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Study on moving target detection to passive radar based on FM broadcast transmitter

Journal of Systems Engineering and Electronics 2007年第3期18卷 462-468页

作者： Zhu Jiabing Tao Liang Hong yi Education Ministry Key Lab of Intelligent Computing and Signal Processing Anhui Univ. Hefei 230039 P. R. China Inst. of Signal Processing East China Research Inst. of Electronic Engineering Hefei 230031 P. R. China

Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field. First of all, direct-path interference （DPI） suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation（FM） broadcast transmitter is analyzed in this article; Secondly, a space-time-frequency domain synthetic solution to this problem is introduced： Adaptive nulling array processing is considered in the space domain, DPI cancellation based on adaptive fractional delay interpolation （AFDI） technique is used in planned time domain, and long-time coherent integration is utilized in the frequency domain; Finaily, an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator, Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

关键词： passive radar direct path interference adaptive beamforming adaptive fractional delay interpolation,long-time coherent integration.

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Adaptive beamforming passive radar based on FM radio transmitter

Adaptive beamforming passive radar based on FM radio transmi...

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RADAR 2007 - The Institution of Engineering and Technology International Conference on Radar Systems

作者： Zhu, Jiabing Hong, Yi Tao, Liang East China Research Institute of Electronic Engineering China Education Ministry Key Lab. of Intelligent Computing and Signal Processing Anhui University China

ISBN: (纸本)9780863418488

One of the major problems in continuous wave bistatic radar based on FM radio transmitter is direct path interference(DPI). This is the signal received directly from a transmitter by the receive channel antenna. The DPI and the reflected signal are coherent, have similar structure except for the mutual delay and Doppler frequency shift. To detect targets it is necessary to suppress or remove the DPI signal. First of all, the DPI signal based on FM radio transmitter is analyzed. Secondly, the approach based on adaptive nulling array processing is introduced in detail to solve this problem. Finally, associated signal processing schemes of the FM-radio-based passive radar is discussed. Simulation results by applying real collected data show the proposed method is effective.

关键词： Beamforming

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A novel adaptive filtering algorithm for SAR speckle reduction

A novel adaptive filtering algorithm for SAR speckle reducti...

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2007 1st Asian and Pacific Conference on Synthetic Aperture Radar, APSAR 2007

作者： Zhu, Jiabing Chen, Renyuan Hong, Yi East China Research Institute of Electronic Engineering China Education Ministry Key Lab. of Intelligent Computing and Signal Processing Anhui University China

ISBN: (纸本)1424411882

The novel adaptive filtering algorithm based on the analysis of the detail images obtained from the wavelet decomposition of the original noisy image is proposed in the paper. The base idea is to compute the wavelet decomposition of the noisy image to reduce the amplitude of insignificant detail coefficients in the wavelet subspaces by selecting an adaptive filter window of size, the adaptive windowing algorithm was introduced where the window size is automatically adjusted depending on the samples statistics in the boundary of this window such as mean z and standard deviation σz, and then utilizing modified 2nd order Lee filtering. One of the advantages of this approach over the traditional speckle filtering method is the fact that textures are preserved while speckle is reduced. Experimental simulations by real SAR images show it are effective. © 2007 IEEE.

关键词： Wavelet decomposition

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Multirracial and R/S analysis of protein structure

Multirracial and R/S analysis of protein structure

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SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing

作者： Zheng, Tingting Cheng, Jiaxing Mao, Junjun Song, Jie Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Mathematics and Computational Science Anhui University Hefei 230039 China

ISBN: (纸本)0769529097

The spacing distance of amino acids is used to study the relationship between the primary structure and structural classification of large proteins. Rescaled-range (R/S) analysis was adopted to examine long-range correlation property of proteins. And multifractal property is then discussed by the spacing distance of amino acids. A classification of proteins by assigning to each sequence a point in two-dimensional space (Δα, H) is given to construct a phylogenetic tree. This result is shown to be reasonably satisfactory to α + β class. © 2007 IEEE.

关键词： Proteins

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Algebra and calculus of the resource space model

Algebra and calculus of the resource space model

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3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007

作者： Xing, Yunpeng Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)0769530079

Resource Space Model (RSM) is a semantic model to manage resources in the future interconnection environment. The query capability is an important aspect of RSM as a semantic resource management model. This paper reports the research result on the query capability of RSM from two perspectives: resource space algebra and resource space calculus. The equivalence of the resource space algebra and the resource space calculus has been discussed. © 2007 IEEE.

关键词： Algebra

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ART and fuzzy K-means clustering based algorithm for packet classification

ART and fuzzy K-means clustering based algorithm for packet ...

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2007 IEEE International Conference on Control and Automation, ICCA

作者： Bo, Qu Shuiping, Gou Licheng, Jiao Institute of Intelligent Information Processing National Key Lab. for Radar Signal Processing Xidian University PO Box 224 710071 Xi'an China

ISBN: (纸本)1424408180

Existing algorithms for packet classification always deal with a ready rule set. However, now a day, large classifiers' rule sets are huger and huger (say, 100 000 rules). Generated these rules by hand is so hard, and causes lots of redundant rules. In this paper, we present a two stage cluster based algorithm for packet classification, which aims to generate niter rules automatically for permitted packets. Based on the scheme, a three-field packet classification for permitted packets (sev-address, sev-port and protocol) is proposed. Experimental results show that the scheme can significantly reduce needed filter rules for permitted packets and the range of IP address lookup. © 2007 IEEE.

关键词： Clustering algorithms

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A NEW HIGH ACCURACY RETRIEVAL MODEL BASED ON QUOTIENT SPACE

A NEW HIGH ACCURACY RETRIEVAL MODEL BASED ON QUOTIENT SPACE

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2007中国宁波国际计算机科学与技术学术大会

作者： Yang Weimin Li Longshu Key Lab.of Intelligent Computing & Signal Processing Anhui University Ministry of Education Department of Computer Science and Engineering Anhui University

ISBN: (纸本)9780972147903

The effectiveness of ad-hoc retrieval systems appears to have reached a *** the research community is investigating an assortment of variables that will help them develop increasingly accurate retrieval *** paper presents a new method of high accuracy retrieval of document,which is based on quotient *** describes the problem space from different granularity:sentence,paragraph and document,and studies the relations among different granularities.

关键词： Quotient space High accuracy retrieval Granularity analysis Rough set

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New algorithm of target classification in polarimetric SAR

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Journal of Systems Engineering and Electronics 2008年第2期000卷

作者： Wang Yang Lu Jiaguo Wu Xianliang Wang Yang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Lu Jiaguo (The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Wu Xianliang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China)

The different approaches used for target decomposition (TD) theory in radar polarimetry are reviewed and three main types of theorems are introduced: those based on Mueller matrix, those using an eigenvector analysis of the coherency matrix, and those employing coherent decomposition of the scattering matrix. Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated success in many fields. A new algorithm of target classification, by combining target decomposition and the support vector machine, is *** conduct the experiment, the polarimetric synthetic aperture radar (SAR) data are used. Experimental results show that it is feasible and efficient to target classification by applying target decomposition to extract scattering mechanisms, and the effects of kernel function and its parameters on the classification efficiency are significant.

关键词： polarimetric synthetic aperture radar target decomposition support vector machine target classifi-cation kernel function.

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Urban road network extraction from SAR image

Urban road network extraction from SAR image

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MIPPR 2007: Remote Sensing and GIS Data processing and Applications;and Innovative Multispectral Technology and Applications

作者： Cheng, Pengxue Hu, Maolin Lab. of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469540

In this paper, a technique for the extraction of roads in a high resolution synthetic aperture radar (SAR) image is presented. And a three-step method is developed for the extraction of road network from space borne SAR image: the process of the feature points, road candidate detection and connection. Roads in a high resolution SAR image can be modeled as a homogeneous dark area bounded by two parallel boundaries. Dark areas, which represent the candidate positions for roads, are extracted from the image by a Gaussian probability iteration segmentation. Possible road candidates are further processed using the morphological operators. And the roads are accurately detected by Hough Transform, and the extraction of lines is achieved by searching the peak values in Hough Space. In this process, to detect roads more accurately, post-processing, including noisy dark regions removal and false roads removal is performed. At last, Road candidate connection is carried out hierarchically according to road established models. Finally, the main road network is established from the SAR image successfully. As an example, using the ERS-2SAR image data, automatic detection of main road network in Shanghai Pudong area is presented.

关键词： Feature extraction

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Point matching of two images under large different resolution

Point matching of two images under large different resolutio...

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MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition

作者： Ruan, Lei Hu, Maolin Lab. of Intelligent Computing and Signal Processing AnHui University Hefei AnHui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469502

Image matching is the first step in almost any 3D computer vision task, and hence has received extensive attention. In this paper, the problem is addressed from a novel perspective, which is different from the classic stereo matching paradigm. Two images with different resolutions, that is high resolution versus low resolution are matched. Since the high resolution image only corresponds to a small region of the low resolution one, the matching task therefore consists in finding a small region in the low resolution image that can be assigned to the whole high resolution image under the plane similarity transformation, which can be defined by the local area correlation coefficient to match the interest points and rectified by similarity transform. Experiment shows that our matching algorithm can be used for scale changing up to a factor of 6. And it is successful to deal with the point matching between two images under large scale.

关键词： Image matching

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