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2021 CIE International Conference on Radar, Radar 2021

作者： Zhang, Zhiguo Shen, Wenjie Yue, Xiaoyang Lin, Yun Hong, Wen Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geospatial Information Processing and Application System Beijing China School of Information Science and Technology North China University of Technology Radar Monitoring Technology Laboratory Beijing China

ISBN: (纸本)9781665498142

With the goal of detecting moving targets, this paper proposes a new single channel Circular Synthetic Aperture Radar (CSAR) moving targets detection algorithm based on Low-rank Sparse Decomposition (LRSD). This algorithm utilizes the correlation among overlap subaperture logarithmic amplitude image sequences, the static clutter is regarded as low-rank component and the moving targets is considered as sparse component. Then, the background image sequence (without moving target) and the foreground image sequence (moving targets) can be extracted by the LRSD. Considering the unknown foreground image distribution, this paper proposes a Local Dynamic Threshold based on Otsu (LDTO) method independent of image distribution to detect moving targets. Finally, the experiment on the X-band airborne Gotcha Data demonstrates the effectiveness of the proposed algorithm. © 2021 IEEE.

关键词： circular synthetic aperture radar local dynamic threshold based on Otsu low rank sparse decomposition moving target detection

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High-Resolution Urban Flows Forecasting With Coarse-Grained Spatiotemporal Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 315-327页

作者： Xu, Zhenyi Kang, Yu Cao, Yang Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Department of Automation University of Science and Technology of China Hefei230026 China Chinese Academy of Sciences Key Laboratory of Technology in GeoSpatial Information Processing and Application System Beijing100192 China

Urban flow monitoring and forecasting systems play important roles in smart city management. However, due to the long-lasting and enormous deployment cost of ubiquitous traffic monitoring devices (e.g., loop detectors, traffic video detection), it is very difficult to predict flow in high-resolution (HR) with limited monitoring devices. The existing spatiotemporal network based methods usually predict the urban flow in the same spatial scale without considering the spatial correlations between coarse-grained and fine-grained urban flows. To tackle these issues, we propose a HR spatiotemporal transformer network (HRSTT) to predict fine-grained urban flow. Specifically, residual convolution units are employed to constructs the high-level features of three-view temporal (e.g., closeness, period, and trend) flow data. Then, a transformer block is designed to jointly learn the spatiotemporal dynamic features of each temporal flow with self-attention mechanism. For the external factors (e.g., holidays, weather conditions) are extracted by embedding dense networks, which are fused with high level coarse-grained flow feature maps with gated-fusion scheme. Finally, the coarse-grained fusion feature maps are transferred to the distributional upsampling module, generating the fined-grained flow map of target predicted time. Furthermore, the proposed model is evaluated with several baselines on real-world TaxiBJ datasets, demonstrating the state-of-the-art performance of our approach on the fine-grained urban flow forecasting problem. © 2020 IEEE.

关键词： Deep neural networks

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An azimuth resample method for bistatic SAR motion compensation 8

An azimuth resample method for bistatic SAR motion compensat...

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8th European Conference on Synthetic Aperture Radar, EUSAR 2010

作者： Qiu, Xiaolan Han, Bin Meng, Dadi Hu, Donghui Ding, Chibiao Key Laboratory of Technology in Geo-spatial Information Processing and Application System IECAS China China

ISBN: (纸本)9783800732722

Motion compensation is an indispensable step for generating a high quality image in the airbore SAR system. In bistatic SAR, there are two separate platforms and their velocities cannot keep same all the time. So the echoes are transmitted and received at uniform positions, respectively, which deteriorate the imaging results. In this paper, an azimuth resample method for compensating the velocity variance along the flying direction is promoted, and the difference of azimuth resample between mono static SAR and bistatic SAR is pointed out. Finally, simulated results show the validity of the method. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Motion compensation

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AZIMUTH AMBIGUITIES SUPPRESSION FOR MULTICHANNEL SAR IMAGING BASED ON L2,q REGULARIZATION: INITIAL RESULTS OF NON-SPARSE SCENARIO

AZIMUTH AMBIGUITIES SUPPRESSION FOR MULTICHANNEL SAR IMAGING...

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2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

作者： Liu, Mingqian Li, Jie Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences China Key Laboratory of Technology in Geospatial Information Processing and Application System China University of Chinese Academy of Sciences Beijing100190 China

The azimuth multichannel SAR is competent to achieve high-resolution and wide-swath (HRWS) imaging. For some spaceborne multichannel SAR systems, the pulse repetition frequency (PRF) of each channel at some beam positions is less than that of uniform sampling, hence leading to the azimuth ambiguities in the recovered images. In this paper, a novel azimuth ambiguity suppression method for multichannel SAR imaging based on L2,q regularization (0 2,q regularization from single-channel SAR system to multichannel SAR system and develop the proposed method. Finally, we demonstrate the effectiveness of the proposed method for non-sparse scenarios. Simulations and Gaofen-3 real data experiments are carried out to verify the validity of proposed method. ©2021 IEEE

关键词： Synthetic aperture radar

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Directional Analysis of Urban Expansion Based on Sub-pixel and Regional Scale: A Case Study of Main Districts in Guangzhou, China

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Chinese Geographical Science 2019年第4期29卷 652-666页

作者： ZHAO Yi ZHONG Kaiwen XU Jianhui SUN Caige WANG Yunpeng Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou 510640 China Guangzhou Institute of Geography Guangzhou 510070 China University of Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangzhou 510070 China Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou 510070 China

Multi-scale data have had a wide-ranging level of performance in the area of urban change monitoring. Herein we investigate the correlation between the impervious surface fraction(ISF) and the Defense Meteorological Satellite Program/Operational Linescan system(DMSP/OLS) nighttime stable light(NTL) data with respect to the urban expansion in the main districts of Guangzhou. Landsat 5 Thematic Mapper and Landsat 8 Operational Land Image(OLI) data from 1988 to 2015 were used to extract the ISF using the linear spectral mixture analysis model and normal difference build-up index at the sub-pixel scale. DMSP/OLS NTL data from 1992 to 2013 were calibrated to illustrate the urban nighttime light conditions at the regional scale. Urban expansion directions were identified by statistics and kernel density analysis for the ISF study area at the sub-pixel scale. In addition, the correlation between the ISF and DMSP/OLS NTL data were illustrated by linear regression analysis. Furthermore, Profile Graph in ArcGIS was employed to illustrate the urban expansion from the differences in correlation in different directions. The conclusions are as follows: 1) The impervious surface(IS)in the study area has expanded to the northeast and the east, starting with the old urban zones, and the high-density IS area has increased by321.14 km^2. 2) The linear regression analysis reveals a positive correlation between the ISF and the DMSP/OLS NTL data. The multi-scale data changes are consistent with the actual urban planning of Guangzhou. 3) The DMSP/OLS NTL data overestimate the urban extent because of its saturation and blooming effects, causing its correlation with ISF to decrease. The pattern of urban expansion influences the saturation and blooming effects of the DMSP/OLS NTL data.

关键词： impervious surface fraction linear spectral mixture analysis nighttime light kernel density profile graph

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Comprehensive Evaluation of Eight Methods for Generating 1-km Monthly Composite Hourly Land Surface Temperature in 2011 Under Clear Sky

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Journal of Geophysical Research: Atmospheres 2025年第9期130卷

作者： Wang, Dazhong Zhan, Wenfeng Wang, Shasha Göttsche, Frank-M. Dong, Pan Liu, Zihan Wang, Chenguang Jiang, Sida Ji, Yingying Jiang, Lu Xu, Yuyue Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Nanjing China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing China Institute of Meteorology and Climate Research (IMK)-Atmospheric Trace Gases and Remote Sensing (ASF) Karlsruhe Institute of Technology (KIT) Eggenstein-Leopoldshafen Germany School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China School of Geography and Ocean Science Nanjing University Nanjing China

The monthly composite hourly land surface temperature (LST) under clear sky at 1-km resolution (denoted as Tmh) plays a critical role in various fields such as urban and agricultural managements. Existing methods for ... 详细信息

The monthly composite hourly land surface temperature (LST) under clear sky at 1-km resolution (denoted as T_mh) plays a critical role in various fields such as urban and agricultural managements. Existing methods for estimating T_mh fall into four categories: single-source methods employing spatial downscaling or diurnal temperature cycle (DTC) models and multisource methods employing spatiotemporal fusion or DTC models. Despite this methodological diversity, a comprehensive evaluation of their respective strengths and weaknesses remains lacking, posing a challenge for advancing T_mh estimation. To address this critical gap, we performed a wide-ranging comparison of eight representative approaches for estimating T_mh, comprising two from each category. Their accuracies were assessed over various timescales and conditions, utilizing in situ LST observations from 77 ground-based stations worldwide. Our evaluations show that DTC-based multisource approaches exhibit the highest overall accuracy, outperforming both spatial downscaling-based single-source approaches and spatiotemporal fusion-based multisource approaches. Conversely, the performance of DTC-based single-source methods exhibits substantial disparity. This observed pattern of overall accuracy remains valid across months, seasons, land cover types, and climatic zones. Furthermore, our assessments indicate that accuracies are time-of-day dependent. Spatial downscaling and spatiotemporal fusion approaches are most effective around 2 hr after sunrise, while DTC-based approaches show better performance around midday. Our findings suggest that this work holds potential significance for generating fine-resolution hourly LST data with enhanced accuracy. © 2025. American Geophysical Union. All Rights Reserved.

关键词： diurnal temperature cycle model estimation land surface temperature spatial downscaling spatiotemporal fusion

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AUTOMATIC MODULATION RECOGNITION BASED ON SST AND DEEP LEARNING MODEL

AUTOMATIC MODULATION RECOGNITION BASED ON SST AND DEEP LEARN...

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IET International Radar Conference 2023, IRC 2023

作者： Xiang, Jianbing Lv, Xiaolei Han, Bing Zhong, Lihua Fang, Linlin Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781839539954

As the electromagnetic environment in battlefields becomes increasingly complex, automatic modulation recognition for noncooperation radiation source signal is becoming vital and challenging. Most previous works were more likely to cause low recognition accuracy with high computational complexity in low signal-to-noise ratio (SNR), and only considered spatial or temporal attributes of signal which ignores the feature interaction. In this paper, we firstly apply synchrosqueezing transform (SST) to extract high resolution and robustness time-frequency feature as one of signal representation, and convert the signal into the in-phase/quadrature (I/Q) components as another signal representation, which enhances the diversity of signal representation. Then, we propose a deep learning model to achieve automatic recognition, which has two streams and each stream consists of the convolutional neural network (CNN), bistatic long short-term memory (BiLSTM) and temporal attention (TAT). It efficiently explores the feature from each signal representation and enhances the key features by the introduction of TAT, furthermore, it implements feature interaction to form a new feature matrix. Finally, experiments and analysis were conducted using the RadioML2016.10a dataset. The experimental results showed that compared to other algorithms, this method has higher robustness and perform better recognition accuracy under low SNR. © The Institution of Engineering & technology 2023.

关键词： Convolutional neural networks

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A Hybrid MAC Protocol for Data Transmission in Smart Grid 33

A Hybrid MAC Protocol for Data Transmission in Smart Grid

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第三十三届中国控制会议

作者： WANG Fang KANG Yu TAN Xiaobin YU Kai Department of Automation and CAS Key Laboratory of Technology in Geo-spatial Information processing and application SystemUniversity of Science and Technology of China Shanghai Institute of Micro-system and Information Technology Chinese Academy of Sciences

ISBN: (纸本)9781479947249

In the information transmission process of Smart Grid, the collection and transmission of power consumption data of the massive users are very important. The data can be classified into the periodic and the alarm data. Different types of data are different in terms of their priority, reliability and real-time, and the alarm data has more rigid requirements of priority, real-time and reliability. Based on the characteristics of the data transmitted by smart grid and the QoS requirement, a new hybrid MAC protocol, HTC-MAC(Hybrid TDMA/CSMA MAC) protocol is proposed. Based on TDMA /CSMA and their combination, this protocol proposes an alarm priority function(APF) and a node clustering method to allocates the resources dynamically, in order to reduce the transmission delay and data loss. Simulation results show that the protocol has a good performance in reducing packet loss rate and network communication delay.

关键词： Smart grid MAC protocol CDMA TDMA

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ERROR ESTIMATION and UNAMBIGUOUS RECONSTRUCTION for Chinese FIRST DUAL-CHANNEL SPACEBORNE SAR IMAGING

ERROR ESTIMATION and UNAMBIGUOUS RECONSTRUCTION for Chinese ...

引用

ISPRS geospatial Week 2017

作者： Jin, T. Qiu, X. Hu, D. Ding, C. University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Technology in Geospatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems. © Authors 2017.

关键词： digital beamforming (DBF) high-resolution and wide-swath (HRWS) orthogonal subspace method (OSM) Synthetic aperture radar (SAR) unambiguous reconstruction

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Geometry-aware image completion via multiple examples 22

Geometry-aware image completion via multiple examples

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22nd Pacific Conference on Computer Graphics and applications, PG 2014

作者： Wang, Guihang Chen, Xuejin Hu, Siyu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China China

ISBN: (纸本)9783905674736

When browsing through photographs taken during a trip, it can be a distressing discovery to find many other bystanders captured within the frame. A visually compelling snapshot preserves the desired subject in the foreground, and eliminates irrelevant persons or objects. In this paper, we present a new image completion algorithm that retains the geometric consistency of the scene using Internet photo collections. Our key insight allows us to successfully fill the missing regions with content derived from related images with distinct features, or from visible parts of the input image with repetitive textures. The final composition for the missing regions is guided by a confidence map combining the two types of example images. We validate our algorithm on a variety of scenes which are challenging for state-of-the-art completion techniques. The completion results successfully preserve the geometry consistency for complex structures in a wide range of depths. © The Eurographics Association 2014.

关键词： Geometry

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