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2019 International Conference on Communications, information System, and Computer Engineering, CISCE 2019

作者： Li, Jie Jiang, Bin Liang, Wenyan Zhu, Jun Xiong, Ying Tang, Bin Science and Technology on Communication Information Security Control Laboratory 36th Research Institute of CETC Jiaxing China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728136813

A new airborne synthetic aperture radar (SAR) jamming-swing error phase modulation jamming is presented. The method uses the swing error of the line-of-sight SAR during the motion of the airborne SAR and modulate the phase error caused by the swing error to the radar signal received by the jammer to generate the jamming signal and transmit the jamming signal to the radar receiver. The effectiveness of this jamming method against the common motion error compensation algorithm-phase gradient autofocus (PGA) algorithm is analyzed. The simulation experiment verifies the correctness of the theoretical analysis. © 2019 IEEE.

关键词： Error compensation

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Code rate estimation and code sequence retrieval of the binary phase-coded radar signal using further autocorrelation analysing

Code rate estimation and code sequence retrieval of the bina...

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2019 International Conference on Communications, information System, and Computer Engineering, CISCE 2019

作者： Jiang, Bin Li, Jie Yang, Xiaohong Zhu, Jun Xiong, Ying Tang, Bin Science and Technology on Communication Information Security Control Laboratory 36th Research Institute of CETC Jiaxing China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728136813

The binary phase-coded radar signal code rate estimation and code sequence retrieval are important in EW and ELINT. In this paper, the statistical autocorrelation function of the binary phase-coded radar signal is studied in depth, and a code rate estimation and a code sequence retrieval method are proposed. With the signal symbol length rough estimation, the sampling points of calculating statistical autocorrelation function can be adaptively selected. Furthermore, exploring the valley points of the autocorrelation function envelope to detect the signal phase abrupt points, the signal code rate can be estimated and the code sequence can be recovered. Experimental results corroborate that the proposed method can effectively reduce the mean square errors of the code rate estimation and code sequence retrieval in low signal to noise ratio (SNR) conditions. © 2019 IEEE.

关键词： Mean square error

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Bitstream protocol classification mechanism based on feature extraction

Bitstream protocol classification mechanism based on feature...

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2019 International Conference on Networking and Network Applications, NaNA 2019

作者： Wang, Wei Bai, Binbin Wang, Yichuan Hei, Xinhong Zhang, Li Science and Technology on Communication Information Security Control Laboratory No.36 Research Institution of CETC China College of Computer Science and Engineering Xi'An University of Technology Xi'an China

ISBN: (纸本)9781728126296

In recent years, with the continuous expansion of network communication scale, the types of niche protocols and various proprietary communication protocols are increasing day by day, but botnet and various network attacks have also emerged in endlessly. However, most of the commonly used network protocol recognition software uses a single method, and can only identify specific network data packets or data streams, the degree of automation is low, and the recognition accuracy is not high. In view of the above situation, this paper takes the bit flow protocol data frame as the research object, takes the multi-protocol recognition as the goal, and carries on the protocol feature recognition by comparing the data flow characteristics and the evaluation index. The features of the protocol to be detected are compared with the existing protocol features of the feature base, and the similarity between each protocol is judged. The extracted composite features are digitalized to generate 0-1 matrix, and clustering analysis is completed. The frame vector quantification algorithm of message data is designed and implemented to improve the clustering efficiency. The experimental results show that, compared with the traditional algorithm, the protocol eigenvector algorithm improves the accuracy by 15%, which can make the unknown protocol format be generated faster. © 2019 IEEE.

关键词： Network security

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GPU-Accelerated Multipath Clutter Cancellation Algorithm for DTMB-Based Passive Radar

GPU-Accelerated Multipath Clutter Cancellation Algorithm for...

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information science, Parallel and Distributed Systems (ISPDS), International Conference on

作者： Zirong Bu Huijie Zhu Jiachuan Qian Science and Technology on Communication Information Security Control Laboratory Jiaxing China No. 36 Research Institute of China Electronics Technology Group Corporation Jiaxing China

ISBN: (数字)9781728196688

ISBN: (纸本)9781728196695

In order to extract the target echo in the monitoring channel, the direct wave and the clutter should be suppressed in the signal processing of the passive radar. The batch version of the Extensive Cancellation Algorithm (ECA-B) is an effective time-domain clutter cancellation algorithm that can suppress direct waves and multipath clutter. And it has better robustness than ECA. However, ECA-B is a computationally intensive algorithm. Therefore, the Graphic Processing Unit (GPU) accelerated ECA-B algorithm has been studied and implemented on GPU by exploring the parallelism of the ECA-B algorithm. The paper contains the description of the algorithm implementation and the performance results analysis of the measured data.

关键词： Testing Radar Parallel processing information science Graphics processing units Conferences

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Classification and Recognition of Underwater Target Based on MFCC Feature Extraction

Classification and Recognition of Underwater Target Based on...

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IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

作者： Yuze Tong Xin Zhang Yizhou Ge School of Marine Science and Technology Northwestern Polytechnical University Xi’an China Science and Technology on Communication Information Security Control Laboratory NO.36 Research Institute of CETC Jiaxing China

ISBN: (数字)9781728172026

ISBN: (纸本)9781728172033

The key to underwater target recognition is to extract the effective features of underwater target radiation noise. This paper presents an effective method for underwater target recognition and classification by extracting Mel-Frequency Cepstral Coefficients (MFCCs) features of underwater target radiation noise. Compared with traditional spectral analysis methods, MFCC makes full use of the non-linear auditory effect of the human ear with different perception capabilities for sounds of different frequencies. In this paper, the classification experiment of the radiated noise of the three types of measured underwater targets is done, where the MFCC feature vectors of the three types of targets are extracted, and the K-Nearest Neighbor (K-NN) algorithm is used to classify and identify them. Finally, the experimental results show that the method is effective.

关键词： Feature extraction Mel frequency cepstral coefficient Target recognition Classification algorithms Filter banks Ear Auditory system

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Demodnet: Learning soft demodulation from hard information using convolutional neural network

arXiv

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arXiv 2020年

作者： Zheng, Shilian Zhou, Xiaoyu Chen, Shichuan Qi, Peihan Yang, Xiaoniu Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China

Soft demodulation is a basic module of traditional communication receivers. It converts received symbols into soft bits, that is, log likelihood ratios (LLRs). However, in the non-ideal additive white Gaussian noise (AWGN) channel, it is difficult to accurately calculate the LLR. In this letter, we propose a demodulator, DemodNet, based on a fully convolutional neural network with variable input and output length. We use hard bit information to train the DemodNet, and we propose log probability ratio (LPR) based on the output layer of the trained DemodNet to realize soft demodulation. The simulation results show that under the AWGN channel, the performance of both hard demodulation and soft demodulation of DemodNet is very close to the traditional methods. In three non-ideal channel scenarios, i.e., the presence of frequency deviation, additive generalized Gaussian noise (AGGN) channel, and Rayleigh fading channel, the performance of channel decoding using the soft information LPR obtained by DemodNet is better than the performance of decoding using the exact LLR calculated under the ideal AWGN assumption. © 2020, CC-BY.

关键词： Demodulation

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A Novel Threat Sensing Architecture for Heterogeneous Cognitive Sensor Networks

A Novel Threat Sensing Architecture for Heterogeneous Cognit...

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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Ren, Yongji Zhang, Yun Zhou, Zheng Xu, Xiaofeng Liu, Xiaolei Naval Aviation University Yantai China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Yantai Vocational College Yantai China

ISBN: (纸本)9781728123455

With the rapid development and application of novel network information technologies, the various radar and/or communication transmitters have become more intelligent and networked in modern electromagnetic operational environment, which causes the threat sensing architecture of traditional electronic warfare system more inadequate, especially encountering unknown threat signals or networked targets. In this case, the threat sensing becomes one of the biggest challenges that the traditional electronic warfare system is facing. Therefore, this paper proposed a novel heterogeneous architecture for cognitive sensor networks to facilitate efficient threat sensing. To deal with the heterogeneous problem of cognitive sensor networks, multiple constraints satisfaction based approach has been employed. And the game based resources scheduling scheme has been utilized to facilitate the efficiency. To the best of our knowledge, our work is the first one that introduces the heterogeneous cognitive architecture into threat sensing domain of electronic warfare system. The simulation results show the proposed novel threat sensing architecture for heterogeneous cognitive sensor networks is feasible and effective. © 2019 IEEE.

关键词： Sensor networks

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Data link modeling and simulation based on DEVS 2

Data link modeling and simulation based on DEVS

引用

2nd International Conference on Signal Processing and Machine Learning, SPML 2019

作者： Luo, Zhenxing Zhao, Lulu Tian, Wanyong Yang, Dan Chen, Yiyuan Yu, Jiabin Li, Jianjun Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China CETC Key Laboratory of Data Link Technology Xi'An710071 China Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9781450372213

The Discrete Event System (DEVS)[1] Specification provides a reference standard for the model design and simulation development of complex discrete event state system. It designs a formal mechanism to describe discrete event state, which is composed of a set of strictly abstract mathematical symbols, and provides a strict description mechanism and execution logic for the modeling and Simulation of discrete event state system, it ensures the normalization, reusability and simulation operation ability of the model. As a special link system, Data Link[2] is different from general communication system. It is mainly used between different military platforms to ensure information sharing. By linking sensors, command and control system and weapon platform according to the specified message format and communication protocol, the information system that can automatically transmit the formatted data of battlefield situation, command and guidance, tactical coordination, weapon control, etc., in real time can form a close and efficient tactical link relationship between different combat platforms. In this paper, DEVS is used to simulate the Reporting Responsibility for Air, Surface, and Land tracks in MILSTD-6016B. © 2019 Association for Computing Machinery.

关键词： Discrete event simulation

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A Analysis of Attack and Defense Mobile Ad Hoc Network Based on OPNET

A Analysis of Attack and Defense Mobile Ad Hoc Network Based...

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2019 International Conference on Advanced Material Research and Processing technology, AMRPT 2019

作者： Dai, Jiahao Xu, Xiaofeng Science and Technology on Communication Information Security Control Laboratory Zhejiang Jiaxing China China Electronic Group Corporation No.36 Institute Zhejiang Jiaxing China

Due to the broadcast nature of wireless communications, the damage to mobile ad hoc networks is becoming more and more common. We propose a network stability model that can effectively reflect the network performance when the network is damaged in real time. The Ad Hoc network model is built by using the node model supporting the IEEE802.11 standard provided by OPNET software to simulate the network performance of the network under different degrees of damage. This model provides an effective way for the simulation analysis of network performance under the condition of Ad Hoc network damage. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Mobile ad hoc networks

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Deep learning for cooperative radio signal classification

arXiv

引用

arXiv 2019年

作者： Zheng, Shilian Chen, Shichuan Yang, Xiaoniu Science and Technology on Communication Information Security Control Laboratory

Radio signal classification has a very wide range of applications in cognitive radio networks and electromagnetic spectrum monitoring. In this article, we consider scenarios where multiple nodes in the network participate in cooperative classification. We propose cooperative radio signal classification methods based on deep learning for decision fusion, signal fusion and feature fusion, respectively. We analyze the performance of these methods through simulation experiments. We conclude the article with a discussion of research challenges and open problems. Copyright © 2019, The Authors. All rights reserved.

关键词： Cognitive radio

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