A single performance characteristic for the evaluation of seeker tracking algorithms
This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characte...
Gespeichert in:
| Veröffentlicht in: | Pattern recognition and image analysis 2014-04, Vol.24 (2), p.218-225 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 225 |
|---|---|
| container_issue | 2 |
| container_start_page | 218 |
| container_title | Pattern recognition and image analysis |
| container_volume | 24 |
| creator | Doktorski, L. Michaelsen, E. Repasi, E. |
| description | This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characteristic which is able to assess the threat for ships depending on various scenario parameters. It is shown that for these applications such a single characteristic is sufficient. In order to achieve this five popular tracking algorithms are used. Synthetic IR image sequences are generated to simulate a large set of attack approaches and assemble sufficient statistics on the behavior of the algorithms. The introduced characteristic can also be used for investigations on algorithms themselves, e.g. for sensitivity analyses and parameter optimization of a single algorithm, and for comparison of different algorithms. |
| doi_str_mv | 10.1134/S1054661814020047 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1567079353</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1567079353</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2897-9b139e06ed798acfebff9ce838154b2f7e8ea1451ab34bae04017e2011579393</originalsourceid><addsrcrecordid>eNp1kF1LwzAUhoMoOKc_wLuACN5Uc9KkTS7H8AsGXrj7ksaTLVvXzqQV_PdmbIgoXiXkfc7DyUvIJbBbgFzcvQKToihAgWCcMVEekRFIKbOCAz9O9xRnu_yUnMW4Yowp0HxE5hMafbtokG4xuC5sTGuR2qUJxvYYfOy9pemd9kuk-GGawfS-a2nnaERcYwoSuU4KappFF3y_3MRzcuJME_HicI7J_OF-Pn3KZi-Pz9PJLLNc6TLTNeQaWYFvpVbGOqyd0xZVrkCKmrsSFRoQEkydi9ogEwxK5AxAljrX-Zjc7LXb0L0PGPtq46PFpjEtdkOsQBYlS6TME3r1C111Q2jTcolKQMGE5ImCPWVDF2NAV22D35jwWQGrdjVXf2pOM9cHs4nWNC6kAn38HuRK6vTXnZvvuZiidoHhxwb_yr8AriKLEg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1535360452</pqid></control><display><type>article</type><title>A single performance characteristic for the evaluation of seeker tracking algorithms</title><source>SpringerLink Journals - AutoHoldings</source><creator>Doktorski, L. ; Michaelsen, E. ; Repasi, E.</creator><creatorcontrib>Doktorski, L. ; Michaelsen, E. ; Repasi, E.</creatorcontrib><description>This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characteristic which is able to assess the threat for ships depending on various scenario parameters. It is shown that for these applications such a single characteristic is sufficient. In order to achieve this five popular tracking algorithms are used. Synthetic IR image sequences are generated to simulate a large set of attack approaches and assemble sufficient statistics on the behavior of the algorithms. The introduced characteristic can also be used for investigations on algorithms themselves, e.g. for sensitivity analyses and parameter optimization of a single algorithm, and for comparison of different algorithms.</description><identifier>ISSN: 1054-6618</identifier><identifier>EISSN: 1555-6212</identifier><identifier>DOI: 10.1134/S1054661814020047</identifier><language>eng</language><publisher>Moscow: Nauka/Interperiodica</publisher><subject>Algorithms ; Analysis ; Analysis and Understanding of Images ; Applied sciences ; Artificial intelligence ; Cameras ; Computer Science ; Computer science; control theory; systems ; Concentrates ; Data processing. List processing. Character string processing ; Exact sciences and technology ; Image Processing and Computer Vision ; Image processing systems ; Infrared radiation ; Investigations ; Mathematical models ; Memory organisation. Data processing ; Missiles ; Optimization ; Pattern Recognition ; Pattern recognition. Digital image processing. Computational geometry ; Processing ; Representation ; Sensitivity analysis ; Ships ; Simulation ; Software ; Statistics ; Studies ; Threat assessment ; Tracking ; Tracking control systems</subject><ispartof>Pattern recognition and image analysis, 2014-04, Vol.24 (2), p.218-225</ispartof><rights>Pleiades Publishing, Ltd. 2014</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2897-9b139e06ed798acfebff9ce838154b2f7e8ea1451ab34bae04017e2011579393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1134/S1054661814020047$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1134/S1054661814020047$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28598972$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Doktorski, L.</creatorcontrib><creatorcontrib>Michaelsen, E.</creatorcontrib><creatorcontrib>Repasi, E.</creatorcontrib><title>A single performance characteristic for the evaluation of seeker tracking algorithms</title><title>Pattern recognition and image analysis</title><addtitle>Pattern Recognit. Image Anal</addtitle><description>This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characteristic which is able to assess the threat for ships depending on various scenario parameters. It is shown that for these applications such a single characteristic is sufficient. In order to achieve this five popular tracking algorithms are used. Synthetic IR image sequences are generated to simulate a large set of attack approaches and assemble sufficient statistics on the behavior of the algorithms. The introduced characteristic can also be used for investigations on algorithms themselves, e.g. for sensitivity analyses and parameter optimization of a single algorithm, and for comparison of different algorithms.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Analysis and Understanding of Images</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Cameras</subject><subject>Computer Science</subject><subject>Computer science; control theory; systems</subject><subject>Concentrates</subject><subject>Data processing. List processing. Character string processing</subject><subject>Exact sciences and technology</subject><subject>Image Processing and Computer Vision</subject><subject>Image processing systems</subject><subject>Infrared radiation</subject><subject>Investigations</subject><subject>Mathematical models</subject><subject>Memory organisation. Data processing</subject><subject>Missiles</subject><subject>Optimization</subject><subject>Pattern Recognition</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Processing</subject><subject>Representation</subject><subject>Sensitivity analysis</subject><subject>Ships</subject><subject>Simulation</subject><subject>Software</subject><subject>Statistics</subject><subject>Studies</subject><subject>Threat assessment</subject><subject>Tracking</subject><subject>Tracking control systems</subject><issn>1054-6618</issn><issn>1555-6212</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kF1LwzAUhoMoOKc_wLuACN5Uc9KkTS7H8AsGXrj7ksaTLVvXzqQV_PdmbIgoXiXkfc7DyUvIJbBbgFzcvQKToihAgWCcMVEekRFIKbOCAz9O9xRnu_yUnMW4Yowp0HxE5hMafbtokG4xuC5sTGuR2qUJxvYYfOy9pemd9kuk-GGawfS-a2nnaERcYwoSuU4KappFF3y_3MRzcuJME_HicI7J_OF-Pn3KZi-Pz9PJLLNc6TLTNeQaWYFvpVbGOqyd0xZVrkCKmrsSFRoQEkydi9ogEwxK5AxAljrX-Zjc7LXb0L0PGPtq46PFpjEtdkOsQBYlS6TME3r1C111Q2jTcolKQMGE5ImCPWVDF2NAV22D35jwWQGrdjVXf2pOM9cHs4nWNC6kAn38HuRK6vTXnZvvuZiidoHhxwb_yr8AriKLEg</recordid><startdate>20140401</startdate><enddate>20140401</enddate><creator>Doktorski, L.</creator><creator>Michaelsen, E.</creator><creator>Repasi, E.</creator><general>Nauka/Interperiodica</general><general>Pleiades</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYYUZ</scope><scope>Q9U</scope></search><sort><creationdate>20140401</creationdate><title>A single performance characteristic for the evaluation of seeker tracking algorithms</title><author>Doktorski, L. ; Michaelsen, E. ; Repasi, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2897-9b139e06ed798acfebff9ce838154b2f7e8ea1451ab34bae04017e2011579393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Analysis and Understanding of Images</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Cameras</topic><topic>Computer Science</topic><topic>Computer science; control theory; systems</topic><topic>Concentrates</topic><topic>Data processing. List processing. Character string processing</topic><topic>Exact sciences and technology</topic><topic>Image Processing and Computer Vision</topic><topic>Image processing systems</topic><topic>Infrared radiation</topic><topic>Investigations</topic><topic>Mathematical models</topic><topic>Memory organisation. Data processing</topic><topic>Missiles</topic><topic>Optimization</topic><topic>Pattern Recognition</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Processing</topic><topic>Representation</topic><topic>Sensitivity analysis</topic><topic>Ships</topic><topic>Simulation</topic><topic>Software</topic><topic>Statistics</topic><topic>Studies</topic><topic>Threat assessment</topic><topic>Tracking</topic><topic>Tracking control systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Doktorski, L.</creatorcontrib><creatorcontrib>Michaelsen, E.</creatorcontrib><creatorcontrib>Repasi, E.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><jtitle>Pattern recognition and image analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Doktorski, L.</au><au>Michaelsen, E.</au><au>Repasi, E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A single performance characteristic for the evaluation of seeker tracking algorithms</atitle><jtitle>Pattern recognition and image analysis</jtitle><stitle>Pattern Recognit. Image Anal</stitle><date>2014-04-01</date><risdate>2014</risdate><volume>24</volume><issue>2</issue><spage>218</spage><epage>225</epage><pages>218-225</pages><issn>1054-6618</issn><eissn>1555-6212</eissn><abstract>This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characteristic which is able to assess the threat for ships depending on various scenario parameters. It is shown that for these applications such a single characteristic is sufficient. In order to achieve this five popular tracking algorithms are used. Synthetic IR image sequences are generated to simulate a large set of attack approaches and assemble sufficient statistics on the behavior of the algorithms. The introduced characteristic can also be used for investigations on algorithms themselves, e.g. for sensitivity analyses and parameter optimization of a single algorithm, and for comparison of different algorithms.</abstract><cop>Moscow</cop><pub>Nauka/Interperiodica</pub><doi>10.1134/S1054661814020047</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1054-6618 |
| ispartof | Pattern recognition and image analysis, 2014-04, Vol.24 (2), p.218-225 |
| issn | 1054-6618 1555-6212 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1567079353 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Algorithms Analysis Analysis and Understanding of Images Applied sciences Artificial intelligence Cameras Computer Science Computer science control theory systems Concentrates Data processing. List processing. Character string processing Exact sciences and technology Image Processing and Computer Vision Image processing systems Infrared radiation Investigations Mathematical models Memory organisation. Data processing Missiles Optimization Pattern Recognition Pattern recognition. Digital image processing. Computational geometry Processing Representation Sensitivity analysis Ships Simulation Software Statistics Studies Threat assessment Tracking Tracking control systems |
| title | A single performance characteristic for the evaluation of seeker tracking algorithms |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-13T23%3A29%3A53IST&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=A%20single%20performance%20characteristic%20for%20the%20evaluation%20of%20seeker%20tracking%20algorithms&rft.jtitle=Pattern%20recognition%20and%20image%20analysis&rft.au=Doktorski,%20L.&rft.date=2014-04-01&rft.volume=24&rft.issue=2&rft.spage=218&rft.epage=225&rft.pages=218-225&rft.issn=1054-6618&rft.eissn=1555-6212&rft_id=info:doi/10.1134/S1054661814020047&rft_dat=%3Cproquest_cross%3E1567079353%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1535360452&rft_id=info:pmid/&rfr_iscdi=true |