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IET International Radar Conference 2015

作者： Xin Zhou Yi-zhuang Xie Chen Yang Qing Du Yi Deng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 China Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA USA

ISBN: (纸本)9781510822023

In this paper, a fast fixed-point simulation technology is proposed for a multi-channel synthetic aperture radar (SAR) imaging system. The overall computations in the SAR imaging algorithm is explicitly analysed. FFT operations account for most memory consumption in the imaging flow. Accordingly, a fixed-point FFT algorithm is adopted due to the trade-off between precision and memory occupation of the FPGA implementation. Furthermore, this paper describes an optimized word-length configuration method based on theoretical analysis of architecture of Radix-22 FFT. This methodology is verified in a SystemC development environment due to its superiority of fast and bit-accurate system-level simulation capability. Finally, the proposed SystemC based fixed-point imaging algorithm and the Matlab based floating-point imaging algorithm are both conducted to process point array target raw data. Peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR) is evaluated. Experimental results indicate that profiles in the two cases do not differ greatly, which validates that the proposed fixedpoint algorithm with less resources occupation has comparable accuracy and can meet system requirements.

关键词： SAR SystemC fixed-point arithmetic real-time imaging system-level simulation

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An effective false-alarm removal method based on OC-SVM for SAR ship detection

An effective false-alarm removal method based on OC-SVM for ...

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IET International Radar Conference 2015

作者： Xiaoting Yang Fukun Bi Ying Yu Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 China School of Electronic Information Engineering North China University of Technology Beijing 100144 China School of Information Science and Engineering Yunnan University Kunming 650091 China

ISBN: (纸本)9781510822023

Automatic ship detection from SAR remote sensing imagery is very important, with a wide array of applications in areas such as national marine safety, vessel traffic services, and naval warfare. However, SAR remote sensing images with the high inhomogeneity of sea clutter and complex scene result in a large number of false alarms. This paper focuses on the problem of false alarm removal and coverts it as a classification problem with respect to ship targets and false alarms. However, in real application: (1) Compared to false alarms the number of ships is much smaller, and (2) false alarms with diverse categories and no uniform characteristics are difficult to be distinguished from ships. To solve the problems above, we present a new method based on one-class SVM (OCSVM) combined with grid optimization that only use the data of ships to train classifier in the absence of false alarms. First, 2P-CFAR is adopted to extract ship candidates and 14 features mainly focusing on ship targets are selected. Second, grid optimization is exploited to obtain parameters for OC-SVM training, where it is a compromise between the probability of false alarm and detection rate. Experimental results of OC-SVM on a large SAR image set demonstrate that in comparison with other state-of-the-art methods like SVM, BP neural network, our approach can achieve higher detection accuracy.

关键词： OC-SVM false alarms removal parameters analysis performance comparison ship detection

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Water body extraction based on the LBV transformation analysis for China GF-1 multi-spectral images

Water body extraction based on the LBV transformation analys...

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IET International Radar Conference 2015

作者： Hang Wei Fukun Bi FuQiang Liu Wenchao Liu He Chen Ying Yu Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 China School of Electronic Information Engineering North China University of Technology Beijing 100144 China School of Information Science and Engineering Yunnan University Kunming 650091 China

ISBN: (纸本)9781510822023

For the surface water body extraction from China GF-1 satellite multi-spectral images, this paper proposes a algorithm based on the LBV transformation analysis method. The LBV transformed images can be used more effectively for the analysis of ground features than the original multispectral satellite images. So in the proposed method, the LBV transformation equations for GF-1 images are firstly discussed. Then, by analyzing gray level curves of six typical ground features in L(the general radiance level), B(the visible-infrared radiation) and V(the band radiance variation vector) images respectively, a decision criterion for extracting water body is obtain. And by this decision criterion the water bodies can be quickly and accurately extracted in the complex scenes. The experimental results show that this algorithm can effectively eliminate roads and the shadows of the buildings and cloud on the influence of the water body extraction and can exactly extract the small ponds, lakes and reservoirs. In addition, the proposed algorithm is simple, automatic and highly adaptable.

关键词： China GF-1 LBV Multi-spectral Image Water

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An optimized water detection algorithm for SAR images utilizing SOPC technologies

An optimized water detection algorithm for SAR images utiliz...

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IET International Radar Conference 2015

作者： Yan Liu Lin Li Yizhuang Xie Liang Chen Yi Deng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 China Beijing Institute of Remote Sensing ECE Department of Virginia Polytechnic Institute and State University Falls Church Virginia 22124 USA

This paper investigates a water detection algorithm of region-of-interest extraction based on the combination of sobel edge detection and contrast stretching transformation. The implementation of the proposed method is utilized for SAR (Synthetic Aperture Radar) imaging with SOPC (Systems on a Programmable Chip) embedded technology. It also puts forward an effective and realizable approach for the parallel processing data. The water detection algorithm is first optimized for SOPC system and is implemented on Xilinx Zynq-7020 chip with dual cortex-A9 ARM processors. As a result, the average consumption time of water detection algorithm reduces over 38 percent, which ensures the real-time requirement in the real-time object detection system.

关键词： ARM SAR SOPC water detection 1-stearoyl-2-oleoyl-sn-glycero-3-phosphocholine spatially oscillating photovoltaic current Radar polarimetry Detection algorithms Synthetic aperture radar Rescue Specific absorption rate SAFETY ANALYSIS REPORTS

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Region of interests extraction based on visual saliency for remote sensing image

Region of interests extraction based on visual saliency for ...

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IET International Radar Conference 2015

作者： Long Ma Bin Xu Fukun Bi He Chen Ying Yu Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing 100081 China Beijing Remote Sensing Information Institute Beijing 100192 China School of Electronic Information Engineering North China University of Technology Beijing 100144 China School of Information Science and Engineering Yunnan University Kunming 650091 China

ISBN: (纸本)9781510822023

This paper proposes a novel region of interests extraction method for remote sensing image based on visual saliency analysis as well as the multi-scale saliency fusion mechanism. Firstly, under the theory of multi-scale and multiresolution analysis, the gaussian pyramid representation is generated. Then, various spatial features are exploited to compute saliency maps under different scales. Finally the saliency map could be calculated by the corresponding level fusing as well as the across-scale combination. The comparative experiments validate the effectiveness of the proposed model.

关键词： Multi-scale analysis region of interests remote sensing image processing saliency fusion visual saliency

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A selection method of frequency combination in MF-INSAR system

A selection method of frequency combination in MF-INSAR syst...

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IET International Radar Conference 2015

作者： Yalin Qi Qi Zhang Wenfu Yang Shuangjing Yang Tiandong Liu China academy of Launch vehicle technology Beijing 100076 China Beijing Institute of Spacecraft system Engineering CAST Beijing 100094 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9781510822023

As an extension of the Interferometric Synthetic aperture radar (InSAR), the multi-frequency InSAR can realize high-accuracy elevation extraction of the steep terrain. Though the maximum likelihood estimation (MLE) is widely used in the signal processing of multi-frequency InSAR, the performance of this method can be influenced by the selection of frequency combination. At the beginning, this paper analyses the elevation estimated effectiveness of different frequency combinations from the aspect of Cramer-Rao Lower Bound (CRLB). Then, it calculates the ambiguity cycle as a further filter for the optimal frequency combination. Finally, this paper discusses the adaptability to the phase noise with the help of Monte Carlo simulation strategy. In consideration of these three aspects, a selection method of frequency combination is proposed, and further simulation results are provided in quantity. Relevant researches can be used in the design of multi-frequency InSAR system.

关键词： CRLB MLE Multi-frequency InSAR ambiguity cycle frequency combination phase noise

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Pulse repetition frequency design for geosynchronous SAR in ellipcial orbit

Pulse repetition frequency design for geosynchronous SAR in ...

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IET International Radar Conference 2015

作者： Wei Yin Wenfu Yang Zegang Ding Wei Liu Qingjun Zhang Jingjing Ren Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Lab Beijing Institute of Technology Beijing P.R. China 100081 China Academy of Launch Vehicle Technology Beijing P.R. China 100076 Beijing Institute of Spacecraft System Engineering CAST Beijing P.R. China 100094

Elliptical orbit and squint mode are widely used in the system design of geosynchronous synthetics aperture radar (GEO SAR) to improve the coverage performance. In this paper, the effects of orbit height variation and squint mode to pulse repetition frequency (PRF) design are analyzed. The orbit height variation causes the variation of nadir interference and beam illumination region, and squint mode produces large range cell migration (RCM). These can induce invalidations of the designed PRF. Based on this, the constraints of nadir interference and transmit interference are updated for GEO SAR, and the effective time for the designed PRF is derived. PRF number required for imaging in one orbital period is analyzed.

关键词： Pulse repetition frequency (PRF) effective time nadir interference orbit height variation range cell migration (RCM) effective time PULSE REPETITION RATE Prolactin-Releasing Hormone Strabismus Orbits Synthetic aperture radar Rescue Specific absorption rate SAFETY ANALYSIS REPORTS Eye Sockets Genetically engineered organisms

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Graph Definition Language for G-SQL

Graph Definition Language for G-SQL

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IEEE India Conference (INDICON)

作者： K. Nayyar H. Nayyar Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing P.R. China School of Information and Electronics Beijing Institute of Technology Beijing P.R. China

This paper is written to extend on my previous paper, Nayyar (2004). This paper categorizes G-SQL that was presented in the previous paper as a Graph Manipulation Language (GML) for generation of graphs. This paper introduces a new `Graph Definition Language for G-SQL' (GDL) and also updates GML to integrate with the new GDL. The purpose of the new Graph Definition Language (GDL) is to create a customized look and feel of graphs. It shall provide the user with the ability to define the UI components of a graph such as graph size, color of plotted values, graph title attributes etc.

关键词： Data analysis Warehousing Database languages Java Displays

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Deep Stable Learning for Cross-lingual Dependency Parsing

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ACM Transactions on Asian and Low-Resource Language information processing 1000年

作者： Haijiang Liu Chen Qiu Qiyuan Li Maofu Liu Li Wang Jinguang Gu Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Institute of Scientific and Technical Information of China Beijing China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing China

The Cross-lingual Dependency Parsing (XDP) task poses a significant challenge due to the differences in dependency structures between training and testing languages, known as the out-of-distribution (OOD) problem. Our research delved into this issue in the XDP dataset by selecting 43 languages from 22 language families. We found that the primary factor of the OOD problem is the unbalanced length distribution among languages. To address the impact of the OOD problem, we propose deep stable learning for Cross-lingual Dependency Parsing (SL-XDP), which utilizes deep stable learning with a feature fusion module. In detail, we implemented five feature fusion operations for generating comprehensive representations with dependency relations and the deep stable learning algorithm to decorrelate dependency structures with sequence length. Our experiments on Universal Dependencies have demonstrated that SL-XDP can lessen the impact of the OOD problem and improve the model generalization among 21 languages, with a maximum improvement of 18%.

关键词： Cross-lingual Dependency Parsing Deep Stable Learning Out-of-Distribution Problem

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