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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Chen, Guanren Liu, Wei Zhai, Jiquan Zhou, Weiqi Zhao, Shengzhi Cheng, Qiang Jiangsu Provincial Key Laboratory of Detection and Perception Technology National Key Laboratory of Radar Detection and Sensing Nanjing Research Institute of Electronics Technology Nanjing China

ISBN: (纸本)9798331515669

This study proposes a task scheduling method dedicated to fast patrol of geosynchronous surveillance airspace and observation of the satellites inside it using a reflector radar array. Satellite movement time, antenna movement time (point to target) and dwell time (target observation) are considered in modeling, which makes the problem time-dependent. The large surveillance airspace is divided into several sub-airspaces in terms of the distribution of target satellites, while the scheduling of each sub-airspace is performed seriatim following a certain direction. Genetic algorithm (GA) with some modifications is employed to solve the scheduling problem and optimize the patrol time of every single sub-airspace, so as to obtain the optimized total patrol time of the whole surveillance airspace. Simulation is carried out for validation. A notional radar array comprising 5 reflector radars is utilized to conduct a fast patrol of the surveillance airspace that span 20°S~20°N and 110°E~180°E. The results show that: all observation tasks, i.e., the 189 geosynchronous satellites within the surveillance airspace, are evenly distributed to each radar, while the total patrol time is diminished to 490 seconds, which proves the efficacy of the developed scheduling method in geosynchronous surveillance. © 2024 IEEE.

关键词： Surveillance radar

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ISAR Image 3D Reconstruction Based on Improved KLT Algorithm 6

ISAR Image 3D Reconstruction Based on Improved KLT Algorithm

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Ma, Mingyu Hou, Yingni Nanjing Research Institute of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing210039 China

ISBN: (纸本)9798350353594

This paper presents a method utilizing inverse synthetic aperture radar (ISAR) imaging for target matching and three-dimensional (3D) reconstruction. First, the Harris algorithm is employed to extract feature point from the image. Then, an improved algorithm based on Kanade-Lucas- Tomasi (KL T) is introduced for tracking and matching these feature points. The method conducts affine matrix, incorporating hierarchical iteration and bidirectional matching of two consecutive frames to enhance the number of matching point set, improve tracking accuracy, and establish feature points association across sequential images. Finally, the factorization method is applied to achieve the 3D reconstruction of the target. Experimental results validate the effectiveness of this 3D reconstruction approach. © 2024 IEEE.

关键词： 3D reconstruction

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Swin Transformer-Based Unsupervised Domain Adaptation for ISAR Satellite Classification 2

Swin Transformer-Based Unsupervised Domain Adaptation for IS...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Du, Liang Cheng, Qiang Nanjing Research Institutue of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing210039 China

ISBN: (纸本)9798331515669

Radar images contain rich information, encompassing motion, dimensionality, and electromagnetic characteristics. Unlike optical images, radar images are resilient to varying weather conditions and lighting, enabling continuous monitoring across diverse applications. However, substantial differences between radar and optical images, including their generation processes, definitions, and noise distributions, pose significant challenges for transfer learning, particularly in zero-shot inference when applying computer vision models to radar images, especially inverse synthetic aperture radar (ISAR) images. In practical applications, access to abundant labeled optical images is common, while labeled ISAR images are often scarce, making it difficult to learn effective representations of ISAR objects in an unsupervised setting. This disparity underscores the need for robust domain adaptation techniques to bridge the gap between labeled optical data and unlabeled ISAR data, enabling accurate ISAR object classification without relying on extensive labeled ISAR datasets. This paper presents a novel approach that integrates state-of-the-art attention-based pre-trained vision models with metric learning to effectively leverage unlabeled ISAR images. By capturing shared features across domains, the proposed method achieves high classification performance on a satellite dataset, demonstrating results comparable to those obtained under supervised settings. © 2024 IEEE.

关键词： Radar imaging

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High Precision Cooperative Location Method for Multistatic Radar Based on Sparse Recovery 9

High Precision Cooperative Location Method for Multistatic R...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Zhu, Hengcheng Chen, Yawei Yang, Wenjun Nanjing Research Institute of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing210039 China

ISBN: (纸本)9798350376548

In the case of target location using multistatic radar in the far-field region, the linear superimposed cross-location method tends to generate more false alarms and misses, resulting in lower location accuracy. To solve this problem, a method of multistatic radar working together for sparse target location is proposed. Exploiting the sparse characteristics of targets mainly existing within specific ranges, a high-precision cooperative location method based on sparse recovery for multistatic radar is introduced. By employing sparse algorithms and nonlinear processing, the traditional cross-location method for multistatic radar is improved, thereby enhancing the location accuracy of the multistatic system. Simulation results show that this method can accurately locate the actual position of the target, achieving high-precision location of cooperative multistatic radar in far-field region. © 2024 IEEE.

关键词： Multistatic radars

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Spatial-Polarization Domain Joint Filtering Under Interference Polarization Agility 4

Spatial-Polarization Domain Joint Filtering Under Interferen...

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4th International Conference on Electronics, Circuits and Information Engineering, ECIE 2024

作者： Mao, Yuwei Meng, Jinli Nanjing Research Institute of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing210039 China

ISBN: (纸本)9798350388312

When the polarization parameter agile interference enters from the main lobe, the traditional sampling algorithm will cause weight mismatch, and the radar interference suppression performance will be significantly reduced. To achieve high performance filtering, on the horizontal and vertical dual-polarization sensitive array, a Segment Sampling Filtering(SSF) algorithm based on spatial-polarization domain adaptive filtering is proposed in this paper. On the basis of establishing the spatial-polarization domain receiving signal model, the interference signals are segmented according to the polarization parameters, and the interference signals with different polarization parameters are sampled. Then the main lobe interference is suppressed by the combined adaptive filtering of spatial-polarization domain. A large number of simulation experiments show that the proposed filtering algorithm has a higher output SINR (Signal to Interference plus Noise Ratio) and a higher interference rejection ratio, and then the main lobe interference with agile polarization parameters can be suppressed. © 2024 IEEE.

关键词： Adaptive filtering

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A Novel Method of Ground Target Positioning based on Heterologous Image Registration 2

A Novel Method of Ground Target Positioning based on Heterol...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Shang, Shize Wu, Han Chen, Yawei Cheng, Qiang Xia, Linghao Yang, Yuhao Nanjing Research Institute of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Perception Technology Nanjing210039 China

ISBN: (纸本)9798331515669

In this paper, we propose a target high-precision positioning method based on heterogeneous image registration, including target longitude, latitude and altitude. The longitude and latitude are obtained by registering video SAR images with optical map, and the positioning information on the optical map is precisely known. Based on the registration of video SAR images and optical video images, the target height can be solved according to the projection direction difference of the height target on the two types of images, and the target altitude is calculated by adding the ground altitude. The video SAR and optical video images come from the integrated sensor, and the high frame rate imaging of video SAR can simultaneously satisfy the positioning of moving and stationary targets. Finally, the positioning results of this method is verified by measured data. © 2024 IEEE.

关键词： Image registration

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Improved algorithm of multi-mainlobe interference suppression under uncorrelated and coherent conditions

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Journal of Southeast University(English Edition) 2025年第1期41卷 84-90页

作者： CAI Miaohong CHENG Qiang MENG Jinli ZHAO Dehua Nanjing Research Institute of Electronics Technology Nanjing 210039China National Key Laboratory of Radar Detection and Sensing Nanjing 210039China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing 210039China

A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe *** algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)*** mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP ***,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference *** results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.

关键词： mainlobe interference suppression adaptive beamforming spatial spectral estimation iterative adaptive algorithm blocking matrix preprocessing

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Radar Target Recognition Architecture with Automatic Sample Annotation Capability 4

Radar Target Recognition Architecture with Automatic Sample ...

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4th International Symposium on Computer technology and Information Science, ISCTIS 2024

作者： Sun, Jingming Li, Shiguo Zhang, Qiang Yang, Yuhao Wang, Tianyun Nanjing Research Institute of Electronics Technology Nanjing210039 China National Key Laboratory of Radar Detection and Sensing Nanjing210039 China Jiangsu Provincial Key Laboratory of Detection and Perception Technology Nanjing210039 China China Satellite Maritime Tracking and Control Department Jiangyin214431 China

ISBN: (纸本)9798350354560

Radar data acquisition constrained by uncertainties requires that the radar target recognition system needs to have dynamic learning capability. As a key, automatic sample annotation directly restricts the practicalization of radar target recognition technology, which is mainly based on the supervised learning method. Aiming at the automatic sample annotation problem in radar target recognition based on high resolution range profiles, a radar target recognition architecture with automatic sample annotation capability is proposed by combining traditional target recognition technology with deep learning technology, which can effectively improve the robustness of radar target recognition system. The experimental results based on the measured data show that the proposed architecture can efficiently complete the automatic annotation of data samples required for training radar target recognition models, accelerate the application of radar target recognition under the condition of insufficient data, support the online learning of radar target recognition, and have strong engineering practicability. © 2024 IEEE.

关键词： Self-supervised learning

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Spatiotemporal influence of driving factors on water conservation in underdeveloped plateau regions: a case in the Yellow River Basin of Sichuan, China

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Journal of Mountain Science 2025年第4期22卷 1289-1305页

作者： WANG Xuan MA Lei LU Heng LIU Chao NIE Ruihua LI Naiwen TAN Xiao YANG Zhengli Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China State Key Laboratory of Hydraulics and Mountain River Engineering College of Hydraulic and Hydroelectric EngineeringSichuan UniversityChengdu 610065China

The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainable *** effectively enhancing WC necessitates a comprehensive understanding of its driving factors and corresponding intervention strategies,existing studies have largely neglected the spatiotemporal heterogeneity of both natural and socio-economic ***,this study explored the spatiotemporal heterogeneity of WC drivers in YRS using multi-scale geographically weighted regression(MGWR)and geographically and temporally weighted regression(GTWR)models from an eco-hydrological *** discovered that downstream regions,which are more developed,achieved significantly better WC than upstream *** results also demonstrated that the influence of temperature and wind speed is consistently dominant and temporally stable due to climate stability,while the influence of vegetation shifted from negative to positive around 2010,likely indicating greater benefits from understory *** growth positively impacted WC in upstream regions but had a negative effect in the more developed downstream *** findings highlight the importance of targeted water conservation strategies,including locally appropriate revegetation,optimization of agricultural and economic structures,and the establishment of eco-compensation mechanisms for ecological conservation and sustainable development.

关键词： Water conservation Multi-scale Geographically Weighted Regression Geographically and Temporally Weighted Regression The Yellow River Basin in Sichuan Province Spatiotemporal variation

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Modeling, Analysis and Optimization of Low-Altitude Air Traffic Control in Joint Radar and Communication Networks 20

Modeling, Analysis and Optimization of Low-Altitude Air Traf...

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20th European Radar Conference, EuRAD 2023

作者： Xu, Xianzhe Li, Shikang Tao, Rentuo Chen, Yawei Xia, Linghao Yang, Yuhao Nanjing Research Institute of Electronics Technology China CETC Key Laboratory of IntelliSense Technology China Jiangsu Provincial Key Laboratory of Detection and Perception Technology China

ISBN: (纸本)9782874870743

This paper investigates the low-altitude air traffic control in joint radar and communication (JRC) networks. Small base stations (SBSs) apply JRC technology to serve unmanned aerial vehicles (UAVs) by sensing UAVs and transmitting the sensing information to the macro base station (MBS), which assists for low-altitude air traffic control. We formulate this control problem as a service strategy optimization problem, where SBSs need to perform multiple sense and communication operations within each scheduling period. The goal is to maximize the network service profit, which is obtained from serving UAVs by SBSs. We prove that the objective function of the optimization problem is submodular and then propose a greedy-based service algorithm to solve it efficiently with low complexity. The proposed algorithm provably achieves at least 1 - 1/√e of the optimum value. Simulation results show that our proposed algorithm performs close to the optimal solution with different system parameters. © 2023 European Microwave Association (EuMA).

关键词： Air traffic control

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