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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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A NETWORK COMPRESSION METHOD BASED ON NETWORK ARCHITECTURE SEARCH FOR SAR TARGET DETECTION

A NETWORK COMPRESSION METHOD BASED ON NETWORK ARCHITECTURE S...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhao, Penghe Jiang, Zhengjie Qi, Baogui Chen, He Chen, Liang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy of Beijing Institute of Technology Zhejiang Jiaxing314019 China

ISBN: (纸本)9781839539954

With the development of high-resolution satellites, real-time processing of satellite data has become a major development trend. However, due to the limitations of onboard resources, onboard real-time processing faces problems such as insufficient storage space, insufficient operating memory, and high computational complexity. To address the above issues, we propose a Synthetic Aperture Radar (SAR) image detection algorithm based on neural network structure search. By designing efficient and flexible search spaces, search strategies, and subnet evaluation modules, lightweight detection networks that meet specific task requirements can be searched from the original detection network. The proposed method was tested on three SAR ship datasets, and the results showed that the proposed method can reduce model complexity and improve inference speed while keeping detection accuracy nearly lossless. © The Institution of Engineering & technology 2023.

关键词： Radar target recognition

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AN EARTH-BASED RADAR HIGH RESOLUTION IMAGING technology OF THE MOON BASED ON SUB-APERTURE DELAY DOPPLER ALGORITHM

AN EARTH-BASED RADAR HIGH RESOLUTION IMAGING TECHNOLOGY OF T...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhang, Guangwei Ding, Zegang Wei, Yi Li, Gen Zhang, Tianyi 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

The delay Doppler algorithm is the earliest developed and the most used frequency-domain imaging algorithm for the moon, which is suitable for low resolution imaging. Howeaver, this algorithm usually assumes that the Doppler phase induced by the rotation of the target is only first order. This assumption is not suitable for high resolution imaging with long-term observation. In this paper, an earth-based radar high resolution imaging technology based on sub-aperture delay Doppler algorithm is proposed. This paper first analyses the basic constraints of the sub-aperture division, which avoid the ARU and ADU effects in each sub-aperture and ensure that the Doppler phase is linear. Then, the sub-aperture delay Doppler imaging is performed to obtain the sub-aperture images. Then, multiple sub-aperture delay Doppler images can be projected into the geographic coordinate system based on the RD positioning model. Finally, multiple sub-aperture images can be coherently fused to obtain a full-aperture image. Computer simulation results and experimental results based on a distributed coherent radar prototype system validate the proposed algorithm. © The Institution of Engineering & technology 2023.

关键词： Frequency domain analysis

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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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A Fast MART Method with Voxel Filtering for GEO SAR-Based Computerized Ionospheric Tomography

A Fast MART Method with Voxel Filtering for GEO SAR-Based Co...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Yi Sui Xichao Dong Zhiyang Chen Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Ionospheric monitoring is crucial for space environment assessment and the success of space mission. Traditional computerized ionospheric tomography (CIT) based on Global Navigation Satellite System (GNSS) are constrained ground receivers, while CIT based on geosynchronous synthetic aperture radar (GEO SAR) offers an ionospheric tomography solution that does not rely on ground receivers. This approach leverages the abundant Permanent Scatterer (PS) points in the SAR image for electron density reconstruction, providing strong adaptability to various environments. However, due to the large number of PS points in the large coverage area of GEO SAR and the abundance of total electron density (TEC) data, the conventional multiplicative algebraic reconstruction technique (MART) is inefficient in processing iteration. To this end, this paper proposes a fast MART method based on Voxel Filtering, and verifies the effectiveness of the proposed method through a tomographic experiment. The results show that the proposed method ensures reliable tomographic results, effectively improves the iteration speed, and significantly improves the computational efficiency, which provides strong support for GEO SAR-based CIT with huge TEC data.

关键词： Global navigation satellite system Filtering Space missions Receivers Tomography Radar polarimetry Reliability Synthetic aperture radar Image reconstruction Electrons

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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

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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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