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检索条件"机构=Science and Technology on Automatic Target Recognition Laboratory"

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Design and implementation of a radar waveform playback system for real-time digital signal processing test

Design and implementation of a radar waveform playback syste...

引用

IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Yingxiao Zhao Yang Su Rui Huang Pengjiang Hu Zengping Chen Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781538616093

This paper designs a radar waveform playback system used for real-time digital signal processing test. The system reads radar waveform data stored in a disk array, and transfers it to a real-time signal processing system. The timing sequence and speed of the waveform data played back is the same as when radar in target tracking operation. The system comprises a disk array server, which is used for data recording and storing, and two FPGA (Field Programming Gate Array) fiber boards, which is used for data playback and transmission. Firstly, data transmission from the server to the fiber boards is realized by DMA (Direct Memory Access) in PCI Express protocol. And the DMA control flow for the system is proposed. Secondly, the method of timing control according to radar working mode is proposed. Accurate timing control can be realized by FPGA. Thirdly, the problem of asynchronous data transmission between two fiber boards caused by incoherent clock is solved. We propose two synchronization methods based on software and hardware respectively, and analyze the application conditions of each method. This paper offers a reference for the implementation of waveform playback in a radar system, and can be helpful for the function test of the realtime digital signal processing system.

关键词： Radar Field programmable gate arrays Real-time systems Timing Radar signal processing Digital signal processing Arrays

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Joint target Tracking and Classification with Scattering Center Model for Radar Sensor

Joint Target Tracking and Classification with Scattering Cen...

引用

International Conference on Control, Automation and Information sciences (ICCAIS)

作者： Ronghui Zhan Liping Wang Jun Zhang Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (数字)9781728123110

ISBN: (纸本)9781728123127

In this paper, a model-based joint tracking and classification (JTC) method for wideband radar is proposed. The method is based on 3D scattering center model (3D-SCM), which is used to generate the predicted high range resolution profile (HRRP) with the information of target aspect angle. The aspect angle is derived from the target state with particle filter. target classification is implemented through the data match and correlation of observed HRRP with predicted HRRPs. For the continuity of tracking procedure, the estimate uncertainty of target state and class probability decreases as the filter's recursion proceeds, and thus to obtain a stable tracking and classification result. The effectiveness of the proposed method is validated by simulation results for maritime ship targets.

关键词： Solid modeling target tracking Radar tracking Scattering Three-dimensional displays Predictive models

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A novel dual-channel joint analysis and measurement algorithm on broadband cross-channel radar radiant signal

A novel dual-channel joint analysis and measurement algorith...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yurong Wan Tao Li Zengping Chen Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781509060948

Accurate and quick parameter estimation of linear Frequency Modulation (LFM) signal is always the research hot. In this paper, an improved dual-channel joint analysis of measurement algorithm is proposed for the recognition and parameter estimation of cross-channel LFM signal. First, coarse chirp rates are estimated by delay-related correlative dechirp, and then signal is identified coarsely by a comparison of chirp rates of two channels. Second, the initial frequency and chirp rate of channel A are estimated based on the Fractional Fourier Transform (FRFT) which needs to do local search. Finally, the estimated chirp rate of channel A is utilized to identify the signal in channel B with the parameters in time and frequency domain. Simulation results show that accuracy of recognition and parameter estimation for cross-channel LFM signal is satisfying when the signal to noise rate (SNR) is not less than -16 dB.

关键词： Chirp Parameter estimation Channel estimation Algorithm design and analysis Signal to noise ratio Estimation Electromagnetics

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A New target Detection Method for Noncooperative Bistatic Radar Based on Fractional Fourier Transform and Wavelet Transform

A New Target Detection Method for Noncooperative Bistatic Ra...

引用

IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference

作者： Zejia Tang Qinglong Bao Zengping Chen Caiyong Lin Sen Wang Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

Although the template matching method is an effective way to acquire direct waves, there is a certain deviation in the acquisition and estimation of direct waves. The deviation of direct wave parameters directly affects the performance of subsequent related algorithms. In this paper, we mainly evaluate the performance of the pulse compression(PC) algorithm with non-cooperative radar parameters, and propose a direct detection method based on fractional Fourier and wavelet denoising. This paper gives the detection performance curve of this new method. The result shows that there is a certain gap between the proposed method and the ideal pulse compression method, but it has excellent performance with respect to the deviation of the direct wave parameters. Therefore, it is an excellent method to detect the target under a specific signal-to-noise ratio in the non-cooperative bistatic radar.

关键词： Non-cooperative bistatic radar FRFT Wavelet transform Pulse compression

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Attention Scale-Aware Deformable Network for Inshore Ship Detection in Surveillance Videos 1st

Attention Scale-Aware Deformable Network for Inshore Ship D...

引用

1st CAAI International Conference on Artificial Intelligence, CICAI 2021

作者： Liu, Di Zhang, Yan Zhao, Yan Zhang, Yu National Key Laboratory of Science and Technology on Automatic Target Recognition College of Electronic Science and Technology National University of Defense Technology Changsha410073 China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783030930455

Aiming at detecting multi-scale inshore ships in surveillance videos, a one-stage detector namely Attention Scale-aware Deformable Network (ASDN) is proposed in this paper by employing two primary components including Attention Scale-aware Module (ASM) and Deformable Convolutional Network (DCN). Moreover, ASM composed of several branches of convolutions with specially designed kernels and a Convolutional Block Attention Modules (CBAM), is designed for extracting and refining non-local features of multi-scale inshore ships with large aspect ratios at the topmost feature layer. DCN is adopted to capture irregular significant features of ships by modulating input features using parameterized offsets and amplitudes at lateral connections of fine-grained feature pyramid. Experiments conducted on public Seaships7000 dataset demonstrate the contributions of ASM and DCN, and the effectiveness of our method for multi-scale inshore ship detection in surveillance videos in comparison with other Convolutional Neural Network (CNN) based methods, e.g., FPN, Libra R-CNN, SSD, YOLOv3, RefineDet. © 2021, Springer Nature Switzerland AG.

关键词： Convolution

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Open Set target recognition Based on Multi-task Compressed Sensing using Multi-view High Range Resolution Profiles

Open Set Target Recognition Based on Multi-task Compressed S...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhang, Huiqiang Liu, Shengqi Teng, Shuhua Qu, Shuang Deng, Jie Yu, Zhenlin National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha China College of Electronic Information Hunan First Normal University Changsha410205 China

ISBN: (纸本)9781839539954

This paper focuses on a specific application for a target recognition system. That is, the system input may be out-of-library from an unknown category and multiple observations can be obtained from a small angle interval. To efficiently utilize the multi-view samples for target identification in open-set situation, an open set recognition method using multi-view high range resolution profiles (HRRP) based on Multi-task Compressed Sensing (MtCS) is presented. First, the reconstruction errors of multi-view HRRPs on the over-completed dictionary are obtained by MtCS, and a modified metrics is constructed with the reconstruction error. Next, extreme value theory (EVT) is introduced to model the distribution of the metrics, and then the open-set recognition problem is transformed into a hypothesis test problem. The proposed method can effectively reject the out-of-library samples, and meanwhile exploit the prior information that the multiple observations are strongly correlated to improve the recognition performance of samples from known targets. The efficiency of the proposed method is identified through the recognition experiments on the HRRP data generated from MSTAR SAR chips. © The Institution of Engineering & technology 2023.

关键词： Compressed sensing

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A Lightweight SAR Ship Detection Method Based on Improved YOLOv8

A Lightweight SAR Ship Detection Method Based on Improved YO...

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IET International Radar Conference 2023, IRC 2023

作者： Guo, Yue Zhan, Ronghui Chen, Shiqi Li, Luzhuo Zhang, Jun National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha China College of Information and Communication National University of Defense Technology Wuhan China Beijing University of Technology Beijing China

ISBN: (纸本)9781839539954

The complex background and small size of targets pose challenges for ship detection in SAR (Synthetic Aperture Radar) images. Currently, deep learning-based methods have been widely used for SAR ship detection. However, the neural networks involved in these methods have a large number of parameters, which hinders their practical applications on resource-constrained platforms. This paper proposes a lightweight SAR detection algorithm specifically designed for small ship targets in SAR images. Firstly, we adopt a decoupling strategy to reconstruct the backbone network, effectively reducing the number of parameters. Secondly, a new regression loss function MPDIoU is proposed to enhance the detection accuracy of small ship bounding boxes and improve the regression speed of the model. Finally, we conduct experiments on the SSDD and HRSID datasets, and the results show that our proposed method achieves improvement in mAP (mean average precision) by 97.8% and 89.2% respectively, while the model weight parameters is only 72.5% of the standard YOLOv8n. © The Institution of Engineering & technology 2023.

关键词： Synthetic aperture radar

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Parameter estimation of LFM signals intercepted by a composite local oscillation SNYFR

Parameter estimation of LFM signals intercepted by a composi...

引用

IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Tao Li Xiaolei Fan Qian Zhu Zengping Chen Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha Hunan China

Nyquist Folding Receiver (NYFR) is a novel ultrawideband interception receiver architecture, which can sample a large range wideband signal by single Analog-to-Digital Converter (ADC). And the Synchronous Nyquist Folding Receiver (SNYFR) is an improved structure of NYFR. In this paper, a new SNYFR structure based on composite Sinusoidal Frequency Modulated (SFM) Local Oscillator (LO) is proposed. For Linear Frequency Modulated (LFM) signals intercepted by this SNYFR, a Nyquist Zone (NZ) estimation and parameter estimation algorithm based on instantaneous autocorrelation is deduced. The complexity of the algorithm is lower, which reduces the difficulty of resolving the LFM/SFM hybrid modulated signals after the ADC of SNYFR. Computer simulation shows that effective detection of multi-component LFM signals and accurate parameters estimation can be achieved by the proposed algorithm when the signal to noise ratio (SNR) is better than -8dB.

关键词： Frequency modulation Local oscillators Time-frequency analysis Bandwidth Parameter estimation Receivers

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Experimental Study of Aircraft Detection by PBR Exploiting Uncooperative Radar as Illuminator

Experimental Study of Aircraft Detection by PBR Exploiting U...

引用

2018 International Conference on Information, Electronic and Communication Engineering(IECE 2018)

作者： Qian ZHU Qing-long BAO Pan-he HU Zeng-ping CHEN Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Shen Zhen University

Common successful trials on Passive Bi-static Radar(PBR) exploit civil communication signals as opportunity illuminators. In this paper, we consider a passive radar system utilizing uncooperative radar as illuminator to detect the aircraft. Specifically, the illuminator radar is frequency agile and PRI agile. And we propose a whole compatible signal processing scheme for this system. A field experiment is done to validate the feasibility of this system. For the convenience of evaluation, we choose several real-time civil airlines as the operating objects. Resorting to the automatic dependent surveillance(ADS-B) database and the active radar's detection results, the correction and precision of the aircraft detection results can be verified.

关键词： Passive bi-static radar Aircraft detection Uncooperative radar

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A new feature selection method based on relief and SVM-RFE

A new feature selection method based on relief and SVM-RFE

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International Conference on Signal Processing Proceedings (ICSP)

作者： Ruigang Fu Ping Wang Yinghui Gao Xiaoqiang Hua Science and Technology on Automatic Target Recognition laboratory National University of Defense Technology Changsha Hunan CN

ISBN: (纸本)9781479921898

In original data, there may exist redundant features, irrelevant features, noisy features besides informative features. Extracting informative features while eliminating the others is the goal of feature selection. This paper proposed a new feature selection algorithm based on Relief algorithm and SVM-RFE algorithm, and it is strongly targeted to eliminate the unnecessary features. Finally, We test the proposed method on three data sets from UCI, and treat accuracy, size of optimal subset, time-cost as evaluations, the experimental results show that the proposed algorithm has a better performance than Relief algorithm and SVM-RFE algorithm except time-cost.

关键词： Classification algorithms Accuracy Algorithm design and analysis Support vector machines Noise measurement Feature extraction Ionosphere

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