Loading…

Sequential Experiment Design Method Based on Uniformity and Distortion of Responses

With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming in aviation military has become increasingly fierce. There are some special requirements for radar countermeasure experiments. For example, such experiments are often divided into se...

Full description

Saved in:
Bibliographic Details
Published in:Acta Mathematicae Applicatae Sinica 2023-07, Vol.39 (3), p.778-790
Main Authors: Huang, Qian-yi, Qi, Liang-wei, Zhang, Jing-ke, Tang, Yu
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c268t-271e08f178d697eab486f751ac3ba914bbba2bb741ad824d4d1769ba1ce45b793
container_end_page 790
container_issue 3
container_start_page 778
container_title Acta Mathematicae Applicatae Sinica
container_volume 39
creator Huang, Qian-yi
Qi, Liang-wei
Zhang, Jing-ke
Tang, Yu
description With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming in aviation military has become increasingly fierce. There are some special requirements for radar countermeasure experiments. For example, such experiments are often divided into several stages, and responses of the previous stages will become factors of the next stages. Moreover, the experiment design can only consider some typical level values of the factors. However, the experiment factors are mostly continuous variables. Thus when there are some jumps in the response, and the value granularity of the factor level is large, the responses fail to reflect the distortion process, which makes it difficult to explore the radar performance boundary. Therefore, it is necessary to study the sequential experiment design method with the optimization goals of response uniformization and response distortion process characterization. In this paper, a sequential experiment design strategy based on Kriging model is established. Firstly, Kriging model is used to fit the initial experimental data to obtain the response surface. In order to enhance the uniformity of response distribution, Shannon entropy is applied to the objective function as the measure of uniformity. While for the situation of response distortion, we consider replacing the existing experiment points with those whose corresponding responses have a larger gradient norm. It means that the response value near these points will change rapidly, so they are more valuable for research. Then we use the peak surface in the three-dimensional space to intuitively verify the effect of the above algorithms on response uniformization and response distortion process characterization, and use the simulated annealing algorithm to solve them. The simulation results show that our sequential experiment strategy has a good effect. Finally, we apply the strategy to the practical problem of radar countermeasure experiment, and the obtained results also perform well.
doi_str_mv 10.1007/s10255-023-1065-4
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2827022255</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2827022255</sourcerecordid><originalsourceid>FETCH-LOGICAL-c268t-271e08f178d697eab486f751ac3ba914bbba2bb741ad824d4d1769ba1ce45b793</originalsourceid><addsrcrecordid>eNp1kE9LAzEQxYMoWKsfwFvAczSTzSbZo7b1D1QEa88h2c3WLW2yJluw396UCp48DcO894b3Q-ga6C1QKu8SUFaWhLKCABUl4SdoBAIUKaqCnaIRBaFIJWRxji5SWlMKshByhBYL97VzfujMBs--exe7bd7w1KVu5fGrGz5Dgx9Mcg0OHi9914a47YY9Nr7B0y4NIQ5dvoQWv7vUB59cukRnrdkkd_U7x2j5OPuYPJP529PL5H5OaibUQJgER1ULUjWiks5YrkQrSzB1YU0F3FprmLWSg2kU4w1vQIrKGqgdL62sijG6Oeb2MeQSadDrsIs-v9RMMUkZy0iyCo6qOoaUomt1n0uauNdA9YGdPrLTmZ0-sNM8e9jRk7LWr1z8S_7f9AO-9HHI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2827022255</pqid></control><display><type>article</type><title>Sequential Experiment Design Method Based on Uniformity and Distortion of Responses</title><source>Springer Link</source><creator>Huang, Qian-yi ; Qi, Liang-wei ; Zhang, Jing-ke ; Tang, Yu</creator><creatorcontrib>Huang, Qian-yi ; Qi, Liang-wei ; Zhang, Jing-ke ; Tang, Yu</creatorcontrib><description>With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming in aviation military has become increasingly fierce. There are some special requirements for radar countermeasure experiments. For example, such experiments are often divided into several stages, and responses of the previous stages will become factors of the next stages. Moreover, the experiment design can only consider some typical level values of the factors. However, the experiment factors are mostly continuous variables. Thus when there are some jumps in the response, and the value granularity of the factor level is large, the responses fail to reflect the distortion process, which makes it difficult to explore the radar performance boundary. Therefore, it is necessary to study the sequential experiment design method with the optimization goals of response uniformization and response distortion process characterization. In this paper, a sequential experiment design strategy based on Kriging model is established. Firstly, Kriging model is used to fit the initial experimental data to obtain the response surface. In order to enhance the uniformity of response distribution, Shannon entropy is applied to the objective function as the measure of uniformity. While for the situation of response distortion, we consider replacing the existing experiment points with those whose corresponding responses have a larger gradient norm. It means that the response value near these points will change rapidly, so they are more valuable for research. Then we use the peak surface in the three-dimensional space to intuitively verify the effect of the above algorithms on response uniformization and response distortion process characterization, and use the simulated annealing algorithm to solve them. The simulation results show that our sequential experiment strategy has a good effect. Finally, we apply the strategy to the practical problem of radar countermeasure experiment, and the obtained results also perform well.</description><edition>English series</edition><identifier>ISSN: 0168-9673</identifier><identifier>EISSN: 1618-3932</identifier><identifier>DOI: 10.1007/s10255-023-1065-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Applications of Mathematics ; Continuity (mathematics) ; Design of experiments ; Design optimization ; Design techniques ; Distortion ; Electronic countermeasures ; Entropy (Information theory) ; Experiments ; Jamming ; Math Applications in Computer Science ; Mathematical and Computational Physics ; Mathematics ; Mathematics and Statistics ; Military aviation ; Radar ; Simulated annealing ; Theoretical</subject><ispartof>Acta Mathematicae Applicatae Sinica, 2023-07, Vol.39 (3), p.778-790</ispartof><rights>The Editorial Office of AMAS &amp; Springer-Verlag GmbH Germany 2023</rights><rights>The Editorial Office of AMAS &amp; Springer-Verlag GmbH Germany 2023.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c268t-271e08f178d697eab486f751ac3ba914bbba2bb741ad824d4d1769ba1ce45b793</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Huang, Qian-yi</creatorcontrib><creatorcontrib>Qi, Liang-wei</creatorcontrib><creatorcontrib>Zhang, Jing-ke</creatorcontrib><creatorcontrib>Tang, Yu</creatorcontrib><title>Sequential Experiment Design Method Based on Uniformity and Distortion of Responses</title><title>Acta Mathematicae Applicatae Sinica</title><addtitle>Acta Math. Appl. Sin. Engl. Ser</addtitle><description>With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming in aviation military has become increasingly fierce. There are some special requirements for radar countermeasure experiments. For example, such experiments are often divided into several stages, and responses of the previous stages will become factors of the next stages. Moreover, the experiment design can only consider some typical level values of the factors. However, the experiment factors are mostly continuous variables. Thus when there are some jumps in the response, and the value granularity of the factor level is large, the responses fail to reflect the distortion process, which makes it difficult to explore the radar performance boundary. Therefore, it is necessary to study the sequential experiment design method with the optimization goals of response uniformization and response distortion process characterization. In this paper, a sequential experiment design strategy based on Kriging model is established. Firstly, Kriging model is used to fit the initial experimental data to obtain the response surface. In order to enhance the uniformity of response distribution, Shannon entropy is applied to the objective function as the measure of uniformity. While for the situation of response distortion, we consider replacing the existing experiment points with those whose corresponding responses have a larger gradient norm. It means that the response value near these points will change rapidly, so they are more valuable for research. Then we use the peak surface in the three-dimensional space to intuitively verify the effect of the above algorithms on response uniformization and response distortion process characterization, and use the simulated annealing algorithm to solve them. The simulation results show that our sequential experiment strategy has a good effect. Finally, we apply the strategy to the practical problem of radar countermeasure experiment, and the obtained results also perform well.</description><subject>Algorithms</subject><subject>Applications of Mathematics</subject><subject>Continuity (mathematics)</subject><subject>Design of experiments</subject><subject>Design optimization</subject><subject>Design techniques</subject><subject>Distortion</subject><subject>Electronic countermeasures</subject><subject>Entropy (Information theory)</subject><subject>Experiments</subject><subject>Jamming</subject><subject>Math Applications in Computer Science</subject><subject>Mathematical and Computational Physics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Military aviation</subject><subject>Radar</subject><subject>Simulated annealing</subject><subject>Theoretical</subject><issn>0168-9673</issn><issn>1618-3932</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LAzEQxYMoWKsfwFvAczSTzSbZo7b1D1QEa88h2c3WLW2yJluw396UCp48DcO894b3Q-ga6C1QKu8SUFaWhLKCABUl4SdoBAIUKaqCnaIRBaFIJWRxji5SWlMKshByhBYL97VzfujMBs--exe7bd7w1KVu5fGrGz5Dgx9Mcg0OHi9914a47YY9Nr7B0y4NIQ5dvoQWv7vUB59cukRnrdkkd_U7x2j5OPuYPJP529PL5H5OaibUQJgER1ULUjWiks5YrkQrSzB1YU0F3FprmLWSg2kU4w1vQIrKGqgdL62sijG6Oeb2MeQSadDrsIs-v9RMMUkZy0iyCo6qOoaUomt1n0uauNdA9YGdPrLTmZ0-sNM8e9jRk7LWr1z8S_7f9AO-9HHI</recordid><startdate>20230701</startdate><enddate>20230701</enddate><creator>Huang, Qian-yi</creator><creator>Qi, Liang-wei</creator><creator>Zhang, Jing-ke</creator><creator>Tang, Yu</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20230701</creationdate><title>Sequential Experiment Design Method Based on Uniformity and Distortion of Responses</title><author>Huang, Qian-yi ; Qi, Liang-wei ; Zhang, Jing-ke ; Tang, Yu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c268t-271e08f178d697eab486f751ac3ba914bbba2bb741ad824d4d1769ba1ce45b793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Applications of Mathematics</topic><topic>Continuity (mathematics)</topic><topic>Design of experiments</topic><topic>Design optimization</topic><topic>Design techniques</topic><topic>Distortion</topic><topic>Electronic countermeasures</topic><topic>Entropy (Information theory)</topic><topic>Experiments</topic><topic>Jamming</topic><topic>Math Applications in Computer Science</topic><topic>Mathematical and Computational Physics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Military aviation</topic><topic>Radar</topic><topic>Simulated annealing</topic><topic>Theoretical</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huang, Qian-yi</creatorcontrib><creatorcontrib>Qi, Liang-wei</creatorcontrib><creatorcontrib>Zhang, Jing-ke</creatorcontrib><creatorcontrib>Tang, Yu</creatorcontrib><collection>CrossRef</collection><jtitle>Acta Mathematicae Applicatae Sinica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huang, Qian-yi</au><au>Qi, Liang-wei</au><au>Zhang, Jing-ke</au><au>Tang, Yu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sequential Experiment Design Method Based on Uniformity and Distortion of Responses</atitle><jtitle>Acta Mathematicae Applicatae Sinica</jtitle><stitle>Acta Math. Appl. Sin. Engl. Ser</stitle><date>2023-07-01</date><risdate>2023</risdate><volume>39</volume><issue>3</issue><spage>778</spage><epage>790</epage><pages>778-790</pages><issn>0168-9673</issn><eissn>1618-3932</eissn><abstract>With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming in aviation military has become increasingly fierce. There are some special requirements for radar countermeasure experiments. For example, such experiments are often divided into several stages, and responses of the previous stages will become factors of the next stages. Moreover, the experiment design can only consider some typical level values of the factors. However, the experiment factors are mostly continuous variables. Thus when there are some jumps in the response, and the value granularity of the factor level is large, the responses fail to reflect the distortion process, which makes it difficult to explore the radar performance boundary. Therefore, it is necessary to study the sequential experiment design method with the optimization goals of response uniformization and response distortion process characterization. In this paper, a sequential experiment design strategy based on Kriging model is established. Firstly, Kriging model is used to fit the initial experimental data to obtain the response surface. In order to enhance the uniformity of response distribution, Shannon entropy is applied to the objective function as the measure of uniformity. While for the situation of response distortion, we consider replacing the existing experiment points with those whose corresponding responses have a larger gradient norm. It means that the response value near these points will change rapidly, so they are more valuable for research. Then we use the peak surface in the three-dimensional space to intuitively verify the effect of the above algorithms on response uniformization and response distortion process characterization, and use the simulated annealing algorithm to solve them. The simulation results show that our sequential experiment strategy has a good effect. Finally, we apply the strategy to the practical problem of radar countermeasure experiment, and the obtained results also perform well.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10255-023-1065-4</doi><tpages>13</tpages><edition>English series</edition></addata></record>
fulltext fulltext
identifier ISSN: 0168-9673
ispartof Acta Mathematicae Applicatae Sinica, 2023-07, Vol.39 (3), p.778-790
issn 0168-9673
1618-3932
language eng
recordid cdi_proquest_journals_2827022255
source Springer Link
subjects Algorithms
Applications of Mathematics
Continuity (mathematics)
Design of experiments
Design optimization
Design techniques
Distortion
Electronic countermeasures
Entropy (Information theory)
Experiments
Jamming
Math Applications in Computer Science
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Military aviation
Radar
Simulated annealing
Theoretical
title Sequential Experiment Design Method Based on Uniformity and Distortion of Responses
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T20%3A41%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sequential%20Experiment%20Design%20Method%20Based%20on%20Uniformity%20and%20Distortion%20of%20Responses&rft.jtitle=Acta%20Mathematicae%20Applicatae%20Sinica&rft.au=Huang,%20Qian-yi&rft.date=2023-07-01&rft.volume=39&rft.issue=3&rft.spage=778&rft.epage=790&rft.pages=778-790&rft.issn=0168-9673&rft.eissn=1618-3932&rft_id=info:doi/10.1007/s10255-023-1065-4&rft_dat=%3Cproquest_cross%3E2827022255%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c268t-271e08f178d697eab486f751ac3ba914bbba2bb741ad824d4d1769ba1ce45b793%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2827022255&rft_id=info:pmid/&rfr_iscdi=true