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Bistatic weak target detection method using non-cooperative air surveillance radar

Journal of Systems science & Complexity 2015年第5期28卷 954-963页

作者： Dinghe Wang Qinglong Bao Ruiqi Tian Zengping Chen Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology

At present, most of the passive radar system researches utilize FM radios, TV broadcasts, navigation satellites,etc. as illuminators. The transmitted signals are not specifically designed radar waveforms. In this work, the frequency agile, phased array air surveillance radar(ASR) is used as the illuminator of opportunity to detect the weak target. The phased array technology can help realize beam agility to track targets from different aspects simultaneously. The frequency agility technology is widely employed in radar system design to increase the ability of anti-jamming and increase the detection probability. While the frequency bandwidth of radar signals is usually wide and the range resolution is high, the range cell migration effect is obvious during the long time integration of non-cooperative bistatic radar. In this context, coherent integration methods are not applicable. In this work, a parametric non-coherent integration algorithm based on task de-interweaving is proposed. Numerical experiments verify that this is effective in weak target detection.

关键词： air surveillance radar non-cooperative bistatic taskde-interweave.

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Environment-Driven Online LiDAR-Camera Extrinsic Calibration

arXiv

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arXiv 2025年

作者： Huang, Zhiwei Li, Jiaqi Zhong, Ping Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Tongji University Shanghai201804 China The School of Computer Science and Engineering Central South University Hunan Changsha410083 China The National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Hunan Changsha410073 China The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China

LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle variations in sensor data and environmental contexts. This paper introduces EdO-LCEC, the first environment-driven, online calibration approach that achieves human-like adaptability. Inspired by the human perceptual system, EdO-LCEC incorporates a generalizable scene discriminator to actively interpret environmental conditions, creating multiple virtual cameras that capture detailed spatial and textural information. To overcome cross-modal feature matching challenges between LiDAR and camera, we propose dual-path correspondence matching (DPCM), which leverages both structural and textural consistency to achieve reliable 3D-2D correspondences. Our approach formulates the calibration process as a spatial-temporal joint optimization problem, utilizing global constraints from multiple views and scenes to improve accuracy, particularly in sparse or partially overlapping sensor views. Extensive experiments on real-world datasets demonstrate that EdO-LCEC achieves state-of-the-art performance, providing reliable and precise calibration across diverse, challenging environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Spatio-temporal data

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Observability analysis of feature aided terminal guidance systems

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Journal of Systems Engineering and Electronics 2015年第1期26卷 127-133页

作者： Shijie Fan Hongqi Fan Huaitie Xiao Jianpeng Fan Qiang Fu National Key Laboratory of Automatic Target Recognition National University of Defense Technology College of Electronic Science and Engineering National University of Defense Technology

Feature aided design of estimators and guidance laws can significantly improve the interception performance of the terminal guidance system. The achieved enhancement can be effectively assessed by observability analysis methods. This paper first analyzes and discusses the existing assessment methods in a typical endgame scenario with target orientation observations. To get over their deficiencies, a novel singular value decomposition（SVD） method is proposed. Employing both theoretical analysis and numerical simulation, the proposed method can represent the degree of state observability which is enhanced by integrating target features more completely and quantitatively.

关键词： terminal guidance feature aided observability singular value orientation observation

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Parameter Estimation of Multi-Component LFM Signals Based on STFT+Hough Transform and Fractional Fourier Transform 2

Parameter Estimation of Multi-Component LFM Signals Based on...

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2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Xu, Fenfei Bao, Qinglong Chen, Zengping Pan, Shengsen Lin, Caiyong National University of Defense Technology Science and Technology on Automatic Target Recognition Laboratory China

ISBN: (纸本)9781538618035

T248 separate and estimate the parameters of multi-component linear frequency modulation(LFM) signals in the presence of white Gaussian noise, a new method based on fractional Fourier transform(FRFT) with the help of short-time Fourier transform(STFT) and Hough transform is proposed. The theory of FRFT for estimating the chirp rate of the multi-component LFM signal is analyzed. Pointing out the phenomenon that when the amplitudes of the strong and weak component signals differ greatly, the weak component signal is disturbed by the strong component signal and can not be detected by the search method. This paper analyzes the advantages of using Hough transform after STFT, and then proposes the use of STFT+Hough transform to estimate the chirp to guide FRFT for small-scale search. The parameters of the strong signal components are estimated one by one, and the strong signal are eliminated in the fractional Fourier transform domain by using very narrow band-stop filtering to improve the reliability of the multi-component signal parameter estimation. The effectiveness of this method is verified by computer simulation. © 2018 IEEE.

关键词： Frequency estimation

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A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

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Journal of Systems Engineering and Electronics 2023年第4期34卷 879-893页

作者： JIANG Libing ZHENG Shuyu YANG Qingwei YANG Peng WANG Zhuang Science and Technology on Automatic Target Recognition National University of Defense TechnologyChangsha410073China Xi’an Satellite Measurement and Control Center Xi’an 710600China

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)*** this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)***,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction ***,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix ***,scattering centers can be reconstructed with specific three dimensional *** simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

关键词： three dimensional inverse synthetic aperture radar(3D ISAR)imaging space target improved orthogonal matching pursuit(OMP)algorithm scattering centers

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Staring-imaging satellite pointing estimation based on sequential ISAR images

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Chinese Journal of Aeronautics 2024年第8期37卷 261-276页

作者： Canyu WANG Libing JIANG Weijun ZHONG Xiaoyuan REN Zhuang WANG National Key Laboratory of Automatic Target Recognition National University of Defense TechnologyChangsha 410073China Xi’an Satellite Control Center Xi’an 710600China

Pointing estimation for spacecraft using Inverse Synthetic Aperture Radar(ISAR)images plays a significant role in space situational awareness and ***,feature extraction and cross-range scaling of ISAR images create bottlenecks that limit performances of current estimation ***,the emergence of staring imaging satellites,characterized by complex kinematic behaviors,presents a novel challenge to this *** address these issues,this article proposes a pointing estimation method based on Convolutional Neural Networks(CNNs)and a numerical optimization algorithm.A satellite’s main axis,which is extracted from ISAR images by a proposed Semantic Axis Region Regression Net(SARRN),is chosen for investigation in this article due to its unique ***,considering the kinematic characteristic of the staring satellite,an ISAR imaging model is established to bridge the target pointing and the extracted *** on the imaging model,pointing estimation and cross-range scaling can be described as a maximum likelihood estimation problem,and an iterative optimization algorithm modified by using the strategy of random sampling-consistency check and weighted least squares is proposed to solve this ***,the pointing of targets and the cross-range scaling factors of ISAR images are *** experiments based on actual satellite orbital parameters verify the effectiveness of the proposed *** work can improve the performance of satellite reconnaissance warning,while accurate cross-range scaling can provide a basis for subsequent data processes such as 3D reconstruction and attitude estimation.

关键词： Staring-imaging Agile satellite Inverse Synthetic Aperture Radar(ISAR) Pointing estimation Cross-range scaling

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Parameter Extraction of Direct Wave for Passive Radar Using Suboptimal Nearest-Neighbor Approach 2

Parameter Extraction of Direct Wave for Passive Radar Using ...

引用

2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Hu, Panhe Li, Jingyu Bao, Qinglong Chen, Zengping Pan, Shengsen National University of Defense Technology Science and Technology on Automatic Target Recognition Laboratory Changsha China

ISBN: (纸本)9781538618035

Under the trend of complex electromagnetic environment and development of new radar system, the direct wave of noncooperative radar is easily affected by clutter, multipath, and other noncooperative illuminators. These problems make it difficult for passive radar to extract the parameters of the direct wave. In this paper, a novel signal processing method using suboptimal nearest-neighbor (SNN) approach is proposed to acquire accurate parameters of direct wave. In this method, the parameter estimation of direct wave is converted to time-frequency data association. Firstly, the direct wave is processed with time-frequency analysis. Then, the SNN approach is applied to perform time-frequency data association and acquire the associated time-frequency line. Finally, the rough parameters are measured by calculating the positions of time-frequency line and accurate parameters are obtained by template matching with the known parameters. Simulation and experimental results verify the feasibility of the proposed method. © 2018 IEEE.

关键词： Parameter extraction

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Weak target detection algorithm for non-cooperative bistatic radar

Weak target detection algorithm for non-cooperative bistatic...

引用

IET International Radar Conference 2015

作者： Wang, Dinghe Bao, Qinglong Niu, Zhaodong Chen, Zengping Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781849199940

At present, most of the passive radar system researches utilize FM radios, TV broadcasts, navigation satellites etc. as illuminators. The transmitted signals are not specifically designed radar waveforms. In this work, a frequency agile, phased array Air Surveillance Radar (ASR) is used as illuminator of opportunity for weak target detection. In this case, coherent integration methods are not applicable. Thus, a parametric non-coherent integration algorithm based on task de-interweaving is proposed. Numerical experiments verify that this method is effective in weak target detection.

关键词： Surveillance radar

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A target detection method for non-cooperative PBR with frequency-agile and pri-agile radar

A target detection method for non-cooperative PBR with frequ...

引用

IET International Radar Conference 2015

作者： Lin, Caiyong Hu, Panhe Bao, Qinglong Zhang, Shuyan Chen, Zengping Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781849199940

In case of passive bistatic radar (PBR) using a phased array radar (PAR) as the non-cooperative illuminator, there are problems that signal parameters of the transmitter are unknown and signal coherence is damaged. Aiming at the issues, this article presents a target detection method for PBR using PAR as the non-cooperative illuminator. Firstly, the method uses the direct wave to estimate signal parameters, and then pulse compresses scattered wave. Secondly, the compressed wave is aligned by fast-time dimension so that a Range-Time (R-T) map can be obtained. Finally, the target is detected according to the trajectory in R-T map. The field experimental results demonstrate the effectiveness of this method.

关键词： Tracking radar

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A track processing method of multi-target based on passive radar

A track processing method of multi-target based on passive r...

引用

IET International Radar Conference 2015

作者： Zhang, Shuyan Bao, Qinglong Lin, Caiyong Chen, Zengping Science and Technology on Automatic Target Recognition Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781849199940

According to the characteristics of passive radar, a new method of multi-target track processing based on Kalman filter is proposed, which is Track Searching based on Kalman Filter(TSKF). In this method, velocity method [1] is used firstly to find possible track and an adaptive association gate is adopted to associate with successive measurements. Secondly, Kalman filter is used to predict locations of successive measurements. Finally, Nearest Neighbor method is used to search all points belonging to the possible track and confirm the track. After that the algorithm need to go to a next cycle to find new target tracks. In order to demonstrate the validity of the proposed method, experiments with real data were conducted to compare with traditional Kalman method.

关键词： Kalman filters

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