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检索条件"机构=Key Laboratory of Science and Technology on Near-Surface Detection"

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Shoal Target Recognition Based on Sample Data Enhancement and Target detection 3rd

Shoal Target Recognition Based on Sample Data Enhancement an...

引用

3rd International Conference on Advanced Intelligent Technologies, ICAIT 2022

作者： Wang, Jian Jun Xu, Yue Lin Wang, Shi Rui Du, Xing Yue CSSC Ocean Exploration Technology Institute Co. Ltd Jiangsu Wuxi China Science and Technology On Near-Surface Detection Laboratory Jiangsu Wuxi China

ISBN: (纸本)9789819952021

For shoal targets (boats, cars, people, etc.), the data is scarce and fuzzy, and it is difficult to detect and identify. A data enhancement technology based on generative adversarial network and target detection method based on multi-scale feature fusion and knowledge distillation are proposed. First, in the absence of paired data, it is not necessary to establish a one-to-one mapping between training data, and learn the method CycleGAN from the source data domain X to the target data domain Y, so as to realize the migration between the source domain and the target domain. So as to obtain shoal target images in different environments, construct shoal target datasets of different categories, and solve the problem of scarcity and blur of shoal target data. Then, by studying the use of atrous convolution to replace the general convolution kernel, the small target detection performance is improved and the spatial feature pyramid pooling structure based on the attention mechanism is used to realize the fusion of local features and global features, enrich the feature information of the target itself, and suppress the influence of environmental factors such as illumination on target detection improves the detection performance of the model in dark night scenes, so as to achieve target detection and recognition. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Distillation

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BOTTOM REVERBERATION SUPPRESSION USING DELAY-DOPPLER DECONVOLUTION FOR THE detection OF LOW-SPEED SMALL TARGETS IN VERY SHALLOW WATER 28

BOTTOM REVERBERATION SUPPRESSION USING DELAY-DOPPLER DECONVO...

引用

28th International Congress on Sound and Vibration, ICSV 2022

作者： Yacong, Zhao Xionghou, Liu Chao, Sun Jie, Zhuo Yixin, Yang School of Marine Science and Technology Northwestern Polytechnical University Shaanxi Xi'an710072 China Shaanxi Key Laboratory of Underwater Information Technology Shaanxi Xi'an710072 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China

ISBN: (纸本)9789811850707

In the scenarios of detecting the underwater low-speed small targets (e.g., frogmen or UUVs) in the very shallow water environment (e.g., harbor or shoal where the water depth is about several meters), much attention has been attracted on reverberation suppression. Based on the Doppler difference between the moving target echoes and the bottom reverberation dominant in the very shallow water, the traditional matched filtering may realize the separation of the bottom reverberation and the target echoes. However, the Doppler incurred by low-speed small targets is quite small, so the performance on the bottom reverberation suppression seriously degrades due to the limitation of Doppler resolution of the traditional approach. Therefore, it is urgent to improve its Doppler resolution to separate low-speed small targets out from the nearly static bottom reverberation. Generally, the reverberation and the target echoes can be considered as the weighted sum of the copies of transmitted signal with different delay and Doppler, which indicates that "the cross-ambiguity function of the received echo is approximately the two-dimensional convolution of the auto-ambiguity function of transmitted signal and the generalized "target" reflectivity density function (i.e., the weighted sum of the 2-D Dirac Delta function convolved with different delays and Doppler shifts)". In this paper, regarding the auto-ambiguity function of the transmitted signal as the 2-D point spread function (PSF), an iterative deconvolution algorithm called the Richardson-Lucy (R-L) algorithm is exploited to deblur the conventional delay-Doppler output. This processing can obtain approximately the generalized "target" reflectivity density function similar to the thumbtacks, which can significantly improve the resolution of the delay and Doppler of the raw output, and separate the slow-speed small targets submerged by the bottom reverberation. Simulations show the effectiveness and superiority of the proposed

关键词： Reflection

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An unsupervised aerial tracking method of camouflaged targets in complex environments 3

An unsupervised aerial tracking method of camouflaged target...

引用

3rd International Conference on Defence technology, ICDT 2022

作者： Liu, Yang Wang, Cong-Qing 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 UAVs and the development of various technologies related to computer vision, much attention has been devoted to UAV-based target tracking. For the task of tracking camouflaged people in complex environments, there is a shortage of annotated datasets and poor backbone feature extraction network capabilities, which will cause tracking drift and tracking lag. To achieve unsupervised UAV target tracking under unsupervised conditions, a new target tracking model has been designed. First, we roughly detect moving targets using a camouflaged segmentation network, and then apply dynamic programming to generate smooth candidate boxes. Secondly, a deeper convolutional neural network is designed for feature extraction to replace the original backbone network, and the residual structure is modified to ensure tracking effectiveness. Extensive comparative experiments have shown that the proposed unsupervised method performs the task of UAV target tracking well. © Published under licence by IOP Publishing Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Lightweight-YOLOv5s for the camouflaged personnel detection in the woodland 3

Lightweight-YOLOv5s for the camouflaged personnel detection ...

引用

3rd International Conference on Defence technology, ICDT 2022

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

Unmanned aerial vehicles(UAVs) technology and target detection technology are increasingly integrated. However, the target detection networks are cumbersome and complex, and it is hard to directly deploy these networks on the UAVs. To address this problem, a Lightweight-YOLOv5s which can be applied to the UAVs is proposed to detect the camouflaged personnel in the woodland. Depthwise separable convolutions are added to the YOLOv5s for reducing the parameters and computational effort. Then a new channel pruning method based on Batch Normalization(BN) layer scaling factor with adaptive sparsity training is proposed for network compression, which can balance the compression ratio and accuracy of the detection. The pruned network is then fine-tuned to detect the camouflaged personnel. In addition, a special dataset is built for the camouflaged personnel detection in the woodland. The quantitative results on this dataset prove that the proposed Lightweight-YOLOv5s greatly improve the YOLOv5s. Parameters from 7.06M to 1.86M, floating point operations from 16.4G to 9.9G and inference time from 8.16ms to 7.06ms. Besides, mAP of the Lightweight-YOLOv5s is 0.83, which shows the excellent detection performance of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Antennas

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Application of update lifting morphological wavelet and non-negative matrix factorization for wheeled and tracked vehicles classification 9

Application of update lifting morphological wavelet and non-...

引用

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

作者： Ding, Kai Du, Kai Qi, Xiaogang Xu, Yuelin Cui, Junqi Science and Technology on Near -Surface Detection Laboratory Wuxi214035 China 31104 Troops Nanjing210007 China Xidian University Xi'an710071 China

This paper presents an available scheme based on update lifting morphological wavelet (ULMW) and Non-negative matrix factorization (NMF) for wheeled and tracked vehicles classification. The ULWM algorithm which utilizes the update operator, means the morphological filter to replace the linear filter can preserve the impulsive shape details in seismic signal. Meanwhile the NMF method can reduce the computation cost. The traditional linear wavelet analysis and statistical analysis are compared with the presented scheme. Experimental results demonstrate that the presented scheme achieves a promising performance on extracting impulsive features of seismic signal and recognizing ground moving target. © Published under licence by IOP Publishing Ltd.

关键词： Non-negative matrix factorization

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Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter 2

Ship Tracking with Static Electric Field Based on Adaptive P...

引用

2nd International Conference on Electronic Information technology and Computer Engineering, EITCE 2018

作者： Hu, Shouwei Yan, Bing Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu214035 China College of Weapon Engineering Naval University of Engineering Wuhan Hubei430033 China

An adaptive progressive update extended Kalman filter is introduced for unknown noise in ship tracking using static electric field. The corresponding state space model is established;the algorithm is introduced, and the simulation is designed. The simulation results show that the adaptive algorithm can effectively improve the performance of the algorithm, when the noise covariance deviates from the real value;the finite number of noise covariance estimation is beneficial to the stability of the filter. © The Authors, published by EDP sciences, 2018.

关键词： Extended Kalman filters

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A Method Based on Relaxation Frequency for Object Recognition

A Method Based on Relaxation Frequency for Object Recognitio...

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2022 International Conference on Signal Processing, Computer Networks, and Communications, SPCNC 2022

作者： Qu, ShiHua Jiang, HeJun Luo, ZhaoPeng Wang, Zhan Zheng, FanFu Xiao, KeZhen Wu, MeiWu The 50th Research Institute of China Electronics Technology Group Corporation Shanghai200331 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China

ISBN: (纸本)9781510664616

This paper proposes a target recognition technique based on target relaxation frequency parameters. These parameters are calculated from the frequency response observed by multi-frequency magnetic induction. Firstly, we prepare multi-frequency response and class labels of various materials. The least-square optimization method calculates the prepared materials' relaxation frequency characteristic parameter matrix. Secondly, the matrix is used in the linear regression method to calculate the regression model's undetermined coefficients. Then the coefficients help us to obtain the class label of the target. Finally, we compare the target label with the prepared class labels to identify the substance type of the target. The results show that the technique proposed in this paper can accurately identify and classify the substance type of the target, and the multi-frequency magnetic induction technology based on relaxation frequency can be applied in substance identification. © 2023 SPIE.

关键词： Least squares approximations

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UAV-Borne Landmine detection via Intelligent Multispectral Fusion 4

UAV-Borne Landmine Detection via Intelligent Multispectral F...

引用

4th International Conference on Applied Machine Learning, ICAML 2022

作者： Guo, Hangfu Jiang, Hejun Hu, Jun Luo, Chaopeng School of Electronics and Communication Engineering Sun Yat-Sen University Shenzhen518107 China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China

ISBN: (纸本)9781665462655

Compared with traditional landmine detection methods, the unmanned aerial vehicle borne measure is more suitable for rapidly detecting large-area minefields of scatterable landmines. We propose a multispectral fusion strategy based on a deep learning model to facilitate landmine detection. With a UAV-borne multispectral cruise platform, we set up a multispectral dataset of scatterable landmines, where varieties of minefields with different ground vegetation environments are considered. The proposed technique includes a structure with adjustable weights to fulfill the fusion and refinement, and maximize the utilization of multispectral information. Experimental comparisons of the predictions before and after fusion demonstrate that our proposed fusion strategy can improve the recall rate and achieve significant gains over single-spectrum detection, especially for the occluded mines, and confirm the feasibility of the multispectral data with reasonable processing for the landmine detection. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Speckle suppression of SAR image using boundary and contextual constraint 5

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

引用

IET International Radar Conference 2020, IET IRC 2020

作者： Yuming, Wang Chaopeng, Luo Tian, Jin Yansong, Zhang 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

ISBN: (纸本)9781839535635

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. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Speckle

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Unmanned unexploded ordnance detection system based on magnetic method 20

Unmanned unexploded ordnance detection system based on magne...

引用

20th International Conference on Ground Penetrating Radar, GPR, 2024

作者： Xu, Y.L. Zhou, Y.J. Ding, K. Lv, R.Q. Wu, M.W. Wang, Z. Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China The 50th Research Institute of China Electronics Technology Group Corporation Shanghai200331 China

Magnetic method is one of the main methods of UXO detection. This paper uses cesium optical pump magnetic detection module combined with UAV to build an unmanned UXO detection system, and introduces the detection principle and composition of the system. At the same time, the system is used to detect four kinds of UXO targets. The test results show that the system can detect ferromagnetic UXO targets, and can locate the position of UXO targets through magnetic anomaly images. Finally, the limit detection range of four kinds of targets is tested, and the limit detection range of 155 projectiles can reach 4.5m, which meets the actual detection requirements © Published under licence by IOP Publishing Ltd.

关键词： Target tracking

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