Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect
For a conventional narrowband radar system, its insufficient bandwidth usually leads to the lack of detectable information of the target, and it is difficult for the radar to classify the target types, such as rotor helicopter, propeller aircraft, and jet aircraft. To address the classification prob...
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Veröffentlicht in: | Mathematical problems in engineering 2022-01, Vol.2022, p.1-11 |
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description | For a conventional narrowband radar system, its insufficient bandwidth usually leads to the lack of detectable information of the target, and it is difficult for the radar to classify the target types, such as rotor helicopter, propeller aircraft, and jet aircraft. To address the classification problem of three different types of aircraft target, a joint multifeature classification method based on the micro-Doppler effect in the echo caused by the target micromotion is proposed in this paper. Through the characteristics analysis of the target simulation echoes obtained from the target scattering point model, four features with obvious distinguishability are extracted from the time domain and frequency domain, respectively, that is, flicker interval, fractal dimension, modulation bandwidth, and second central moment. Then, a support vector machine model will be applied to the classification of the three different types of aircraft. Compared with the conventional method, the proposed method has better classification performance and can significantly improve the classification probability of aircraft target. The simulations are carried out to validate the effectiveness of the proposed method. |
doi_str_mv | 10.1155/2022/3154854 |
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To address the classification problem of three different types of aircraft target, a joint multifeature classification method based on the micro-Doppler effect in the echo caused by the target micromotion is proposed in this paper. Through the characteristics analysis of the target simulation echoes obtained from the target scattering point model, four features with obvious distinguishability are extracted from the time domain and frequency domain, respectively, that is, flicker interval, fractal dimension, modulation bandwidth, and second central moment. Then, a support vector machine model will be applied to the classification of the three different types of aircraft. Compared with the conventional method, the proposed method has better classification performance and can significantly improve the classification probability of aircraft target. The simulations are carried out to validate the effectiveness of the proposed method.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2022/3154854</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Aircraft ; Algorithms ; Bandwidths ; Classification ; Doppler effect ; Feature extraction ; Flicker ; Fractal geometry ; Fractals ; Helicopters ; Jet aircraft ; Mathematical problems ; Narrowband ; Noise ; Radar equipment ; Simulation ; Support vector machines</subject><ispartof>Mathematical problems in engineering, 2022-01, Vol.2022, p.1-11</ispartof><rights>Copyright © 2022 Saiqiang Xia et al.</rights><rights>Copyright © 2022 Saiqiang Xia et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-91ee26b04997c869e52b98b49e57f6c581d6102631360f88cdb5efbc9f996fdd3</citedby><cites>FETCH-LOGICAL-c337t-91ee26b04997c869e52b98b49e57f6c581d6102631360f88cdb5efbc9f996fdd3</cites><orcidid>0000-0003-3416-8197</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,782,786,27931,27932</link.rule.ids></links><search><contributor>Wen, Fangqing</contributor><contributor>Fangqing Wen</contributor><creatorcontrib>Xia, Saiqiang</creatorcontrib><creatorcontrib>Zhang, Chaowei</creatorcontrib><creatorcontrib>Cai, Wanyong</creatorcontrib><creatorcontrib>Yang, Jun</creatorcontrib><creatorcontrib>Hua, Liangfa</creatorcontrib><creatorcontrib>Wei, Xu</creatorcontrib><creatorcontrib>Jiang, Haiman</creatorcontrib><title>Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect</title><title>Mathematical problems in engineering</title><description>For a conventional narrowband radar system, its insufficient bandwidth usually leads to the lack of detectable information of the target, and it is difficult for the radar to classify the target types, such as rotor helicopter, propeller aircraft, and jet aircraft. 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The simulations are carried out to validate the effectiveness of the proposed method.</description><subject>Aircraft</subject><subject>Algorithms</subject><subject>Bandwidths</subject><subject>Classification</subject><subject>Doppler effect</subject><subject>Feature extraction</subject><subject>Flicker</subject><subject>Fractal geometry</subject><subject>Fractals</subject><subject>Helicopters</subject><subject>Jet aircraft</subject><subject>Mathematical problems</subject><subject>Narrowband</subject><subject>Noise</subject><subject>Radar equipment</subject><subject>Simulation</subject><subject>Support vector machines</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEtPwzAQhC0EEqVw4wdY4ggBP2LHPpZQHlIBCRWJW-T4QV2FONgpFf-eRO2Z045W345mB4BzjK4xZuyGIEJuKGa5YPkBmGDGacZwXhwOGpE8w4R-HIOTlNYIEcywmAA781FH5Xq4VPHT9rBsVEreea16H1r4bPtVMNCFCMvQ_th23KoGvqgYw7ZWrYFvyqgIb1WyBo4XXseQ3YWua2yEc-es7k_BkVNNsmf7OQXv9_Nl-ZgtXh-eytki05QWfSaxtYTXKJey0IJLy0gtRZ0PonBcM4ENHx7hFFOOnBDa1My6WksnJXfG0Cm42Pl2MXxvbOqrddjEIW-qCMdSDsZYDNTVjhqCphStq7rov1T8rTCqxiKrschqX-SAX-7wlW-N2vr_6T9AAXJy</recordid><startdate>20220104</startdate><enddate>20220104</enddate><creator>Xia, Saiqiang</creator><creator>Zhang, Chaowei</creator><creator>Cai, Wanyong</creator><creator>Yang, Jun</creator><creator>Hua, Liangfa</creator><creator>Wei, Xu</creator><creator>Jiang, Haiman</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0003-3416-8197</orcidid></search><sort><creationdate>20220104</creationdate><title>Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect</title><author>Xia, Saiqiang ; 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To address the classification problem of three different types of aircraft target, a joint multifeature classification method based on the micro-Doppler effect in the echo caused by the target micromotion is proposed in this paper. Through the characteristics analysis of the target simulation echoes obtained from the target scattering point model, four features with obvious distinguishability are extracted from the time domain and frequency domain, respectively, that is, flicker interval, fractal dimension, modulation bandwidth, and second central moment. Then, a support vector machine model will be applied to the classification of the three different types of aircraft. Compared with the conventional method, the proposed method has better classification performance and can significantly improve the classification probability of aircraft target. 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subjects | Aircraft Algorithms Bandwidths Classification Doppler effect Feature extraction Flicker Fractal geometry Fractals Helicopters Jet aircraft Mathematical problems Narrowband Noise Radar equipment Simulation Support vector machines |
title | Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect |
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