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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

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

ISBN: (纸本)9798331515669

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. © 2024 IEEE.

关键词： Ionospheric measurement

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SAR Tomography with Improved Non-Local Means Filtering Based on Adaptive Window

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Journal of Beijing Institute of technology 2023年第6期32卷 670-684页

作者： Shenglei Wang Zhiyang Chen Yuanhao Li Cheng Hu Radar Research Laboratory School of Information and ElectronicsBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of TechnologyBeijing 100081China

In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR *** from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this *** paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR ***,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed *** results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.

关键词： NL-means filter adaptive window SAR interferogram filtering SAR tomography

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Repeat-pass space-surface bistatic SAR tomography:accurate imaging and first experiment

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Science China(information Sciences) 2024年第9期67卷 245-262页

作者： Zhiyang CHEN Yuanhao LI Cheng HU Shenglei WANG Xinpeng CHEN Mihai DATCU Andrea Virgilio MONTI-GUARNIERI Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Advanced Technology Research Institute Beijing Institute of Technology CEOSpace Tech University Politehnica of Bucharest Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano

Space-surface bistatic synthetic aperture radar(SS-BiSAR) offers an additional observation angle for monostatic spaceborne SAR, making it a promising technology for high-accuracy deformation retrieval technology in local regions. Repeat-pass SS-BiSAR tomography can accurately estimate the surfaces of buildings and steep areas, effectively removing terrain phases during deformation retrieving. However, inaccuracies in the orbital ephemeris can lead to image geometry distortion, reducing image pair coherence,introducing interferometric phase errors, and consequently deteriorating tomographic precision. This paper precisely models the image geometry distortion and interferometric phase error caused by repeat-pass ephemeris error. We propose an ephemeris correction method based on the chirp-Z transform to address these issues. Furthermore, we introduce an accurate tomography model to improve 3D reconstruction *** first SS-BiSAR tomography experiment, conducted using the Chinese Lutan-1 satellite, demonstrates that the correlation coefficient is improved by 0.16 after ephemeris error correction. Moreover, the density and precision of the tomographic point cloud are improved by 13.7% and 12.1%, respectively.

关键词： space-surface SAR tomography orbit error image distortion Lutan-1

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An Efficient Transposition Method for Spaceborne SAR Data Based on HBM 2

An Efficient Transposition Method for Spaceborne SAR Data Ba...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Li, Yongrui Lv, HuShan Xu, Ming Chen, Liang Yang, Zhu Xie, Yizhuang Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Technology Research Institute Beijing China

ISBN: (纸本)9798331515669

The onboard real-time processing of Spaceborne synthetic aperture radar (SAR) is of great significance for the rapid acquisition of surface information. As a key step of SAR imaging processing, the efficiency of data transposition directly affects the imaging quality and processing speed. In order to solve the problem of traditional double data rate synchronous dynamic random-access memory (DDR SDRAM) limiting the transposition speed, this paper proposes a SAR data transposition method based on high bandwidth memory (HBM). The method makes full use of the high bandwidth and multichannel characteristics of HBM, and significantly improves the transposition speed by optimising the data read/write process, providing a new solution for real-time imaging processing of satellite-borne SAR. © 2024 IEEE.

关键词： Dynamic random access storage

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Exploring the Potential of Ultra-Low Latency Spiking Neural Network in Remote Sensing Image Classification

Exploring the Potential of Ultra-Low Latency Spiking Neural ...

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IET International Radar Conference 2023, IRC 2023

作者： Li, Jiahao Xu, Ming Chen, He Li, Can Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781839539954

With the rapid advancement of artificial intelligence, the depth of artificial neural networks (ANN) has increased, resulting in higher power consumption and resource utilization. To address these concerns, researchers have begun to explore spiking neural networks (SNN) as an alternative. SNN offers the potential for improved energy efficiency while achieving comparable performance. In recent years, there has been a growing interest in applying SNN to remote sensing classification scenarios. However, one major challenge hindering its widespread adoption is the high latency associated with real-time processing. To address this challenge, we adopt a novel hybrid training approach that combines ANN-SNN conversion with backpropagation through time. We evaluate the effectiveness of our approach on three publicly available datasets: MSTAR, AID and UCMerced. Our experiment results demonstrate that the proposed ultra-low latency SNN achieves classification accuracy rates of 99.05%, 91.36%, and 92.62%, respectively, with a single time step. To the best of our knowledge, this is the first time to apply ultra-low latency SNN to remote sensing image classification tasks. Our findings suggest that this innovative approach has significant potential for future research in the deployment of these models for on-board processing. © The Institution of Engineering & technology 2023.

关键词： Image classification

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Partial Triple Modular Redundancy Method for Fault-Tolerant Circuit based on HITS Algorithm 36

Partial Triple Modular Redundancy Method for Fault-Tolerant ...

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36th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT 2023

作者： Xie, Yu Yu, Wen-Yue Zhang, Ning Chen, He Xie, Yi-Zhuang Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

ISBN: (纸本)9798350315004

Circuits related to nuclear facilities and on-orbit circuits typically require fault-tolerant reinforcement to cope with harsh radiation environments. While the traditional fully Triple Modular Redundancy (TMR) method can effectively reinforce circuits, it suffers from the problems of large circuit area and high power consumption. To solve this problem, this paper proposes a Partial TMR method based on the HITS algorithm (Hyperlink-Induced Topic Search), which can effectively perform circuit fault tolerance. This method sorts the importance of triggers in the circuit based on the HITS algorithm and uses the Fault Interval time (MTBF) of the Bi-Logic Cone model as the judgment criterion to determine the number of triggers that need to be redundantly designed under partial TMR. Some commonly used modules of an on-orbit processor were tested to verify the effectiveness of the proposed redundancy method in this paper. The experimental results show that the resource overhead can be reduced by at least 20% while achieving an MTBF of 99.9% under TMR. © 2023 IEEE.

关键词： Redundancy

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A Satellite Data-Driven Coherent Parameters Estimation Method via Hierarchical HGRFT for Distributed Coherent Aperture Radar

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 791-804页

作者： Li, Pucheng Ding, Zegang Li, Linghao Lv, Linhan Li, Zhe Zhu, Rui Wang, Guanxing Beijing Institute of Technology Radar Research Laboratory School of Information and Electronics Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401331 China

The distributed coherent aperture radar (DCAR) utilizes full coherent processing (FCP). Compared to single radar unit observations, N radar units can achieve an N3 times increase in signal-to-noise ratio (SNR), providing an advantage in observing distant targets. However, its stringent requirements for time and phase of multiple radar units make coherent parameters (CPs) estimation the crucial aspect of FCP. This article introduces a satellite data-driven CPs estimation method via hierarchical and hybrid generalized Radon-Fourier transform (HHGRFT). First, the FCP procedure is outlined, and the signal model with CPs is established. Second, the principles for selecting satellites and observation time in the experimental setup are induced, along with an analysis of the SNR variations during processing. Furthermore, through a hierarchical processing approach using the generalized Radon-Fourier transform (GRFT), interpulse coherence (IPC) processing, interunit-radar coherence (IURC) processing, and inter-subaperture coherent or noncoherent processing are sequentially conducted. The utilization of generalized sharpness (GS) and gradient descent method facilitated CPs estimation, subsequently enhancing the SNR post-coherence processing. Finally, the proposed method has been validated through simulation and successfully applied to a real DCAR system. © 2023 IEEE.

关键词： Signal to noise ratio

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A tracking filter algorithm for migratory birds based on group situation constraints 2

A tracking filter algorithm for migratory birds based on gro...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Li, Biao Wang, Rui Cai, Jiong Beijing Key Laboratory of Embedded Real-Time Information Processing Technology The Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (纸本)9798331515669

Aerial animal migration is closely related to human life, and radar is one of the most effective means of observing it. However, scanning radar has a low data rate, a short integration time, and lacks prior knowledge of target speed, while migratory animals exhibit high mobility. These factors make traditional tracking filter algorithms ineffective at predicting their movement. To address this issue, this paper proposes a tracking filter algorithm based on group dynamics constraints, leveraging the characteristic behavior of migratory animals flying in groups. First, the dynamic state of the group is calculated using the group as the research unit. Then, tracking filtering is performed under the constraint of group dynamics. Simulation and field data have verified the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Invertebrates

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Modeling and Analysis of the Impacts of Temporal-Spatial Variant Troposphere on Ground-Based SAR Imaging of Asteroids

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Journal of Beijing Institute of technology 2023年第6期32卷 727-739页

作者： Tingting Fu Yuanhao Li Zhiyang Chen Zheng Wu Cheng Hu Radar Research Laboratory School of Information and ElectronicsBeijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Embedded Real-time Information Processing Technology the Chongqing Institute of Meteorological Sciences Chongqing 401147China

The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor ***-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of *** ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant *** spatiotemporal freezing tropospheric models are *** cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of *** the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background *** the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase *** simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.

关键词： near-Earth asteroids ground-based SAR troposphere ray tracing

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Dual-Level Contrast Enhancement Method for Infrared Small Target Detection 2

Dual-Level Contrast Enhancement Method for Infrared Small Ta...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Sun, Haotian Wang, Wenzheng Xu, Yuhan Jin, Qiuyu Zhang, Zipeng Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Institute of Technology School of Information and Electronics Beijing China

ISBN: (纸本)9798331515669

In the field of target detection, infrared small target detection(ISTD) is a critical area of research, playing a vital role in reconnaissance, guidance, and early warning systems. Existing spatial Filtering algorithms perform well in clean backgrounds;however, as these filters require manual design based on prior knowledge, they are prone to interference from complex scenes (e.g., clouds, buildings), leading to target omission. Small targets typically exhibit blurry features and weak energy, making direct detection susceptible to interference from high-intensity areas, which may result in missed detections. To tackle these challenges, this paper presents a two-tier contrast improvement method (DLCE). First, a gradient filter group is used to enhance the signal-to-noise ratio (SNR) of the target, and then, built upon the concept of local contrast measurement (LCM), a novel intensity calculation method is developed. The new contrast window design effectively enhances the target's SNR. Compared with existing algorithms, like MPCM (Multi-Scale Patch-based Contrast Measurement) on publicly available datasets, the proposed method more effectively enhances the target's radiative intensity while suppressing background noise. The effectiveness of the proposed algorithm is confirmed by the simulation results. © 2024 IEEE.

关键词： Alarm systems

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