Loading…
HRR target recognition using the geometry information of scattering centers
In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | 940 vol.2 |
container_issue | |
container_start_page | 936 |
container_title | |
container_volume | 2 |
creator | Zhang Xun Zhuang Zhaowen Guo Guirong |
description | In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the geometry parameters are more robust to the aspect angle variations than the range profile. The dimension of the feature vector based on the geometry parameters is much smaller than that based on the range profile that can be used as a good feature vector. The algorithm is applied to the recognition of three scaled models of aircraft using a radial basis function (RBF) neural network. |
doi_str_mv | 10.1109/NAECON.1997.622754 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_622754</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>622754</ieee_id><sourcerecordid>622754</sourcerecordid><originalsourceid>FETCH-ieee_primary_6227543</originalsourceid><addsrcrecordid>eNp9jksKwjAYhAMiKNoLdJULWJu0MWYppVIQKhT3JZS_MWITSeKit7c-1g4DM_DNYhCKSZoQkoptfSiLc50QIXiyo5SzfIYiwffp5CzjlJEFiry_pZMY44LmS3SqmgYH6RQE7KCzyuigrcFPr43C4QpYgR0guBFr01s3yA-2PfadDAHce9aBmZpfo3kv7x6iX65QfCwvRbXRANA-nB6kG9vvs-wvfAEd3z4m</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>HRR target recognition using the geometry information of scattering centers</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Zhang Xun ; Zhuang Zhaowen ; Guo Guirong</creator><creatorcontrib>Zhang Xun ; Zhuang Zhaowen ; Guo Guirong</creatorcontrib><description>In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the geometry parameters are more robust to the aspect angle variations than the range profile. The dimension of the feature vector based on the geometry parameters is much smaller than that based on the range profile that can be used as a good feature vector. The algorithm is applied to the recognition of three scaled models of aircraft using a radial basis function (RBF) neural network.</description><identifier>ISBN: 9780780337251</identifier><identifier>ISBN: 0780337255</identifier><identifier>DOI: 10.1109/NAECON.1997.622754</identifier><language>eng</language><publisher>IEEE</publisher><subject>Data mining ; Diffraction ; Frequency ; Information geometry ; Neural networks ; Radar cross section ; Radar scattering ; Scattering parameters ; Solid modeling ; Target recognition</subject><ispartof>Proceedings of the IEEE 1997 National Aerospace and Electronics Conference. NAECON 1997, 1997, Vol.2, p.936-940 vol.2</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/622754$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/622754$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang Xun</creatorcontrib><creatorcontrib>Zhuang Zhaowen</creatorcontrib><creatorcontrib>Guo Guirong</creatorcontrib><title>HRR target recognition using the geometry information of scattering centers</title><title>Proceedings of the IEEE 1997 National Aerospace and Electronics Conference. NAECON 1997</title><addtitle>NAECON</addtitle><description>In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the geometry parameters are more robust to the aspect angle variations than the range profile. The dimension of the feature vector based on the geometry parameters is much smaller than that based on the range profile that can be used as a good feature vector. The algorithm is applied to the recognition of three scaled models of aircraft using a radial basis function (RBF) neural network.</description><subject>Data mining</subject><subject>Diffraction</subject><subject>Frequency</subject><subject>Information geometry</subject><subject>Neural networks</subject><subject>Radar cross section</subject><subject>Radar scattering</subject><subject>Scattering parameters</subject><subject>Solid modeling</subject><subject>Target recognition</subject><isbn>9780780337251</isbn><isbn>0780337255</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1997</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNp9jksKwjAYhAMiKNoLdJULWJu0MWYppVIQKhT3JZS_MWITSeKit7c-1g4DM_DNYhCKSZoQkoptfSiLc50QIXiyo5SzfIYiwffp5CzjlJEFiry_pZMY44LmS3SqmgYH6RQE7KCzyuigrcFPr43C4QpYgR0guBFr01s3yA-2PfadDAHce9aBmZpfo3kv7x6iX65QfCwvRbXRANA-nB6kG9vvs-wvfAEd3z4m</recordid><startdate>1997</startdate><enddate>1997</enddate><creator>Zhang Xun</creator><creator>Zhuang Zhaowen</creator><creator>Guo Guirong</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1997</creationdate><title>HRR target recognition using the geometry information of scattering centers</title><author>Zhang Xun ; Zhuang Zhaowen ; Guo Guirong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_6227543</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1997</creationdate><topic>Data mining</topic><topic>Diffraction</topic><topic>Frequency</topic><topic>Information geometry</topic><topic>Neural networks</topic><topic>Radar cross section</topic><topic>Radar scattering</topic><topic>Scattering parameters</topic><topic>Solid modeling</topic><topic>Target recognition</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhang Xun</creatorcontrib><creatorcontrib>Zhuang Zhaowen</creatorcontrib><creatorcontrib>Guo Guirong</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhang Xun</au><au>Zhuang Zhaowen</au><au>Guo Guirong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>HRR target recognition using the geometry information of scattering centers</atitle><btitle>Proceedings of the IEEE 1997 National Aerospace and Electronics Conference. NAECON 1997</btitle><stitle>NAECON</stitle><date>1997</date><risdate>1997</risdate><volume>2</volume><spage>936</spage><epage>940 vol.2</epage><pages>936-940 vol.2</pages><isbn>9780780337251</isbn><isbn>0780337255</isbn><abstract>In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the geometry parameters are more robust to the aspect angle variations than the range profile. The dimension of the feature vector based on the geometry parameters is much smaller than that based on the range profile that can be used as a good feature vector. The algorithm is applied to the recognition of three scaled models of aircraft using a radial basis function (RBF) neural network.</abstract><pub>IEEE</pub><doi>10.1109/NAECON.1997.622754</doi></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 9780780337251 |
ispartof | Proceedings of the IEEE 1997 National Aerospace and Electronics Conference. NAECON 1997, 1997, Vol.2, p.936-940 vol.2 |
issn | |
language | eng |
recordid | cdi_ieee_primary_622754 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Data mining Diffraction Frequency Information geometry Neural networks Radar cross section Radar scattering Scattering parameters Solid modeling Target recognition |
title | HRR target recognition using the geometry information of scattering centers |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T11%3A30%3A42IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=HRR%20target%20recognition%20using%20the%20geometry%20information%20of%20scattering%20centers&rft.btitle=Proceedings%20of%20the%20IEEE%201997%20National%20Aerospace%20and%20Electronics%20Conference.%20NAECON%201997&rft.au=Zhang%20Xun&rft.date=1997&rft.volume=2&rft.spage=936&rft.epage=940%20vol.2&rft.pages=936-940%20vol.2&rft.isbn=9780780337251&rft.isbn_list=0780337255&rft_id=info:doi/10.1109/NAECON.1997.622754&rft_dat=%3Cieee_6IE%3E622754%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-ieee_primary_6227543%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=622754&rfr_iscdi=true |