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Radar Main-Lobe Jamming Suppression Based on Adaptive Opposite Fireworks Algorithm
In the presence of the main lobe jamming, the performance of the modern radar system would degrade significantly. In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection wh...
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Published in: | IEEE Open Journal of Antennas and Propagation 2021, Vol.2, p.138-150 |
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creator | Luo, Weilin Jin, Hongbin Li, Hao Duan, Keqing |
description | In the presence of the main lobe jamming, the performance of the modern radar system would degrade significantly. In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection when the radar is subjected to main lobe jamming. First, a signal model for BSS applied in the anti-main lobe jamming is provided, and the number of source signals is estimated. Then, an adaptive opposite learning operator is designed to improve the optimization capability and convergence speed of the basic Fireworks Algorithm (FWA). Finally, pulse compression is performed for separated signals to achieve peak detection. The simulation result shows that the proposed algorithm can effectively extract target echo under suppression jamming and deception jamming, and the separation precision is relatively high, and its convergence speed is superior. |
doi_str_mv | 10.1109/OJAP.2020.3036878 |
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In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection when the radar is subjected to main lobe jamming. First, a signal model for BSS applied in the anti-main lobe jamming is provided, and the number of source signals is estimated. Then, an adaptive opposite learning operator is designed to improve the optimization capability and convergence speed of the basic Fireworks Algorithm (FWA). Finally, pulse compression is performed for separated signals to achieve peak detection. The simulation result shows that the proposed algorithm can effectively extract target echo under suppression jamming and deception jamming, and the separation precision is relatively high, and its convergence speed is superior.</description><subject>adaptive opposite operator</subject><subject>blind source separation</subject><subject>Brain modeling</subject><subject>Covariance matrices</subject><subject>firework algorithm</subject><subject>Fireworks algorithm</subject><subject>Interference</subject><subject>Jamming</subject><subject>Main-lobe jamming suppression</subject><subject>Radar</subject><subject>Radar antennas</subject><subject>swarm intelligence</subject><issn>2637-6431</issn><issn>2637-6431</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNkM1OAjEUhRujiQR5AONmXmCwf9N2liMRhWAwqOumM73FIkMnLWp8e0EIcXVPbs75Fh9C1wQPCcHl7XxaPQ8ppnjIMBNKqjPUo4LJXHBGzv_lSzRIaYUxpgUhhIoeWiyMNTF7Mn6Tz0IN2dS0rd8ss5fProuQkg-b7M4ksNkuVNZ0W_8F2bzrQvJbyMY-wneIHymr1ssQ_fa9vUIXzqwTDI63j97G96-jx3w2f5iMqlneUFWq3IhaFNYyzoQtaSOAlkRCXdBGEkocqQshKKXKWVMLTixwcJwqLDEnRjWW9dHkwLXBrHQXfWvijw7G679HiEtt4tY3a9BOgATsJEDBuGNc1c45xixuLKeOlDsWObCaGFKK4E48gvXesd471nvH-uh4t7k5bDwAnPolLZiQkv0CDS13pg</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Luo, Weilin</creator><creator>Jin, Hongbin</creator><creator>Li, Hao</creator><creator>Duan, Keqing</creator><general>IEEE</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4342-3225</orcidid><orcidid>https://orcid.org/0000-0003-1386-9402</orcidid></search><sort><creationdate>2021</creationdate><title>Radar Main-Lobe Jamming Suppression Based on Adaptive Opposite Fireworks Algorithm</title><author>Luo, Weilin ; Jin, Hongbin ; Li, Hao ; Duan, Keqing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2898-a6b65dd3436d92c6e2917eb52c7121f1b5662228fdab641de4ef42807041a8cd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>adaptive opposite operator</topic><topic>blind source separation</topic><topic>Brain modeling</topic><topic>Covariance matrices</topic><topic>firework algorithm</topic><topic>Fireworks algorithm</topic><topic>Interference</topic><topic>Jamming</topic><topic>Main-lobe jamming suppression</topic><topic>Radar</topic><topic>Radar antennas</topic><topic>swarm intelligence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Luo, Weilin</creatorcontrib><creatorcontrib>Jin, Hongbin</creatorcontrib><creatorcontrib>Li, Hao</creatorcontrib><creatorcontrib>Duan, Keqing</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE Open Journal of Antennas and Propagation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Luo, Weilin</au><au>Jin, Hongbin</au><au>Li, Hao</au><au>Duan, Keqing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Radar Main-Lobe Jamming Suppression Based on Adaptive Opposite Fireworks Algorithm</atitle><jtitle>IEEE Open Journal of Antennas and Propagation</jtitle><stitle>OJAP</stitle><date>2021</date><risdate>2021</risdate><volume>2</volume><spage>138</spage><epage>150</epage><pages>138-150</pages><issn>2637-6431</issn><eissn>2637-6431</eissn><coden>IJSTK4</coden><abstract>In the presence of the main lobe jamming, the performance of the modern radar system would degrade significantly. In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection when the radar is subjected to main lobe jamming. First, a signal model for BSS applied in the anti-main lobe jamming is provided, and the number of source signals is estimated. Then, an adaptive opposite learning operator is designed to improve the optimization capability and convergence speed of the basic Fireworks Algorithm (FWA). Finally, pulse compression is performed for separated signals to achieve peak detection. 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subjects | adaptive opposite operator blind source separation Brain modeling Covariance matrices firework algorithm Fireworks algorithm Interference Jamming Main-lobe jamming suppression Radar Radar antennas swarm intelligence |
title | Radar Main-Lobe Jamming Suppression Based on Adaptive Opposite Fireworks Algorithm |
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