{"id":"https://openalex.org/W3035580486","doi":"https://doi.org/10.1109/plans46316.2020.9110192","title":"A New Approach for Modeling Correlated Gaussian Errors using Frequency Domain Overbounding","display_name":"A New Approach for Modeling Correlated Gaussian Errors using Frequency Domain Overbounding","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3035580486","doi":"https://doi.org/10.1109/plans46316.2020.9110192","mag":"3035580486"},"language":"en","primary_location":{"id":"doi:10.1109/plans46316.2020.9110192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/plans46316.2020.9110192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039786659","display_name":"Steven Langel","orcid":"https://orcid.org/0000-0001-9576-3235"},"institutions":[{"id":"https://openalex.org/I44896327","display_name":"Mitre (United States)","ror":"https://ror.org/03ks2a131","country_code":"US","type":"company","lineage":["https://openalex.org/I44896327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven Langel","raw_affiliation_strings":["Dept. of Communications, SIGINT and PNT, The MITRE Corporation Bedford, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Communications, SIGINT and PNT, The MITRE Corporation Bedford, Massachusetts, USA","institution_ids":["https://openalex.org/I44896327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081638575","display_name":"Omar Garc\u00eda Crespillo","orcid":"https://orcid.org/0000-0002-2598-7636"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Omar Garcia Crespillo","raw_affiliation_strings":["Inst. of Communications and Navigation, German Aerospace Center (DLR), Oberpfaffenhofen-Wessling, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inst. of Communications and Navigation, German Aerospace Center (DLR), Oberpfaffenhofen-Wessling, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055276363","display_name":"Mathieu Joerger","orcid":"https://orcid.org/0000-0002-6391-9095"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mathieu Joerger","raw_affiliation_strings":["Dept. of Aerospace and Ocean Eng, Virginia Tech Blacksburg, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Aerospace and Ocean Eng, Virginia Tech Blacksburg, Virginia, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.495,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.85922432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"868","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10655","display_name":"GNSS positioning and interference","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11325","display_name":"Inertial Sensor and Navigation","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.6374097466468811},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.581332802772522},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5609914660453796},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.558344841003418},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5535931587219238},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5259823203086853},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5131435990333557},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4873007535934448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4473803639411926},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.44498211145401},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44234219193458557},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4282878041267395},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.41147133708000183},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.40728965401649475},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35180675983428955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2009580135345459},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08213144540786743},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07408970594406128}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.6374097466468811},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.581332802772522},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5609914660453796},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.558344841003418},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5535931587219238},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5259823203086853},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5131435990333557},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4873007535934448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4473803639411926},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.44498211145401},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44234219193458557},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4282878041267395},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.41147133708000183},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.40728965401649475},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35180675983428955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2009580135345459},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08213144540786743},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07408970594406128},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/plans46316.2020.9110192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/plans46316.2020.9110192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:135879","is_oa":false,"landing_page_url":"https://elib.dlr.de/135879/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W131934833","https://openalex.org/W1506891285","https://openalex.org/W1572031236","https://openalex.org/W1892473547","https://openalex.org/W2002947147","https://openalex.org/W2059359811","https://openalex.org/W2061426249","https://openalex.org/W2089632713","https://openalex.org/W2094875868","https://openalex.org/W2102948529","https://openalex.org/W2103618012","https://openalex.org/W2140030215","https://openalex.org/W2142542010","https://openalex.org/W2162854795","https://openalex.org/W2168127926","https://openalex.org/W2591717960","https://openalex.org/W2896211679","https://openalex.org/W2905099651","https://openalex.org/W2979788325","https://openalex.org/W3005724679","https://openalex.org/W3034621426","https://openalex.org/W3163082599","https://openalex.org/W4230579786","https://openalex.org/W4248337531","https://openalex.org/W4252380473","https://openalex.org/W6605369238","https://openalex.org/W6630486502","https://openalex.org/W6639608096","https://openalex.org/W6690473655","https://openalex.org/W6757450106","https://openalex.org/W6822082420"],"related_works":["https://openalex.org/W2022823194","https://openalex.org/W2040968278","https://openalex.org/W2144859729","https://openalex.org/W2401337578","https://openalex.org/W3084622875","https://openalex.org/W1987404909","https://openalex.org/W2109377650","https://openalex.org/W2554071524","https://openalex.org/W2344632425","https://openalex.org/W274661425"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,26,62],"new":[4],"method":[5,69],"to":[6],"overbound":[7,57],"Kalman":[8],"filter":[9],"(KF)":[10],"based":[11],"estimate":[12,50],"error":[13,51],"distributions":[14],"in":[15,79],"the":[16,38,44,49,54,58,66],"presence":[17],"of":[18,61,65],"uncertain,":[19],"time-correlated":[20],"noise.":[21],"Each":[22],"noise":[23,55],"component":[24],"is":[25,35,70],"zero-mean":[27],"Gaussian":[28],"random":[29],"process":[30],"whose":[31],"autocorrelation":[32],"sequence":[33],"(ACS)":[34],"stationary":[36],"over":[37],"filtering":[39],"duration.":[40],"We":[41],"show":[42],"that":[43],"KF":[45],"covariance":[46,73],"matrix":[47],"overbounds":[48],"distribution":[52],"when":[53],"models":[56],"Fourier":[59],"transform":[60],"windowed":[63],"version":[64],"ACS.":[67],"The":[68],"evaluated":[71],"using":[72],"analysis":[74],"for":[75],"an":[76],"example":[77],"application":[78],"GPS-based":[80],"relative":[81],"position":[82],"estimation.":[83]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
