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IEEE International Conference on Microwave technology & Computational Electromagnetics (ICMTCE)

作者： Moufa Hu Lei Gao Zhiyong Zhang The State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics&Information System Luoyang Henan China 471003 Science and Technology on Automatic Target Recognition (ATR) NUDT Changsha Hunan China. 410073

Motion compensation is very important for Inverse synthetic aperture radar (ISAR) imaging while the imaging quality is directly dependent on its performance. Range alignment (envelope alignment) is the key procedure of motion compensation. The nonextensive entropy, known as Tsallis entropy, is introduced into ISAR range alignment because of the correlation between adjacent one-dimensional range profile (or long time memory characteristic). Firstly, the principle of range alignment method via minimum Shannon entropy (RAMSE) was summarized. Based on this, a new adjacent range profile alignment method was given via minimum Tsallis entropy (RAMTE). Further, in order to reduce the accumulation of alignment error and jump error, the modified RAMTE (mRAMTE) was presented using accumulation range profile alignment and smooth filter. Based on the criterion of minimum Tsallis entropy, mRAMTE could reduce the alignment error into 1/8 range resolution cell by data interpolation. Simulation results and experiments show that mRAMTE can effectively compensate range walk caused by target motion. And it was also shown that the alignment performance of mRAMTE is better than RAMSE.

关键词： Entropy Imaging Radar imaging Motion compensation Vectors Scattering

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Radar Micro-Doppler Signatures Model Simulation and Feature Extraction of Three Typical LSS targets

Radar Micro-Doppler Signatures Model Simulation and Feature ...

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International Conference on Information science and Control Engineering (ICISCE)

作者： Qi Wu Jinhui Zhao Yue Zhang Yang Huang Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha Teaching and research security center of human resources department National University of Defense Technology Changsha Cognitive radar teaching and research room National University of Defense Technology Changsha

ISBN: (数字)9781728157122

ISBN: (纸本)9781728157139

Small unmanned aerial vehicles (UAVs) detection and discrimination has become increasingly significant due to its extensive application and potential threats. It can be divided into two steps: the first is to distinguish man-made and natural targets and then further characterize UAVs detailed information. Detecting high-speed units of targets using micro-Doppler signatures (mDs) can recognize UAVs from birds quickly. In this paper, pay emphasis on discussing the different evolution of mDs of three typical LSS targets (Quadcopter, Helicopter and Bird) in short-time and long-time integration. In short time interval, instantaneous mDs accord to sinusoidal modulation. Convert spectrum into time-frequency spectrogram, cadence velocity diagram (CVD), sum of cadence velocity diagram (SCVD) and singular value decomposition (SVD) to extract micro-Doppler features accurately. In long-time integration, utilize pulse compression and long-time integration algorithm to obtain single frame Doppler modulation spectrum and propose a regularized log-Doppler spectrogram, enlarging the weak side frequencies and clarify the spectrum width and the number of spectral lines, from which can extract modulation repetition frequency and single bandwidth to distinguish UAVs from birds and estimate more detailed information about the target.

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Low sidelobe pattern synthesis for airborne distributed coherent active phased array radar

Low sidelobe pattern synthesis for airborne distributed cohe...

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IET International Radar Conference (IRC 2023)

作者： Xiuci Mo Zihao Chen Fengfeng Chen Weidong Hu AVIC Leihua Electronic Technology Research Institute Wuxi People's Republic of China National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha People's Republic of China

ISBN: (数字)9781837240982

Airborne distributed coherent active phased array radar can form a large aperture by combining multiple radar echoes scattered in the whole area of the aircraft, which can greatly improve the detection performance compared with the traditiona l single aperture radar. However, the array manifold of distributed coherent radar is complicated due to the influence of 3 - dimensional shadowing and array element anisotropy, which results in the traditional beamformer for the planar array is no longer applicable. Therefore, this paper proposes a beampattern synthesis algorithm that does not require specifying a lobe - level-mask and enables the optimization of array elements in terms of number and position. Numerical examples show that the proposed algorithm can attain a lower peak sidelobe level than the traditional beamformer.

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Approximate attribute reduction algorithm based on general binary relation

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Ruan Jian Xue Bao/Journal of Software 2014年 25卷 169-177页

作者： Teng, Shu-Hua Liao, Fan Lu, Min Zhao, Jian Zhang, Jun Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha410073 China PLA Units: 66295 Baoding072750 China

One of the most attentive applications of rough set is attribute reduction. Addressing the noise in decision information systems, a new method for importance measure of attribute set is presented from the point of view that knowledge can enhance the ability to perform classification. In addition, a new approximate attribute reduction algorithms is proposed based on general binary relation, which can be used to deal with noise and be applicable to many extending model of rough sets. Experimental results demonstrate that the proposed approximate attribute reduction algorithms can effectively increase sensitivity to noise, achieve more compact reduction, and simultaneously improve the classification performance. ©2014 ISCAS.

关键词： Classification (of information)

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Parking, Intelligent Parking System

Parking, Intelligent Parking System

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IEEE Advanced Information technology, Electronic and Automation Control Conference (IAEAC)

作者： Jinhui Zhao Qi Wu Jie Chen Yang Huang Teaching and research security center of human resources department National University of Defense Technology Changsha Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha Cognitive radar teaching and research room Intelligent perception system National University of Defense Technology Changsha

Recently, the problems of parking and finding the car become serious. In order to solve the problems, this paper designe an “"intelligent parking system based on UWB position and navigation technology”" which can effectively solve the problems mentioned above. The whole system consists of three modules: indoor positioning module composed of UWB intelligent positioning bracelet (tag) and positioning base station; Parking and shopping mall data management module; The app module of the user's mobile phone. The whole system expands the functions of each module, making it have eight unique functions: Allocating parking spaces when enter; Accurate indoor positioning; Intelligent navigation; Reverse car search; Data communication; Real-time monitoring and hurdle alarm; Intelligent promotion and online push; Optimize parking lots configuration and reduce costs. It is of great importance to commercial application and popularization value.

关键词： Navigation Automobiles Base stations Databases Software algorithms Servers Real-time systems

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Neural network-based self-interference cancellation method for in-band full-duplex system

Neural network-based self-interference cancellation method f...

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IET International Radar Conference (IRC 2023)

作者： HongYu Zhu WeiDong Hu Chao Wang Yuan Ye NaiChang Yuan College of Electronic Science and Technology National University of Defense Technology Changsha People's Republic of China National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha People's Republic of China Hunan Institute of Advanced Technology Changsha People's Republic of China

ISBN: (数字)9781837240982

In recent years, In-band Full-Duplex (IBFD) has garnered significant research attention in the fields of communications and sensing due to its unique ability to enhance spectral efficiency. However, the strong self-interference signals generated by the transmitter are billions of times stronger than the desired signals. The research and application of IBFD face unprecedented challenges considering radio impairments such as IQ imbalance, phase noise, Gaussian white noise, and power amplifier nonlinearity. To address this issue, this paper proposes a Multi-Domain Self-Interference Cancellation (MDSIC) method and analyzes its fundamental principles. Simulation results demonstrate that the proposed method achieves approximately 100 dB of self-interference cancellation performance. Although the simulations are based on single-input-single-output (SISO) systems, the proposed MDSIC method can be extended to phased-array or multiple-input-multiple-output (MIMO) systems. Furthermore, the self-interference cancellation performance of different neural network structures is verified using experimental data. The analysis of the experimental data confirms that the proposed MDSIC method exhibits stronger applicability in suppressing self-interference in broadband signals compared to traditional methods.

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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...

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IET International Radar Conference (IRC 2023)

作者： Huiqiang Zhang Shengqi Liu Shuhua Teng Shuang Qu Jie Deng Zhenlin Yu National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha People's Republic of China College of Electronic Information Hunan First Normal University Changsha 410205 People's Republic of China

ISBN: (数字)9781837240982

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 metric s, 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 strong ly correlated to improve the recognition performance of samples from known targets. The efficiency of the propos ed method is identified through the recognition experiments on the HRRP data generated from MSTAR SAR chips.

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Periodic ISRJ suppression with convolution generative network in delay-Doppler domain

Periodic ISRJ suppression with convolution generative networ...

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IET International Radar Conference (IRC 2023)

作者： Beichen Fan Pengcheng Wan Yuanzhe Li Weidong Hu Xiaoyong Du Tao Xu National Key Laboratory of Automatic Target Recognition National University of Defense Technology Changsha People's Republic of China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE) National University of Defense Technology Changsha People's Republic of China

ISBN: (数字)9781837240982

Based on digital radio frequency memory (DRFM), interrupted sampling repeater jamming (ISRJ) poses a serious threat to radar systems by generating false targets after matched filtering. The suppression of jamming has become an intriguing topic in recent years. In this paper, the distribution feature of false targets in the delay-Doppler domain is derived by analyzing the target operator and performing Fourier series expansion on the periodic sampling pulse of ISRJ. The solution for suppressing ISRJ is then transformed into a matrix fitting problem, which may require two-dimensional convolution and feature extraction. With the aid of convolutional generative network (CGN), the delay-Doppler matrix of false targets can be reconstructed and cancelled with the original jammed matrix. The ISRJ-suppressed pulse compression output can finally be extracted from the jamming-cancelled matrix. Simulation experiments on three kinds of common radar waveforms are conducted to confirm the effectiveness and universal applicability of the proposed method.

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Anti Repeater Jamming Method Based on Phase Noise Joint Time-Frequency Analysis

Anti Repeater Jamming Method Based on Phase Noise Joint Time...

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

作者： Hui Jiang Weidong Hu Xiaoyong Du Ziqiao Yuan Yifu Hu Hongyu Zhu Xi'an Electronic Engineering Research Institute Xi'an China National Key Laboratory of Automatic Target Recognition National University of Defense Technology Chang Sha China Xi'an Electronic Engineering Research Institute Xi'an China Xi'an China

The jammer utilizes a digital radio frequency memory (DRFM) system to generate a large number of jamming signals highly correlated with the target echo, thereby reducing the performance of radar target detection and tracking. This article establishes a model for the influence of phase noise on the interference signal of a full duplex jammer (transmitting and receiving simultaneously) forwarding system, and analyzes the differences between radar target echo and jamming signal. Perform de-chirping processing on radar received echoes and time-frequency analysis, use bandpass filtering to extract the Allan variance corresponding to jamming and target echoes, as well as the single sideband noise carrier power ratio, to identify the frequency corresponding to target echoes. Finally, the target echo signal is reconstructed after time-frequency domain filtering. The simulation experimental results show that this algorithm can accurately identify real targets and effectively suppress DRFM repeater jamming.

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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 (IRC 2023)

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

ISBN: (数字)9781837240982

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.

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