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Frontiers of Electrical and Electronic Engineering in China 2012年第1期7卷 49-55页

作者： Hongwei LIU Feng CHEN Lan DU Zheng BAO National Laboratory of radar Signal Processing Xidian UniversityXi'an 710071China

Automatic target recognition （ATR） is an important function for modern radar. High resolution range profile （HRRP） of target contains target struc- ture signatures, such as target size, scatterer distribu- tion, etc, which is a promising signature for ATR. Sta- tistical modeling of target HRRPs is the key stage for HRRP statistical recognition, including model selection and parameter estimation. For statistical recognition al- gorithms, it is generally assumed that the test samples follow the same distribution model as that of the train- ing data. Since the signal-to-noise ratio （SNR） of the received HRRP is a function of target distance, the as- sumption may be not met in practice. In this paper, we present a robust method for HRRP statistical recogni- tion when SNR of test HRRP is lower than that of train- ing samples. The noise is assumed independent Gaus- sian distributed, while HRRP is modeled by probabilistic principal component analysis （PPCA） model. Simulated experiments based on measured data show the effective- ness of the proposed method.

关键词： radar target recognition high resolution range profile (HRRP) probabilistic principal component analysis (PPCA)

Depolarization Degree to Determine Dihedral Attribute of radar target

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Journal of Electromagnetic Analysis and Applications 2024年第6期16卷 85-101页

作者： Faisal Aldhubaib Electronics Department Faculty of Technological Studies Public Authority for Applied Education Shuwaikh Kuwait

This paper investigates the ability of the depolarization degree, derived from the characteristic polarization states at the resonant frequency set, to identify corner or swept, i.e. dihedral, changes in same-class targets by a metallic wire example. A well-estimated depolarization degree requires a robust extraction of the fundamental target resonance set in two orthogonal sets of fully co-polarized and cross-polarized polarization channels, then finding the null polarization states using the Lagrangian method. Such depolarization degree per resonance mode has the potential to form a robust feature set because it is relatively less sensitive to onset ambiguity, invariant to rotation, and could create a compact, recognizable, and separable distribution in the proposed feature space. The study was limited to two targets with two swept changes of fifteen degrees within normal incidence;under a supervised learning approach, the results showed that the identification rate converging to upper-bound (100%) for a signal-to-noise ratio above 20 dB and lower-bound around (50%) below −10 dB.

关键词： Polarimetry radar target recognition Time-Domain Analysis Remote Sensing

Ballistic target recognition based on multiple data representations and deep-learning algorithms

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Chinese Journal of Aeronautics 2024年第6期37卷 167-181页

作者： Lixun HAN Cunqian FENG Xiaowei HU Sisan HE Xuguang XU Air and Missile Defense College Air Force Engineering UniversityXi’an 710051China College of Information and Communication National University of Defense TechnologyWuhan 430010China

target recognition is a significant part of a Ballistic Missile Defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition *** paper focuses on systematically investigating the influences of three novel data representations in the Range-Doppler(RD)***,the radar Cross Section(RCS)and micro-Doppler(m-D)characteristics of a cone-shaped ballistic target are ***,three different data representations are proposed:RD data,RD sequence tensor data,and RD trajectory *** accommodate various data inputs,deep-learning models are designed,including a two-Dimensional Residual Dense Network(2D RDN),a three-Dimensional Residual Dense Network-Gated Recurrent Unit(3D RDN-GRU),and a Dynamic Trajectory recognition Network(DTRN).Finally,an Electromagnetic(EM)computation dataset is collected to verify the performances of the networks.A broad range of experimental results demonstrates the effectiveness of the proposed ***,several key parameters of the proposed networks and datasets are extensively studied in this research.

关键词： Ballistic target Micro-Doppler Deep learning Range-Doppler radar target recognition

STUDY ON ALGORITHM OF SENSOR MANAGEMENT BASED ON FUNCTIONS OF EFFICIENCY AND WASTE

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Chinese Journal of Aeronautics 2000年第1期13卷 39-44页

作者：潘泉张洪才戴冠中刘先省 Department of Automatic Control NW Polytechnical University Xi'an 710072 China

Sensor management plays an important role in data fusion system, and this paper presents an algorithm of sensor management that can be used in target detection, identification and tracking. First, the basic concept, rule, range and function of sensor management are introduced. Then, the quantifying problems of target priority and sensor (or combination)-target pairing in multisensor management are discussed and the efficiency and waste functions are established based on the functions of target priority and sensor-target pairing. On this basis, a distribution algorithm of multi-sensor resources is given, which is optimized by the principle of maximum synthesis efficiency in the multisensor system and constrained by sensor maximum tracking power and what target must be scanned. In addition, the waste measure of sensor resources is introduced to improve the algorithm. Finally, a tactical task that includes three sensors and ten targets is set, and the simulation results show that the algorithm is feasible and effective.

关键词： Algorithms Computer simulation Functions Numerical methods radar target recognition radar tracking

radar high resolution range profile recognition via multi-SV method

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Journal of Systems Engineering and Electronics 2017年第5期28卷 879-889页

作者： Long Li Zheng Liu Tao Li National Laboratory of radar Signal Processing Xidian University

For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for feature space. To tackle these issues, a novel target recognition method is designed, denoted by the multiple support vectors (multi-SV) method. With the proposed method, a special framework is constructed by a treble correlate support vector model to segment the feature space to two regions with the distribution of density, and then the description and classification hyperplane for each region are achieved. Based on the support vector framework, this method needs less memory and computation complexity to fit practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of this method.

关键词： radar target recognition high resolution range profile support vector discrimination classification

An Algorithm for Ship Wake Detection from the SAR Images Using the Radon Transform and Morphological Image Processing

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Journal of Systems Engineering and Electronics 2001年第4期12卷 7-12页

作者：金亚秋王世庆 Center for Wave Scattering and Remote Sensing School of Information Science and Technology Fudan University Shanghai 200433 P. R. China

Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.

关键词： Algorithms Image processing Mathematical transformations radar clutter radar target recognition Spurious signal noise Synthetic aperture radar

Techniques for radar Imaging Based onMUSIC Algorithm

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Journal of Systems Engineering and Electronics 1999年第1期10卷 31-38页

作者： Guo, Biao Lu, Xiaoying Chen, Zengping Air Force Inst of radar Beijing China

At first, the radar target scattering centers model and MUSIC algorithm are analyzed in this paper. How to efficiently set the parameters of the MUSIC algorithms is given by a great deal of simulated radar data in experiments. After that, according to measured data from two kinds of plane targets on fully polarized and high range resolution radar system, the author mainly investigated particular utilization of MUSIC algorithm in radar imaging. And two-dimensional radar images are generated for two targets measured in compact range. In the end, a conclusion is drew about the relation of radar target scattering properties and imaging results.

关键词： Algorithms Electromagnetic wave scattering Mathematical models radar systems radar target recognition

radar Cross-Section Measurement Using the Near-Field Single-Frequency Angular-Diversity Technique

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Journal of Systems Engineering and Electronics 2000年第1期11卷 1-7页

作者： Ye, Xiaodong Fang, Dagang Sheng, Weixing Nanjing Univ of Science and Technology Nanjing China

radar cross-section (RCS) measurement with the near-field electromagnetic wave illumination of a target has been proved to be practical. The existing methods employ the multiplefrequency angular-diversity (MFAD) technique, whereas this paper considers the single-frequency angular-diversity (SFAD) technique. The paper takes into account the scattering center modeling and the limitation of higher sidelobes in reconstructing images in the SFAD technique compared to the MFAD technique. A method of combining the SFAD technique with the RELAX approach is presented for the high-resolution extraction of scattering centers on a target. The proposed method offers an excellent RCS recovery, which is validated by numerical results.

关键词： Electromagnetic wave scattering Image reconstruction radar imaging radar target recognition Relaxation processes

Application　of　Heterogeneous　Multiple　Feature　Data　Fusion　to　Multitarget　Association　and　Tracking

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Journal of Systems Engineering and Electronics 1998年第3期9卷 52-60页

作者： Hongwei, Cheng Yiyu, Zhou Zhongkang, Sun Natl Univ of Defense Technology Changsha China

In this paper we discuss a kind of multitarget tracking and association method based on the data fusion of heterogeneous multiple feature data gained by a sensor such as space state, signal amplitude, Doppler frequency and so on. In order to introduce quantitatively those heterogeneous multiple feature data which are possibly gained by a sensor into the discussion of tracking and association problem, we define a correlation measure which we explain as the generalization of conventional association decision. In conventional Nearest Neighbor method, the decision function can take only two values, 1 or 0, to represent the decision of association or not association. In our method, correlation measure can be take any real value from 0 to 1 to represent the extent of correlation. Considering the practical circumstances that some feature data might not be easily gained continuously, we introduce an effective factor to deal with these cases. In the paper we also discuss the comparative computer simulation tests and give the results.

关键词： Computer simulation Correlation theory radar target recognition Signal processing Tracking (position)