检索结果-内蒙古大学图书馆

Covert Communications in D2D Underlaying Cellular Networks With Dual Uncertainties at the Warden

IEEE Internet of Things Journal 2025年第12期12卷 21195-21209页

作者： Du, Zhiyi Chen, Weiyu Luo, Junshan Ding, Haiyang Wang, Shilian Sun, Zhengbo National University of Defense Technology College of Electronic Science and Technology Changsha410073 China National University of Defense Technology College of Information and Communication Wuhan430019 China National Key Laboratory on Blind Signal Processing Chengdu610041 China

Covert device-to-device (D2D) communication aims to hide the existence of D2D transmission behavior from the warden, which plays a pivotal role in bolstering D2D communication security. The existing research on covert D2D communication either considered the interference's assistance with perfect channel state information (CSI) available at the warden, or considered channel distribution information (CDI) at the warden without the assistance of interference. These setups facilitate the performance analyses and the parameters design, which, however, did not fully exploit the potential of covert D2D communication, since both channel uncertainty and interference uncertainty exist in practice. In this paper, two covert schemes are proposed for covert D2D communication with dual uncertainties at the warden, where the warden has imperfect CSI. The base station transmits artificial noise to assist covert communication in the first scheme. In the second scheme, the cellular user adopts variable power to confuse the warden. For both schemes, the closed-form expressions of the warden's approximate minimum detection error probability and the achievable D2D communication rate are derived. The achievable D2D communication rate is maximized by jointly optimizing the transmit power of different links with given covertness requirement. The results suggest that the proposed schemes achieve higher communication performance by considering dual uncertainties. Moreover, the scheme with variable cellular user's transmit power performs better when the covert receiver can not well handle the interference from artificial noise. © 2025 IEEE.

关键词： Mobile telecommunication systems

来源：评论

学校读者我要写书评

暂无评论

High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

引用

Journal of Beijing Institute of technology 2024年第2期33卷 111-118页

作者： Yongjia Dou Guangcai Sun Yuqi Wang Mengdao Xing National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China School of Communication and Information Engineering Xi’an University of Science and TechnologyXi’an 710054China

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to *** this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present *** concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA ***,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA *** results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

关键词： synthetic aperture direction-of-arrival(DOA)estimation coherent accumulation

来源：评论

学校读者我要写书评

暂无评论

A Two-Stage Iteratively Reweighted Least Squares Estimator for Robust Elliptic Localization in the Presence of Impulsive Noise

引用

IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 6601-6616页

作者： Zhao, Xiaoyu Lu, Zukun Li, Jun Huang, Long Yu, Yi Ou, Gang The College of Electronic Science and Technology National University of Defense Technology Changsha410073 China The Key Laboratory of Satellite Navigation Technology Changsha410073 China The National Key Laboratory of Radar Signal Processing Xidian University Xi’an710071 China The Hunan Xinghe Electronics Co.LTD Changsha410073 China

As a range-based localization approach, elliptic localization based on bistatic ranges (BRs) has wide range of applications in multistatic systems. This paper addresses the problem of robust elliptic localization using the minimum `pnorm criterion in scenarios affected by impulsive α-stable noise. To solve the `p-norm formulation, we develop an asymptotically efficient two-stage iteratively reweighted least squares (TSIRLS) estimator via incorporating pseudolinear estimation and multistage weighted least squares estimation into the framework of iteratively reweighted least squares (IRLS) methods. The estimator consists of two cascaded `p-norm minimization estimators. To obtain a closed-form solution at each iteration, we transform nonlinear BR measurement equations into pseudolinear forms through introducing auxiliary variables, thus resulting in an iteratively reweighted pseudolinear least squares (IRPLS) estimator in the first stage. The dependencies of unknown parameters and the estimate error derived from the IRPLS are utilized in the second stage to enhance the performance of target location estimate. The analytical derivation demonstrates that, under the assumptions of a sufficiently large number of measurements and small noise, the final position estimate obtained from the TSIRLS achieves the theoretical covariance of the general `pnorm minimization estimation. Extensive numerical simulations highlight the advantages of TSIRLS over existing least squares and robust estimators in terms of positioning performance and runtime. The TSIRLS is also observed to generate approximately unbiased estimates with mean square errors that closely approach the Cramér-Rao lower bound. © 2025 IEEE.

关键词： Impulse noise

来源：评论

学校读者我要写书评

暂无评论

HF signal Protocol Unique Sequence Classification based on Deep Learning 16

HF Signal Protocol Unique Sequence Classification based on D...

引用

16th International Conference on signal processing Systems, ICSPS 2024

作者： Li, Weihao Wang, Keren You, Ling Huang, Zhitao Xiong, Gang College of Electronic Science and Technology National University of Defense Technology Changsha410073 China National Key Laboratory on Blind Signal Processing Chengdu610041 China

ISBN: (纸本)9781510689251

This paper studies the classification of high frequency (HF) signal unique sequence like the preamble, which helps to identify the HF communication protocol. Targeting at a processing flow of sliding window-based unique sequence classification in the narrowband data, and considering the disadvantages of the traditional unique sequence template correlation method, such as relying on the unique sequence knowledge and its strong correlation, slow calculation speed and the calculation times increase with the number of classes, this paper uses deep learning technology to classify the unique sequence classes. The main improvements are that, based on the two classical convolutional neural networks, the relationship between the model receptive field and signal symbol rate is analyzed and adjusted accordingly;and in order to make the local symbol features extracted by convolutional network context-related, a multi-head self-attention layer is introduced behind it. In the experiments, 7 types of real-world signals and background signals are used. The results show that the improved neural networks obtain classification F1 performances similar to that of the traditional high-precision template correlation method, and their processing speed is dozens of times faster than the latter. © 2025 SPIE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Joint optimization algorithm based on array optimization and pattern synthesis 4

Joint optimization algorithm based on array optimization and...

引用

4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Liao, Haiyun Tao, Haihong Zhong, Tiantian Cao, Han Song, Dawei Xidian Universitriy National Laboratory of Radar Signal Processing Xi'an China China Academy of Space Technology National Key Laboratory of Science and Technology on Space Microwave Xi'an China

ISBN: (纸本)9798350394375

By optimizing the weights of each element in the array to control the array pattern, the performance of radar can be improved. In this paper, we study the relationship between the position of the array antenna and the weighted value of the array antenna. Based on the given desired pattern, the position of the array antenna and the weighted value of the array are optimized to realize the pattern synthesis. Since the proposed optimization problem is a non-deterministic polynomial problem, a cyclic algorithm is proposed under non-convex constraints to optimize the coordinates and weights with the least number of array antennas in an approximate given desired pattern. Our numerical experiments shows that the proposed algorithm is universal and can control the level of the mainlobe and sidelobe of the pattern, for example, it is used in the design optimization of the phased array emission pattern of unmanned aerial vehicles. © 2024 IEEE.

关键词： Antenna phased arrays

来源：评论

学校读者我要写书评

暂无评论

Improving ECAPA-TDNN Performance with Coordinate Attention

引用

Journal of Shanghai Jiaotong University (science) 2024年 1-7页

作者： Liu, Shuanghong Song, Zhida He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The current mainstream networks, such as squeeze and excitation residual neural network (SE-ResNet) and emphasized channel attention, propagation and aggregation based time delay neural network (ECAPA-TDNN), enhance the capability of speaker embedding extractors to extract more discriminative speaker embeddings by incorporating squeeze and excitation (SE) attention within the convolutional blocks. However, the SE attention focuses solely on encoding inter-channel information, overlooking the importance of spatial positional information and time-frequency information, which are crucial for the model’s performance. In this paper, we first experimentally compare the effectiveness of several mainstream attention mechanisms in the computer vision domain for the ECAPA-TDNN model. Next, we focus on the substantial improvements that coordinate attention (CA) brings to the ECAPA-TDNN model. The introduction of CA can help the model embed time-frequency information into the channel representation. Even without using AS-Norm, our proposed model achieves relative reductions of about 5.3% equal error rate (EER) and 5.5% minimum detection cost function (minDCF) on both the Voxceleb-O and Voxceleb-H test sets compared to the ECAPA-TDNN baseline model. In addition, the EER is relatively reduced by 9.46% on the CN-Celeb1 test set. This result strongly demonstrates that the CA module can effectively improve the generalization ability of the ECAPA-TDNN model. © Shanghai Jiao Tong University 2024.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Misspecified CRB for TDOA based Passive Localization 16

Misspecified CRB for TDOA based Passive Localization

引用

16th International Conference on signal processing Systems, ICSPS 2024

作者： Cao, Jingmin Wan, Qun Chen, Ying Du, Fen Liu, Yang Li, Wei University of Electronic Science and Technology of China Chengdu China Southwest China Institute of Electronic Technology Chengdu China National Key Laboratory on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510689251

Misspecified CRB (MCRB) is a lower bound on the variance of estimators when the parametric mode is not fully characterizing the behavior of the measurements. This paper derives the TDOA localization model and the performance bound under misspecification of the mean value of the measurement noise. The MCRB can not only play the same role as the CRB but also be used to assess performance under misspecified model. It’s a generalization of the classical CRB to misspecified model framework. For comparison, the specified CRB for TDOA localization with non-zero-mean Gaussian model is aslo investigaed. MCRB is equate to the specified CRB when the mean value of the measurement noise is equal to zero. The simmulation results are satisfy the theoretical analysis. © 2025 SPIE.

关键词： Velocity measurement

来源：评论

学校读者我要写书评

暂无评论

Adaptive Target Birth Intensity Based on Scene Optimization 5

Adaptive Target Birth Intensity Based on Scene Optimization

引用

5th International Conference on Intelligent Control, Measurement and signal processing, ICMSP 2023

作者： Zhao, Jiuchao Zhan, Ronghui Cao, Jingmin Peng, Huafeng College of Electronic Science and Engineering National University of Defense Technology Changsha China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9798350336030

The effective multi-target detection and tracking has always been a research hotspot in the field of radar, and there are many factors that affect the performance of the algorithm for multi-target tracking. Aiming at the target birth issue, this paper proposes an adaptive target birth intensity method based on scene optimization. This method is mainly applied to the radar long-term continuous monitoring scenario, and the monitoring area is divided into the target-birth consideration area and non-target-birth consideration area by some prior information of the monitoring area and the target status. And then the target birth process in the target-birth consideration area is strengthened, while the clutter interference from the non-target-birth consideration area is eliminated, so as to improve the target tracking performance and processing efficiency. Finally, the effectiveness and robustness of the proposed algorithm are verified by simulation experiments and analysis. © 2023 IEEE.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Improving Speaker Verification Back-End with Graph Neural Networks

引用

Journal of Shanghai Jiaotong University (science) 2025年 1-9页

作者： Chen, Jinfeng Fang, Zhihua He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China School of Intelligence Science and Technology Xinjiang University Urumqi830017 China Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

Currently, research on speaker verification tasks is primarily concentrated on enhancing deep speaker models to extract high-quality speaker embeddings. Nevertheless, this speaker embeddings can be regarded as potential graph structures. Therefore, this paper introduces a graph neural network-based speaker verification back-end approach, treating the speaker embeddings derived from the front-end as graph structures and leveraging graph neural networks to uncover the relationships among embeddings, thereby achieving superior-quality speaker embeddings. In addition, we propose a group updating method to solve the problem of memory overflow when the number of nodes is excessive. Extensive experiments and ablation studies were carried out on the VoxCeleb dataset, and the experimental outcomes validate the effectiveness of our proposed graph neural network speaker back-end in significantly boosting the performance of speaker verification systems. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Graph embeddings

来源：评论

学校读者我要写书评

暂无评论

Anomalous Sound Detection Using Time-Frequency Feature and Mixbatch

引用

Journal of Shanghai Jiaotong University (science) 2025年 1-8页

作者： Huang, Shun Zhang, Yunxiang Fang, Zhihua Tang, Minrui Xu, Ruifeng He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China School of Intelligence Science and Technology Xinjiang University Urumqi830017 China Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The sound emitted by machines under abnormal working conditions exhibits various frequency patterns. Currently, the most advanced anomalous sound detection (ASD) approach is to apply a multi-head self-attention mechanism to the Log-Mel spectrogram for automatic frequency pattern analysis. However, the Log-Mel spectrogram may filter out high-frequency components of abnormal sounds;thus the use of self-attention mechanisms on Log-Mel spectrogram seems to have certain limitations. In this paper, we construct a simple convolutional neural network to extract comprehensive frequency features from raw audio to complement spectral-temporal information fusion. The parameters of this neural network are continuously updated during the training process to extract better frequency features for downstream classification neural networks in ASD. Additionally, a method for data augmentation in the batch dimension was developed to help the classification model learn both types of comprehensive features simultaneously. The proposed method achieved an AUC of 94.13% and a pAUC of 89.09% on the DCASE 2020 Challenge Task 2 dataset. Even when using only the features proposed in this paper, an AUC of 84.62% was achieved. (Figure presented.). © Shanghai Jiao Tong University 2025.

关键词： Spectrographs

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：