Tracking solar radio bursts using Bayesian multilateration
Solar radio bursts (SRBs), are emitted by electrons propagating through the corona and interplanetary space. Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. Here, we p...
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description | Solar radio bursts (SRBs), are emitted by electrons propagating through the corona and interplanetary space. Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. Here, we present a novel multilateration algorithm called BayEsian LocaLisation Algorithm (BELLA). In addition, apparent SRB positions from BELLA are compared with comparable localisation methods and the predictions of solar wind models. BELLA uses Bayesian inference to create probabilistic distributions of source positions and their uncertainties. This facilitates the estimation of algorithmic, instrumental, and physical uncertainties in a quantitative manner. We validated BELLA using simulations and a Type III SRB observed by STEREO A/B and Wind. BELLA tracked the Type III source from \(\sim\) 10--150 \(R_{sun}\) (2-0.15 MHz) along a spiral trajectory. This allowed for an estimate of an apparent solar wind speed of \(v_{sw} \sim\) 400 km s\(^{-1}\) and a source longitude of \(\phi_0 \sim\) 30deg. We compared these results with well-established methods of positioning: Goniopolarimetric (GP), analytical time-difference-of-arrival (TDOA), and Solar radio burst Electron Motion Tracker (SEMP). We found them to be in agreement with the results obtained by BELLA. Additionally, the results aligned with solar wind properties assimilated by the Heliospheric Upwind Extrapolation with time dependence (HUXt) model. We have validated BELLA and used it to identify apparent source positions as well as velocities and densities of the solar wind. Furthermore, we identified higher than expected electron densities, suggesting that the true emission sources were at lower altitudes than those identified by BELLA, an effect that may be due to appreciable scattering of electromagnetic waves by electrons in interplanetary space. |
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Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. Here, we present a novel multilateration algorithm called BayEsian LocaLisation Algorithm (BELLA). In addition, apparent SRB positions from BELLA are compared with comparable localisation methods and the predictions of solar wind models. BELLA uses Bayesian inference to create probabilistic distributions of source positions and their uncertainties. This facilitates the estimation of algorithmic, instrumental, and physical uncertainties in a quantitative manner. We validated BELLA using simulations and a Type III SRB observed by STEREO A/B and Wind. BELLA tracked the Type III source from \(\sim\) 10--150 \(R_{sun}\) (2-0.15 MHz) along a spiral trajectory. This allowed for an estimate of an apparent solar wind speed of \(v_{sw} \sim\) 400 km s\(^{-1}\) and a source longitude of \(\phi_0 \sim\) 30deg. We compared these results with well-established methods of positioning: Goniopolarimetric (GP), analytical time-difference-of-arrival (TDOA), and Solar radio burst Electron Motion Tracker (SEMP). We found them to be in agreement with the results obtained by BELLA. Additionally, the results aligned with solar wind properties assimilated by the Heliospheric Upwind Extrapolation with time dependence (HUXt) model. We have validated BELLA and used it to identify apparent source positions as well as velocities and densities of the solar wind. Furthermore, we identified higher than expected electron densities, suggesting that the true emission sources were at lower altitudes than those identified by BELLA, an effect that may be due to appreciable scattering of electromagnetic waves by electrons in interplanetary space.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2402.08590</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Bayesian analysis ; Charged particles ; Electromagnetic radiation ; Electrons ; Interplanetary space ; Localization ; Physics - Solar and Stellar Astrophysics ; Physics - Space Physics ; Probabilistic inference ; Radio waves ; Solar radio bursts ; Solar wind ; Statistical inference ; Time dependence ; Tracking ; Uncertainty ; Wave propagation ; Wind speed</subject><ispartof>arXiv.org, 2024-02</ispartof><rights>2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,784,885,27925</link.rule.ids><backlink>$$Uhttps://doi.org/10.1051/0004-6361/202347747$$DView published paper (Access to full text may be restricted)$$Hfree_for_read</backlink><backlink>$$Uhttps://doi.org/10.48550/arXiv.2402.08590$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Cañizares, L A</creatorcontrib><creatorcontrib>Badman, S T</creatorcontrib><creatorcontrib>Maloney, S A</creatorcontrib><creatorcontrib>Owens, M J</creatorcontrib><creatorcontrib>Weigt, D M</creatorcontrib><creatorcontrib>Carley, E P</creatorcontrib><creatorcontrib>Gallagher, P T</creatorcontrib><title>Tracking solar radio bursts using Bayesian multilateration</title><title>arXiv.org</title><description>Solar radio bursts (SRBs), are emitted by electrons propagating through the corona and interplanetary space. Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. Here, we present a novel multilateration algorithm called BayEsian LocaLisation Algorithm (BELLA). In addition, apparent SRB positions from BELLA are compared with comparable localisation methods and the predictions of solar wind models. BELLA uses Bayesian inference to create probabilistic distributions of source positions and their uncertainties. This facilitates the estimation of algorithmic, instrumental, and physical uncertainties in a quantitative manner. We validated BELLA using simulations and a Type III SRB observed by STEREO A/B and Wind. BELLA tracked the Type III source from \(\sim\) 10--150 \(R_{sun}\) (2-0.15 MHz) along a spiral trajectory. This allowed for an estimate of an apparent solar wind speed of \(v_{sw} \sim\) 400 km s\(^{-1}\) and a source longitude of \(\phi_0 \sim\) 30deg. We compared these results with well-established methods of positioning: Goniopolarimetric (GP), analytical time-difference-of-arrival (TDOA), and Solar radio burst Electron Motion Tracker (SEMP). We found them to be in agreement with the results obtained by BELLA. Additionally, the results aligned with solar wind properties assimilated by the Heliospheric Upwind Extrapolation with time dependence (HUXt) model. We have validated BELLA and used it to identify apparent source positions as well as velocities and densities of the solar wind. Furthermore, we identified higher than expected electron densities, suggesting that the true emission sources were at lower altitudes than those identified by BELLA, an effect that may be due to appreciable scattering of electromagnetic waves by electrons in interplanetary space.</description><subject>Algorithms</subject><subject>Bayesian analysis</subject><subject>Charged particles</subject><subject>Electromagnetic radiation</subject><subject>Electrons</subject><subject>Interplanetary space</subject><subject>Localization</subject><subject>Physics - Solar and Stellar Astrophysics</subject><subject>Physics - Space Physics</subject><subject>Probabilistic inference</subject><subject>Radio waves</subject><subject>Solar radio bursts</subject><subject>Solar wind</subject><subject>Statistical inference</subject><subject>Time dependence</subject><subject>Tracking</subject><subject>Uncertainty</subject><subject>Wave propagation</subject><subject>Wind speed</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GOX</sourceid><recordid>eNotj01Lw0AYhBdBsNT-AE8GPCe-efcz3rT4BQUvuYc32Y1sTZO6m4j996atp4GZYZiHsZscMmGkhHsKv_4nQwGYgZEFXLAFcp6nRiBesVWMWwBApVFKvmAPZaDmy_efSRw6Ckkg64eknkIcYzLFY_BEBxc99clu6kbf0egCjX7or9llS110q39dsvLluVy_pZuP1_f14yYliSrVJIEL0er5kcqtbV1hhdRK1-i0RlKCJDeicRIbboCMautGFBrU7Fhb8yW7Pc-ewKp98DsKh-oIWJ0A58bdubEPw_fk4lhthyn086cKC1Q814VU_A_d4VLJ</recordid><startdate>20240213</startdate><enddate>20240213</enddate><creator>Cañizares, L A</creator><creator>Badman, S T</creator><creator>Maloney, S A</creator><creator>Owens, M J</creator><creator>Weigt, D M</creator><creator>Carley, E P</creator><creator>Gallagher, P T</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>GOX</scope></search><sort><creationdate>20240213</creationdate><title>Tracking solar radio bursts using Bayesian multilateration</title><author>Cañizares, L A ; Badman, S T ; Maloney, S A ; Owens, M J ; Weigt, D M ; Carley, E P ; Gallagher, P T</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a526-7a50344f724061ddfe9d45767b2e772a64a5384ce52c380a86fbc49706e52ddb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Bayesian analysis</topic><topic>Charged particles</topic><topic>Electromagnetic radiation</topic><topic>Electrons</topic><topic>Interplanetary space</topic><topic>Localization</topic><topic>Physics - Solar and Stellar Astrophysics</topic><topic>Physics - Space Physics</topic><topic>Probabilistic inference</topic><topic>Radio waves</topic><topic>Solar radio bursts</topic><topic>Solar wind</topic><topic>Statistical inference</topic><topic>Time dependence</topic><topic>Tracking</topic><topic>Uncertainty</topic><topic>Wave propagation</topic><topic>Wind speed</topic><toplevel>online_resources</toplevel><creatorcontrib>Cañizares, L A</creatorcontrib><creatorcontrib>Badman, S T</creatorcontrib><creatorcontrib>Maloney, S A</creatorcontrib><creatorcontrib>Owens, M J</creatorcontrib><creatorcontrib>Weigt, D M</creatorcontrib><creatorcontrib>Carley, E P</creatorcontrib><creatorcontrib>Gallagher, P T</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content 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>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>arXiv.org</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cañizares, L A</au><au>Badman, S T</au><au>Maloney, S A</au><au>Owens, M J</au><au>Weigt, D M</au><au>Carley, E P</au><au>Gallagher, P T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tracking solar radio bursts using Bayesian multilateration</atitle><jtitle>arXiv.org</jtitle><date>2024-02-13</date><risdate>2024</risdate><eissn>2331-8422</eissn><abstract>Solar radio bursts (SRBs), are emitted by electrons propagating through the corona and interplanetary space. Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. Here, we present a novel multilateration algorithm called BayEsian LocaLisation Algorithm (BELLA). In addition, apparent SRB positions from BELLA are compared with comparable localisation methods and the predictions of solar wind models. BELLA uses Bayesian inference to create probabilistic distributions of source positions and their uncertainties. This facilitates the estimation of algorithmic, instrumental, and physical uncertainties in a quantitative manner. We validated BELLA using simulations and a Type III SRB observed by STEREO A/B and Wind. BELLA tracked the Type III source from \(\sim\) 10--150 \(R_{sun}\) (2-0.15 MHz) along a spiral trajectory. This allowed for an estimate of an apparent solar wind speed of \(v_{sw} \sim\) 400 km s\(^{-1}\) and a source longitude of \(\phi_0 \sim\) 30deg. We compared these results with well-established methods of positioning: Goniopolarimetric (GP), analytical time-difference-of-arrival (TDOA), and Solar radio burst Electron Motion Tracker (SEMP). We found them to be in agreement with the results obtained by BELLA. Additionally, the results aligned with solar wind properties assimilated by the Heliospheric Upwind Extrapolation with time dependence (HUXt) model. We have validated BELLA and used it to identify apparent source positions as well as velocities and densities of the solar wind. Furthermore, we identified higher than expected electron densities, suggesting that the true emission sources were at lower altitudes than those identified by BELLA, an effect that may be due to appreciable scattering of electromagnetic waves by electrons in interplanetary space.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.2402.08590</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Bayesian analysis Charged particles Electromagnetic radiation Electrons Interplanetary space Localization Physics - Solar and Stellar Astrophysics Physics - Space Physics Probabilistic inference Radio waves Solar radio bursts Solar wind Statistical inference Time dependence Tracking Uncertainty Wave propagation Wind speed |
title | Tracking solar radio bursts using Bayesian multilateration |
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