Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar

This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of atmospheric and oceanic technology 2011-12, Vol.28 (12), p.1581-1597
Hauptverfasser: Curtis, Christopher D, Torres, Sebastián M
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1597
container_issue 12
container_start_page 1581
container_title Journal of atmospheric and oceanic technology
container_volume 28
creator Curtis, Christopher D
Torres, Sebastián M
description This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.
doi_str_mv 10.1175/JTECH-D-10-05042.1
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_923199102</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2558266521</sourcerecordid><originalsourceid>FETCH-LOGICAL-c411t-f4e057dc8ae1d36ac5dec09fb5569d8d50b763f0534d68f68f028abc6221eb9d3</originalsourceid><addsrcrecordid>eNp9kUtr3DAUhUVpodO0f6Ar0S7ajRNdyZKt5ZBHH4QktFO6NNfSdcbBY08kTyD_vncyXRUaEIjD-Tgc6QjxHtQxQGVPvq_OT78WZwWoQllV6mN4IRZgNctSu5dioSrj2ar0a_Em5zulFBhwCzEtI27n_oHkDxxvSV4_UMq42Q79eCvnSS7Duid2LzDPlOTPgOO4t6ZRzmuSVzj304iD_E3IOnFKxCRXlOeWorxZY6ZYLFPCx4P1VrzqcMj07u99JH5dnK-4--X1l2-ny8silABz0ZXEZWOokSAah8FGCsp3rbXOxzpa1VbOdMqaMrq646N0jW1wWgO1Ppoj8emQu03T_Y7rNJs-BxoGHGna5cZrA96D0kx-fpYEV0Hp68qWjH74B72bdomfz3n82U4bZxn6-D9I18yoSpeeKX2gQppyTtQ129RvMD02oJr9pM3TpM3ZXj9N2oD5A7lRk1I</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2826207249</pqid></control><display><type>article</type><title>Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar</title><source>American Meteorological Society</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Curtis, Christopher D ; Torres, Sebastián M</creator><creatorcontrib>Curtis, Christopher D ; Torres, Sebastián M</creatorcontrib><description>This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.</description><identifier>ISSN: 0739-0572</identifier><identifier>EISSN: 1520-0426</identifier><identifier>DOI: 10.1175/JTECH-D-10-05042.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Algorithms ; Climatology ; Computation ; Computer applications ; Distributed processing ; Doppler effect ; Estimates ; Marine ; Meteorological data ; Meteorological radar ; Oversampling ; Radar ; Radar arrays ; Signal processing ; Software ; Studies ; Surveillance ; Temporal resolution ; Test stands ; Time series ; Variance ; Weather ; Weather radar</subject><ispartof>Journal of atmospheric and oceanic technology, 2011-12, Vol.28 (12), p.1581-1597</ispartof><rights>Copyright American Meteorological Society 2011</rights><rights>Copyright American Meteorological Society Dec 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-f4e057dc8ae1d36ac5dec09fb5569d8d50b763f0534d68f68f028abc6221eb9d3</citedby><cites>FETCH-LOGICAL-c411t-f4e057dc8ae1d36ac5dec09fb5569d8d50b763f0534d68f68f028abc6221eb9d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3681,27924,27925</link.rule.ids></links><search><creatorcontrib>Curtis, Christopher D</creatorcontrib><creatorcontrib>Torres, Sebastián M</creatorcontrib><title>Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar</title><title>Journal of atmospheric and oceanic technology</title><description>This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.</description><subject>Algorithms</subject><subject>Climatology</subject><subject>Computation</subject><subject>Computer applications</subject><subject>Distributed processing</subject><subject>Doppler effect</subject><subject>Estimates</subject><subject>Marine</subject><subject>Meteorological data</subject><subject>Meteorological radar</subject><subject>Oversampling</subject><subject>Radar</subject><subject>Radar arrays</subject><subject>Signal processing</subject><subject>Software</subject><subject>Studies</subject><subject>Surveillance</subject><subject>Temporal resolution</subject><subject>Test stands</subject><subject>Time series</subject><subject>Variance</subject><subject>Weather</subject><subject>Weather radar</subject><issn>0739-0572</issn><issn>1520-0426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kUtr3DAUhUVpodO0f6Ar0S7ajRNdyZKt5ZBHH4QktFO6NNfSdcbBY08kTyD_vncyXRUaEIjD-Tgc6QjxHtQxQGVPvq_OT78WZwWoQllV6mN4IRZgNctSu5dioSrj2ar0a_Em5zulFBhwCzEtI27n_oHkDxxvSV4_UMq42Q79eCvnSS7Duid2LzDPlOTPgOO4t6ZRzmuSVzj304iD_E3IOnFKxCRXlOeWorxZY6ZYLFPCx4P1VrzqcMj07u99JH5dnK-4--X1l2-ny8silABz0ZXEZWOokSAah8FGCsp3rbXOxzpa1VbOdMqaMrq646N0jW1wWgO1Ppoj8emQu03T_Y7rNJs-BxoGHGna5cZrA96D0kx-fpYEV0Hp68qWjH74B72bdomfz3n82U4bZxn6-D9I18yoSpeeKX2gQppyTtQ129RvMD02oJr9pM3TpM3ZXj9N2oD5A7lRk1I</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Curtis, Christopher D</creator><creator>Torres, Sebastián M</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8AF</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20111201</creationdate><title>Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar</title><author>Curtis, Christopher D ; Torres, Sebastián M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-f4e057dc8ae1d36ac5dec09fb5569d8d50b763f0534d68f68f028abc6221eb9d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Climatology</topic><topic>Computation</topic><topic>Computer applications</topic><topic>Distributed processing</topic><topic>Doppler effect</topic><topic>Estimates</topic><topic>Marine</topic><topic>Meteorological data</topic><topic>Meteorological radar</topic><topic>Oversampling</topic><topic>Radar</topic><topic>Radar arrays</topic><topic>Signal processing</topic><topic>Software</topic><topic>Studies</topic><topic>Surveillance</topic><topic>Temporal resolution</topic><topic>Test stands</topic><topic>Time series</topic><topic>Variance</topic><topic>Weather</topic><topic>Weather radar</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Curtis, Christopher D</creatorcontrib><creatorcontrib>Torres, Sebastián M</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</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>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Journal of atmospheric and oceanic technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Curtis, Christopher D</au><au>Torres, Sebastián M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar</atitle><jtitle>Journal of atmospheric and oceanic technology</jtitle><date>2011-12-01</date><risdate>2011</risdate><volume>28</volume><issue>12</issue><spage>1581</spage><epage>1597</epage><pages>1581-1597</pages><issn>0739-0572</issn><eissn>1520-0426</eissn><abstract>This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/JTECH-D-10-05042.1</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0739-0572
ispartof Journal of atmospheric and oceanic technology, 2011-12, Vol.28 (12), p.1581-1597
issn 0739-0572
1520-0426
language eng
recordid cdi_proquest_miscellaneous_923199102
source American Meteorological Society; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection
subjects Algorithms
Climatology
Computation
Computer applications
Distributed processing
Doppler effect
Estimates
Marine
Meteorological data
Meteorological radar
Oversampling
Radar
Radar arrays
Signal processing
Software
Studies
Surveillance
Temporal resolution
Test stands
Time series
Variance
Weather
Weather radar
title Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T23%3A39%3A31IST&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=Adaptive%20Range%20Oversampling%20to%20Achieve%20Faster%20Scanning%20on%20the%20National%20Weather%20Radar%20Testbed%20Phased-Array%20Radar&rft.jtitle=Journal%20of%20atmospheric%20and%20oceanic%20technology&rft.au=Curtis,%20Christopher%20D&rft.date=2011-12-01&rft.volume=28&rft.issue=12&rft.spage=1581&rft.epage=1597&rft.pages=1581-1597&rft.issn=0739-0572&rft.eissn=1520-0426&rft_id=info:doi/10.1175/JTECH-D-10-05042.1&rft_dat=%3Cproquest_cross%3E2558266521%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=2826207249&rft_id=info:pmid/&rfr_iscdi=true