Range Profile Target Recognition Using Sparse Representation Based on Feature Space
A novel method is presented to improve the recognition rate of warhead in this paper. Firstly, a tool for electromagnetic calculation, like CST Microwave Studio, is used to simulate the frequency response of the electromagnetic scattering. Secondly, the echo and further the range profile are acquire...
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Published in | Shanghai jiao tong da xue xue bao Vol. 22; no. 5; pp. 615 - 623 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Shanghai
Shanghai Jiaotong University Press
01.10.2017
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1007-1172 1995-8188 |
DOI | 10.1007/s12204-017-1879-4 |
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Abstract | A novel method is presented to improve the recognition rate of warhead in this paper. Firstly, a tool for electromagnetic calculation, like CST Microwave Studio, is used to simulate the frequency response of the electromagnetic scattering. Secondly, the echo and further the range profile are acquired from the frequency response by further processing. Thirdly, a set of discriminative features is extracted from the range profiles of the target. Fourthly, these features are used to construct a dictionary for the sparse representation classifier. Finally,the sample of the target can be classified by solving the sparsest coefficients. Since the reconstruction result is determined by a linear combination of the training samples, this method has a good robustness for the variable features. By formulating the problem within a feature-based sparse representation framework, the presented method combines the discriminative features of each sample during the sparse recovery process rather than in a postprocessing manner. Moreover, based on the feature representation space rather than a single feature or image pixel, the constructed dictionary exhibits both strong expressive and discriminative powers that can enhance the classification performance of the test sample. A series of test results based on the simulated data demonstrates the effectiveness of our method. |
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AbstractList | A novel method is presented to improve the recognition rate of warhead in this paper. Firstly, a tool for electromagnetic calculation, like CST Microwave Studio, is used to simulate the frequency response of the electromagnetic scattering. Secondly, the echo and further the range profile are acquired from the frequency response by further processing. Thirdly, a set of discriminative features is extracted from the range profiles of the target. Fourthly, these features are used to construct a dictionary for the sparse representation classifier. Finally, the sample of the target can be classified by solving the sparsest coefficients. Since the reconstruction result is determined by a linear combination of the training samples, this method has a good robustness for the variable features. By formulating the problem within a feature-based sparse representation framework, the presented method combines the discriminative features of each sample during the sparse recovery process rather than in a postprocessing manner. Moreover, based on the feature representation space rather than a single feature or image pixel, the constructed dictionary exhibits both strong expressive and discriminative powers that can enhance the classification performance of the test sample. A series of test results based on the simulated data demonstrates the effectiveness of our method. |
Author | 吕文涛 王军锋 郁文贤 包晓敏 |
AuthorAffiliation | School of Information Science and Technology, Zhejiang Sci-Tech University;School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University |
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Cites_doi | 10.1109/TAES.2010.5595608 10.1109/LGRS.2013.2262073 10.1109/TNN.2005.849821 10.1109/78.969508 10.2529/PIERS090902092851 10.1109/TAES.2010.5417158 10.1109/TIP.2007.901243 10.1007/s12204-017-1809-5 10.1109/JSTARS.2015.2436694 10.1109/TSMCA.2003.808253 10.1109/MSP.2007.4286571 10.1109/TAES.2002.1008975 10.1109/CISP.2014.7003946 10.1049/iet-rsn.2014.0113 10.1109/TSP.2005.849161 10.1109/TAES.2010.5595607 10.1109/JSTSP.2007.910971 10.1109/JSTSP.2007.910281 10.1049/iet-rsn.2014.0325 10.1109/TPAMI.2008.79 10.1137/S1064827596304010 10.1109/TAES.2003.1261122 10.1109/TSP.2006.881199 10.1109/TAES.2007.4383594 |
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Keywords | warhead recognition A range profile echo simulation TP 753 feature dictionary sparse representation |
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Title | Range Profile Target Recognition Using Sparse Representation Based on Feature Space |
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