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Scale effect removal and range migration correction for hypersonic target coherent detection

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Journal of Systems Engineering and electronics 2024年第1期35卷 14-23页

作者： WU Shang SUN Zhi JIANG Xingtao ZHANG Haonan DENG Jiangyun LI Xiaolong CUI Guolong School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar ***,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual ***,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration *** eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation *** to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation *** last,this paper gives several simulations to assess the viability of ScLRT.

关键词： hypersonic target detection coherent integration(CI) scale effect(SE)removal range migration(RM)correction scaled location rotation transform(ScLRT)

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence Technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng Kaili.Jiang Zhixing Zhou Yuxin Zhao Kailun Tian Haixin Yan Bin Tang School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic *** methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative *** paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse *** results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

A lightweight false alarm suppression method in heterogeneous change detection

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Journal of Systems Engineering and electronics 2024年第4期35卷 899-905页

作者： XU Cong HE Zishu LIU Haicheng School of electronic and Information Engineering Heilongjiang Institute of EngineeringHarbin 150026China School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection *** paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different *** with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change *** evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.

关键词： convolutional neural network(CNN) graph convolu-tional network(GCN) heterogeneous change detection lightweight false alarm suppression

Improve Chinese Aspect Sentiment Quadruplet Prediction via Instruction Learning Based on Large Generate Models

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Computers, Materials & Continua 2024年第3期78卷 3391-3412页

作者： Zhaoliang Wu Yuewei Wu Xiaoli Feng Jiajun Zou Fulian Yin College of Information and communication Engineering Communication University of ChinaBeijing100024China The State Key Laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China Department of electronic Engineering Tsinghua UniversityBeijing100084China

Aspect-Based Sentiment Analysis(ABSA)is a fundamental area of research in Natural Language Processing(NLP).Within ABSA,Aspect Sentiment Quad Prediction(ASQP)aims to accurately identify sentiment quadruplets in target sentences,including aspect terms,aspect categories,corresponding opinion terms,and sentiment ***,most existing research has focused on English ***,while ASQP has seen significant progress in English,the Chinese ASQP task has remained relatively *** inspiration from methods applied to English ASQP,we propose Chinese generation templates and employ prompt-based instruction learning to enhance the model’s understanding of the task,ultimately improving ASQP performance in the Chinese ***,under the same pre-training model configuration,our approach achieved a 5.79%improvement in the F1 score compared to the previously leading ***,when utilizing a larger model with reduced training parameters,the F1 score demonstrated an 8.14%***,we suggest a novel evaluation metric based on the characteristics of generative models,better-reflecting model *** results validate the effectiveness of our approach.

关键词： ABSA ASQP LLMs sentiment analysis Chinese comments

A peak enhancement of frequency response of waveguide integrated silicon-based germanium avalanche photodetector

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Journal of Semiconductors 2024年第7期45卷 61-68页

作者： Linkai Yi Daoqun Liu Wenzheng Cheng Daimo Li Guoqi Zhou Peng Zhang Bo Tang Bin Li Wenwu Wang Yan Yang Zhihua Li institute of Microelectronics Chinese Academy of SciencesBeijing 100029China School of electronic Electrical and communication Engineering University of Chinese Academy of SciencesBeijing 100049China

Avalanche photodetectors(APDs) featuring an avalanche multiplication region are vital for reaching high sensitivity and responsivity in optical transceivers. Waveguide-coupled Ge-on-Si separate absorption, charge, and multiplication(SACM)APDs are popular due to their straightforward fabrication process, low optical propagation loss, and high detection sensitivity in optical communications. This paper introduces a lateral SACM Ge-on-Si APD on a silicon-on-insulator(SOI) wafer, featuring a 10 μm-long, 0.5 μm-wide Ge layer at 1310 nm on a standard 8-inch silicon photonics platform. The dark current measures approximately 38.6 μA at-21 V, indicating a breakdown voltage greater than-21 V for the device. The APDs exhibit a unitgain responsivity of 0.5 A/W at-10 V. At-15 V, their responsivity reaches 2.98 and 2.91 A/W with input powers of-10 and-25 dBm, respectively. The device's 3-dB bandwidth is 15 GHz with an input power of-15 dBm and a gain is 11.68. Experimental results show a peak in impedance at high bias voltages, attributed to inductor and capacitor(LC) circuit resonance, enhancing frequency response. Furthermore, 20 Gbps eye diagrams at-21 V and-9 dBm input power reveal signal to noise ratio(SNRs) of 5.30. This lateral SACM APD, compatible with the stand complementary metal oxide semiconductor(CMOS) process,shows that utilizing the peaking effect at low optical power increases bandwidth.

关键词： photodetectors optical communications responsivity 3-dB bandwidth

Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array

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Chinese Journal of electronics 2024年第1期33卷 175-184页

作者： Xichao ZHAN Zhongwen SUN Feng SHU Yiwen CHEN Xin CHENG Yuanyuan WU Qi ZHANG Yifan LI Peng ZHANG School of Information and communication Engineering Hainan University School of electronic and Optical Engineering Nanjing University of Science and Technology

For a sub-connected hybrid multiple-input multiple-output(MIMO) receiver with K subarrays and N antennas, there exists a challenging problem of how to rapidly remove phase ambiguity in only single time-slot. A direction of arrival(DOA) estimator of maximizing received power(Max-RP) is proposed to find the maximum value of K-subarray output powers, where each subarray is in charge of one sector, and the center angle of the sector corresponding to the maximum output is the estimated true DOA. To make an enhancement on precision, Max-RP plus quadratic interpolation(Max-RP-QI) method is designed. In the proposed Max-RP-QI, a quadratic interpolation scheme is adopted to interpolate the three DOA values corresponding to the largest three receive powers of *** achieve the Cramer Rao lower bound, a Root-MUSIC plus Max-RP-QI scheme is developed. Simulation results show that the proposed three methods eliminate the phase ambiguity during one time-slot and also show low computational complexities. The proposed Root-MUSIC plus Max-RP-QI scheme can reach the Cramer Rao lower bound,and the proposed Max-RP and Max-RP-QI are still some performance losses 2–4 d B compared to the Cramer Rao lower bound.

关键词： Phased arrays Interpolation Wireless sensor networks Direction-of-arrival estimation Simulation Receiving antennas Massive MIMO

RFFsNet-SEI:a multidimensional balanced-RFFs deep neural network framework for specific emitter identification

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Journal of Systems Engineering and electronics 2024年第3期35卷 558-574,F0002页

作者： FAN Rong SI Chengke HAN Yi WAN Qun School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China institute of electronic and Electrical Engineering Civil Aviation Flight University of ChinaGuanghan 618307China

Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of *** this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,***,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train *** introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is *** improves physical interpretability of ***,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of ***,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is ***,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction *** results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.

关键词： specific emitter identification(SEI) deep learning(DL) radio frequency fingerprint(RFF) multidimensional feature extraction(MFE) variational mode decomposition(VMD)

CNN-LSTM based incremental attention mechanism enabled phase-space reconstruction for chaotic time series prediction

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Journal of electronic Science and Technology 2024年第2期22卷 77-90页

作者： Xiao-Qian Lu Jun Tian Qiang Liao Zheng-Wu Xu Lu Gan Bidding and Purchasing Center University of Electronic Science and Technology of ChinaChengdu611731China Yibin Research institute University of Electronic Science and Technology of ChinaYibin644000China School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu611731China

To improve the prediction accuracy of chaotic time series and reconstruct a more reasonable phase space structure of the prediction network,we propose a convolutional neural network-long short-term memory(CNN-LSTM)prediction model based on the incremental attention ***,a traversal search is conducted through the traversal layer for finite parameters in the phase ***,an incremental attention layer is utilized for parameter judgment based on the dimension weight criteria(DWC).The phase space parameters that best meet DWC are selected and fed into the input ***,the constructed CNN-LSTM network extracts spatio-temporal features and provides the final prediction *** model is verified using Logistic,Lorenz,and sunspot chaotic time series,and the performance is compared from the two dimensions of prediction accuracy and network phase space ***,the CNN-LSTM network based on incremental attention is compared with long short-term memory(LSTM),convolutional neural network(CNN),recurrent neural network(RNN),and support vector regression(SVR)for prediction *** experiment results indicate that the proposed composite network model possesses enhanced capability in extracting temporal features and achieves higher prediction ***,the algorithm to estimate the phase space parameter is compared with the traditional CAO,false nearest neighbor,and C-C,three typical methods for determining the chaotic phase space *** experiments reveal that the phase space parameter estimation algorithm based on the incremental attention mechanism is superior in prediction accuracy compared with the traditional phase space reconstruction method in five networks,including CNN-LSTM,LSTM,CNN,RNN,and SVR.

关键词： Chaotic time series Incremental attention mechanism Phase-space reconstruction

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

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China communications 2024年第1期21卷 148-162页

作者： Yizhe Zhao Yanliang Wu Jie Hu Kun Yang School of Information and communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower *** this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)*** joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless *** the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)*** results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

关键词： energy harvesting modulation(EHM) integrated data and energy transfer(IDET) performance analysis wireless data transfer(WDT) wireless energy transfer(WET)