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Chinese Control Conference

作者： Wang Luo Haobin Dong Jian Ge Huan Liu Bingjie Bar Cheng Zhang Zhiwen Yuan Jun Zhu Haiyang Zhang Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Wuhan Hubei China Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu China

This paper presents an all-solid porous Ag/AgCl electric field sensor with ultralow-potential drift for detecting the seafloor electric field signals. The superiority of porous electrode compared with flat electrode on the polarization stability is expounded, and the technological process using solid state agglomeration in developing the all-solid porous Ag/AgCl electrode core are described. Moreover, a new sensor shell is proposed. Numerous parameters, e.g., polarization resistance, self-potential, drift, etc., of the proposed electrode are tested. The experimental results show that the self-potential is less than ±0.1 mV, the source resistance is less than 0.01H, and the drift potential is less than ±5μV/24h, which indicate the superior performance of the proposed Ag/AgCl electric field sensor for marine electric field exploration.

关键词： Electrodes Electric potential Resistance Electric fields Solids Thermal stability Sea measurements

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3D non-stationary geometry-based stochastic model for unmanned aerial vehicle air-to-ground multi-input multi-output channels

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Journal of Southeast University(English Edition) 2022年第4期38卷 323-331页

作者： Yan Feng Zhou Tianxiang Li Hao Pang Jingming Ding Kai Xia Weiwei Shen Lianfeng National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Science and Technology on Near-Surface Detection Laboratory Wuxi 214035China Jiangsu Zhongli Electronic Information Sci-Tech Co. Ltd.Changshu 215542China

A three-dimensional non-stationary geometry-based stochastic model for unmanned aerial vehicle(UAV)air-to-ground multi-input multi-output(MIMO)channels is *** scatterers surrounding the UAV and ground station are assumed to be distributed on the surface of two cylinders in the proposed *** impact of UAV rotations and accelerated motion is considered to describe channel *** computational methods of the corresponding time-variant parameters,such as UAV antenna array angles,time delays,and maximum Doppler frequencies,are theoretically *** model is then used to derive channel statistical properties such as space-time correlation functions and Doppler power spectral ***,numerical simulations are run to validate the channel s statistical *** simulation results show that increasing the UAV and ground station accelerations can reduce the time correlation function and increase channel non-stationarity in the time ***,the UAV s rotation significantly influences the spatial correlation function,with rolling having a greater influence than ***,the different directions of UAV movement significantly impact the Doppler power spectral density.

关键词： unmanned aerial vehicles(UAVs) geometry-based stochastic model(GBSM) air-to-ground channels

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Aerial Tracking of Camouflaged People in Woodlands Via Unsupervised Learning

SSRN

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SSRN 2023年

作者： Liu, Yang Wang, Congqing Xu, Bin Zhou, Yongjun College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Science and Technology on Near-Surface Detection Laboratory Wuxi214000 China

With the widespread use of unmanned aerial vehicles (UAVs) and computer vision, much attention has been devoted to aerial tracking. Previous tracking methods were mostly implemented in clean and well-lit environments, making it challenging to track camouflaged people rapidly and accurately in woodlands. In this work, we develop a novel unsupervised learning framework for camouflaged people aerial tracking (named UCAT) based on transformer. Specifically, a camouflaged people discovery strategy is proposed to rapidly generate training samples from the unlabeled videos captured by the UAV. Dynamic programming is also employed to filter noises to generate smooth candidate frames. To make full use of multi-level feature information, a transformer fusion framework is designed to integrate shallow spatial information and in-depth semantic features. For reducing computing consumption, the spatial attention reduction mechanism is embedded to the multi-head attention for fast tracking. Further, we build a dataset for evaluating the effect of camouflaged people tracking called Cam235, which consists of 85 manually labeled test sequences and over 100k frames of the unlabeled training set. Comprehensive experiments on Cam235-test and popular tracking benchmarks show that the UCAT learned from unlabeled videos performs well in camouflaged people tracking, demonstrating the practical value of the tracker. © 2023, The Authors. All rights reserved.

关键词： Unsupervised learning

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UAV trajectory planning algorithmfor data collection in wireless sensor networks

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Journal of Southeast University(English Edition) 2020年第4期36卷 376-384页

作者： Yan Feng Chen Jiahui Wu Tao Li Hao Pang Jingming Liu Wanzhu Xia Weiwei Shen Lianfeng National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Jiangsu Zhongli Electronic Information Sci-Tech Co. Ltd.Changshu 215542China Science and Technology on Near-Surface Detection Laboratory Wuxi 214035China

In order to maximize the value of information(VoI)of collected data in unmanned aerial vehicle(UAV)-aided wireless sensor networks(WSNs),a UAV trajectory planning algorithm named maximum VoI first and successive convex approximation(MVF-SCA)is ***,the Rician channel model is adopted in the system and sensor nodes(SNs)are divided into key nodes and common ***,the data collection problem is formulated as a mixed integer non-linear program(MINLP)*** problem is divided into two sub-problems according to the different types of SNs to seek a sub-optimal solution with a low ***,the MVF-SCA algorithm for UAV trajectory planning is proposed,which can not only be used for daily data collection in the target area,but also collect time-sensitive abnormal data in time when the exception *** results show that,compared with the existing classic traveling salesman problem(TSP)algorithm and greedy path planning algorithm,the VoI collected by the proposed algorithm can be improved by about 15%to 30%.

关键词： unmanned aerial vehicle wireless sensor networks trajectory planning data collection value of information

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Optimization of Overhauser magnetometer based on multi-channel frequency measurement algorithm

Optimization of Overhauser magnetometer based on multi-chann...

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Chinese Control Conference (CCC)

作者： Guanzhong Wang Haobin Dong Jian Ge Vang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Wuhan Hubei China Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu China

Overhauser magnetometer is a weak magnetic measuring instrument based on the dynamic nuclear polarization of free radical species. It has the characteristics of high precision, high sensitivity, low power consumption and continuous measurement. It is widely used in geophysics, aeromagnetic surveying, satellite Magnetic measuring, military and various engineering fields. Aiming at the problem that the measurement accuracy of the magnetometer prototype is low and the measurement effect is poor when the angle between the probe axis and the geomagnetic field is 0°, several optimization methods are proposed and the magnetometer is optimized by adding the frequency measurement channel on the basis of the prototype. Based on the standard deviation of GSM-19 measurement data, comparing the experimental data that use the multi -channel frequency measurement algorithm, the standard deviation of prototype data decreases from 0.397 to 0.203 when the angle between probe axial and geomagnetic field is 45°, the standard deviation of the prototype data decreases from 0.631 to 0.371 when the angle between probe axial and geomagnetic field is 0°, which provides an important reference for the follow-up optimization of the magnetometer.

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PCA applied to Data Fusion for Subsurface Target Imaging of Full-polarimetric GPR 9

PCA applied to Data Fusion for Subsurface Target Imaging of ...

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9th International Conference on Environmental and Engineering Geophysics, ICEEG 2020

作者： Xue, Cewen Feng, Xuan Zhou, Haoqiu Li, Xiaotian Liang, Wenjing Wang, Ying College of Geo-Exploration Science and Technology Jilin University No.938 Xi MinZhu Street Changchun130026 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China Institute of National Development and Security Studies Jilin University No.2699 Qianjin Street Changchun130012 China No.938 Xi MinZhu Street Changchun130026 China

Full-polarimetric ground penetrating radar (GPR) can obtain more comprehensive polarization data (called VV, HH, VH) for the same target than traditional commercial radar (only VV). We need to use data fusion technology to combine the polarization information of the three different polarization modes. However, the full-polarimetric GPR data fusion method has one weighted average fusion, which will mask the advantages of full polarization. Principal component analysis (PCA) is a technology of data dimensionality reduction and compression which can use VV, HH and VH as a three-dimensional data to conduct data dimensionality reduction and find the best data fusion results. In order to check the reliability, we obtained the full-polarimetric GPR data of three typical targets in the laboratory for analysis. Then we compare PCA with the weighted average fusion method by using the instantaneous amplitude and conclude that PCA can fuse full-polarimetric GPR data better than weighted average fusion. © Published under licence by IOP Publishing Ltd.

关键词： Principal component analysis

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Optimal Design of End Suspension Electromagnet for Medium Speed Maglev Train

Optimal Design of End Suspension Electromagnet for Medium Sp...

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Chinese Control Conference (CCC)

作者： Peichang Yu Shelin Chen Ming Gao Qing Yang Lianchun Wang Jinhui Li College of Intelligence Science and Technology National University of Defense Technology Changsha China CRRC Tangshan Co. Ltd Tangshan China Science and Technology on Near-surface Detection Laboratory Wuxi China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In order to solve the discernment of bearing capacity and system controllable of end-suspension electromagnet caused by eddy current effect of the medium-speed maglev train, the optimal design of the end-electromagnet is carried out. First of all, the suspension force of the electromagnet is analyzed based on basic electromagnetic theory. The theoretical equation of electromagnetic force considering the eddy current effect is established, and the characteristics of the eddy current effect in the speed range of 0 to 200 km/h are analysed. Then, this article discussed the optimal design of the end electromagnet for medium-speed maglev train. On the one hand, from the perspective of the existing electromagnet, the relationship between the loss of magnetic flux density and speed, length of the electromagnet was studied to clarify the feasibility of the optimal scheme. On the other hand, from the perspective of the dynamics of the suspension module, an optimization scheme for load capacity of the suspension module is proposed by considering the effects of magnetic saturation. At last, the dynamical and electric model of the optimal end electromagnet were established, and the controllability analysis was performed. The research and simulation show that the optimal design of the end electromagnet combined with the adjustment of the bearing force from the vehicle can meet the requirements of the medium speed maglev train operating in the whole range speed of 0-200km/h.

关键词： Electromagnets Suspensions Magnetic levitation Magnetic flux Force Coils

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Intelligent Traffic Monitoring with Distributed Acoustic Sensing

arXiv

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arXiv 2024年

作者： Xie, Dongzi Wu, Xinming Guo, Zhixiang Hong, Heting Wang, Baoshan Rong, Yingjiao School of Earth and Space Sciences University of Science and Technology of China Hefei China Mengcheng National Geophysical Observatory Mengcheng China Science and Technology Near-Surface Detection Laboratory Wuxi China

Distributed Acoustic Sensing (DAS) is promising for traffic monitoring, but its extensive data and sensitivity to vibrations, causing noise, pose computational challenges. To address this, we propose a two-step deep-learning workflow with high efficiency and noise immunity for DAS-based traffic monitoring, focusing on instance vehicle trajectory segmentation and velocity estimation. Our approach begins by generating a diverse synthetic DAS dataset with labeled vehicle signals, tackling the issue of missing training labels in this field. This dataset is used to train a Convolutional Neural Network (CNN) to detect linear vehicle trajectories from the noisy DAS data in the time-space domain. However, due to significant noise, these trajectories are often fragmented and incomplete. To enhance accuracy, we introduce a second step involving the Hough transform. This converts detected linear features into point-like energy clusters in the Hough domain. Another CNN is then employed to focus on these energies, identifying the most significant points. The inverse Hough transform is applied to these points to reconstruct complete, distinct, and noise-free linear vehicle trajectories in the time-space domain. The Hough transform plays a crucial role by enforcing a local linearity constraint on the trajectories, enhancing continuity and noise immunity, and facilitating the separation of individual trajectories and estimation of vehicle velocities (indicated by trajectory slopes in the Hough domain). Our method has shown effectiveness in real-world datasets, proving its value in real-time processing of DAS data and applicability in similar traffic monitoring scenarios. All related codes and data are available at https://***/TTMuTian/itm/. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Speckle suppression of SAR image using boundary and contextual constraint

Speckle suppression of SAR image using boundary and contextu...

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IET International Radar Conference (IET IRC 2020)

作者： W. Yuming L. Chaopeng J. Tian Z. Yansong College of Information Science and Engineering Hunan Normal University Changsha China Science and Technology on Near-Surface Detection Laboratory Wuxi China College of Electronic Science and Technology National University of Defense Technology Changsha China

Speckle suppression is a important preprocessing step for synthetic aperture radar (SAR). In this paper, a speckle suppression algorithm based boundary and contextual constraint is studied for enhancing image, which includes the establishment of speckle model based on boundary constraint, the analysis of speckle factor weighted constraint model based on contextual regularization, and the process of speckle factor estimation. The performance of this algorithm is validated by using the data acquired over an airship mounted SAR system.

关键词： airships speckle synthetic aperture radar radar imaging

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A full-polarimetric GPR system and its application in ice crack detection 9

A full-polarimetric GPR system and its application in ice cr...

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9th International Conference on Environmental and Engineering Geophysics, ICEEG 2020

作者： Li, Xiaotian Feng, Xuan Liang, Wenjing Xue, Cewen Zhou, Haoqiu Wang, Ying College of Geo-Exploration Science and Technology Jilin University No.938 Xi Min Zhu Street Changchun130026 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China Institute of National Development and Security Studies Jilin University No.2699 Qianjin Street Changchun130012 China No.938 Xi Min Zhu Street Changchun130026 China

The warming season of Antarctica, where sea ice melts and breaks, is often the golden time for Antarctic research. But this season is also a high frequency season for the formation of ice crack, the existence of which poses a serious threat to Antarctic scientific research. Therefore, it is of important significance to monitor the trend, location, and depth of Antarctic sea ice crack in real time. Ice crack detection often uses ground penetrating radar (GPR) technology. Compared with the single-polarimetric GPR, full-polarimetric GPR can obtain more comprehensive polarization information. Therefore, a full-polarimetric GPR system based on the horn antenna is built in this paper to obtain more abundant ice crack information. Then we apply it to detect a small-scale ice crack atop frozen lakes. The analysis of the experiments and data fusion processing results can verify the effectiveness of the system for the detection of ice crack and lay the foundation for subsequent actual detection. © Published under licence by IOP Publishing Ltd.

关键词： Ground penetrating radar systems

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