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SSRI-NET: AN ITERATIVE NETWORK FOR SAR SUPER-RESOLTION IMAGING

SSRI-NET: AN ITERATIVE NETWORK FOR SAR SUPER-RESOLTION IMAGI...

引用

2022 International Conference on Radar Systems, RADAR 2022

作者： Wang, Ziwen Wei, Yangkai Ding, Zegang School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

ISBN: (纸本)9781839537776

SAR imaging is a widely used technique to solve the remote sensing problem. However, the image resolution of traditional imaging methods is limited by signal bandwidth. In order to solve this problem, a new iterative network is proposed to obtain SAR super-resolution images, i.e., SAR Super-Resolution Imaging Network (SSRI-Net). The proposed SSRI-Net is designed to implement SAR super-resolution imaging. In SSRI-Net, the SAR echo is transformed to the SAR reconstruction image, while an additional decoder part does the opposite operation. The SSRI-Net is composed of the unfolded Alternating Direction Method of Multipliers (ADMM), and the decoder part is formulated into a linear mapping to achieve self-supervised imaging. Numerical simulation and real-data experiment in microwave anechoic chamber demonstrate the robustness and effectiveness of the proposed method. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Image resolution

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PRELIMINARY RESULTS OF UAV ULTRAWIDEBAND SAR TOMOGRAPHY BASED ON MULTI-PASS DATA

PRELIMINARY RESULTS OF UAV ULTRAWIDEBAND SAR TOMOGRAPHY BASE...

引用

2022 International Conference on Radar Systems, RADAR 2022

作者： Sun, Yu Li, Linghao Ding, Zegang Wang, Yan Ma, Xinnong Sun, Xinshuai School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

ISBN: (纸本)9781839537776

Unmanned-aerial-vehicle(UAV) synthetic aperture radar(SAR) tomography can overcome the overlapping and geometric distortion inherent in two-dimensional(2-D) SAR and provide three-dimensional(3-D) radar images of observation scenes flexibly and cheaply. In 2021, a novel P-band ultra-wide-band(UWB) SAR system was designed and installed on a multi-rotor UAV, and multi-angle multi-pass UAV SAR tomography data was collected using this UWB SAR system. This paper demonstrates a UAV-borne SAR tomography experiment, including system introduction, experiment design, data processing, and imaging results. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Tomography

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ORBIT ERROR ESTIMATION IN GROUND-BASED RADAR LUNAR 3D IMAGING BASED ON MINIMUM ENTROPY

ORBIT ERROR ESTIMATION IN GROUND-BASED RADAR LUNAR 3D IMAGIN...

引用

IET International Radar Conference 2023, IRC 2023

作者： Yang, Yuewen Zhu, Kaiwen Wang, Zhen Ding, Zegang Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Ground-based (GB) radar is an effective approach in lunar observation. In GB radar lunar three-dimensional (3D) high-resolution imaging, orbital measurement error will degrade the image quality, and should be estimated and compensated. In this manuscript, an orbit error estimation and compensation method for GB radar lunar 3D imaging based on minimum entropy is proposed. First, echo model considering orbit error is established. Thereafter an autofocus algorithm based on back projection and minimum entropy is proposed to acquire fine-resolved image. Furthermore, particle swarm optimization (PSO) algorithm based on dynamic inertia weight is used to estimate the optimal compensation parameter to minimize the image entropy. Finally, computer simulation results validate the effectiveness of the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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Ground-based Radar Three-Dimensional Imaging for Moon under Sparse Observations

Ground-based Radar Three-Dimensional Imaging for Moon under ...

引用

IET International Radar Conference 2023, IRC 2023

作者： Liu, Peiyao Zhu, Kaiwen Wang, Zhen Ding, Zegang Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China

ISBN: (纸本)9781839539954

Ground-based radar system (GBRs) is a powerful tool to obtain three-dimensional (3-D) imagery of the interested celestial bodies, such as the moon. However, in 3-D moon imaging with GBRs, positions for observation are distributed sparsely, and it will lead to imaging ambiguity in height dimension. In this article, a ground-based radar 3-D imaging method for moon under sparse observation is proposed. First, baseline distribution is analyzed, and an optimal baseline selection algorithm based on spatial baseline density maximization is applied. Then, a tomographic 3-D imaging algorithm is discussed, and compressive sensing (CS) technique is used to recover the elevation signal under sparse observation. Moreover, computer simulations are conducted and validate the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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GEOSYNCHRONOUS SAR 3-D TARGET RECONSTRUCTION BASED ON MULTI-ANGLE OBSERVATION

GEOSYNCHRONOUS SAR 3-D TARGET RECONSTRUCTION BASED ON MULTI-...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhu, Kaiwen Zhang, Tianyi Li, Linghao Ding, Zegang Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Geosynchronous synthetic aperture radar (GEO SAR) has the ability of multi-angle observation, and the potential to reconstruct the three-dimensional (3-D) structure of target. To fully utilize this ability, a 3-D target reconstruction method based on multi-angle observation and forward projection is proposed. The core idea of the proposed method is to determine whether target exists on a 3-D position by forward projecting the 3-D position onto the multi-angle SAR images. The proposed method is well validated via simulation and real data experiment. © The Institution of Engineering & technology 2023.

关键词： 3D reconstruction

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Research on SAR Image Matching Based on SAR-Harris Detector and Adaptive Locally-Affine Matching

Research on SAR Image Matching Based on SAR-Harris Detector ...

引用

IET International Radar Conference 2023, IRC 2023

作者： Wu, Guanghui Shi, Hao Chen, Fan Pan, Hongxin Chen, Liang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Synthetic aperture radar (SAR) image matching is an essential step in SAR image processing. The synthetic aperture radar-scale invariant feature transform (SAR-SIFT), which combines the ratio of exponentially weighted averages (ROEWA) operator with multiscale Harris detection and employs Random Sample Consensus (RANSAC) for matching and filtering, has shown promising results. However, SAR-SIFT suffers from low matching efficiency in specific scenarios, and RANSAC exhibits strong randomness and potential problems of non-convergence. To address these problems, this paper introduces an approach that combines scale-space layers reduction in the SAR-Harris detector with the efficient Adaptive Locally-Affine Matching (AdaLAM) to enhance SAR image matching performance. The proposed SAR-SIFT-AdaLAM method is experimentally evaluated on two sets of different SAR images for matching, and the results indicate an improvement of approximately 25% in the number of matching points compared to the SAR-SIFT, along with a reduction of about 30% in matching time, demonstrating its effectiveness. © The Institution of Engineering & technology 2023.

关键词： Synthetic aperture radar

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ECHO MODELING FOR ASTEROIDS WITH ROUGH SURFACE IN GOUND-BASED SAR IMAGING

ECHO MODELING FOR ASTEROIDS WITH ROUGH SURFACE IN GOUND-BASE...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhou, Ziyi Zhu, Kaiwen Wei, Yangkai Ding, Zegang School of Information and Electronics Beijing Institute of Technology Beijing China BeijingKey Laboratory of Embedded Real-Time Information Processing Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China

ISBN: (纸本)9781839539954

With the development of radar imaging technology, asteroid imaging has become one of the focal points in astronomical radar research. However, in simulation and verification experiments for asteroids observation, the traditional point target approximation method is often inadequate in capturing geometric features and surface topography of asteroid. To address this issue, this paper proposes an improved method for generating asteroid echo specifically tailored for asteroid imaging tasks. Firstly, the relative motion between the radar and the asteroid is calculated to determine the slant range phase. Simultaneously, an amplitude factor that varies with the observation angle is introduced, correcting the isotropic scattering of traditional point target. Subsequently, considering the rough characteristic of asteroid surfaces, an echo generation process is presented based on the Monte Carlo method. Finally, computer simulation experiments are conducted to complete the echo generation and radar imaging of asteroid and its typical surface topography features. The experiments validate the correctness and effectiveness of the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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ROBUST JOINT ASSOCIATION AND REGISTRATION UNDER LARGE SENSOR BIAS

ROBUST JOINT ASSOCIATION AND REGISTRATION UNDER LARGE SENSOR...

引用

IET International Radar Conference 2023, IRC 2023

作者： Ni, Na Jiang, Qi Mao, Huafeng Zhang, Jichuan Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

Radar observation of group targets has recently received much attention in the flight mechanism research and many other applications. Group targets are usually closely spaced with lots of missed detections and false alarms, making it difficult for spatial reconstruction. Multisensor systems make use of data from multiple radars to provide more accurate measurements and robust tracks than a single radar, playing an important role in the group targets observation. In the data fusion processes, multisensor measurements are associated after transformed into a global coordinate system. However, large sensor bias makes it difficult to associate measurements of closely spaced targets given outliers, and nonideal association further increase the sensor bias estimation error. In this paper, we proposed a robust joint association and registration method to simultaneously acquire sensor bias estimates and association results. A nonlinear least median of squares estimator is used to achieve better accuracy and robustness of sensor bias estimation. Simulation results show the better bias estimation and association performance of the proposed method compared to other algorithms. © The Institution of Engineering & technology 2023.

关键词： Radar measurement

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An Adaptive OS-CFAR detector for Dynamic group targets

An Adaptive OS-CFAR detector for Dynamic group targets

引用

IET International Radar Conference 2023, IRC 2023

作者： Shi, Mengxin Jiao, Longxiang Jiang, Qi Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

Effective detection of group targets is of great significance to people's livelihood and national security. Flocks of birds, UAV swarms and other group targets are closely spaced in the radar beam and have high dynamics, which can easily lead to the mismatch of the traditional detector parameters and missed detection. Therefore, in this paper, to solve this problem, we established the detection model of the corresponding scene, derived the probability density function expression of the threshold, and proposed the OS-CFAR detector parameter correction method with the expectation of the maximum number of detected targets as the optimization criterion. Taking the OSPA distance as the detection performance index, the detection performance under different detection parameters is compared to verify the effectiveness of this algorithm, and the experiments show that the algorithm proposed in this paper can effectively reduce the target missed detection in the group targets scene. © The Institution of Engineering & technology 2023.

关键词： Target tracking

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Performance Analysis of Sub-object Partition Method for Linear Formation Targets

Performance Analysis of Sub-object Partition Method for Line...

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IET International Radar Conference 2023, IRC 2023

作者： Xu, Li'ang Jiang, Qi Zhang, Jichuan Wang, Rui Hu, Cheng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Shandong Jinan China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (纸本)9781839539954

The structure of bird formation is complex and variable. Traditional sub-object partition methods cannot match different types of linear formations, leading to a degradation of performance. Recently, a new sub-object partition method applicable to different formations has been proposed. However, the performance of the method has not been analyzed and verified thoroughly. This paper analyses the effectiveness of the proposed method. The statistical rules are proposed to evaluate the performance of the sub-object partition. A series of simulations are conducted using the method of controlling variates, with several important parameters of the method and formation being chosen and discussed separately. And the quantitative results of partition accuracy are demonstrated and the impact of each parameter on partition performance is discussed. Based on the conclusion above, an empirical method for parameter initialization is proposed, which guides the practical applications. © The Institution of Engineering & technology 2023.

关键词： CLUSTERING FORMATION TARGET GROUP TARGET SUB-OBJECT PARTITION

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