Fixed-lag alpha-beta filter for target trajectory smoothing
A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimat...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2004-10, Vol.40 (4), p.1417-1421 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1421 |
|---|---|
| container_issue | 4 |
| container_start_page | 1417 |
| container_title | IEEE transactions on aerospace and electronic systems |
| container_volume | 40 |
| creator | Ogle, T.L. Blair, W.D. |
| description | A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing. |
| doi_str_mv | 10.1109/TAES.2004.1386894 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_journals_883591882</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1386894</ieee_id><sourcerecordid>28274025</sourcerecordid><originalsourceid>FETCH-LOGICAL-c386t-73a4a989eb13eb02019d67ed49936285d31e0e001c7f36f5eb237b742141251f3</originalsourceid><addsrcrecordid>eNqNkUFLAzEQhYMoWKs_QLwsHvS0NZNkNwmepLQqFDxYzyG7O9tu2XZrkoL992ZpQfAgnoZhvvd4wyPkGugIgOqH-dPkfcQoFSPgKldanJABZJlMdU75KRlQCirVLINzcuH9Kq5CCT4gj9PmC6u0tYvEttulTQsMNqmbNqBL6s4lwboFhiQ4u8IydG6f-HXXhWWzWVySs9q2Hq-Oc0g-ppP5-CWdvT2_jp9maRmjhFRyK6xWGgvgWFBGQVe5xEpozXOmsooDUoyJSlnzvM6wYFwWUjAQEAPXfEjuD75b133u0AezbnyJbWs32O280RQkKKl5JO_-JJlSmkHO_gEyKSjLInj7C1x1O7eJ7xqleKZBqd4NDlDpOu8d1mbrmrV1ewPU9PWYvh7T12OO9UTNzUHTIOIPf7x-A4vmiPE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>883591882</pqid></control><display><type>article</type><title>Fixed-lag alpha-beta filter for target trajectory smoothing</title><source>IEEE Electronic Library Online</source><creator>Ogle, T.L. ; Blair, W.D.</creator><creatorcontrib>Ogle, T.L. ; Blair, W.D.</creatorcontrib><description>A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.2004.1386894</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Aircraft components ; Covariance matrix ; Data processing ; Electronic systems ; Equations ; Estimates ; Gain ; Gaussian noise ; Kalman filters ; Mathematical analysis ; Noise measurement ; Smoothing ; Smoothing methods ; State estimation ; Steady-state ; Time measurement ; Trajectories ; Trajectory</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2004-10, Vol.40 (4), p.1417-1421</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-73a4a989eb13eb02019d67ed49936285d31e0e001c7f36f5eb237b742141251f3</citedby><cites>FETCH-LOGICAL-c386t-73a4a989eb13eb02019d67ed49936285d31e0e001c7f36f5eb237b742141251f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1386894$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,782,786,798,27933,27934,54767</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1386894$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ogle, T.L.</creatorcontrib><creatorcontrib>Blair, W.D.</creatorcontrib><title>Fixed-lag alpha-beta filter for target trajectory smoothing</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing.</description><subject>Aircraft components</subject><subject>Covariance matrix</subject><subject>Data processing</subject><subject>Electronic systems</subject><subject>Equations</subject><subject>Estimates</subject><subject>Gain</subject><subject>Gaussian noise</subject><subject>Kalman filters</subject><subject>Mathematical analysis</subject><subject>Noise measurement</subject><subject>Smoothing</subject><subject>Smoothing methods</subject><subject>State estimation</subject><subject>Steady-state</subject><subject>Time measurement</subject><subject>Trajectories</subject><subject>Trajectory</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqNkUFLAzEQhYMoWKs_QLwsHvS0NZNkNwmepLQqFDxYzyG7O9tu2XZrkoL992ZpQfAgnoZhvvd4wyPkGugIgOqH-dPkfcQoFSPgKldanJABZJlMdU75KRlQCirVLINzcuH9Kq5CCT4gj9PmC6u0tYvEttulTQsMNqmbNqBL6s4lwboFhiQ4u8IydG6f-HXXhWWzWVySs9q2Hq-Oc0g-ppP5-CWdvT2_jp9maRmjhFRyK6xWGgvgWFBGQVe5xEpozXOmsooDUoyJSlnzvM6wYFwWUjAQEAPXfEjuD75b133u0AezbnyJbWs32O280RQkKKl5JO_-JJlSmkHO_gEyKSjLInj7C1x1O7eJ7xqleKZBqd4NDlDpOu8d1mbrmrV1ewPU9PWYvh7T12OO9UTNzUHTIOIPf7x-A4vmiPE</recordid><startdate>20041001</startdate><enddate>20041001</enddate><creator>Ogle, T.L.</creator><creator>Blair, W.D.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope><scope>F28</scope></search><sort><creationdate>20041001</creationdate><title>Fixed-lag alpha-beta filter for target trajectory smoothing</title><author>Ogle, T.L. ; Blair, W.D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-73a4a989eb13eb02019d67ed49936285d31e0e001c7f36f5eb237b742141251f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Aircraft components</topic><topic>Covariance matrix</topic><topic>Data processing</topic><topic>Electronic systems</topic><topic>Equations</topic><topic>Estimates</topic><topic>Gain</topic><topic>Gaussian noise</topic><topic>Kalman filters</topic><topic>Mathematical analysis</topic><topic>Noise measurement</topic><topic>Smoothing</topic><topic>Smoothing methods</topic><topic>State estimation</topic><topic>Steady-state</topic><topic>Time measurement</topic><topic>Trajectories</topic><topic>Trajectory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ogle, T.L.</creatorcontrib><creatorcontrib>Blair, W.D.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library Online</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ogle, T.L.</au><au>Blair, W.D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fixed-lag alpha-beta filter for target trajectory smoothing</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>2004-10-01</date><risdate>2004</risdate><volume>40</volume><issue>4</issue><spage>1417</spage><epage>1421</epage><pages>1417-1421</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TAES.2004.1386894</doi><tpages>5</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0018-9251 |
| ispartof | IEEE transactions on aerospace and electronic systems, 2004-10, Vol.40 (4), p.1417-1421 |
| issn | 0018-9251 1557-9603 |
| language | eng |
| recordid | cdi_proquest_journals_883591882 |
| source | IEEE Electronic Library Online |
| subjects | Aircraft components Covariance matrix Data processing Electronic systems Equations Estimates Gain Gaussian noise Kalman filters Mathematical analysis Noise measurement Smoothing Smoothing methods State estimation Steady-state Time measurement Trajectories Trajectory |
| title | Fixed-lag alpha-beta filter for target trajectory smoothing |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-11-29T15%3A39%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fixed-lag%20alpha-beta%20filter%20for%20target%20trajectory%20smoothing&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Ogle,%20T.L.&rft.date=2004-10-01&rft.volume=40&rft.issue=4&rft.spage=1417&rft.epage=1421&rft.pages=1417-1421&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/TAES.2004.1386894&rft_dat=%3Cproquest_RIE%3E28274025%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=883591882&rft_id=info:pmid/&rft_ieee_id=1386894&rfr_iscdi=true |