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IEEE Conference on Industrial Electronics and applications (ICIEA)

作者： Zhentong Gao Qiantong Wang Zongxu Pan Hui Long Yuxin Hu Zheng Li Key Laboratory of Technology in Geo-spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665409858

3D object detection is an important task in autonomous driving scenario, which is the basis of perception and understanding of 3D scenes. LiDAR and camera are two commonly used sensors in 3D object detection tasks. However, using a single sensor to collect data will make some objects difficult to detect because both sensors have insurmountable shortcomings. Unexpectedly, LiDAR-only detection methods tend to show better performance than the multi-sensor methods in public benchmarks. This shows that people need to further explore the methods of combining the data of the two sensors. Recently, PointPainting has been presented to combine the data of LiDAR and camera more efficiently by attaching the result of image semantic segmentation to point cloud data as new channels. In this paper, we propose an error anchor punishment mechanism based on image semantic segmentation results. After the semantic augmentation of the point cloud data, we judge whether the semantic result of each point is correct by traversing the groundtruth boxes. Further, we assign different weights to each anchor according to the error points contained in each anchor. Experimental results on the KITTI valid set show that SemanticAnchors achieves better performance in both 3D and birds eyes view benchmarks. In particular, our method adds little extra computation and achieves performance improvement in all categories.

关键词： Point cloud compression Training Three-dimensional displays Laser radar Semantic segmentation Semantics Object detection

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An Approach for Spaceborne InSAR DEM Inversion Integrated with Stereo-SAR Method

An Approach for Spaceborne InSAR DEM Inversion Integrated wi...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Fangfang Li Yueting Zhang Xiaolan Qiu Key Laboratory of Geo-spatial Information Processing and Application System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has the capability of high precise topographic mapping for large area. However, on the one hand, digital elevation models (DEM) inversion needs at least one ground control points (GCP) to obtain absolute interferometric phase as the unwrapped phase is just a relative value. On the other hand, the baseline value used for DEM inversion also needs to be calibrated using GCPs due to the measure error. In practice, it is difficult to manually deploy GCPs especially in the area of steep topography. At present, with the improvement of orbital measure accuracy and system time accuracy for spaceborne SAR satellite, high precise absolute 3D location information of some stable point scatterers can be obtained by stereo SAR using data from different viewing angles. Therefore, this paper combines stereo SAR with InSAR. These point scatters are used as GCPs to calibrate baseline and estimate absolute phase. As a result, high accurate DEM generation without GCPs can be achieved. The experiment using TerraSAR-X data verifies the effectiveness of this method.

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SAR Image Compression Based on Low-Frequency Suppression and Target Perception 8th

SAR Image Compression Based on Low-Frequency Suppression and...

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8th EAI International Conference on Machine Learning and Intelligent Communications, MLICOM 2023

作者： Deng, Jiawen Huang, Lijia Wu, Yifan Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783031717154

Synthetic Aperture Radar (SAR) images are widely used in the field of remote sensing. To store and transmit the growing amount of SAR image data, more efficient compression algorithms are required. In this paper, a new framework for compressing SAR images is proposed based on deep learning. Firstly, we propose a new two-stage transformation based on low-frequency suppression of input data to achieve high information entropy and low quantization loss. To explore the redundancy between regions of interest and regions of non-interest, an image compression model for target perception is proposed to convert the input SAR image into a compact latent representation together with the target perception map. To evaluate the performance of the algorithm, we conducted experiments on SAR image dataset. The results show that the proposed algorithm is significantly better than the traditional processing algorithm in terms of data input, and can effectively preserve and improve the performance of the image compression model. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Image compression

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SAR Change Detection Based on keypoint Graph Structure and Cosegmentation-Based Refinement

SAR Change Detection Based on Keypoint Graph Structure and C...

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Geology, Mapping and Remote Sensing (ICGMRS), International Conference on

作者： Jingxing Zhu Rui Liu Niangang Jiao Feng Wang Hongjian You Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350365719

ISBN: (纸本)9798350365726

Change detection between high-resolution Synthetic Aperture Radar (SAR) images remains a challenging task. Due to the effectively integration of structure and intensity information, graph-based methods have made some progress in SAR change detection. But it still faces the issues of robustness of graph construction and incomplete change detection outcomes. To tackle these challenges, we propose an improved keypoint-based graph structure change detection approach. First, we propose a keypoint extraction strategy guided by a coarse change map to better describe potential change areas. Second, we construct stable graph structures on these keypoints with employing a robust distance measurement that considers the statistical properties of SAR images. Then, the keypoint difference image (KDI) is derived through measuring the consistency of graph structures between pre-and post-time SAR images. Next, keypoint change map (KCM) is generated through clustering KDI by k-means. Finally, we use co-segmentation superpixel mask to refine the KCM and obtain accurate and complete binary change map. We validate the effective of proposed framework on GF-3 dataset. Experimental results demonstrate the superior performance of our method compared to alternative method.

关键词： Image segmentation Geology Noise Focusing Speckle Radar polarimetry Robustness

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TOPOGRAPHIC CORRECTION OF ETM IMAGES BASED ON SMOOTHED TERRAIN

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Journal of Electronics(China) 2012年第3期29卷 271-278页

作者： Jiang Kang Zhao Yongchao Geng Xiurui Tang Hairong Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Beijing 100100China Institute of Electronics Chinese Academy of SciencesBeijing 1001P0China Graduate University Chinese Academy of SciencesBeijing 100040China

A new empirical topographic correction method is proposed in this paper. The main idea of the new method is smoothing the slope angle of terrain in the first place and then performing the cosine correction based on the smoothed terrain. A comparison is conducted among the new method and several other common methods using Landsat-7 ETM+ data. Visual analysis and statistical analysis are adopted to assess the performance of these methods from two aspects: overcorrection, homogeneity within a land cover class. Comparison results indicate that the new method is superior to the cosine correction, Gamma correction, Sun-Canopy-Sensor correction, and Minnaert correction. Compared with common methods, the proposed one can eliminate overcorrection better and is an effective topographic correction method.

关键词： Topographic correction Landsat-7 ETM Smoothed terrain

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3D Object Detection Based on Feature Fusion of Point Cloud Sequences

3D Object Detection Based on Feature Fusion of Point Cloud S...

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IEEE Conference on Industrial Electronics and applications (ICIEA)

作者： Zhenyu Zhai Qiantong Wang Zongxu Pan Wenlong Hu Yuxin Hu Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665409858

Increasing the number of lines of lidar can alleviate the sparsity of point cloud, but the cost of high-line lidar is higher. From the perspective of algorithm, the fusion of continuous point clouds frames can obtain more abundant information, which is expected to be a means to achieve high-performance object detection on low-line lidar. At present, most multi-frame point cloud fusion methods stack different frames after registration. This fusion method, which introduces GPS, ego-motion, and other information for registration, can only align static objects, not larger moving objects. In this paper, we implement a multi-frame fusion method based on Non-Local, which does not need registration and takes into account both moving and stationary objects. We validated the model performance on the NuScenes dataset. Experimental results show that the performance of the proposed fusion method is better than that of fusion method by stacking frames after registration.

关键词： Point cloud compression Industrial electronics Laser radar Three-dimensional displays Costs Fuses Stacking

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Influence of beam stepping control and pointing deviation on image quality of spaceborne sliding spotlight SAR 3

Influence of beam stepping control and pointing deviation on...

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3rd China International SAR Symposium, CISS 2022

作者： Zeng, Tian Li, Zheng Yang, Wei Men, Zhirong Beihang University School of Electronic and Information Engineering Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350398717

ISBN: (纸本)9798350398717

Sliding spotlight mode is widely used in spaceborne SAR to achieve high resolution. However, due to the difficulty for antenna beam to scan continuously, it usually works by step scanning, which leads to paired-echo in SAR images. Meanwhile, the pointing of the antenna often deviates from the preset value when scanning, resulting in an increase in the amplitude of the paired echo. This paper works on the effect of beam stepping control and pointing deviation on image quality of Ka band spaceborne sliding spotlight SAR. Firstly, the azimuth echo signal in sliding spotlight mode under the beam stepping control and pointing deviation is modeled. Then, the influence of beam stepping control and pointing deviation is analyzed by using the paired-echo theory, and the quantitative relationship between beam granularity and pointing deviation and paired-echo is presented. Finally, the validity of the theoretical analysis is verified by computer simulation. The method in this paper provides a reliable basis for the design of parameters in spaceborne sliding spotlight SAR system. © 2022 IEEE.

关键词： Synthetic aperture radar

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Secrecy relaying strategy over correlated fading channels using CSI estimation 5

Secrecy relaying strategy over correlated fading channels us...

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5th International Conference on Communication and information processing, ICCIP 2019

作者： Chen, Wang Wang, Mingzhi Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences No. 19 North 4th Ring Road West Haidian District Beijing100191 China

ISBN: (纸本)9781450372589

Cooperative relaying is considered as an effective method to improve the secrecy performance of wireless communications. However, the existing relay selection strategies do not consider the channel correlations between the main and eavesdropping links which limits the secrecy performance. In this paper, the authors explore how to select relay under correlated fading channels in a multiple decode-and-forward (DF) relay network. To this end, the authors adopt the minimum mean squared error (MMSE) method to estimate the channel state information (CSI) of relay-eavesdropper link based on the channel correlation and then propose the single-relay selection (SRS) strategy. Simulation results show that the proposed SRS strategy outperforms other SRS strategies significantly. To further improve the secrecy performance of the DF system, we propose a novel multiple-relay selection (MRS) method for correlated channels taking advantage of estimating the relay-eavesdropper channel. Results show that our MRS strategy performs better than its SRS version and other MRS strategies. We also find that the our MRS strategy gets more performance gain than other strategies with the number of relays increases indicating the effectiveness of estimating the eavesdropping channel in secure relaying. © 2019 Association for Computing Machinery.

关键词： Channel state information

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Analysis of phase preservation and interferometric offset test in sparse SAR imaging

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Science China(information Sciences) 2024年第2期67卷 219-231页

作者： Zhongqiu XU Bingchen ZHANG Guangzuo LI Xueli ZHAN Yanfei BAO Yirong WU Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of Sciences PLA Academy of Military Sciences

Sparse synthetic aperture radar(SAR) imaging has emerged as a reliable microwave imaging scheme in the recent decade and excels in down-sampling reconstruction and full-sampling performance improvements such as noise, sidelobe, speckle, and ambiguity suppression. To utilize complex image products of sparse reconstruction for improvement in polarimetric, interferometric, and tomographic SAR imaging, it is necessary to evaluate the phase preservation of sparse SAR imaging. In this study, we first introduce the general alternating direction method of multipliers(ADMM) as the universal framework for sparse reconstruction algorithms and adopt chirp scaling algorithm(CSA)-based azimuth-range decouple operators to avoid expensive data storage and processing. Further, we theoretically analyze the phase preservation of the sparse reconstruction algorithm through a comparison with the reconstruction results of CSA. Finally,we conduct the interferometric offset test on the sparse reconstruction results of simulated and real Gaofen-3(GF-3) SAR data, demonstrating the phase-preserving ability of sparse methods.

关键词： sparse SAR imaging phase preservation interferometric offset test general ADMM azimuth-range decouple

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InSAR DEM Reconstruction Based on Backprojection Algorithm in Two Converse Flights 6

InSAR DEM Reconstruction Based on Backprojection Algorithm i...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Hu, Xiaoning Xiang, Maosheng Wang, Bingnan Fu, Xikai University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

Interferometric synthetic aperture radar (InSAR) can be used to extract digital elevation model (DEM) with high accuracy. However, the side looking geometry of synthetic aperture radar (SAR) may cause geometric distortions such as shadow and layover in the mountainous terrain, which will reduce the quality of generated DEM. Fusion of two or more different aspects of InSAR data can deal with this problem. We propose an InSAR DEM reconstruction method based on backprojection (BP) algorithm in two converse flights. This method utilizes the feature of BP algorithm that geocoding has been realized in imaging process to simplify the fusion process of multi-aspect InSAR data. In addition, an iterative DEM extraction method is introduced to improve DEM accuracy. Experimental results verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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