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3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021

作者： Xiaoyun, Shen Zixuan, Zhao Siyuan, Zhang Weidong, Jiao Chong, Ma Tianying, Wang Tianjin Key Lab for Advanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9781665425186

To accurately perceive sudden airflow changes during flight and avoid aviation safety risks caused by sudden weather at high altitudes, it is necessary to invert and reconstruct the wind field during flight. Based on the random sample consensus estimation, the improved Least Squares algorithm is used to fit the Automatic Dependent Surveillance-Broadcast (ADS-B) data. Firstly, the vertical wind profile is constructed by inverting the wind vectors at different altitude levels at the fixed airport location and compared with the meteorological data of the European Center for Medium-Range Weather Forecasts (ECMWF) to verify the feasibility and accuracy of the algorithm. Then, the wind field under the complete track of a specific flight is reconstructed to obtain the wind field distribution along the route. Finally, regional wind fields at different altitudes are reconstructed using multiaircraft data in a fixed range. The experimental results show that this method can better reflect the real complex wind field structure. © 2021 IEEE

关键词： Weather forecasting

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Track prediction algorithm based on GA-BPNN 3

Track prediction algorithm based on GA-BPNN

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3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021

作者： Jiao, Weidong Ma, Chong Tianjin Key Lab for Advanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9781665425186

A track prediction algorithm is proposed based on the Genetic Algorithm (GA) and Back Propagation neural network (BPNN), in which the GA is used to optimize the initial weights and thresholds of hidden layers of the network. Firstly, a 5-5-4 topology of the BPNN for track prediction is established according to the characteristics of track prediction. Its inputs are historical tracks, and the output just is the predicted track. Secondly, the weights and thresholds of the BPNN are regarded as genes of individual in GA to construct chromosomes, individuals, and populations. Then, the optimal solution of the GA is used as the weights and thresholds of the BPNN for network training to get a better output. In the experiment, the track data are derived from Automatic Dependent Surveillance-Broadcast, and experimental results show that the proposed algorithm can improve both the accuracy and time efficiency of the BPNN. In addition, we use the predicted track of the proposed method to detect flight conflict by constructing conflict scenarios. The detecting process and results are visualized in the Geographic Information System, and the correct results of detecting again show that the proposed method is reliable. © 2021 IEEE

关键词： Forecasting

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Robust beamforming method based on FDA-MIMO radar

Robust beamforming method based on FDA-MIMO radar

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IET International Radar Conference (IRC 2023)

作者： Zhixia Wu Shengqi Zhu Jingwei Xu Lan Lan Ximin Li Feilong Liu Yike Wang Qingyun Kan National Key Lab. of Radar Signal Processing Xidian University Xi'an 710071 People's Republic of China

ISBN: (数字)9781837240982

In this work, a robust two-dimensional beamforming algorithm based on frequency diversity array multiple-input multiple-output (FDA-MIMO) radar is proposed. The algorithm focuses on scenarios where mainlobe deceptive jamming and sidelobe barrage jamming coexist, taking into account estimation errors in the jamming angle-range. The algorithm initially employs a smoothing technique to eliminate true targets from the samples, utilizing the Mailloux method to expand the null associated with jamming, thereby ensuring robustness against errors. Simulation results confirm the effectiveness of the proposed algorithm.

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Precoding Schemes for Wireless Beam Modulation System

Precoding Schemes for Wireless Beam Modulation System

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IEEE Conference on Vehicular Technology (VTC)

作者： Xiao Chen Congxi Liu Xinyan Yu Hang Long Wireless Signal Processing and Network Lab. Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Millimeter wave communication systems offer a new perspective for addressing bandwidth congestion, but their high hardware cost and power consumption limit their application in Internet of Things (IoT) devices. A wireless beam modulation (WBM) system has been proposed as a cost-effective alternative. The patch antenna array on the IoT nodes formulates two transmit beams with different directions. Information bits are transmitted through the energy difference of aligned beams by WBM. However, challenges arise from the random emission of beams and the avoidance of complex data processing, resulting in signal attenuation and reduced communication quality. In this paper, the optimal precoding scheme is first derived, and then we design a manifold optimization-based precoding scheme that directly handles the constant modulus constraint of the precoding vectors. Simulation results show that the proposed precoding scheme achieves a significant performance improvement over existing ones and performs close to the theoretical upper bound when the gains of the different paths in the channel are fairly consistent.

关键词： Wireless communication Vehicular and wireless technologies Upper bound Precoding Simulation Transmitting antennas Modulation

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lab.l Matching: It Is Complicated

Label Matching: It Is Complicated

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International Conference on Information Fusion

作者： Kuangyu Di Tiancheng Li Guchong Li Yan Song Xudong Dang Key Lab. Inform. Fusion Tech Northwestern Polytechnical University Xi’an China National Key Laboratory of Radar Signal Processing Xidian University Xi’an China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper addresses the intractable track matching problem involved in multi-sensor multi-target tracking using the lab.led multi-Bernoulli filters. Unlike the unlab.led density defined in the common state space, the lab.led multi-target density is defined in the joint state and lab.l space, where the lab.l contains time-series/history information of the underlying track. To measure the similarity between lab.led densities (individual tracks) that is required for inter-sensor track matching and fusion, one has to account for the divergences in both state and lab.l spaces. The challenge, however, arises from the lack of a proper metric to measure the lab.l difference. It requires considering the entire trajectory of the track, encompassing the whole-life information from the birth of the track to the present. In this paper, we provide a solution of comparing and matching lab.ls based on the whole-life time-series state distributions of the lab.ls/tracks, by extending the common divergences like the Cauchy-Schwarz and Kullback-Leibler from distributions at a single time-instant to those over time-series. Representative scenarios are considered for illustration.

关键词： Radio frequency Matched filters Target tracking Density measurement Information filters Extraterrestrial measurements Trajectory

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ESA-Net: A network for enhancing small target detection performance in SAR imagery aircraft

ESA-Net: A network for enhancing small target detection perf...

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IET International Radar Conference (IRC 2023)

作者： Ping Han Han Zhao Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin People's Republic of China

ISBN: (数字)9781837240982

In synthetic aperture radar (SAR) image aircraft target detection, aircraft small targets have a lower AP than aircraft targets and large targets due to the small number of pixel points they occupy and background clutter interference. To solve this problem, this paper proposes a network for enhancing the performance of aircraft small target detection for SAR images(ESA-Net). The network is designed based on yolov5s with a backbone network BH-CSPDarknet and a detection head ***-CSPDarknet allocates more computational resources in the shallow layer of the network to process high-resolution feature maps, which effectively extracts richer feature information of aircraft small ***-Head provides appropriate feature preferences for classification and localisation tasks to provide TFA-Head provides appropriate feature information for classification and positioning task feature preferences, which can effectively suppress the background clutter interference while enhancing the aircraft small target features. The experimental results using the SAR-ADRD dataset show that the method improves the average accuracy of YOLOv5s by 1.9% and the average accuracy of aircraft small targets by 15.6%.

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A SELF-ADAPTIVE SUBGRADIENT EXTRAGRADIENT ALGORITHM WITH INERTIAL EFFECTS FOR VARIATIONAL INEQUALITIES

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2022年第2期84卷 69-80页

作者： Dong, Qiao-Li Li, Xiao-Huan Yin, Tzu-Chien College of Science and Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin300300 China College of Science Civil Aviation University of China Tianjin300300 China Research Center for Interneural Computing China Medical University Hospital China Medical University Taichung40402 Taiwan

In this paper, we introduce a new self-adaptive subgradient extragradient algorithm with inertial effects for variational inequality, for which the stepsize is chosen by a new way. The weak convergence of the algorithm is established. The numerical examples are given which illustrate the efficiency and advantage of the proposed algorithms. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Variational techniques

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Path planning based on fuzzy-control Dynamic Window Approach 3

Path planning based on fuzzy-control Dynamic Window Approach

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3rd International Conference on Control and Intelligent Robotics, ICCIR 2023

作者： Chen, Wantong Yang, Qianqian Chen, Min Li, Xiaoqiang Liu, Zhuo Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin China School of Electronic Information and Automation Civil Aviation University of China Tianjin China Beijing Sky Aviation Co. Ltd China Sichuan Jiuzhou Aerocont Technologies Co. Ltd China

ISBN: (纸本)9781510671867

A method integrating rapidly-exploring random tree (RRT) and improved dynamic window approach (DWA) is proposed to realize obstacle avoidance of mobile robots in complex dynamic obstacle environments. Based on the known environment information, the global optimal safe path is generated using the improved RRT algorithm. To address the problem of too many invalid nodes in the expansion of the RRT algorithm, the efficiency of the algorithm is improved by introducing a bidirectional alternating search (BAS) strategy;the forward search tree and the backward search tree alternate searching paths with new nodes as the target nodes until the paths meet;and the redundant nodes in the paths are removed using path node filtering to shorten the path. Secondly, the DWA algorithm is used to track the improved RRT algorithm to plan the path. When unknown obstacles appear in the environment, the weights of the DWA algorithm evaluation function are dynamically adjusted by fuzzy control to avoid the obstacles and return to the original route in time. Finally, the simulation experiments verify that the proposed improved fusion algorithm in complex dynamic environment has short running time, small path cost, and always keeps a safe distance from the obstacles to ensure the optimal path is tracked while safely avoiding the dynamic obstacles. © 2023 SPIE.

关键词： Fuzzy control

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Airport Runway Conflict Detection And Visual Simulation

Airport Runway Conflict Detection And Visual Simulation

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Aerospace Engineering and Systems (ISAES), International Symposium on

作者： Tao Song Siyuan Zhang Xiaoyun Shen Siming Yan Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin China Technical Support Department Chongqing Sub-bureau of Southwest China Reginal ATMB Chongqing China

ISBN: (数字)9798350350418

ISBN: (纸本)9798350350425

In order to prevent runway intrusion events due to the incorrect deployment of aircraft by controllers with insufficient situational awareness, a 3D visual simulation system for runway conflict detection is designed. By analyzing different types of conflict scenarios of aircraft arrival and departure, the runway conflict models are constructed, and for different conflict models, the spatial distance method is used to determine whether runway incursion of the aircraft occurs. Then the combination of spatial distance and time threshold are used for the conflict alarm. The runway protection area is constructed, the aircraft motion model of the airport surface is established based on the data of airport surveillance data. The visual simulation of the arrival and departure conflict detection algorithm is realized on the Unreal Engine 4 platform. The experimental results show that according to the arrival and departure conflict detection, when aircrafts are close to each other and less than the encounter time threshold, the system can detect the runway conflict in real time and give the alarm.

关键词： Visualization Solid modeling Analytical models Three-dimensional displays Atmospheric modeling Airports Aircraft manufacture Aircraft Detection algorithms Engines

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FOCT: Few-shot Industrial Anomaly Detection with Foreground-aware Online Conditional Transport 24

FOCT: Few-shot Industrial Anomaly Detection with Foreground-...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Tian, Long Zhao, Hongyi Lu, Ruiying Wang, Rongrong Wu, Yujie Wang, Liming He, Xiongpeng Liu, Xiyang National Pilot School of Software Engineering Xi'Dian University Xi'an Shi Chang'an Qu China School of Cyber Engineering Xidian University Xi'an Shi Chang'an Qu China National Key Lab. of Radar Signal Processing Xidian University Xi'an Shi Chang'an Qu China National Pilot School of Software Engineering Xi'Dian University Xi'an Chang'an Qu China

ISBN: (纸本)9798400706868

Few-Shot Industrial Anomaly Detection (FS-IAD) has drawn great attention most recently since data efficiency and the ability to design algorithms for fast migration across products have become the main concerns. The difficulty of memory-based IAD in low-data regime primarily lies in inefficient measurement between the memory bank and query images. We address such a pivotal issue from a new perspective of optimal matching between features of image regions. Taking the unbalanced nature of query features into consideration, we adopt Conditional Transport (CT) as a metric to compute the structural distance between representations of the two sets to determine feature relevance. CT distance generates the optimal matching flows between unbalanced structural elements that achieve the minimum matching cost, which can be directly used for IAD since it well reflects the differences of query images compared with the normal memory. Realizing the fact that query images usually come one-by-one or batch-by-batch, we further propose an Online Conditional Transport (OCT) by making full use of the current and historical query images for IAD via simultaneously calibrating the memory bank using the online query images and matching features between the calibrated memory and the current query image. Go one step further, for sparse foreground products, we employ a predominant segment model to implement Foreground-aware OCT (FOCT) for improving the effectiveness and efficiency of OCT by forcing the model to pay more attention to diverse targets rather than redundant backgrounds when calibrating the memory bank. FOCT can improve the diversity of calibrated memory, which is critical for robust FS-IAD in practice. Besides, FOCT is flexible since it can be friendly plugged and played with any pre-trained backbones, such as WRN, and any pre-trained segment models, such as SAM. The effectiveness and efficiency of our model is demonstrated across diverse datasets, including benchmarks of MVTec and

关键词： Anomaly detection

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