and decision Conference, CCDC

作者： Jiexi Liu Chenyu Wang Lei Xu Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Beijing China

ISBN: (纸本)9781665478977

Target Detection is one of the most important tasks in Computer Vision, which has broad application prospects in many scenes. For the past few years, great progress has been made in this field with the rapid development of deep learning technology. However, it’s still a big challenge at complex scenarios such as dim environment for traditional single-modal visible images. To address this problem, researchers introduce thermal images as additional modal in consideration of that thermal cameras are less susceptible to interference and explore how to fuse the two modalities information effectively. Nevertheless, the lack of large labeled and high-quality visible-thermal datasets hampers the usage of convolutional neural networks for detection. Therefore, we propose to use image-to-image translation model combined with a differentiable data augmentation method to generate fake thermal images from labeled visible images and use multi-modal target detection model to prove the validity of the method. Our experiment results show that our method can provide us a large labeled dataset of synthetic visible-thermal image pairs with better generalization and the introduction of thermal modality can obtain a better performance than single modality.

关键词： Deep learning Computer vision Fuses Object detection Interference Detectors Data models

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Distortion correction method in the high-precision and high-speed CCD measurement system

Distortion correction method in the high-precision and high-...

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Chinese control Conference (CCC)

作者： Jing Li Junzheng Wang Renjian Hao Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology 100081 China

In the high-precision and high-speed measurement system, the distortion of CCD pixes will give a greater margin of error to measurement results. According to the characteristic of noise leading to the image distortion, this article establishes the image transformation model. Data fitting based method is used for correcting image distortion. For the distortion caused by camera installation, the perspective transformation is used to correcting the image. And then the four points calibration method is adopted to calibrating the measurement system. Experiments adopt the high speed area array CCD to gather images with the circular facula in the target area launched by the laser, and calculate the real position of the facula in the target area, adopt the high accurate displacement sensor to give the true displacement of the target which is used to verify the real position of the facula in the target area. The results show that the algorithm can reduce the influence of image distortion, which advances the measurement accuracy efficiently.

关键词： Charge coupled devices Distortion measurement Optical distortion Cameras Measurement uncertainty Calibration Real-time systems

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Three-dimensional deployment optimization of sensor network based on an improved Particle Swarm Optimization algorithm

Three-dimensional deployment optimization of sensor network ...

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World Congress on intelligent control and Automation (WCICA)

作者： Xiao-yan Lian Juan Zhang Chen Chen Fang Deng Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing China

Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targets with complex properties. In this paper, a method for 3D deployment optimization of sensor network based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. Many factors such as coverage scale, detection probability and resource utilization are synthetically considered to optimize the sensor network's overall detection performance. To evaluate the network's performance, four indexes are presented and the 3D deployment space is divided into different height levels. Accordingly, the mathematical model is formulated by weighting the performance indexes and height levels due to their importance degrees. In order to solve the optimization problem, an algorithm called WCPSO is carried out, which has a dynamic inertia weight and adaptable acceleration constants. Verified by the simulation results, the presented 3D deployment optimization method effectively improves the sensor network's detection performance. The method in this paper can provide guidance and technical reference in future application of relevant research.

关键词： Optimization Indexes Mathematical model Acceleration Algorithm design and analysis Resource management Performance analysis

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