Metric selection for information theoretic sensor management
Different information theoretic sensor management approaches are compared in a Bayesian target-tracking problem. Specifically, the performance using the expected Renyi divergence with different parameter values is compared theoretically and experimentally. Included is the special case in which the e...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 8 |
|---|---|
| container_issue | |
| container_start_page | 1 |
| container_title | |
| container_volume | |
| creator | Aughenbaugh, J.M. La Cour, B.R. |
| description | Different information theoretic sensor management approaches are compared in a Bayesian target-tracking problem. Specifically, the performance using the expected Renyi divergence with different parameter values is compared theoretically and experimentally. Included is the special case in which the expected Renyi divergence is equal to the expected Kullback-Leibler divergence, which is also equivalent to both the mutual information and the expected change in differential entropy for this Bayesian updating problem. The example problem involves a single target moving in a circle, four bearing-only sensors, and two time-delay sensors. A particle filter based tracker is used. |
| doi_str_mv | 10.1109/ICIF.2008.4632451 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4632451</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4632451</ieee_id><sourcerecordid>4632451</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-e2dd34588327b55d6cf49b1dc623abb464e5ed59e5ebdbd8b150fc7c24d5b90e3</originalsourceid><addsrcrecordid>eNotT81Kw0AYXJGC2uYBxEteIPHb3-yCFwm2Bipeei_780VXmkSye_HtjbWXGYYZhhlC7inUlIJ57NpuWzMAXQvFmZD0ihSm0RwAmNCas2tyxzVAw8EwfUOKlL4WjxrVABe35OkN8xx9mfCEPsdpLPtpLuO44GDPOn_iNGM-Z8a0mIMd7QcOOOYNWfX2lLC48Jocti-H9rXav--69nlfRQO5QhYCF_JvTOOkDMr3wjgavGLcOieUQIlBmgVdcEE7KqH3jWciSGcA-Zo8_NdGRDx-z3Gw88_x8pf_ArHGSjw</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Metric selection for information theoretic sensor management</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Aughenbaugh, J.M. ; La Cour, B.R.</creator><creatorcontrib>Aughenbaugh, J.M. ; La Cour, B.R.</creatorcontrib><description>Different information theoretic sensor management approaches are compared in a Bayesian target-tracking problem. Specifically, the performance using the expected Renyi divergence with different parameter values is compared theoretically and experimentally. Included is the special case in which the expected Renyi divergence is equal to the expected Kullback-Leibler divergence, which is also equivalent to both the mutual information and the expected change in differential entropy for this Bayesian updating problem. The example problem involves a single target moving in a circle, four bearing-only sensors, and two time-delay sensors. A particle filter based tracker is used.</description><identifier>ISBN: 3800730928</identifier><identifier>ISBN: 9783800730926</identifier><identifier>EISBN: 9783000248832</identifier><identifier>EISBN: 3000248838</identifier><identifier>DOI: 10.1109/ICIF.2008.4632451</identifier><language>eng</language><publisher>IEEE</publisher><subject>Atmospheric measurements ; Bayesian methods ; Covariance matrix ; divergence ; Entropy ; Kullback-Leibler ; mutual information ; Particle filters ; Particle measurements ; Rényi ; sensor management ; Target tracking</subject><ispartof>2008 11th International Conference on Information Fusion, 2008, p.1-8</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4632451$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4632451$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Aughenbaugh, J.M.</creatorcontrib><creatorcontrib>La Cour, B.R.</creatorcontrib><title>Metric selection for information theoretic sensor management</title><title>2008 11th International Conference on Information Fusion</title><addtitle>ICIF</addtitle><description>Different information theoretic sensor management approaches are compared in a Bayesian target-tracking problem. Specifically, the performance using the expected Renyi divergence with different parameter values is compared theoretically and experimentally. Included is the special case in which the expected Renyi divergence is equal to the expected Kullback-Leibler divergence, which is also equivalent to both the mutual information and the expected change in differential entropy for this Bayesian updating problem. The example problem involves a single target moving in a circle, four bearing-only sensors, and two time-delay sensors. A particle filter based tracker is used.</description><subject>Atmospheric measurements</subject><subject>Bayesian methods</subject><subject>Covariance matrix</subject><subject>divergence</subject><subject>Entropy</subject><subject>Kullback-Leibler</subject><subject>mutual information</subject><subject>Particle filters</subject><subject>Particle measurements</subject><subject>Rényi</subject><subject>sensor management</subject><subject>Target tracking</subject><isbn>3800730928</isbn><isbn>9783800730926</isbn><isbn>9783000248832</isbn><isbn>3000248838</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT81Kw0AYXJGC2uYBxEteIPHb3-yCFwm2Bipeei_780VXmkSye_HtjbWXGYYZhhlC7inUlIJ57NpuWzMAXQvFmZD0ihSm0RwAmNCas2tyxzVAw8EwfUOKlL4WjxrVABe35OkN8xx9mfCEPsdpLPtpLuO44GDPOn_iNGM-Z8a0mIMd7QcOOOYNWfX2lLC48Jocti-H9rXav--69nlfRQO5QhYCF_JvTOOkDMr3wjgavGLcOieUQIlBmgVdcEE7KqH3jWciSGcA-Zo8_NdGRDx-z3Gw88_x8pf_ArHGSjw</recordid><startdate>200806</startdate><enddate>200806</enddate><creator>Aughenbaugh, J.M.</creator><creator>La Cour, B.R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200806</creationdate><title>Metric selection for information theoretic sensor management</title><author>Aughenbaugh, J.M. ; La Cour, B.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-e2dd34588327b55d6cf49b1dc623abb464e5ed59e5ebdbd8b150fc7c24d5b90e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Atmospheric measurements</topic><topic>Bayesian methods</topic><topic>Covariance matrix</topic><topic>divergence</topic><topic>Entropy</topic><topic>Kullback-Leibler</topic><topic>mutual information</topic><topic>Particle filters</topic><topic>Particle measurements</topic><topic>Rényi</topic><topic>sensor management</topic><topic>Target tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Aughenbaugh, J.M.</creatorcontrib><creatorcontrib>La Cour, B.R.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Aughenbaugh, J.M.</au><au>La Cour, B.R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Metric selection for information theoretic sensor management</atitle><btitle>2008 11th International Conference on Information Fusion</btitle><stitle>ICIF</stitle><date>2008-06</date><risdate>2008</risdate><spage>1</spage><epage>8</epage><pages>1-8</pages><isbn>3800730928</isbn><isbn>9783800730926</isbn><eisbn>9783000248832</eisbn><eisbn>3000248838</eisbn><abstract>Different information theoretic sensor management approaches are compared in a Bayesian target-tracking problem. Specifically, the performance using the expected Renyi divergence with different parameter values is compared theoretically and experimentally. Included is the special case in which the expected Renyi divergence is equal to the expected Kullback-Leibler divergence, which is also equivalent to both the mutual information and the expected change in differential entropy for this Bayesian updating problem. The example problem involves a single target moving in a circle, four bearing-only sensors, and two time-delay sensors. A particle filter based tracker is used.</abstract><pub>IEEE</pub><doi>10.1109/ICIF.2008.4632451</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISBN: 3800730928 |
| ispartof | 2008 11th International Conference on Information Fusion, 2008, p.1-8 |
| issn | |
| language | eng |
| recordid | cdi_ieee_primary_4632451 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Atmospheric measurements Bayesian methods Covariance matrix divergence Entropy Kullback-Leibler mutual information Particle filters Particle measurements Rényi sensor management Target tracking |
| title | Metric selection for information theoretic sensor management |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T15%3A42%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Metric%20selection%20for%20information%20theoretic%20sensor%20management&rft.btitle=2008%2011th%20International%20Conference%20on%20Information%20Fusion&rft.au=Aughenbaugh,%20J.M.&rft.date=2008-06&rft.spage=1&rft.epage=8&rft.pages=1-8&rft.isbn=3800730928&rft.isbn_list=9783800730926&rft_id=info:doi/10.1109/ICIF.2008.4632451&rft_dat=%3Cieee_6IE%3E4632451%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783000248832&rft.eisbn_list=3000248838&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4632451&rfr_iscdi=true |