Loading…

Interception time and uncertainty optimization for tangent-impulse orbit interception problem

The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we st...

Full description

Saved in:
Bibliographic Details
Published in:Defence technology 2022-03, Vol.18 (3), p.418-440
Main Authors: Hong, Yang, Xin-hong, Li, Wen-zhe, Ding
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3
cites cdi_FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3
container_end_page 440
container_issue 3
container_start_page 418
container_title Defence technology
container_volume 18
creator Hong, Yang
Xin-hong, Li
Wen-zhe, Ding
description The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we study the minimum time interception problem and the minimum terminal interception error problem under tangent impulse conditions and give an orbit optimization method that considers the interception time and the interception uncertainty. First, we express the interceptor's transfer time equation as a form of flight path angle, establish a global optimization model for solving the minimum time tangent impulse interception and give a hybrid optimization algorithm based on Augmented Lagrange Genetic Algorithm - Sequential Quadratic Programming (ALGA-SQP). Secondly, we use the universal time equation and Bootstrap resampling technology to calculate the interceptor's terminal error distribution and establish the relevant global optimization model by using the circumscribed cuboid volume of the interceptor's terminal position error ellipsoid as the optimization index. Finally, we combined the above two single-objective optimization models to establish a global multi-objective optimization model that considers interception time and interception uncertainty and gave a hybrid multi-objective optimization algorithm based on Non-dominated Sorting Genetic Algorithm II - Goal Achievement Method (NSGA2-GAM). The simulation example verifies the effectiveness of this method.
doi_str_mv 10.1016/j.dt.2021.02.006
format article
fullrecord <record><control><sourceid>elsevier_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_dd34053d30544270a79a67aa4e220538</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2214914721000143</els_id><doaj_id>oai_doaj_org_article_dd34053d30544270a79a67aa4e220538</doaj_id><sourcerecordid>S2214914721000143</sourcerecordid><originalsourceid>FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3</originalsourceid><addsrcrecordid>eNp1kE9rwzAMxcPYYKXrfcd8gWSy4yTObqPsT6Gwy3YcxrGU4tDExXEH3aefu47Ry04ST3o_pJcktwxyBqy663MMOQfOcuA5QHWRzDhnImuYqC_P-utkMU09ADAZtbKeJR-rMZA3tAvWjWmwA6V6xHQ_GvJB2zEcUhdng_3SPxud82nQ44bGkNlht99OlDrf2pDac9DOu3ZLw01y1em4svit8-T96fFt-ZKtX59Xy4d1ZgTwkBnDOs5a6tC0ppIStSy5xIYEq7HiDa86aHSHUmBFsgbNG0YoCJoaC15hMU9WJy463audt4P2B-W0VT-C8xulfbBmSwqxEFAWWEApBI-sutFVrbUgzqMuIwtOLOPdNHnq_ngM1DFt1SsM6pi2Aq5i2tFyf7JQ_PHTkleTsRQjROvJhHiE_d_8DbehiHM</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Interception time and uncertainty optimization for tangent-impulse orbit interception problem</title><source>ScienceDirect</source><source>EZB Electronic Journals Library</source><creator>Hong, Yang ; Xin-hong, Li ; Wen-zhe, Ding</creator><creatorcontrib>Hong, Yang ; Xin-hong, Li ; Wen-zhe, Ding</creatorcontrib><description>The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we study the minimum time interception problem and the minimum terminal interception error problem under tangent impulse conditions and give an orbit optimization method that considers the interception time and the interception uncertainty. First, we express the interceptor's transfer time equation as a form of flight path angle, establish a global optimization model for solving the minimum time tangent impulse interception and give a hybrid optimization algorithm based on Augmented Lagrange Genetic Algorithm - Sequential Quadratic Programming (ALGA-SQP). Secondly, we use the universal time equation and Bootstrap resampling technology to calculate the interceptor's terminal error distribution and establish the relevant global optimization model by using the circumscribed cuboid volume of the interceptor's terminal position error ellipsoid as the optimization index. Finally, we combined the above two single-objective optimization models to establish a global multi-objective optimization model that considers interception time and interception uncertainty and gave a hybrid multi-objective optimization algorithm based on Non-dominated Sorting Genetic Algorithm II - Goal Achievement Method (NSGA2-GAM). The simulation example verifies the effectiveness of this method.</description><identifier>ISSN: 2214-9147</identifier><identifier>EISSN: 2214-9147</identifier><identifier>DOI: 10.1016/j.dt.2021.02.006</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Hybrid optimization ; Interception uncertainty ; Minimum time ; Multi-objective optimization ; Tangent impulse interception</subject><ispartof>Defence technology, 2022-03, Vol.18 (3), p.418-440</ispartof><rights>2021 China Ordnance Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3</citedby><cites>FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S2214914721000143$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,3536,27905,27906,45761</link.rule.ids></links><search><creatorcontrib>Hong, Yang</creatorcontrib><creatorcontrib>Xin-hong, Li</creatorcontrib><creatorcontrib>Wen-zhe, Ding</creatorcontrib><title>Interception time and uncertainty optimization for tangent-impulse orbit interception problem</title><title>Defence technology</title><description>The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we study the minimum time interception problem and the minimum terminal interception error problem under tangent impulse conditions and give an orbit optimization method that considers the interception time and the interception uncertainty. First, we express the interceptor's transfer time equation as a form of flight path angle, establish a global optimization model for solving the minimum time tangent impulse interception and give a hybrid optimization algorithm based on Augmented Lagrange Genetic Algorithm - Sequential Quadratic Programming (ALGA-SQP). Secondly, we use the universal time equation and Bootstrap resampling technology to calculate the interceptor's terminal error distribution and establish the relevant global optimization model by using the circumscribed cuboid volume of the interceptor's terminal position error ellipsoid as the optimization index. Finally, we combined the above two single-objective optimization models to establish a global multi-objective optimization model that considers interception time and interception uncertainty and gave a hybrid multi-objective optimization algorithm based on Non-dominated Sorting Genetic Algorithm II - Goal Achievement Method (NSGA2-GAM). The simulation example verifies the effectiveness of this method.</description><subject>Hybrid optimization</subject><subject>Interception uncertainty</subject><subject>Minimum time</subject><subject>Multi-objective optimization</subject><subject>Tangent impulse interception</subject><issn>2214-9147</issn><issn>2214-9147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp1kE9rwzAMxcPYYKXrfcd8gWSy4yTObqPsT6Gwy3YcxrGU4tDExXEH3aefu47Ry04ST3o_pJcktwxyBqy663MMOQfOcuA5QHWRzDhnImuYqC_P-utkMU09ADAZtbKeJR-rMZA3tAvWjWmwA6V6xHQ_GvJB2zEcUhdng_3SPxud82nQ44bGkNlht99OlDrf2pDac9DOu3ZLw01y1em4svit8-T96fFt-ZKtX59Xy4d1ZgTwkBnDOs5a6tC0ppIStSy5xIYEq7HiDa86aHSHUmBFsgbNG0YoCJoaC15hMU9WJy463audt4P2B-W0VT-C8xulfbBmSwqxEFAWWEApBI-sutFVrbUgzqMuIwtOLOPdNHnq_ngM1DFt1SsM6pi2Aq5i2tFyf7JQ_PHTkleTsRQjROvJhHiE_d_8DbehiHM</recordid><startdate>202203</startdate><enddate>202203</enddate><creator>Hong, Yang</creator><creator>Xin-hong, Li</creator><creator>Wen-zhe, Ding</creator><general>Elsevier B.V</general><general>KeAi Communications Co., Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>202203</creationdate><title>Interception time and uncertainty optimization for tangent-impulse orbit interception problem</title><author>Hong, Yang ; Xin-hong, Li ; Wen-zhe, Ding</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Hybrid optimization</topic><topic>Interception uncertainty</topic><topic>Minimum time</topic><topic>Multi-objective optimization</topic><topic>Tangent impulse interception</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hong, Yang</creatorcontrib><creatorcontrib>Xin-hong, Li</creatorcontrib><creatorcontrib>Wen-zhe, Ding</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Defence technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hong, Yang</au><au>Xin-hong, Li</au><au>Wen-zhe, Ding</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Interception time and uncertainty optimization for tangent-impulse orbit interception problem</atitle><jtitle>Defence technology</jtitle><date>2022-03</date><risdate>2022</risdate><volume>18</volume><issue>3</issue><spage>418</spage><epage>440</epage><pages>418-440</pages><issn>2214-9147</issn><eissn>2214-9147</eissn><abstract>The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we study the minimum time interception problem and the minimum terminal interception error problem under tangent impulse conditions and give an orbit optimization method that considers the interception time and the interception uncertainty. First, we express the interceptor's transfer time equation as a form of flight path angle, establish a global optimization model for solving the minimum time tangent impulse interception and give a hybrid optimization algorithm based on Augmented Lagrange Genetic Algorithm - Sequential Quadratic Programming (ALGA-SQP). Secondly, we use the universal time equation and Bootstrap resampling technology to calculate the interceptor's terminal error distribution and establish the relevant global optimization model by using the circumscribed cuboid volume of the interceptor's terminal position error ellipsoid as the optimization index. Finally, we combined the above two single-objective optimization models to establish a global multi-objective optimization model that considers interception time and interception uncertainty and gave a hybrid multi-objective optimization algorithm based on Non-dominated Sorting Genetic Algorithm II - Goal Achievement Method (NSGA2-GAM). The simulation example verifies the effectiveness of this method.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.dt.2021.02.006</doi><tpages>23</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2214-9147
ispartof Defence technology, 2022-03, Vol.18 (3), p.418-440
issn 2214-9147
2214-9147
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_dd34053d30544270a79a67aa4e220538
source ScienceDirect; EZB Electronic Journals Library
subjects Hybrid optimization
Interception uncertainty
Minimum time
Multi-objective optimization
Tangent impulse interception
title Interception time and uncertainty optimization for tangent-impulse orbit interception problem
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T20%3A42%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Interception%20time%20and%20uncertainty%20optimization%20for%20tangent-impulse%20orbit%20interception%20problem&rft.jtitle=Defence%20technology&rft.au=Hong,%20Yang&rft.date=2022-03&rft.volume=18&rft.issue=3&rft.spage=418&rft.epage=440&rft.pages=418-440&rft.issn=2214-9147&rft.eissn=2214-9147&rft_id=info:doi/10.1016/j.dt.2021.02.006&rft_dat=%3Celsevier_doaj_%3ES2214914721000143%3C/elsevier_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c402t-cc1f21befdcbc688da8528d9e417d62926f09afd84d6e870a291ed4e097d326d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true