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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

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Misspecified CRB for TDOA based Passive Localization 16

Misspecified CRB for TDOA based Passive Localization

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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

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Adaptive Target Birth Intensity Based on Scene Optimization 5

Adaptive Target Birth Intensity Based on Scene Optimization

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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

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A S-transform Based Algorithm for Doppler Frequency Rate-of-Change Estimation from Coherent Pulse Train 3

A S-transform Based Algorithm for Doppler Frequency Rate-of-...

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2021 3rd International Conference on Computer, Communications and Mechatronics Engineering, CCME 2021

作者： Lan, Zhangfu Peng, Huafeng Zhao, Peiyan National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

The traditional Fourier correlation method has the problem of poor accumulation effect, which leads to the low estimation accuracy of Doppler frequency change rate coherent pulse signal under the condition of low signal-to-noise ratio or short pulse duration. To solve this problem, an estimation algorithm based on S-transform is proposed to estimate the Doppler frequency change rate. By means of higher time-frequency aggregation of S transform, the coherent accumulation of the coherent pulse signal is better realized;Then the high accuracy Doppler frequency change rate is obtained by using the minimum variance criterion in the phase domain. Theoretical derivation and simulation results show that the algorithm in this paper can improve the accuracy of about 1 times compared with the traditional algorithm. It lays a solid foundation for the estimation of the high-precision Doppler frequency change rate in the practical application of subsequent projects, and improves the accuracy of target positioning and tracking. © Published under licence by IOP Publishing Ltd.

关键词： Frequency estimation

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Cooperative Optimization Method of UAV Swarm for Multi-objective High-Precision Location 5th

Cooperative Optimization Method of UAV Swarm for Multi-objec...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Li, Bowen Ji, Xiaoting Huang, Yuanling School of Information System Engineering Information Engineering University Zhengzhou450001 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

ISBN: (纸本)9789811939976

In the field of electromagnetic radiation source location, using UAVs to locate the radiation source target has become a new location method. At present, the UAV swarm cooperative optimization method for high-precision location has some challenges, such as insufficient ability of multi-objective high-precision location, poor timeliness and so on. To solve these problems, this paper proposes a cooperative optimization method of UAV swarm for multi-objective location. Firstly, the multi-objective joint location accuracy is derived, which is taken as the objective function of swarm cooperative optimization. Secondly, in order to allocate multiple UAVs to multiple targets efficiently, the initialization strategy based on target isolation and the random allocation method of UAV based on probability are proposed. Finally, by combining the above improved strategies, an optimization method of UAV swarm cooperative location is proposed. Through the analysis of experimental results, the cooperative optimization method in this paper has obvious advantages in global optimization and convergence ability, which can improve the joint location accuracy and optimization speed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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ASTF: Visual Abstractions of Time-Varying Patterns in Radio signals

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IEEE Transactions on Visualization and Computer Graphics 2023年第1期29卷 214-224页

作者： Zhao, Ying Ge, Luhao Xie, Huixuan Bai, Genghuai Zhang, Zhao Wei, Qiang Lin, Yun Liu, Yuchao Zhou, Fangfang School of Computer Science and Engineering Central South University Changsha China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China College of Information and Communication Engineering Harbin Engineering University Harbin China China Research Institute of Radiowave Propagation Qingdao China

A time-frequency diagram is a commonly used visualization for observing the time-frequency distribution of radio signals and analyzing their time-varying patterns of communication states in radio monitoring and management. While it excels when performing short-term signal analyses, it becomes inadaptable for long-term signal analyses because it cannot adequately depict signal time-varying patterns in a large time span on a space-limited screen. This research thus presents an abstract signal time-frequency (ASTF) diagram to address this problem. In the diagram design, a visual abstraction method is proposed to visually encode signal communication state changes in time slices. A time segmentation algorithm is proposed to divide a large time span into time slices. Three new quantified metrics and a loss function are defined to ensure the preservation of important time-varying information in the time segmentation. An algorithm performance experiment and a user study are conducted to evaluate the effectiveness of the diagram for long-term signal analyses. © 2022 IEEE.

关键词： Data visualization

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Research on Target Detection Based on Clustering and Hough Transform

Research on Target Detection Based on Clustering and Hough T...

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2022 International Conference on Statistics, Data science, and Computational Intelligence, CSDSCI 2022

作者： Luo, Yanpeng Xiong, Jinyu Yang, Yuxiang Zhu, Mingjun Zhang, Tongxin Cheng, Haibing College of Information System Engineering PLA Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510661325

Formation target track sorting is an important problem in multi-target track processing. Unlike the processing of periodic scans and point tracks of active radar, passive positioning data has the problems of irregular positioning period and difficulty in distinguishing multiple targets by target signal attributes. In this paper, we propose a track initiation algorithm for passive positioning system based on density clustering and Hough transform for the characteristics of passive positioning system. The algorithm first uses the density clustering algorithm to identify the cluster centers of targets with large measurement errors, and then uses the Hough transform method to initiate a track. © 2023 SPIE.

关键词： Hough transforms

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A Snapshot Cluster Segmentation Method Based on Dynamic Network

A Snapshot Cluster Segmentation Method Based on Dynamic Netw...

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2022 International Conference on Statistics, Data science, and Computational Intelligence, CSDSCI 2022

作者： Zhang, Tongxin Lu, Luxi College of Information System Engineering PLA Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510661325

Dynamic graph neural networks are a research hotspot in the field of deep learning, especially in social networks, recommendation systems, traffic networks and other fields with very wide applications. At present, most of the commonly used deep learning based network analysis methods are focused on discrete dynamic graph neural networks. However, the effectiveness of discrete graph neural network methods is based on the degree of good or bad snapshot segmentation of dynamic networks, so this paper proposes a snapshot clustering segmentation method (SCSM) for dynamic networks, and researchers can effectively segment the snapshots of dynamic networks by the SCSM method in this paper to make the downstream tasks can get good results. © 2023 SPIE.

关键词： Graph neural networks

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Receiver System Design for Universal Polyphase DFT Digital Channelization Algorithm 5

Receiver System Design for Universal Polyphase DFT Digital C...

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5th IEEE International Conference on Electronics technology, ICET 2022

作者： Lu, Shihang Su, Zhengyu Liao, Kaisheng Li, Chao Xiao, Zhuoling Yan, Bo Lin, Shuisheng Wu, Bo University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory National Key Laboratory of Science and Technology on Blind Signal Processing School of Information and Communication Engineering China

ISBN: (纸本)9781665485081

Receiver plays a vital role in various electronic countermeasure systems and has always been a hot topic to research. Based on the traditional receiver digital channelization structure, this paper further researches and derives the high-efficiency digital channelization structure based on polyphase discrete Fourier transform corresponding to various application scenarios. Then we design a 256-sub-channel digital channelization system and implement it on a 64-channel parallel digital down converter to verify the structure. The system design relies on system on chip as the platform, and we verify the feasibility of it on field programmable gate array. © 2022 IEEE.

关键词： System-on-chip

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Heterogeneous-attributes enhancement deep framework for network embedding

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Frontiers of Computer science 2021年第6期15卷 121-131页

作者： Lisheng QIAO Fan ZHANG Xiaohui HUANG Kai LI Enhong CHEN Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of ChinaHefei 230022China National Key Laboratory of Blind Signal Processing Chengdu 610041China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230022China

Network embedding,which targets at learning the vector representation of vertices,has become a crucial issue in network ***,considering the complex structures and heterogeneous attributes in real-world networks,existing methods may fail to handle the inconsistencies between the structure topology and attribute ***,more comprehensive techniques are urgently required to capture the highly non-linear network structure and solve the existing inconsistencies with retaining more *** that end,in this paper,we propose a heterogeneous-attributes enhancement deep framework(HEDF),which could better capture the non-linear structure and associated information in a deep learningway,and effectively combine the structure information of multi-views by the combining *** this line,the inconsistencies will be handled to some extent and more structure information will be preserved through a semi-supervised *** extensive validations on several real-world datasets show that our model could outperform the baselines,especially for the sparse and inconsistent situation with less training data.

关键词： network embedding heterogeneous-attributes deep framework inconsistent

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