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IEEE Advanced Information technology, Electronic and Automation Control Conference (IAEAC)

作者： Yu Qiu Shuang Zhang Shudong Chen Chaopeng Luo College of Electronic Science and Engineering Jilin University Changchun China Science and Technology on Near-Surface Detection Laboratory Wuxi China

Localization of unexploded ordnance (UXO) with transient electromagnetic (TEM) system is a principle and necessary problem in detection procedures, especially beset by low data diversity and high positioning uncertainty. In this paper, procedures for targets location are presented in detail with cued data collected by potable TEM sensor JPMD, which is designed to provide diverse time-domain data of high quality with one transmitter coil and five 3-component receiving coils. Based on the single dipole model, the target is located with the data collected at a single spatial point by the differential evolution (DE) optimization algorithm which can be subdivided into three steps. With the structure and parameters of JPMD sensors and data inversion process described briefly, a field test site of 5 m × 5 m measurement grid was conducted to present the specific UXO localization procedures at Jilin University. Results indicate that all the UXO-like targets can be detected distinctly with JPMD. The location of single object can be inversed rapid in tolerable error at one single point. For two objects with overlapping signals as one, the inverted horizontal position is basically in the middle of them and depth is a bit smaller than theory.

关键词： Data models Magnetic field measurement Electromagnetics Optimization Time measurement Mathematical model Linear programming

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Research on Object detection and Location Using Semantic Segmentation 11th

Research on Object Detection and Location Using Semantic Seg...

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11th International Conference on Green Intelligent Transportation Systems and Safety, 2020

作者： Zhu, Huijie Cai, Yan Guo, Yingchun Feng, Xiang Zhang, Wenya Department of Automation Shanghai Jiao Tong University Shanghai200240 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China The 28th Research Institution of China Electronics Technology Group Corporation Nanjing210007 China School of Automation Beijing Information Science and Technology University Beijing100101 India

ISBN: (纸本)9789811654282

Object detection and location generally require multiple sensors and multiple deep networks to achieve. For a specific application scenario, this paper proposes an algorithm based on semantic segmentation to display object detection and location at the same time. Due to the small size of the target in the image, especially the vertex of the target occupies very few pixels, the HRnet semantic segmentation algorithm with higher resolution is adopted. Due to the unbalanced class distribution and the small number of training samples, data augmentation and Lovasz Softmax loss function are used in a targeted manner. After experimental verification, in this data set, HRnet is superior to other algorithms. And by using data augmentation and Lovasz Softmax loss function, the accuracy and IoU have been greatly improved, especially the target vertex area with few samples. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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A Hyperspectral Nonlinear Unmixing Network for nearshore Underwater Target detection

A Hyperspectral Nonlinear Unmixing Network for Nearshore Und...

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Artificial Intelligence, Networking and Information technology (AINIT), International Seminar on

作者： Jiaxuan Liu Jiahao Qi Ping Zhong Junhe Jiang Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China Science and Technology on Near-Surface Detection Laboratory Wuxi China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

The existing hyperspectral underwater target detection algorithms are ineffective in adapting to nearshore environments, owing to the difficulty of extracting target signals from cluttered nearshore backgrounds combined with weak target signals. To this end, hyperspectral unmixing (HU) is well suited in this paper for nearshore underwater target detection (UTD) task to address these issues, by extracting background endmembers and separating out weak target signals simultaneously. Specifically, we propose a novel nonlinear unmixing network for nearshore underwater target detection (NUN-UTD). It comprises an unsymmetrical autoencoder and a target prior preservation module to adapt to the complex nearshore environment. Experiments demonstrate that NUN-UTD achieves the best detection performances and visual results compared with other state-of-the-art methods.

关键词： Seminars Visualization Object detection Task analysis Information technology Artificial intelligence

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Algorithm Research of Magnetometer Assisted Inertial Navigation System for Mobile Robots

Algorithm Research of Magnetometer Assisted Inertial Navigat...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Yingjiao Rong Yentze Ko Xinan Wang Guangyi Shi Science and Technology on Near-Surface Detection Laboratory Wuxi China Shenzhen Graduate School Peking University Shenzhen China

ISBN: (数字)9781728166520

ISBN: (纸本)9781728166537

Mobile robots have broad application prospects in military, industrial, agricultural, commercial, transportation, and logistics fields. The core problem of mobile robot lies in the autonomous navigation ability of mobile robot. Inertial navigation system based on MEMS sensor is one of the research hotspots in the field of inertial navigation in recent years and one of the main research directions in the future. Aiming at the positioning of the mobile robot, this paper adopts the magnetometer assisted inertial navigation system, the navigation system consisting of a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer. The heading is calculated with three sensors, the velocity error is compensated, and calculate the position. In this paper, an Extended Kalman Filter for mobile robot navigation system is proposed to improve the position accuracy of the navigation system. Experiments are carried out to verify and analyze the filter with the experimental results.

关键词： Mathematical model Magnetometers Mobile robots Inertial navigation Kalman filters Robots Magnetic separation

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Gaussian Mixtures Match and Fusion Algorithms for Multi-Sensor Multi-Target Tracking

Gaussian Mixtures Match and Fusion Algorithms for Multi-Sens...

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International Conference on Information Fusion

作者： Han Shen-Tu Yingjiao Rong Yunfei Guo Ji-An Luo Yifang Shi Institution of Information and Control Hangzhou Dianzi University Hangzhou China Science and Technology on Near-Surface Detection Laboratory Wuxi China

ISBN: (数字)9780996452786

ISBN: (纸本)9781728118406

The results of single sensor Gaussian Mixture PHD Tracker (GM-PHDT) will deteriorate when tracking targets in dense clutter and low detection rate environments. In this work, we propose three multi-sensor multi-target GM-PHD fusion algorithms. For the proposed algorithms, we obtain the multi-sensor posterior GMs by fusing the matched GMs from multiple sensors. Specifically, the GM matching and fusing methods are proposed to fullfill the applicable GM-PHD algorithms. The simulation results demonstrated the efficiency of the proposed algorithms.

关键词： Target tracking Mathematical model Clutter Probability Approximation algorithms Object detection Fuses

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A Practical Control Strategy for Magnetic Levitation System against Two Probes Failures

A Practical Control Strategy for Magnetic Levitation System ...

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Chinese Control Conference (CCC)

作者： Jinhui Li Kai Ding Jianmei Sun Chi Wang Hongtao Zhao Huijie Zhu Science and Technology on Near-Surface Detection Laboratory Wuxi China Department of Precision Mechanical Engineering Shanghai University Shanghai China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper addresses the active control for magnetic levitation system against two probes failures, which degrades the stability of the levitation control, decreases the ride comfort near the rail joint. Firstly, a minimum interaction model containing vertical dynamics of electromagnets, cabin and traditional control scheme is developed. The output characteristics of probes near or under the typical joint are obtained by fitting experimental data. It shows that the maximum of the deviation values is up to 11mm, which should be attenuated effectively. Inspired by the probes' output characteristics and limited response range in the process of crossing the joint, a practical joint recognition method is explored. It shows that the joint can be identified timely. Then a pair of complementary filters acting on acceleration and limited gap signal is developed to reconstruct the levitation gap signals. It shows that the deviations of the synthesized value are reduced substantially. After building the overall dynamic model with details, numerical simulations are carried out, and the results illustrating the improvement of stability and extended low speed range are provided.

关键词： Probes Levitation Electromagnets Rails Fluctuations Electromagnetic forces

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Acoustic Target Recognition Based on MFCC and SVM 22nd

Acoustic Target Recognition Based on MFCC and SVM

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22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022

作者： Ding, Kai Zheng, Shoujun Qi, Xiaogang Huang, Shan Liu, Haoting Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China School of Mathematics and Statistics Xidian University Xi’an710071 China Nanjing ATE Electronic Tech Co. Ltd. Nanjing China Beijing Engineering Research Center of Industrial Spectrum Imaging University of Science and Technology Beijing100083 China

ISBN: (纸本)9789811947858

Feature extraction and classification are the main body of acoustic target recognition. Firstly, amplitude extraction based on harmonic set, MFCC and wavelet packet decomposition are selected as feature selection methods to extract the features of four kinds of measured sound signals respectively. Then, the feature vectors extracted by MFCC method with the best clustering effect are combined with GMM classifier, BP neural network, OVO-SVMs and multi-layer support vector machine as classifiers, and MATLAB is used for simulation recognition and classification. Finally, the recognition results are compared and analyzed. The results show that BP neural network has the best recognition effect, but its robustness is poor, the experimental results are unstable, and the selection of training and test data has a great impact on the recognition rate. The multi classification algorithm based on support vector machine has a better stable recognition rate. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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Angle of arrival (AOA)-based cross-localization algorithm using orientation angle for improved target estimation in far-field environments

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International Journal of Simulation: Systems, science and technology 2016年第31期17卷 20.1-20.8页

作者： Xu, Penghao Yan, Bing Hu, Shouwei Department of Weaponry Engineering Naval University of Engineering WuhanHubei430033 China Science and Technology on Near-Surface Detection Laboratory WuxiJiangsu214035 China

Passive positioning systems with a small aperture array exhibit poor accuracy of target estimation in far-field environments. To improve this accuracy, this paper presents a novel angle-of-arrival (AOA)-based cross-localization algorithm for direction finding using orientation angle. Improved geometric and numerical target-positioning models are constructed after analyzing the mechanism of the conventional AOA-based cross-positioning algorithm. The target predication equation is then derived using the constructed models, and the equation for nonlinear estimation is linearized using the Taylor series. An unbiased estimation of the target is obtained by optimizing the control of the iteration process, thus achieving an accurate positioning of the target. The performance of the proposed algorithm was evaluated in terms of its effectiveness and positioning accuracy under varying signal-to-noise conditions and orientation angle-measurement errors. Simulation results shows that the proposed algorithm is capable of positioning the target effectively, and offers better positioning accuracy than traditional algorithms under conditions of large AOA measurement errors or high-level background noise. © 2016, UK Simulation Society. All rights reserved.

关键词： Iterative methods

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The design of controller in permanent magnet linear synchronous motor

The design of controller in permanent magnet linear synchron...

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Chinese Automation Congress (CAC)

作者： Zhen Jia Jie Li Peichang Yu Jinhui Li Peng Leng Engineering Research Center of Maglev Technology National University of Defense Technology Changsha China Science and technology on near-surface detection laboratory Wuxi China

In this paper, the q-d axis currents in the vector control of permanent magnet synchronous linear motor are coupled with each other, which affects the control performance of the motor. By establishing a model of permanent magnet synchronous linear motor and analyzing the coupling reasons, a feedforward decoupling method is proposed to realize the current control of motor. On this basis, an anti-saturation integration algorithm is proposed to solve the saturation integral problem in motor speed-loop control. The system simulation results show that the decoupling current control performance is significantly improved, and the speed response performance is good.

关键词： Permanent magnet motors Synchronous motors Permanent magnets Steady-state Mathematical model Machine vector control Stators

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A resonant cavity based on birdcage coil for overhauser geomagnetic sensor

A resonant cavity based on birdcage coil for overhauser geom...

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2018 IEEE International Instrumentation and Measurement technology Conference, I2MTC 2018

作者： Bai, Bingjie Dong, Haobin Ge, Jian Liu, Huan Zhang, Cheng Wang, Luo Institute of Geophysics and Geomatics China University of Geosciences Hubei Wuhan China School of Automation China University of Geosciences Hubei Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan China Science and Technology on Near-Surface Detection Laboratory Jiangsu Wuxi China

ISBN: (纸本)9781538622223

The resonant cavity is an important component of Overhauser magnetometer sensor. Its function is to make the working substance generate dynamic nuclear polarization effect in the sensor. An alternative design of resonant cavity based on the birdcage coil structure was proposed to make the resonant frequency in accordance with the polarization frequency of the working substance. The structure and equivalent circuit of resonant cavity were analyzed. The model of resonant cavity was established and S-parameter is calculated to verify the frequency consistency of the resonant cavity and working substance. In addition, output signal experiment and simultaneous comparison testing of sensor prototype were conducted. Overall, this design has the advantages of high performance and strong anti-interference. © 2018 IEEE.

关键词： Equivalent circuits

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