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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...

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IET International Radar Conference (IRC 2023)

作者： Penghe Zhao Zhengjie Jiang Baogui Qi He Chen Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 People's Republic of China

ISBN: (数字)9781837240982

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.

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Orbit Determination Error Analysis and Compensation for Multi-static GEO SAR Imaging

Orbit Determination Error Analysis and Compensation for Mult...

引用

IET International Radar Conference 2023, IRC 2023

作者： Liu, Yan Zhang, Wentao Chen, Zhiyang Dong, Xichao Huang, Xiaotao Chen, Leping School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100084 China Beijing Institute of Remote Sensing Equipment Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China College of Electronic Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9781839539954

The high orbit altitude of Geosynchronous Synthetic Aperture Radar (GEO SAR) introduces a significant challenge of long synthetic aperture times, which restricts the application of rapid imaging. A multi-static GEO SAR system consisting of multiple satellites flying along track can be employed to jointly image, and thus, to reduce the synthetic aperture time, but the orbit determination errors of different satellites will bring serious defocusing effect to the sub-image synthesis. In this paper, the effects of orbit determination errors on sub-image offset, defocusing and constant phase errors are analyzed in the multi-static GEO SAR system, and an orbit determination error correction method based on phase gradient autofocus (PGA) and interferometric phase estimation is proposed. Simulation results validate the effectiveness of the method. © The Institution of Engineering & technology 2023.

关键词： Error compensation

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An Adaptive Phase Noise Filtering Approach for Multi-Frequency Interferometric SAR

An Adaptive Phase Noise Filtering Approach for Multi-Frequen...

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2021 CIE International Conference on Radar, Radar 2021

作者： Wang, Zhen Ding, Zegang Wang, Yan Ma, Xinnong Li, Linghao Zeng, Tao Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology China

ISBN: (纸本)9781665498142

Multi-frequency (MF) interferometric SAR (InSAR) provides an effective way for the surveying of steep terrains. Phase noise filtering is a key step in MF-InSAR processing which determines the quality of the interferograms and affects the accuracy of inversed elevation. Different from the traditional filtering method of single frequency (SF) InSAR, an adaptive filtering approach for MF-InSAR based on MF phase fusion is proposed in this paper. The main contributions of this method is summarized into two aspects. First, the local fringe frequency estimation (LFFE) is extended from SF to MF case. Second, the non-linear model is introduced in the adaptive phase filtering in the local window based on MF-LFFE to adapt to complex terrains. The computer simulation and the real dual-frequency airborne experiment validate the proposed approach. © 2021 IEEE.

关键词： interferometric SAR local fringe frequency estimation multi-frequency phase noise filtering

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FOUNDATION PIT DEFORMATION MEASUREMENT TECHNIQUE BASED ON GROUND-BASED INTERFEROMETRIC RADAR

FOUNDATION PIT DEFORMATION MEASUREMENT TECHNIQUE BASED ON GR...

引用

IET International Radar Conference 2023, IRC 2023

作者： Wang, Changjun Zhou, Hanpu Wang, Jian Gao, Jiake Deng, Yunkai Tian, Weiming Beijing Building Research Institute Co. Ltd. CSCEC Beijing100076 China Radar Research Lab School of Information and Electronics Bejing Institute of Technology Bejing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology China Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China

ISBN: (纸本)9781839539954

The deformation monitoring data of foundation pit is an important criterion for forecasting and strengthening measures in the field of building safety. During the construction period, the foundation pit will be affected by load, temperature change, random disturbance and other effects to produce deformation. Due to the complex deformation process of foundation pit, it is hard to accurately describe and separate the load trend deformation and elastic thermal deformation by mathematical expression. Excessive thermal deformation may cause cracks in the surrounding pavement and affect the judgment of load deformation. This paper first introduces the deformation measurement method of foundation pit based on differential interferometry technology using ground-based interferometric radar. Based on the obtained deformation type, the simulation verifies the separation effect of wavelet transform on different deformation trends and periodic components. Through the foundation pit deformation monitoring experiment of Tongzhou infrastructure project, the wavelet transform method is used to decompose the foundation pit deformation curve, and the extracted periodic component has good consistency with the temperature information. © The Institution of Engineering & technology 2023.

关键词： Wavelet decomposition

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Radar Echo Modeling and Doppler Characteristic Fitting Method for UAVs Based on Multi-Scattering Point Model

Radar Echo Modeling and Doppler Characteristic Fitting Metho...

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

作者： Li’Ang Xu Qi Jiang Rui Wang Jichuan Zhang Longxiang Jiao Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The radar echo characteristics of unmanned aerial vehicles provide important information for identification. The radar echoes of various types of UAVs are modeled by the multi-scattering point modeling method. A Doppler characteristic modeling method for unmanned aerial vehicles based on the mixture Gaussian algorithm is proposed, in which the slow-time dimension data are extracted from the Range- Doppler and fitted by the mixture Gaussian algorithm. The parameters of the Gaussian distribution components representing the unmanned aerial vehicle's Doppler spread characteristics are obtained using the algorithm. The simulated radar echoes of the multi-rotor unmanned aerial vehicle and the flapping-wing unmanned aerial vehicle are used for analysis. The performance of the fitting is acceptable and the way in which various parameters affect the Doppler characteristics is discussed and concluded.

关键词： Analytical models Radar cross-sections Target recognition Fitting Gaussian distribution Autonomous aerial vehicles Data models Doppler radar Doppler effect Data mining

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LT-1 Differential Tomography: First Results and Comparison between Monostatic and Bistatic Systems

LT-1 Differential Tomography: First Results and Comparison b...

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

作者： Shimeng Zhou Zhiyang Chen Yuanhao Li Cheng Hu Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Beijing China School of Information and Electronic Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Differential Tomography SAR technology integrates the advantages of Differential Interferometric SAR and Tomographic SAR, enabling four-dimensional imaging in areas with SAR layover to obtain elevation and deformation information of the target area. Compared to the traditional monostatic mode, the space-based bistatic observation mode has the advantages of interference immunity and richer information acquisition. This paper uses Differential Tomography SAR technology to perform deformation inversion on the LuTan-1 monostatic and space-based bistatic data. While obtaining the elevation information and linear deformation rate of the observed scene, it also compares the results and performance of Differential Tomography under the two different *** final conclusion is that LuTan-1 demonstrates strong capabilities in differential tomography. Additionally, the differential tomography performance of space-based bistatic systems is superior to that of monostatic systems.

关键词： Point cloud compression Accuracy Deformation Buildings Interference Tomography Data processing Root mean square Standards Monitoring

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Tiny Target Detection with Adaptive Weighted Feature Fusion in UAV Images

Tiny Target Detection with Adaptive Weighted Feature Fusion ...

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

作者： Xiaohui Kang Lingjie Zheng Zhiyuan Deng Yuqi Han Linbo Tang Chenwei Deng Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

With the development of drones, imaging lenses and other equipment, effective and accurate detection of tiny targets in drone remote sensing images has become a hotspot. However, the features of tiny targets are weak and difficult to extract. Most existing methods enhance the target feature expression by directly superimposing and fusing multi-scale feature maps. Only the features with stronger responses in adjacent feature maps can be enhanced, while the targets with weaker responses may be diluted. For this reason, an adaptive weighted fusion small target detection algorithm is designed. To enhance the proportion of small targets in feature maps of different resolutions, a bidirectional feature pyramid network is designed. The adaptive weights are set according to the feature density in the feature map, and they will be used to perform bidirectional fusion on feature maps to reduce the interference of background and large targets on the features of small targets. Besides, we design multi-scale dilated convolution, which is injected into the feature fusion network. In this way, we successfully enhance the expression of small target feature. Finally, we test the algorithm via the public dataset VisDrone, the results show that our methods significantly improve the accuracy of small target detection.

关键词： Accuracy Convolution Semantics Object detection Transforms Feature extraction Autonomous aerial vehicles Remote sensing Drones Lenses

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A method for enhancing infrared small target images under complex sky backgrounds

A method for enhancing infrared small target images under co...

引用

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

作者： Yuhan Xu Linbo Tang Haotian Sun Beijing Key Laboratory of Embedded Real-Time Information Processing Radar Research LabSchool of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Infrared target detection is currently widely used in both military and civilian fields. Due to the lower resolution of infrared images compared to visible light images and the lack of texture information in small targets, the quality of infrared small target images is often poor and not suitable for direct detection. Therefore, enhancing low-quality infrared small target images is a necessary step before object detection can be performed. This article presents a method for enhancing infrared images of small targets. The process begins with applying guided filtering to the original image. The resulting detail layer is then used as a guided image for a second guided filtering of the base layer, producing a second detail layer. Additionally, a novel approach to local contrast enhancement is introduced, which applies contrast enhancement specifically to this secondary detail layer. Experimental results has been demonstrated that the enhancement method proposed in this paper significantly improves the visibility of the target area while reducing background interference, without losing information about small targets. Additionally, this method outperforms other common techniques in terms of enhancement effect, as shown in comparative experiments.

关键词： Image quality Image resolution Object detection Interference information filters Data processing Image enhancement

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Modeling and Verification of processing Engines in SAR Imaging SoC

Modeling and Verification of Processing Engines in SAR Imagi...

引用

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

作者： Zhihan Zhang Chao Yang Yizhuang Xie Yongrui Li Ao Zhang Radar Research Lab School of Information and Electoronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Shanghai Institute of Satellite Engineering Shanghai China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

With the development of real-time requirements for Synthetic Aperture Radar (SAR) imaging technology, SAR imaging processing SoC (System on Chip) has become an important research field at present. The subsystem for SAR imaging processing in the SAR imaging SoC needs to be fully verified during the development process. This article designs a UVM-based random verification environment, focusing on the verification requirements of key computing engines and interaction engines in the SAR imaging processing SoC. At the same time, a modeling method for computing engines and interaction engines is proposed, which can quickly and accurately describe the functions and behaviors of processing engines. Collaborating with the verification environment and the reference C model, the design under test achieves satisfactory coverage results. Consequently, the functionality of the processing engines within the subsystem can be comprehensively and effectively verified. The content studied in this article has certain value for the engineering verification implementation of SAR imaging algorithms in the SoC.

关键词： Computational modeling Focusing Streaming media Radar polarimetry Data models Real-time systems Timing System-on-chip Engines Synthetic aperture radar

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Robust Adaptive OS-CFAR Detector for Maneuvering Group Target Based on Formation Prior Knowledge

Robust Adaptive OS-CFAR Detector for Maneuvering Group Targe...

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

作者： Mengxin Shi Qi Jiang Rui Wang Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China The Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Detecting the individuals such like the bird flocks or a UAV swarm is a great challenge for radar systems. The lack of prior knowledge about the characteristics of dynamic group targets leads to the performance degradation of conventional detectors. In this study, we present a robust adaptive OS-CFAR detector for maneuvering group targets, leveraging prior knowledge of their formation. The group target’s state is updated and predicted using the random matrix approach. The projection length of the group target in the radar beam direction is computed using the predicted information during the group target tracking process. Using the projection length, the number of reference units occupied by the group target within the reference window is determined, and this prior knowledge is applied to update the detection parameters of the OS-CFAR detector. The simulation result shows that the algorithm can update the detection parameters timely and avoid target missed detection.

关键词： Target tracking Simulation Radar detection Detectors Radar Radar tracking Prediction algorithms time measurement Real-time systems Motion measurement

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